Diagnostically useful results in real time
16 claims: 6 independent, 10 dependent
- 1狭窄セグメントを有する心臓血管系の血管機能を評価するためのプロセッサーを備えるコンピュータの作動方法において、前記プロセッサーによって実行される方法は、 第1の投影角度で記録された心臓血管系の第1の医療用画像および第2の投影角度で記録された心臓血管系の第2の医療用画像を医療用撮像装置から受信することと、 少なくとも以下のステップを実行することによって、前記第1の医療用画像および前記第2の医療用画像に基づいて前記心臓血管系をモデリングする少なくとも一つの直径または断面積を有する第1の血管モデルを作成することと、 (i)第1および第2の医療用画像のそれぞれにおいて、心臓血管系の枝を通過する血管中心線を決定することと、 (ii)前記第1および第2の投影角度の間の差を考慮して、前記第1および第2の医療用画像に関する互いの血管中心線の対応を決定することによって、前記第1および第2の医療用画像の心臓血管系の枝の間の一致を識別することと、 (iii)ステップ(ii)において識別された一致のそれぞれについて、第1の医療用画像および第2の医療用画像の血管中心線の血管端で始まる経路追跡を使用して心臓血管系の二分岐部または三分岐部での互いに接続された枝を識別することと、そして、 (iv)ステップ(i)から決定された血管中心線、ステップ(ii)から識別された一致、およびステップ(iii)から心臓血管系の二分岐部または三分岐部での互いに接続された、識別された枝を使用して第1の血管モデルを作成することと、 前記第1の血管モデル中の前記狭窄セグメントを通る流れの特性に関する第1の値を決定することと、ここで、前記第1の値は第1の血管モデルの狭窄セグメントにおける心臓血管系の直径または断面積の少なくとも一つ から計算された第1の抵抗であり 、 狭窄セグメントの少なくとも一部の幾何学的形状に少なくとも1つの修正を行って、前記第1の血管モデルから第2の血管モデルを生成することと、 前記第2の血管モデルに対する前記狭窄セグメントを通る流れの特性に関する第2の値を決定することと、 ここで、 前記第2の値は第2の血管モデルの狭窄セグメントにおける心臓血管系の直径または断面積の少なくとも一つ から計算された第2の抵抗であり 、 前記第1の血管モデルによってモデル化される前記心臓血管系の血管機能を定量化する流動指数を算出することを備え、ここにおいて、前記算出することは、前記第1の血管モデルおよび前記第2の血管モデルにおける流れの特性に関する第1および第2の値を比較することに基づく方法。
- 2前記第1の医療用画像および前記第2の医療用画像は、2-D血管造影画像を含む請求項1に記載の方法。
- 3前記2-D血管造影画像は、血管セグメントに対して10%以内の精度の血管幅の決定を行うことを可能にする十分な解像度を有している請求項2に記載の方法。
- 4前記流動指数は、前記第1の血管モデルおよび前記第2の血管モデルにおける流れの特性に関する第1および第2の値の比に基づき算出される請求項1に記載の方法。
- 5前記流動指数に基づいて血管再生の提案を決定することをさらに含む請求項 1 に記載の方法。
- 6前記第1の血管モデルおよび前記第2の血管モデルは、血管セグメントデータの接続された枝を備え、それぞれの前記枝は流れに対する対応する血管抵抗に関連付けられる請求項1に記載の方法。
- 7前記第1の血管モデルは、前記心臓血管系の血管壁の径方向の3-D記述を含む請求項 6 に記載の方法。
- 8前記第2の血管モデルは、前記第1の血管モデルにおける前記狭窄セグメントより大きな径を有する推定再生血管を備える請求項1に記載の方法。
- 9前記第2の血管モデルは、隣接する非狭窄セグメントの特性に基づき前記狭窄セグメントを正常化することによって得られる正常化された血管を備える請求項1に記載の方法。
- 10前記第1の血管モデルおよび前記第2の血管モデルのそれぞれは、血管系の少なくとも3つの分岐部が狭窄セグメントを超えて遠位に拡張する、前記血管系の一部に対応する請求項1に記載の方法。
- 11前記第1の血管モデルは、前記心臓血管系の血管セグメントに沿った経路を備える請求項2に記載の方法。
- 12前記第1の血管モデルおよび前記第2の血管モデルのそれぞれは、前記狭窄セグメントから遠位に拡張する前記心臓血管系の一部に対応する請求項1に記載の方法。
- 13プログラム命令が格納され、前記プログラム命令がコンピュータによって読み込まれると請求項1の方法を実行することを前記コンピュータに行わせる、コンピュータ可読媒体を備える、コンピュータソフトウェア製品。
- 14狭窄セグメントを有する心臓血管系の血管機能を評価するためのシステムにおいて、 第1の投影角度で記録された心臓血管系の第1の医療用画像および第2の投影角度で記録された心臓血管系の第2の医療用画像を医療用撮像装置から受信し、 少なくとも以下のステップを実行することによって、前記第1の医療用画像および前記第2の医療用画像に基づいて、前記心臓血管系をモデリングする少なくとも一つの直径または断面積を有する第1の血管モデルを作成し、 (i)第1および第2の医療用画像のそれぞれにおいて心臓血管系の枝を通過する血管中心線を決定することと、 (ii)前記第1および第2の投影角度の間の差を考慮して、前記第1および第2の医療用画像に関する互いの血管中心線の対応を決定することによって、前記第1および第2の医療用画像の心臓血管系の枝の間の一致を識別することと、 (iii)ステップ(ii)において識別された一致のそれぞれについて、第1の医療用画像および第2の医療用画像の血管中心線の血管端で始まる経路追跡を使用して心臓血管系の二分岐部または三分岐部での互いに接続された枝を識別することと、そして、 (iv)ステップ(i)から決定された血管中心線、ステップ(ii)から識別された一致、およびステップ(iii)から心臓血管系の二分岐部または三分岐部での互いに接続された、識別された枝を使用して第1の血管モデルを作成すること、 前記狭窄セグメントを通る前記第1の血管モデル中の流れの特性に関する第1の値を決定し、ここで、前記第1の値は第1の血管モデルの狭窄セグメントにおける心臓血管系の直径または断面積の少なくとも一つ から計算された第1の抵抗であり 、 狭窄セグメントの少なくとも一部の幾何学的形状に少なくとも1つの修正を生じさせて、前記第1の血管モデルから第2の血管モデルを生成し、 前記第2の血管モデルに対する前記狭窄セグメントを通る流れの特性に関する第2の値をさらに決定し、ここで、第2の値は第2の血管モデルの狭窄セグメントにおける心臓血管系の直径または断面積の少なくとも一つ から計算された第2の抵抗であり 、 前記第1の血管モデルによってモデリングされた前記心臓血管系の前記血管機能を定量化する流動指数を算出するように構成されたコンピュータを備え、ここにおいて、前記コンピュータは、前記第1の血管モデルと前記第2の血管モデルにおける流れの特性に関する第1および第2の値を比較することによって、前記流動指数を算出するシステム。
- 15前記コンピュータは、前記第1の医療用画像および前記第2の医療用画像の受信から5分以内に前記流動指数を算出するように構成される請求項 14 に記載のシステム。
- 16前記第1の血管モデルからの前記第2の血管モデルの生成は、前記狭窄セグメントによる流れの制限を無視することを含む請求項1に記載の方法。
Independent claims16
583 paragraphs, as filed
Mutual reference to related applications This application is incorporated herein by reference in its entirety, US Provisional Patent Application No. 61 / 752,526 filed on January 15, 2013, filed on September 29, 2013. It claims the priority benefit of US Provisional Patent Application No. 14 / 040,688 and International Patent Application No. PCT / IL2013 / 050869 filed on October 24, 2013.
This application contains one of three simultaneous filing applications, agent reference numbers 58285, 58286, and 58287.
The present invention relates to vascular modeling in some of those embodiments, and more specifically, without limitation, real-time exponents related to vascular function and diagnosis-eg, catheter insertion imaging. During the execution of the (catheterized imaging procedure)-related to the use of vascular models to generate.
Arterial stenosis is one of the most serious forms of arterial disease. In clinical practice, the severity of stenosis can be determined by using simple geometric parameters, such as determining the proportion of stenosis diameter, or by blood circulation, such as pressure-based myocardial flow reserve ratio (FFR). Estimated by either measuring dynamics-based parameters. FFR is an invasive measure of the functional severity of coronary artery stenosis. The FFR measurement technique involves the insertion of a 0.014 guide wire equipped with a small pressure transducer that is placed over the arterial stenosis, which is the maximum blood flow within the area of the stenosis and the maximum blood within the same area without the stenosis. Represents the ratio to flow rate. Previous studies have shown that FFR <0.75 is an accurate predictor of ischemia, and delays in percutaneous coronary intervention for lesions with FFR 0.75 are safe. It looked like.
An FFR cutoff value of 0.8 is typically used in clinical practice to induce angiogenesis, supported by long-term outcome data. FFR values in the range of 0.75 to 0.8 are typically considered to be the "gray zone" of uncertain clinical significance.
For blood flow modeling and blood flow evaluation, for example, to "Method And System For Patient-Specific Modeling Of Blood Flow", which describes an embodiment including a system for determining cardiovascular information for a patient. , Taylor's US Publication Patent Application No. 2012/0059246. The system may include at least one computer system that is configured to receive patient-specific data regarding the geometry of at least a portion of the patient's anatomy. Part of the anatomy may include at least a portion of the patient's aorta and at least a portion of multiple coronary arteries exiting a portion of the aorta. At least one computer system creates a three-dimensional model that represents part of the anatomical structure based on patient-specific data, and is a physics-based model related to blood flow characteristics within part of the anatomical structure. Can also be constructed to determine the blood flow reserve ratio within a portion of the anatomical structure based on a three-dimensional model and a physics-based model.
Additional background technologies include:
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The disclosures of all documents mentioned above and throughout this specification, as well as the disclosures of all documents referred to in these documents, are incorporated herein by reference.
According to aspects of some embodiments of the invention, receiving a first vascular model of the cardiovascular system for performing vascular evaluation and a first vascular representing flow through a stenotic segment of the vascular system. Determining at least one characteristic based on the model and generating a second vascular model with elements corresponding to the first vascular model and at least one modification containing a difference in at least one characteristic of flow. A method is provided that comprises calculating a flow index that compares the first model with the second model.
According to some embodiments of the invention, the difference in at least one characteristic of flow is between at least one characteristic of the flow through the constricted segment and the characteristic of the flow in the corresponding segment of the second model. Have a difference between.
According to some embodiments of the present invention, the blood vessel model is calculated based on a plurality of 2-D angiographic images.
According to some embodiments of the invention, angiographic images allow for vascular width determination within 10% of the vascular segment according to at least a third bifurcation from the major human coronary artery. Has sufficient resolution to do.
According to some embodiments of the present invention, the flow index comprises a prediction of increased flow that can be achieved by intervention to remove the stenosis from the stenosis segment.
According to some embodiments of the invention, the comparative flow index is calculated based on the ratio of the corresponding flow characteristics of the first and second vascular models.
According to some embodiments of the present invention, the comparative flow index is calculated based on the ratio of the corresponding flow characteristics of the narrowed and non-stenotic segments.
According to some embodiments of the invention, the method comprises reporting the comparative flow index as a single number per stenosis.
According to some embodiments of the invention, at least one characteristic of the flow comprises a flow rate.
According to some embodiments of the present invention, the comparative flow index represents a blood flow reserve index that comprises the ratio of the maximum flow through a stenotic vessel to the maximum flow through a stenotic vessel from which the stenosis has been removed. To be equipped.
According to some embodiments of the invention, the comparative flow index is relative to angiogenesis.<u style="single">Suggestion</u>Used in determining.
According to some embodiments of the present invention, the comparative flow index comprises a value indicating capacity to restore flow by removing the stenosis.
According to some embodiments of the present invention, the first and second vascular models include connected branches of vascular segment data, each branch associated with a corresponding vascular resistance to flow.
According to some embodiments of the invention, the vascular model does not include a 3-D description that is detailed in the radial direction of the vessel wall.
According to some embodiments of the present invention, the second vascular model is a conventional model comprising a vessel having a relatively large diameter that replaces the stenotic vessel in the first vascular model.
According to some embodiments of the present invention, the second vascular model is a conventional model comprising normalized blood vessels obtained by normalizing stenotic blood vessels based on the characteristics of adjacent non-stenotic blood vessels. ..
According to some embodiments of the present invention, at least one characteristic of the flow is calculated based on the characteristics of a plurality of vascular segments connected by the flow to the stenotic segment.
According to some embodiments of the present invention, the flow property comprises resistance to fluid flow.
According to some embodiments of the invention, the method distinguishes between a stenotic vessel and the crown of a vascular branch downstream of the stenotic vessel in a first vascular model and fluid flow within the crown. The flow index is calculated based on the volume of the crown and on the contribution of the stenotic vessel to the resistance to fluid flow.
According to some embodiments of the present invention, the first blood vessel model comprises a representation of blood vessel position in three-dimensional space.
According to some embodiments of the invention, each vascular model corresponds to a portion of the vascular system between two consecutive bifurcations of the vascular system.
According to some embodiments of the invention, each vascular model corresponds to a portion of the vascular system that includes a bifurcation of the vascular system.
According to some embodiments of the invention, each vascular model corresponds to a portion of the vascular system that extends at least one bifurcation of the vascular system beyond the stenotic segment.
According to some embodiments of the invention, each vascular model corresponds to a portion of the vascular system that extends at least three branches of the vascular system beyond the stenotic segment.
According to some embodiments of the invention, the vascular model comprises pathways along vascular segments, each of which is mapped along its extent to a position within a plurality of 2-D images. ..
According to some embodiments of the invention, the method comprises acquiring an image of the cardiovascular system and constructing a first vascular model thereof.
According to some embodiments of the invention, each vascular model corresponds to a portion of the vascular system that dilates distally as long as the image resolution allows determination of vascular width within 10% of the correct value. To do.
According to some embodiments of the invention, the vascular model is that of an artificially dilated vascular system at the time of acquisition of the image used to generate the model.
According to one aspect of some embodiments of the invention, a method for vascular evaluation by storing program instructions and receiving multiple 2-D images of the subject's vasculature when the instructions are read by a computer. A computer software product is provided with a computer-readable medium that allows the computer to do what it does.
According to one aspect of some embodiments of the present invention, a plurality of 2-D images for performing a vascular evaluation are received, the plurality of 2-Ds are converted into a first vascular model of the vascular system. A second vascular model that determines at least one characteristic based on a first vascular model that represents the flow through a stenotic segment of the vascular system and has elements corresponding to the first vascular model, and a flow through the stenotic segment. Generate at least one modification, including changing at least one characteristic to the characteristic of the flow as if passing through the corresponding segment where the effect of stenosis is reduced, and the first model and the second model. A system is implemented that comprises a computer configured to calculate the flow index to be compared.
According to some embodiments of the invention, the computer is configured to calculate the flow index within 5 minutes of receiving the first blood vessel model.
According to some embodiments of the invention, the computer is configured to calculate the flow index within 5 minutes of obtaining a 2-D image.
According to some embodiments of the present invention, the computer is located away from the imaging device.
According to one aspect of some embodiments of the present invention, it is based on receiving a vascular model of the cardiovascular system and vascular model representing the flow through the stenotic segment of the vascular system and the coronary vessels to the stenotic segment. Determining at least the first flow characteristic and determining at least the second flow characteristic based on a vascular model representing flow through the coronary vessels without being restricted by the stenotic segment. A method for vascular evaluation is provided that comprises calculating a flow index that compares the flow property with a second flow property.
According to one aspect of some embodiments of the invention, receiving a plurality of 2-D angiographic images of vascular segments contained in a portion of a subject's vascular system and automatically performing a plurality of 2-. Extracting a corresponding set of image features with 2-D feature positions of a vessel segment from each of the D angiographic images and relative position errors in a common 3-D coordinate system where each feature set can be back-projected. Automatically adjust 2-D feature positions to reduce and automatically position 2-D feature positions across image feature sets so that image features projected from a common vessel segment region are associated. Automatically determines the representation of image features based on the association, inspection of the 3-D projection determined from the associated 2-D feature position, and the selection of the best available 3-D projection from it. A method for building a tree model is provided.
According to some embodiments of the present invention, the extracted image feature set comprises a centerline data set containing 2-D centerline positions ordered along the vascular segment.
According to some embodiments of the invention, the determined representation is a 3-D spatial representation of the extent of the vascular segment.
According to some embodiments of the invention, the determined representation is a graphical representation of the extent of the vascular segment.
According to some embodiments of the present invention, all the information necessary to automatically associate 2-D image positions is provided prior to image review by a human operator.
According to some embodiments of the present invention, the adjustment, association, and determination are performed by the elements of the centerline dataset.
According to some embodiments of the present invention, the adjustment is 2 in 3-D space with parameters that make the 2-D centerline position have a closer correspondence between its 3-D back projections. -D Equipped with image registration.
According to some embodiments of the present invention, the extracted image feature set consists of a tree model origin, a locally reduced radius arrangement within the stenotic vessel segment, and a bifurcation across the vessel segment. It has a landmark dataset containing at least one of.
According to some embodiments of the present invention, the extracted image feature set comprises a landmark dataset containing pixel intensity configurations below a predetermined threshold of self-similarity on transformation.
According to some embodiments of the invention, coordination is performed on the elements of the landmark dataset, and association and determination are performed between the elements of the centerline dataset.
According to some embodiments of the present invention, the adjustment is 2 in 3-D space with parameters that make the features of the landmark dataset have a closer correspondence between its 3-D back projections. -D Equipped with image registration.
According to some embodiments of the present invention, registration of a 2-D image comprises registration of the location of an element in a centerline dataset.
According to some embodiments of the invention, the method is based on the value of at least one of a plurality of 2-D angiographic images along a straight line perpendicular to the ordered 2-D centerline position. It is provided to estimate the measurement standard of the directional vessel width.
According to some embodiments of the present invention, estimating a measure of radial vessel width comprises finding a connecting path that runs along either side of the 2-D centerline position. Includes pixels that are images of the boundary region of the vessel wall.
According to some embodiments of the present invention, the boundary region of the vessel wall is determined by analysis of the intensity gradient along the vertical line.
According to some embodiments of the present invention, the measure of radial vessel width is calculated as a function of centerline position.
According to some embodiments of the invention, the determination is based on the projection of the 3-D representation into at least one 2-D plane of multiple 2-D angiographic images. Be prepared to adjust.
According to some embodiments of the present invention, the adjustment is to calculate the 3-D representation of the feature position from the 2-D feature position of the first subset of the plurality of 2-D angiographic images. 2-D feature positions within a second subset of multiple 2-D angiographic images, 3-as if the first 3-D representation was projected into the adjusted image plane of the second subset. It includes adjusting to better match the characteristics of the D representation, calculating with changes to the first and second subsets, and repeating the adjustment until the stop condition is met.
According to some embodiments of the present invention, the stopping condition is that there is no position to adjust to the 2-D feature position above the distance threshold.
According to some embodiments of the present invention, the method defines a surface corresponding to the shape of the subject's heart and uses that surface as a constraint for associating feature positions. Be prepared.
According to some embodiments of the invention, images are acquired after injection of the contrast medium into the vascular system, the method of determining the temporal characteristics of the movement of the contrast medium through the vascular system and the time. Further, it is provided to constrain the feature position based on the characteristic.
According to some embodiments of the invention, a portion of the vascular system comprises a coronary artery.
According to some embodiments of the present invention, the capture of a plurality of 2D angiographic images is performed by a plurality of imaging devices to capture the plurality of 2D angiographic images.
According to some embodiments of the present invention, capture of multiple 2D angiographic images comprises synchronizing multiple imaging devices to capture multiple images at substantially the same time in the heartbeat cycle.
According to one aspect of some embodiments of the present invention, program instructions are stored, and when the instructions are read by a computer, multiple 2D angiographic images of a portion of the vasculature are received to construct a vasculature model. A computer software product is provided that provides a computer-readable medium that allows the computer to perform the methods for.
According to one aspect of some embodiments of the invention, it is logically connected to an angiographic imaging device for capturing multiple 2-D images of a portion of a subject's vascular system for performing vascular evaluation. , Receives multiple 2-D angiographic images from multiple angiographic imaging devices, extracts from each of the multiple 2-D angiographic images an image feature dataset with 2-D feature positions of the vessel segment, and features. Adjust 2-D feature positions to minimize relative position errors in the common 3-D coordinate system so that 2-D feature positions projected onto different images from the common vessel segment region are associated. Find the correspondence between the 2-D feature positions between the image feature datasets and create a 3-D representation of the 2-D feature positions based on the inspection of the 3-D projection determined from the associated 2-D feature positions. A system is realized with a computer configured to make decisions.
According to some embodiments of the present invention, the image feature set configured to be extracted by the system comprises a centerline data set containing 2-D centerline positions ordered along the vascular segment.
According to some embodiments of the present invention, the system is configured to use the position of an element in the centerline dataset as a 2-D feature position.
According to some embodiments of the present invention, the system is a 2-D in 3-D space with parameters that make the 2-D centerline position have a closer correspondence between its 3-D back projections. It is configured to adjust the 2-D feature position based on the registration of the image.
According to some embodiments of the present invention, the measurement of radial vessel width comprises the distance between connecting pathways running along any side of the 2-D centerline position, where the connecting pathway is of the vessel wall. It has pixels that serve as an image of the boundary area.
According to some embodiments of the present invention, image transformation based adjustments can be iteratively performed for at least a second selection of images for the first and second sets of images.
According to some embodiments of the present invention, a portion of the vascular system comprises a tree of coronary arteries from the main coronary artery to at least a third bifurcation.
According to one aspect of some embodiments of the present invention, constructing a vascular tree model and receiving a 2-D image of the vascular tree is associated with each of the images being associated with a corresponding image plane position. Automatically identifying vascular features in 2-D images and geometrically projecting light rays from vascular features within the image plane position to pass homologous vascular features between images through a common image target space. A method is provided that comprises identifying by and associating features with intersecting rays as homologous.
According to some embodiments of the present invention, the intersection of light rays comprises being within a predetermined distance from each other.
According to some embodiments of the present invention, the image plane position is repeatedly updated to reduce the error at the intersection of the rays, and the identification of homologous vascular features is subsequently repeated.
According to one aspect of some embodiments of the present invention, a vascular tree model is constructed to repeatedly back-project light rays from features in a plurality of 2-D images onto a common 3-D plane. Determining the error in ray intersection from features common to 2-D images, adjusting 2-D images, back-projecting, determining, and at least the first additional A method is provided that comprises adjusting the time and repeating.
According to one aspect of some embodiments of the present invention, a model of a portion of the vasculature is prepared, where the elements of this model are in common with the coordinate space of multiple 2-D angiographic images. -Associated with multiple placement descriptions selected from the group consisting of the coordinate space of the D space and the angiographic space with a 1-D spread branched from the connecting node.
According to one aspect of some embodiments of the invention, receiving and 20 minutes after receiving a plurality of 2-D angiographic images of a portion of the subject's vascular system for performing a vascular evaluation. Within, automatic processing of images will generate a first 3-D vascular tree model for a portion of the vascular system with stenotic heart arteries, and restore flow by opening the stenosis based on the vascular tree model. A method is provided that comprises automatically determining an index that quantifies the capacity to do so.
According to some embodiments of the present invention, the capacity indication for restoring flow by opening the stenosis comprises a calculation based on changes in vessel width.
According to some embodiments of the present invention, the automatic processing is performed within 1 K.
According to some embodiments of the invention, automated processing comprises forming a model that does not include a detailed 3-D representation in the radial direction of the vessel wall.
According to some embodiments of the invention, the automatic determination, and the automatic processing, comprises forming a model that does not include dynamic flow modeling.
According to some embodiments of the present invention, the automatic determination comprises a linear modeling of the flow characteristics of blood vessels.
According to some embodiments of the present invention, the vessel tree model represents vessel width as a function of vessel expansion.
According to some embodiments of the invention, the vascular spread comprises a distance along a vascular segment located at a node location on the vascular tree model.
According to some embodiments of the invention, the first 3-D vascular tree model comprises at least three branch nodes between vascular segments.
According to some embodiments of the present invention, the first 3-D vessel tree model comprises a vessel centerline and a vessel width along it.
According to some embodiments of the invention, the first 3-D vascular tree is generated within 5 minutes.
According to some embodiments of the invention, the method comprises calculating the FFR properties for at least one vascular segment of the vascular tree.
According to some embodiments of the present invention, the calculation of the FFR characteristics is based on the first model, with the difference that the second model represents the larger vessel width, the second vessel. It comprises generating a tree model and comparing the first vascular tree model with the second vascular tree model.
According to some embodiments of the present invention, the comparison is to obtain the ratio of the flow rates modeled by the first and second vascular tree models to at least one vascular segment. Be prepared.
According to some embodiments of the invention, the FFR properties are calculated within 1 minute of generating the first 3-D vascular tree model, according to some embodiments of the invention. The FFR property is calculated within 10 seconds of generating the first 3-D vascular tree model and the second 3-D vascular tree model, according to some embodiments of the present invention. The property is a predictor of the pressure measurement determination FFR index with a sensitivity of at least 95%.
According to some embodiments of the present invention, this method is a part of a first 3-D vascular tree, 2-D shared by at least one of a plurality of 2-D angiographic images. It is provided to generate a projection into a coordinate reference frame.
According to some embodiments of the present invention, at least one image is transformed from the original coordinate reference frame to a coordinate reference frame defined relative to the 3-D coordinate reference frame of the 3-D vascular tree. To.
According to some embodiments of the invention, the subject undergoes an intravascular catheter insertion in imaging to produce multiple received 2-D angiographic images, upon receipt of the images, and in the first 3-D. The catheter remains inserted when the vascular tree model is generated.
According to some embodiments of the present invention, the method images a subject and produces a second plurality of 2-D angiographic images of a first generation of a first vascular tree model, a second. Generated after a second reception of an image with multiple images, and a second generation of a first 3-D vascular tree model, where the subject remains catheter inserted into the blood vessel.
According to some embodiments of the invention, the generation is interactive with the subject's ongoing catheterization procedure.
According to some embodiments of the present invention, the calculation of FFR properties is performed interactively with the subject's ongoing catheter insertion procedure.
According to one aspect of some embodiments of the invention, it is logically connected to an angiographic imaging device for capturing multiple 2-D images of a portion of the subject's vascular system for performing vascular evaluation. , Then equipped with a computer configured to calculate the vascular tree model within 5 minutes, where the index of vascular function, which indicates the capacity for flow restoration by opening the stenosis, is within an additional 1 minute. A system that can be determined based on the model is realized.
According to some embodiments of the present invention, the determination based on the vascular tree model produces a second vascular tree model derived from the vascular tree model by widening the vessel width modeled within the area of stenosis. Be prepared.
In some embodiments of the invention, one or more models of the patient's vascular system are generated.
In some embodiments, the first model is generated from actual data collected from images of the patient's vascular system. As appropriate, the actual data includes a portion of the vasculature containing at least one vessel with stenosis. In these embodiments, the first model describes a portion of the vasculature that includes at least one blood vessel with a stenosis. This model is referred to interchangeably with the stenosis model. As appropriate, the actual data will include part of the vasculature, including at least one vessel with stenosis and the crown. In these embodiments, the stenosis model further comprises information relating to the shape and / or volume of the crown and information relating to blood flow and / or resistance to blood flow within the crown.
In some embodiments, the first model is used to calculate an index of vascular function. Preferably, the index also indicates the potential effect of angiogenesis. For example, the index can be calculated based on the volume of the crown in the model and the contribution of the stenotic vessel to resistance to blood flow in the crown.
In some embodiments of the invention, the second model is generated from actual data and modifies one or more strictures present in the patient's vascular system as if they were revascularized. Will be done.
In some embodiments, the first and second models are compared and the index showing the potential effect of angiogenesis determines the physical properties of the first model and the physical properties of the second model. Generated based on comparison.
In some embodiments, the index is a blood flow reserve ratio (FFR), as is known in the art.
In some embodiments, the index is some other measure that potentially correlates with the effect of performing vascular regeneration of one or more vessels at the location of the stenosis, as appropriate.
According to one aspect of some embodiments of the invention, a method for vascular evaluation is provided. This method is to receive multiple 2D angiographic images of a portion of the subject's vasculature and to process the images to generate a first vascular tree for a portion of the vasculature within less than 60 minutes. It is equipped with the use of a computer.
According to some embodiments of the invention, the vasculature has at least one catheter in it other than the angiographic catheter, where the image is processed and the tree is catheterized within the vasculature. Generated while in.
According to some embodiments of the invention, the method comprises using a vascular model to calculate an index indicating vascular function.
According to some embodiments of the invention, the index indicates the need for revascularization.
According to some embodiments of the invention, the calculation is done within less than 60 minutes.
According to one aspect of some embodiments of the present invention, a method of analyzing angiographic images is provided. The method comprises receiving multiple 2D angiographic images of some of the vasculature of a subject and using a computer to process the images to generate a tree model of the vasculature.
According to one aspect of some embodiments of the invention, a method of treating the vascular system is provided. This method captures multiple 2D angiographic images of the subject's vascular system that are stationary on the treatment surface and processes the images while the subject is stationary. It comprises generating a vascular tree for the vascular system, identifying contracted blood vessels in the tree, and inflating a stent at a site of the vascular system corresponding to the contracted blood vessels in the tree.
According to some embodiments of the present invention, the plurality of 2D angiographic images comprises at least three 2D angiographic images, wherein the tree model is a 3D tree model.
According to some embodiments of the present invention, the method distinguishes between a stenotic vessel and the crown of the stenotic vessel in a first vessel tree and calculates resistance to fluid flow within the crown. Here, the index is calculated based on the volume of the crown and on the contribution of the stenotic vessel to resistance to fluid flow.
According to some embodiments of the present invention, the vascular tree comprises data relating to the arrangement, orientation, and diameter of blood vessels at multiple points within a portion of the vascular system.
According to some embodiments of the invention, the method comprises processing an image to generate a second three-dimensional vascular tree for the vasculature, in which the stenotic blood vessels dilate. Corresponds to the first vascular tree replaced by the blood vessels, where the index calculation is based on the first and second trees.
According to some embodiments of the invention, the method comprises processing an image to generate a second three-dimensional vascular tree for the vascular system, the second vascular tree containing no stenosis. Corresponds to a part of the vascular system, which is geometrically similar to the first vascular tree, where the index calculation is based on the first and second trees.
According to some embodiments of the invention, the method comprises obtaining a blood flow reserve ratio (FFR) based on an index.
According to some embodiments of the present invention, the method comprises determining the ratio of the maximum blood flow in the area of the stenosis to the maximum blood flow in the same area without the stenosis based on the index. ..
According to some embodiments of the invention, the method comprises treating a stenotic vessel with minimal invasiveness.
According to some embodiments of the invention, the treatment is performed within less than an hour from the calculation of the index.
According to some embodiments of the invention, the method comprises storing the tree in a computer-readable medium.
According to some embodiments of the invention, this method comprises transmitting the tree to a remote computer.
According to some embodiments of the invention, the method comprises capturing a 2D angiographic image.
According to some embodiments of the present invention, capturing a plurality of 2D angiographic images is performed by a plurality of imaging devices to capture the plurality of 2D angiographic images.
According to some embodiments of the present invention, capturing multiple 2D angiographic images comprises synchronizing multiple imaging devices to capture multiple images at substantially the same time in the heartbeat cycle. ..
According to some embodiments of the invention, the synchronization follows the subject's ECG signal.
According to some embodiments of the invention, the method corresponds to detecting the corresponding image feature in each of the N angiographic images, where N is an integer greater than 1. Calculate image correction parameters based on image features, and geometrically correspond registration of N-1 angiographic images to angiographic images other than N-1 angiographic images based on the correction parameters. Be prepared to do what you want.
According to some embodiments of the invention, the method defines a surface that corresponds to the shape of the subject's heart and uses the surface as a constraint to detect the corresponding image features. Be prepared.
According to some embodiments of the invention, the method comprises compensating for breathing and patient movement.
According to one aspect of some embodiments of the present invention, a computer software product is provided. The computer software product receives multiple 2D angiographic images of the subject's vasculature as the program instructions are stored and the instructions are read by the computer, as shown above and, as appropriate, further detailed below. , Provide a computer-readable medium that allows the computer to perform this method.
According to one aspect of some embodiments of the present invention, a system for vascular evaluation is provided. The system receives multiple imaging devices configured to capture multiple 2D angiographic images of the subject's vasculature and multiple 2D images, as shown above and as appropriate further detailed below. It is equipped with a computer configured to perform this method.
According to one aspect of some embodiments of the invention, it is functionally connected to a plurality of angiographic imaging devices for capturing multiple 2D images of a portion of a subject's vascular system for performing vascular evaluation. It is configured to receive data from multiple angiographic imaging devices and process the images to generate a tree model of the vasculature, where the tree model is along the blood vessels of at least one branch of the vasculature. It comprises the results of geometrical measurements of the vascular system at one or more positions.
According to some embodiments of the present invention, the system comprises a synchronization unit configured to provide a synchronization signal to multiple angiographic imaging devices to synchronize the capture of multiple 2D images of the vascular system. ..
According to some embodiments of the present invention, the computer is configured to receive a subject ECG signal and, based on the ECG signal, select a 2D image corresponding to substantially the same period in the heartbeat cycle.
According to some embodiments of the invention, the system detects the corresponding image feature in each of the N angiographic images, where N is an integer greater than 1. The image correction parameters are calculated based on the characteristics, and the registration of N-1 angiographic images is geometrically corresponded to the angiographic images other than the N-1 angiographic images based on the correction parameters. It comprises an image registration unit configured to do so.
According to some embodiments of the present invention, the computer defines a surface corresponding to the shape of the subject's heart and uses the surface as a constraint to detect the corresponding image feature. It is configured as follows.
According to some embodiments of the invention, the computer is configured to compensate for breathing and patient movement.
According to some embodiments of the present invention, compensation responds to iterative detection of corresponding image features each time for different subsets of angiographic images and repeated detection of corresponding image features. The image correction parameter is updated.
According to some embodiments of the invention, N is greater than 2. According to some embodiments of the invention, N is greater than 3.
According to some embodiments of the invention, the corresponding image feature comprises at least one of a group consisting of the origin of the tree model, the arrangement of the smallest radius within the constricted vessel, and the bifurcation of the vessel. ..
According to some embodiments of the present invention, the tree model comprises data relating to the arrangement, orientation, and diameter of blood vessels at multiple points within a portion of the vasculature.
According to some embodiments of the invention, the tree model comprises measurements of the vasculature at one or more locations along the blood vessels of at least one branch of the vasculature.
According to some embodiments of the present invention, the geometric measurement result of the vasculature is the measurement result at one or more positions along the centerline of at least one branch of the vasculature.
According to some embodiments of the invention, the tree model comprises data relating to blood flow characteristics at one or more of the points.
According to some embodiments of the invention, a portion of the vascular system comprises a cardiovascular artery.
According to one aspect of some embodiments of the invention, a stenosis model for a vascular system that receives a plurality of 2D angiography images of a portion of a subject's vascular system and processes the images to perform vascular evaluation. To obtain the flow characteristics of a stenosis model, with the stenosis model having vascular measurements at one or more locations along the blood vessels of the vascular system, and at least partly the flow in the stenosis model. A method is provided that comprises calculating an index indicating vascular function based on the property.
According to some embodiments of the present invention, the flow characteristics of the stenosis model include resistance to fluid flow.
According to some embodiments of the present invention, the present invention, in the first stenosis model, distinguishes between a stenotic vessel and the crown of the stenotic vessel and calculates resistance to fluid flow within the crown. Here, the index is calculated based on the volume of the crown and on the contribution of the stenotic vessel to resistance to fluid flow.
According to some embodiments of the present invention, the flow characteristics of the stenosis model include fluid flow.
According to some embodiments of the present invention, the stenosis model is a three-dimensional vascular tree.
According to some embodiments of the present invention, the vascular tree comprises data relating to the arrangement, orientation, and diameter of blood vessels at multiple points within a portion of the vascular system.
According to some embodiments of the invention, this process responds to the extension of the stenosis model with one bifurcation, the calculation of new flow characteristics in the expanded stenosis model, and the new flow characteristics. Therefore, the index is updated according to a predetermined standard, and expansion, calculation, and updating are repeated repeatedly.
According to some embodiments of the present invention, this method processes an image to generate a second model for the vascular system and obtains the flow characteristics of the second model, wherein. The calculation of the index is based on the flow characteristics in the stenosis model and the flow characteristics in the second model.
According to some embodiments of the present invention, this method, the second model, is a conventional model comprising an inflated vessel that replaces the stenotic vessel in the stenosis model.
According to some embodiments of the present invention, the stenosis model is a three-dimensional vascular tree and the second model is a second three-dimensional vascular tree.
According to some embodiments of the invention, each of these models lies between two consecutive bifurcations of the vascular system and corresponds to a portion of the vascular system, including a stenosis.
According to some embodiments of the invention, each of these models corresponds to a portion of the vascular system that includes a bifurcation of the vascular system.
According to some embodiments of the invention, each of these models corresponds to a portion of the vascular system that includes a stenosis and extends at least one bifurcation of the vascular system beyond the stenosis.
According to some embodiments of the invention, each of these models corresponds to a portion of the vascular system that includes a stenosis and extends at least three branches of the vascular system beyond the stenosis.
According to some embodiments of the invention, each of the methods, models, corresponds to a portion of the vascular system that includes a stenosis and extends distally, as the resolution of the image allows.
According to some embodiments of the present invention, the stenosis model corresponds to a portion of the vascular system that includes the stenosis, and the second model is geometrically similar to the stenosis model that does not include the stenosis. Corresponds to part of the vascular system.
According to some embodiments of the present invention, this process extends each model with one branch, calculates new flow characteristics in each extended model, and new flow characteristics. In response, it comprises updating the exponent according to a predetermined criterion, and iteratively repeating expansion, calculation, and updating.
According to some embodiments of the present invention, the index is calculated based on the ratio of the flow characteristics in the stenosis model to the flow characteristics in the second model.
According to some embodiments of the invention, the index indicates the need for revascularization.
According to one aspect of some embodiments of the invention, generating a stenosis model of the subject's vascular system for performing vascular evaluation, the stenosis model is along the vascular centerline of the subject's vascular system 1 Acquiring the flow characteristics of a stenosis model, including measurements of the subject's vascular system at one or more locations, and generating a second model of similar spread of the subject's vascular system as a stenosis model, A method is provided that includes obtaining the flow characteristics of two models and calculating an index indicating the need for vascular regeneration based on the flow characteristics in the stenosis model and the flow characteristics in the second model. To.
According to some embodiments of the present invention, the second model is a conventional model that includes an inflated vessel that replaces the stenotic vessel in the stenosis model.
According to some embodiments of the invention, the vasculature comprises the subject's cardiovascular arteries.
According to some embodiments of the present invention, generating a stenosis model of a subject's vascular system involves using multiple angiographic imaging devices to capture multiple 2D images of the subject's vascular system. Includes generating a stenosis model based on multiple 2D images.
According to some embodiments of the present invention, the flow characteristics include fluid flow.
According to some embodiments of the present invention, obtaining the flow characteristics of a stenosis model is a fluid in the subject's vascular system at one or more positions within the subject's vascular system spread included in the stenosis model. Obtaining the flow characteristics of the second model, including measuring the flow, is based, at least in part, on correcting the fluid flow of the stenosis model in consideration of the dilated vessels. Includes calculating fluid flow in a subject's vascular system at one or more locations within the subject's vascular system spread included in.
According to some embodiments of the present invention, the flow characteristics include resistance to fluid flow.
According to some embodiments of the present invention, obtaining the flow characteristics of a stenosis model, at least in part, of the subject at one or more positions within the spread of the vascular system of the subject included in the stenosis model. Acquiring the flow characteristics of the second model, including calculating resistance to flow based on the cross-sectional area of the vascular system, is at least in part within the extent of the subject's vascular system included in the second model. Includes calculating resistance to flow based on the inflated cross-sectional area of the subject's vascular system at one or more positions.
According to some embodiments of the invention, the spread of each one of the stenosis model and the second model is a segment of the vasculature between two consecutive bifurcations of the vasculature, including the stenosis. including.
According to some embodiments of the invention, each one spread of the stenosis model and the second model comprises a segment of the vascular system that includes a bifurcation of the vascular system.
According to some embodiments of the invention, each one of the stenosis model and the second model comprises a stenosis and extends at least one bifurcation of the vasculature beyond the stenosis. Including the spread of the system.
According to some embodiments of the invention, each one of the stenosis model and the second model includes a stenosis and an inflated stenosis, respectively, and constricts at least three bifurcations of the vasculature. Includes the spread of the vascular system, which extends beyond the part.
According to some embodiments of the present invention, each one of the stenosis model and the second model contains a stenosis and expands the vasculature, which extends distally as the resolution of the imaging modality allows. Including.
According to some embodiments of the invention, each one of the stenosis model and the second model comprises a stenosis and extends at least one bifurcation of the vascular system distally beyond the stenosis. The flow characteristics of the stenosis model are stored as the flow characteristics before the stenosis model, and the flow characteristics of the second model are stored as the flow characteristics before the second model, including the spread of the vascular system. Expanding the spread of the model and the second model by one more branch, calculating the new flow characteristics in the stenosis model, calculating the new flow characteristics in the second model, and the need for vascular regeneration Whether or not to calculate the indicated index is that the difference between the new flow characteristics of the stenosis model and the previous characteristics of the stenosis model is smaller than the first specific difference, and the new flow characteristics of the second model and before the second model. If the difference from the characteristic of is less than the second specific difference, an index indicating the need for vascular regeneration is calculated, otherwise the determination is made by repeating storage, enlargement, calculation, and determination. Including further.
According to some embodiments of the present invention, the stenosis model includes an extension of the vascular system that includes the stenosis, and the second model does not include the stenosis and is geometrically similar to the first model. Including the spread of the vascular system.
According to some embodiments of the present invention, the index is calculated as the ratio of the flow characteristics in the stenosis model to the flow characteristics in the second model.
According to some embodiments of the present invention, the calculated index is used to determine the blood flow reserve ratio (FFR).
According to some embodiments of the present invention, the calculated index is used to determine the ratio of maximum blood flow within the area of the stenosis to maximum blood flow within the same area without the stenosis. ..
According to some embodiments of the present invention, generating a stenosis model, acquiring the flow characteristics of the stenosis model, generating a second model, acquiring the flow characteristics of the second model, And the calculation of the index is all performed at the time of diagnostic catheter insertion, before the catheter used for diagnostic catheter insertion is withdrawn from the subject's body.
According to one aspect of some embodiments of the present invention, capturing multiple 2D angiographic images of a subject's vascular system and generating a tree model of the subject's vascular system for performing vascular evaluation. The tree model is of multiple captured 2D angiographic images, including geometric measurements of the subject's vascular system at one or more locations along the vascular centerline of at least one branch of the subject's vasculature. Methods are provided that include using at least a portion of the above and generating a model of the flow characteristics of the first tree model.
According to some embodiments of the invention, the vasculature comprises the subject's cardiovascular arteries.
According to some embodiments of the present invention, capturing multiple 2D angiographic images involves capturing multiple 2D angiographic images using multiple imaging devices.
According to some embodiments of the present invention, capturing a plurality of 2D angiographic images involves synchronizing a plurality of imaging devices to capture the plurality of images at the same time.
According to some embodiments of the invention, the synchronization uses the subject's ECG signal.
According to some embodiments of the present invention, synchronization is to detect corresponding image features in at least a first 2D angiographic image and a second 2D angiographic image of a plurality of 2D angiographic images. And to calculate the image correction parameters based on the corresponding image features and to register at least the second 2D angiography image so that it geometrically corresponds to the first 2D angiography image. Here, the corresponding imaging feature comprises at least one of a group consisting of the origin of the tree model, the arrangement of the minimum radius within the constricted vessel, and the bifurcation of the vessel.
According to one aspect of some embodiments of the present invention, a plurality of angiographic imaging devices are functionally connected to capture multiple 2D images of a subject's vascular system for performing vascular evaluation. It receives data from an angiographic imaging device and uses at least some of the captured 2D images to generate a tree model of the subject's vascular system, where the tree model is of the subject's vascular system. Includes a computer, including geometric measurements of the subject's vascular system at one or more locations along the vascular centerline of at least one branch, configured to generate a model of the flow characteristics of the tree model, The system is realized.
According to some embodiments of the invention, the vasculature comprises the subject's cardiovascular arteries.
According to some embodiments of the present invention, further comprising a synchronization unit configured to supply a synchronization signal to a plurality of angiographic imaging devices to synchronize the capture of multiple 2D images of the subject's vasculature. ..
According to some embodiments of the present invention, a synchronization unit configured to receive a subject's ECG signal and select a 2D image from data from multiple angiographic imaging devices at the same cardiac stage in the 2D image. Further prepare.
According to some embodiments of the present invention, at least the corresponding image features in the first 2D image and the second 2D image are detected from the data from the plurality of angiography imaging devices and based on the corresponding image features. It further comprises an image registration unit configured to calculate image correction parameters and perform registration of at least the second 2D image so as to geometrically correspond to the first 2D image. Image features include at least one of a group consisting of the origin of the tree model, the placement of the smallest radius within the constricted vessel, and the bifurcation of the vessel.
According to one aspect of some embodiments of the invention, generating a stenosis model of the subject's vasculature for performing vascular assessment and the stenosis model along the vascular centerline of the subject's vasculature 1 A stenosis model that includes geometric measurements of the subject's vasculature at one or more locations, includes the stenosis, and extends at least one bifurcation of the vasculature beyond the stenosis, including vascular spread. Acquiring the flow characteristics, generating a second model of the similar extent of the subject's vasculature as a stenosis model, acquiring the flow characteristics of the second model, and the flow characteristics in the stenosis model , Includes calculating an index indicating the need for vascular regeneration based on the flow characteristics in the second model, storing the flow characteristics of the stenosis model as the flow characteristics prior to the stenosis model, The flow characteristics are stored as the flow characteristics before the second model, the spread of the stenosis model and the second model is further expanded by one branch, and the new flow characteristics in the stenosis model are calculated. The difference between the new flow characteristics of the stenosis model and the previous characteristics of the stenosis model determines whether to calculate the new flow characteristics in the second model and the index indicating the need for vascular regeneration. Calculate an index indicating the need for vascular regeneration if it is less than the difference and the difference between the new flow property of the second model and the previous property of the second model is less than the second specific difference, otherwise. For example, a method is provided that further includes storage, expansion, calculation, and determination by repeating the determination.
Unless otherwise noted, all technical and / or scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention relates. A number of methods and materials similar or equivalent to those described herein may be used in performing or testing embodiments of the invention, but exemplary methods and / or materials are described below. Will be done. In the event of a discrepancy, this patent specification, including the definition, takes precedence. In addition, the materials, methods, and examples are merely exemplary and are not intended to be inevitable.
As those skilled in the art will understand, aspects of the invention can be embodied as systems, methods, or computer program products. Accordingly, aspects of the invention are embodiments that are entirely hardware, embodiments that are entirely software (including firmware, resident software, microcode, etc.), or all "circuits", "modules" herein. , Or can take the form of an embodiment that combines a software aspect, commonly referred to as a "system," with a hardware aspect. Further, aspects of the present invention may take the form of a computer program product embodied in one or more computer readable media in which the computer readable program code is embodied. Implementations of the methods and / or systems of embodiments of the present invention may involve performing or completing selected tasks manually, automatically, or in combination.
For example, hardware for performing selected tasks according to embodiments of the present invention may be implemented as chips or circuits. As software, the selected tasks according to embodiments of the present invention may be implemented as multiple software instructions executed by a computer using a suitable operating system. In one exemplary embodiment of the invention, one or more tasks according to an exemplary embodiment of a method and / or system as described herein is a processor for executing multiple instructions. It is run by a data processor, such as an instruction platform. As appropriate, the data processor provides volatile memory for storing instructions and / or data and / or non-volatile storage for storing instructions and / or data, such as magnetic hard disks and / or removable media. Be prepared. As appropriate, network connections are provided as well. A display and / or a user input device such as a keyboard or mouse is similarly provided as appropriate.
A combination of one or more computer-readable media (s) may be utilized. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, electronic, magnetic, optical, electromagnetic, infrared, or a semiconductor system, device, or device, or any suitable combination of those described above. More specific examples (non-exhaustive lists) of computer-readable storage media are electrical connections with one or more wires, portable computer diskettes, hard disks, random access memory (RAM), read-only memory (ROM). ), Erasable programmable read-only memory (EPROM or flash memory), fiber optics, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or a suitable combination of the above. including. In the context of the present specification, a computer-readable storage medium comprises or stores a program used by, or connected to, an instruction execution system, device, or device. It can be a tangible medium that can be.
The computer-readable signal medium may include a data signal propagated, for example, in baseband or as part of a carrier wave, using the computer-readable program code embodied therein. Such propagated signals may take various forms, including, but not limited to, electromagnetic, light, or a suitable combination thereof. A computer-readable signal medium is not a computer-readable storage medium and conveys or propagates a program for use with or in connection with an instruction execution system, device, or device. It can be a computer-readable medium that can be carried or transported.
The program code embodied on a computer-readable medium may be transmitted using a suitable medium, including, but not limited to, wireless, wired, fiber optic cable, RF, etc., or a suitable combination of those described above.
Computer program code for performing operations according to aspects of the invention includes object-oriented programming languages such as Java®, Smalltalk, C ++, or the like, and "C" programming languages or similar programming languages. Can be written in one or a combination of programming languages, including traditional procedural programming languages. The program code is entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer, partly on the remote computer, or partly on the remote computer or server. Can be executed with. In the latter scenario, the remote computer can connect to the user's computer through any type of network, including local area networks (LANs) or wide area networks (WANs), or make connections to external computers (eg,). Can be done via the internet, using an internet service provider.
Aspects of the present invention will be described below with reference to flow diagrams and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It will be appreciated that the respective blocks of the flow diagram and / or block diagram, the combination of blocks in the flow diagram and / or block diagram, can be implemented by computer program instructions. These computer program instructions are sent to a general purpose computer, a dedicated computer, or another programmable data processor to generate one machine, thereby through the processor of the computer or other programmable data processor. It is possible to create a means by which an instruction to be executed performs a function / activity specified in one or more blocks of a flow diagram and / or a block diagram.
These computer program instructions, which can instruct a computer, other programmable data processor, or other device to function in a particular way, can also be stored in a computer-readable medium, thereby. , Instructions stored in a computer-readable medium that contain instructions to perform a function / activity specified in one or more blocks of a flow diagram and / or block diagram can be produced.
These computer program instructions are further loaded onto a computer, other programmable data processor, or other device, thereby a series on the computer, other programmable data processor, or other device. The operation steps of are performed, and the instructions executed on the computer or other programmable data processing device perform the process of performing the function / activity specified in one or more blocks of the flow diagram and / or block diagram. Can be configured.
Some embodiments of the present invention are described herein with reference to the accompanying drawings and images, which are merely examples. It should be noted that the details illustrated are exemplary and are intended for exemplary illustration of embodiments of the present invention, with particular reference to the drawings and images. In this regard, the description accompanying the drawings and images will clarify to those skilled in the art how embodiments of the present invention may be practiced.
<figref num="1">The figure which shows the original image and the flange filtered image processed by some exemplary embodiments of this invention.</figref><figref num="2">FIG. 5 showing a light-colored centerline overlaid on top of the original image of FIG. 1 according to some exemplary embodiments of the invention.</figref><figref num="3A">An image of a coronary vascular tree model produced by some exemplary embodiments of the invention.</figref><figref num="3B">Image of coronary vascular tree model in FIG. 3A, to which dendritic tags have been added by some exemplary embodiments of the invention.</figref><figref num="3C">A simplified diagram of a tree model of a coronary vascular tree produced by some exemplary embodiments of the present invention.</figref><figref num="4">Generated by an embodiment of the invention along a branch of the coronary vascular tree model shown in FIG. 3C as a function of the distance along each branch according to some exemplary embodiments of the invention. A series of nine diagrams showing the radius of a vascular segment.</figref><figref num="5">The figure which shows the coronary arterial tree model, the combination matrix which shows a dendritic tag, and the combination matrix which shows a dendritic resistance, which are all generated by some exemplary embodiments of the present invention.</figref><figref num="6">A tree model of the vasculature, with tags that number the exits of the tree model, generated by the embodiments of the examples of the invention, according to some exemplary embodiments of the invention, the tags correspond to streamlines. The figure which shows.</figref><figref num="7">Branch resistance R of each branch according to some exemplary embodiments of the invention<sub>i</sub>And the calculated flow rate Q of each streamline outlet<sub>i</sub>A simplified diagram of a vascular tree model generated by an embodiment of an example of the present invention, including.</figref><figref num="8">A simplified flow diagram showing FFR index generation according to some exemplary embodiments of the invention.</figref><figref num="9">Simplified flow chart showing another method of FFR index generation according to some exemplary embodiments of the present invention.</figref><figref num="10">A simplified flow diagram showing yet another method of FFR index generation according to some exemplary embodiments of the invention.</figref><figref num="11">A simplified drawing of a vasculature with stenotic and non-stenotic vessels, as associated with some exemplary embodiments of the invention.</figref><figref num="12A">A simplified diagram of a hardware implementation of a system for vascular evaluation constructed by some exemplary embodiments of the invention.</figref><figref num="12B">A simplified diagram of another hardware implementation of a system for vascular evaluation, constructed by some exemplary embodiments of the invention.</figref><figref num="13">A flow diagram illustrating an exemplary overview of steps in vascular model construction according to some exemplary embodiments of the invention.</figref><figref num="14">A flow diagram illustrating an exemplary overview of the details of the steps in vascular model construction according to some exemplary embodiments of the invention.</figref><figref num="15">Schematic of an exemplary arrangement configuration of imaging coordinates for an imaging system according to some exemplary embodiments of the present invention.</figref><figref num="16">A simplified flow diagram of a processing operation involving anisotropic diffusion according to some exemplary embodiments of the present invention.</figref><figref num="17A">A simplified flow diagram of a processing operation including motion compensation according to some exemplary embodiments of the present invention.</figref><figref num="17B">A simplified flow diagram of a processing operation, including alternative or additional methods of motion compensation, according to some exemplary embodiments of the invention.</figref><figref num="18A">FIG. 5 illustrates a mode of calculation of a "heart shell" constraint for ignoring bad ray crossings from a calculated correspondence between images, according to some exemplary embodiments of the invention.</figref><figref num="18B">FIG. 5 illustrates a mode of calculation of a "heart shell" constraint for ignoring bad ray crossings from a calculated correspondence between images, according to some exemplary embodiments of the invention.</figref><figref num="18C">A simplified flow diagram of a processing operation, including constraining pixel correspondence within a volume near the surface of the heart, according to some exemplary embodiments of the invention.</figref><figref num="19A">The figure which shows the identification of the homology between blood vessel branches by some exemplary embodiments of this invention.</figref><figref num="19B">The figure which shows the identification of the homology between blood vessel branches by some exemplary embodiments of this invention.</figref><figref num="19C">The figure which shows the identification of the homology between blood vessel branches by some exemplary embodiments of this invention.</figref><figref num="19D">The figure which shows the identification of the homology between blood vessel branches by some exemplary embodiments of this invention.</figref><figref num="19E">A simplified flow diagram of a processing operation involving identifying homologous regions along a blood vessel branch according to some exemplary embodiments of the invention.</figref><figref num="20A">A simplified flow diagram of a processing operation, including selecting projection pairs along a blood vessel centerline, according to some exemplary embodiments of the invention.</figref><figref num="20B">Schematic representation of the epipolar determination of a 3-D target position from a 2-D image position and its geometric relationship in space, according to some exemplary embodiments of the invention.</figref><figref num="21">A simplified flow diagram of a processing operation, including generating an edge graph and finding a connection path along the edge graph, according to some exemplary embodiments of the invention.</figref><figref num="22">A simplified diagram of an automated VSST scoring system according to some exemplary embodiments of the present invention.</figref><figref num="23">The figure which shows the exemplary branching structure which has a branch which rejoins according to some exemplary embodiments of this invention.</figref><figref num="24">Brand Altman plot as a function of the average of the difference between the FFR index and the image-based FFR index, according to some exemplary embodiments of the invention.</figref>
The present invention relates to vascular modeling in some of those embodiments, and more specifically, without limitation, real-time exponents related to vascular function and diagnosis-eg, catheter insertion imaging. During the execution of-relates to the use of vascular models to generate.
A broad aspect of some embodiments of the present invention relates to calculating the blood flow reserve ratio (FFR) based on imaging a portion of the vascular system.
One aspect of some embodiments of the present invention relates to the calculation of a model of blood flow in a subject. In some embodiments, the portion of the vascular system imaged is a coronary vessel. In some embodiments, the vasculature is an artery. In some embodiments, blood flow is modeled based on vessel diameter in 3-D reconstruction of the vascular tree. As appropriate, vascular resistance is determined based on vessel diameter. As appropriate, vascular resistance is calculated for the stenotic vessel and for the crown of the vessel (the vessel downstream of the stenotic vessel). In some embodiments, the FFR is calculated from a vascular tree, eg, a general 3-D reconstruction of a vascular tree reconstruction from a CT scan. In some embodiments, the reconstruction is performed from the beginning, eg, from 2-D angiographic image data. As appropriate, a given vessel tree meets certain requirements for FFR calculation, for example by reducing the vessel width to a graphical representation as a function of vessel expansion.
One aspect of some embodiments of the invention is the difference in flow rate between a vascular model of a vasculature with potentially stenosis and a different vascular model derived from and / or homologous to the stenotic vasculature model. It is related to the calculation of FFR based on. In some embodiments, the modification to the non-stenotic version of the vascular model is for wall openings (dilations) within the stenotic region based on reference width measurements obtained in one or more other parts of the vasculature. Including decisions. In some embodiments, the reference width measurement result is obtained from the vessel portion on either side of the stenosis. In some embodiments, reference width measurements are obtained from vessels that are naturally non-stenotic in a branch order similar to the stenotic segment.
In some embodiments of the invention, the FFR index is replaced by a model with a potentially constricted vascular segment and said segment with a lower flow resistance segment and / or resistance to flow by said segment. It has a flow rate ratio to the removed model. The potential advantage of determining this ratio is that the index is the effect of potential therapeutic treatment on the vascular system, the opening of the vascular region by percutaneous coronary intervention (PCI), such as stenting. It is a point that has an expression. Another potential advantage of this ratio is well accepted as an indicator of the need for angiogenesis, but in the art requires direct access to both sides of the stenotic lesion. It is a point to measure a parameter (blood flow reserve ratio) generally determined by invasive pressure measurement.
A broad aspect of some embodiments of the invention relates to the generation of vascular tree models.
One aspect of some embodiments of the present invention relates to the construction of a tree model of some of the mammalian vasculature based on the automatic matching of features that are homologous between multiple vascular images. In some embodiments of the invention, the tree model comprises a vascular segment centerline. As appropriate, the homology matching is between the vascular segment centerline and / or a portion thereof. In some embodiments, the modeled spatial relationship between the vascular segment centerlines comprises an association of segment ends at branch nodes.
The potential advantage of using vascular segment centerlines and / or other features that are easily identifiable from the vascular segment data in the image is that they have several pairs in 3-D space based on the imaging configuration. The point is that it provides a rich "meta-feature" that allows the ray crossing test to be taken by back-projecting rays from (or more) individual images. In some embodiments, exact ray crossing is not required, and crossing within the volume is sufficient to establish homology. The isolated features are potentially useful for such cross-based homology discrimination, while the expanded features of the pathway along the vascular segment (eg) for further refinement of the initial potential pseudo-homology discrimination. Note that it allows the use of correlation and / or constraint techniques in some embodiments. Therefore, ray crossing, in some embodiments, replaces the manual identification of homologous features in different vascular projections.
In some embodiments of the invention, the modeled vasculature comprises the vasculature of the heart (cardiovascular system), in particular the vasculature of the coronary arteries and their branches. In some embodiments, the tree model comprises 3-D location information with respect to the cardiovascular system.
One aspect of some embodiments of the present invention is based on and / or through coordinates defined by the features of the vasculature itself in a model of the cardiovascular system (and in particular 3- D Spatial position). In some embodiments, the same vascular features (eg, vascular centerlines) both define the 3-D space of the model and, in addition, include the backbone of the model itself. As appropriate, the centerline is represented according to its 3-D position in space, as well as a position in graph space defined by a vascular tree with connecting segments of the node's centerline. In some embodiments, the vascular segment comprises data associated with a vascular pathway connecting the two branch nodes (eg, vascular centerline).
In some embodiments of the invention, the "consensus" 3-D space defined by matching between vascular feature positions is the result of tree model construction.
The potential advantage of this vascular center modeling approach is related to the constant movement of the heart (where the vascular system is mechanically connected). In some embodiments, the vasculature model is constructed from a series of 2-D images taken sequentially. During cardiovascular imaging and / or between imaging positions, the region of the vasculature is potentially a calibrated position (absolute and / or relative) within its actual and / or 3-D space. ) Is changed. This is due, for example, to heartbeat, respiration, voluntary movements, and / or misalignment in determining the image projection plane. In some embodiments, the imaging protocol is modified to compensate for some of these movements, for example, by synchronizing the moment of imaging to a particular phase of the cardiac cycle (eg, the end of diastole). However, due to, for example, the natural fluctuations of the cardiac cycle, the effects of different out-of-period physiological cycles (heart and respiration), and the limitation of the time period for available imaging, errors are potential after this. Remain in. Therefore, there is potentially no "natural" 3-D space in common with raw 2-D image data. By targeting the consensus space, it is potentially possible to reconstruct the modeling problem with respect to the consistency of the modeling results.
The 3-D position changes, but other features of the vascular position, such as connectivity along the vascular system and / or region ordering, are invariant with respect to motion artifacts. Therefore, it is a potential advantage to use the characteristics of the vascular system itself to determine the frame of reference in which 3-D reconstruction can be established. In some embodiments, a feature based on 3-D reconstruction comprises a 2-D centerline of vascular segments present in multiple images in which homology is established by an automatic, appropriately repetitive method. The potential advantage of using the centerline as the basis for 3-D modeling is that the centerline that secures the construction of the model tree can also be used independently as a 1-D coordinate system. Therefore, the centerline can be used as the basis for reconstruction to ensure the consistency and / or continuity of the tree model features associated with the centerline position.
In some embodiments, other features related to the vasculature are used as landmarks, such as points of minimum vascular width, vascular bifurcations, and / or vascular origins. As appropriate, vascular features such as centerlines are transformed (without themselves being the target of cross-image matching) with conversion to landmark features before being incorporated into the vascular tree model.
One aspect of some embodiments of the present invention uses repetitive projection and back projection between the 2-D and 3-D coordinate systems to bring the 2-D image plane to the 3-D coordinate of the target coordinates. D Involved in reaching the consensus coordinate system associated with the system.
In some embodiments of the invention, the assignment of consensus 3-D positions to landmark vascular features (eg, vascular centerlines) projected from a single target area onto multiple 2-D images during imaging is It features a reprojection and / or reregistration of the 2-D image itself and better matches the "consensus" 3-D space. As appropriate, reprojection assigns a different image plane to the 2-D image than was originally recorded. As appropriate, reregistration comprises non-linear distortion of the image, for example, to compensate for cardiac deformation during imaging. Reprojection and / or re-registration is performed iteratively, as appropriate, for example, by defining different image groups as "goals" and "matching" in different feature registration iterations. In some embodiments of the invention, different numbers of images are used to define homologous features and for subsequent analysis of additional image features (such as vessel width) to which the homologous features are associated. ..
One aspect of some embodiments of the invention relates to reducing the complexity of calculating tree decisions, which allows faster processing to reach clinical conclusions.
In some embodiments, some of the image data (eg, "non-feature" pixel values) is appropriately maintained in a 2-D representation without the need for a complete 3-D reconstruction. In some embodiments, the calculation of 3-D positions of non-landmark features, such as vessel wall positions, is thereby avoided, simplified, and / or postponed. In particular, in some embodiments, the vessel edge is recognized from the direct processing of 2-D image data (eg, including examination of the image gradient perpendicular to the vessel centerline). As appropriate, the determined edges are projected into 3-D space (eg, perpendicular to the 3-D centerline position) without the need to project the original image pixel data into a 3-D voxel representation. Represented as one or more radii that extend to).
In addition or alternative, vessel wall location is determined and / or processed within one or more "1-D" spaces defined by a frame of reference with a position along the centerline. (For example, to determine vascular resistance). As appropriate, this process is independent of, for example, the projection of wall position into 3-D space. In some embodiments, the complexity of the calculation is further reduced by reducing the model to the 1-D function of the centerline position, for example, to determine the vascular flow characteristics.
One aspect of some embodiments of the invention relates to relationships between vascular model components with different dimensions. In some embodiments, 1-D, 2-D, and / or 3-D positions with non-positional or partial non-positional characteristics, and / or logical connectivity, and / or characteristics are direct functions. And / or indirectly related to each other through an intermediate frame of reference.
In some embodiments, for example, the vascular model comprises one or more of the following features:
2-D images with positions in 3-D space defined by the relationships between homologous features in, one or more vascular properties, such as diameter, radius, flow rate, flow resistance, and / or curvature. Vessel spread with one or more 1-D axes for a function of, vascular spread with one or more 1-D axes for a function of position in 3-D space, position along the vascular spread Connectivity between vascular spreads, 2-D images that map the 1-D axes of vascular spreads, described as nodes for (for example, nodes connecting the ends of vascular segments), on one axis 2-D frame with vascular spread along, and image data orthogonal to vascular spread along the second axis.
A broad aspect of some embodiments of the invention relates to the real-time determination of a vascular tree model and / or its use to provide clinical diagnostic information while a catheter insertion procedure is in progress for a subject.
One aspect of some embodiments of the present invention relates to utilizing real-time automatic vascular status determination to interactively manipulate a clinical diagnostic method as it progresses. The real-time determination comprises, in some embodiments, a determination within the time frame of the catheter insertion procedure, eg, 30 minutes, 1 hour, or less, more, or intermediate time. More specifically, the real-time determination comprises determining the catheter insertion procedure and / or timing just right to influence the outcome, starting from the image on which the vascular condition determination is based. For example, selecting a specific part of the vascular tree for the initial calculation is a potential advantage, and the calculation is short enough to influence the decision to perform a particular PCI procedure, such as stent implantation. Is likely to be completed. For example, a 5 minute delay to the calculation of an FFR with two main vessel branches calculates the first branch when the first branch appears to be particularly important based on the results of a rough review of the image data. By choosing to be the initial stage of 2. It can be reduced to a delay of 5 minutes. In addition, or alternative, if the calculation is fast, the FFR results can be updated once or multiple times during the catheterization procedure. For example, in the first stent implantation, the perfusion status at other sites is sufficient to trigger a self-regulating change in vessel width, which can potentially alter the expected effects of subsequent stent implantation. change. It can also be compared, for example, with the expected effect on the image of the actual stent implantation on the vessel width, thereby verifying that the desired effect on the flow volume is achieved. Some embodiments of the invention allow interface control of vascular models and / or how vascular properties are calculated, control model updates based on newly available image data, and /. Or it is configured to select a comparison between actual and / or predicted vascular condition models.
One aspect of some embodiments of the present invention relates to the construction of a vascular tree model suitable for the target prediction of potential clinical intervention outcomes. As appropriate, the clinical intervention is a PCI procedure such as stent implantation. In some embodiments of the invention, the goal is to focus on the stage of vascular tree model building to lead to pre- / post-results regarding vascular parameters that are directly available for clinical modification. .. In some embodiments, the vascular parameter is vascular width (eg, modifiable by stenting). The potential advantage of focusing modeling on determining the difference between pre- and post-treatment states of the vasculature offsets (and / or / or) the effect of model modification by approximation of other vascular details. The size is reduced). In particular, they have potential importance for operational concerns such as "Does the changes brought about by the intervention usefully improve the clinical situation regarding the known effects of the variables targeted by the intervention?" Is reduced. As a potential result, calculations that would otherwise be performed to fully model the functional and / or anatomical properties of the vasculature may be omitted. Potentially, this increases the rate at which the flow index can be generated.
One aspect of some embodiments of the invention is a framework for structuring one or more selected, clinically relevant parameters (such as vessel width, flow resistance, and flow itself). It is involved in the formation of model representations of vascular targeting. In some embodiments, the structure comprises a vascular dilatation approach to modeling, where position along the vascular segment defines the frame of reference. Optionally, the frame of reference for vascular spread comprises a division between branches linked to the nodes of the vascular tree. Potentially, this comprises a dimensional reduction that reduces calculation time.
In some embodiments, the 3-D position model in the vascular model is formed from potentially incomplete or accurate initial position information. This is achieved, for example, by annealing to a self-consistent framework by an iterative process of adjusting location information to improve consistency between the acquired data. Adjustments include, for example, transforming the image plane, deforming the image itself to increase similarity, and / or ignoring outliers that interfere with consensus decisions. Potential alternatives that seek to ensure the fidelity of the framework to a particular real-world configuration (eg, one or more "real" 3-D configurations of parts of the vasculature in space) The target approach performs a large amount of calculations on the benefits gained for estimating the target parameters. In contrast, frameworks that emphasize internal consistency in services that support calculations related to target parameters can potentially reduce computational load using a consensus-like approach. In particular, this approach is potentially suitable for combination with the calculation of changes in the vascular system, as explained above.
Prior to elaborating at least one embodiment of the invention, the invention is described in its application examples in the following description and / or the structural details and components and / or methods shown in the drawings. It will be understood that it is not necessarily limited to the arrangement of. The present invention may utilize other embodiments, or may be practiced or practiced in various ways.
Note that the coronary vascular system, and more specifically the coronary arterial system, is used in the exemplary embodiments described below. The examples are not meant to limit embodiments of the invention to coronary arteries, and embodiments of the invention potentially apply to other vascular systems, such as the venous and lymphatic systems. ..
In some embodiments, a first model of blood flow within the subject is constructed based on imaging the subject's vascular system. Typically, the first model is constructed from a vascular system that includes problem segments of the vascular system, such as stenosis in at least a portion of the blood vessel. In some embodiments of the invention, the first model corresponds to a portion of the vasculature that includes at least one blood vessel with a stenosis. In these embodiments, the first model describes a portion of the vasculature that includes at least one vessel with a stenosis and a crown. In these embodiments, the first model optionally includes information relating to the shape and / or volume of the crown and information relating to blood flow and / or resistance to blood flow in the stenotic vessel and / or crown. Including further.
Typically, but not always, a second model is built. The second model, as appropriate, describes at least a partially healthy vasculature corresponding to the first model. In some embodiments, the second model is constructed by changing the stenosis of the first model to a more open state, as would be the case if the stent opened the stenosis. In one embodiment, the second model selects a segment of the subject's vasculature that contains healthy vessels that resemble the problematic vessels of the first model and uses it to replace the stenotic vessels. It is built by things.
The construction of the blood vessel model will be described below.
In some embodiments, an index is calculated that indicates the need for revascularization. This can be done based on the first model or the result of a comparison of the first and second models of blood flow. The index is appropriately used in the same manner as the pressure measurement derived FFR index, which causes the stenotic vessel to flow into the vasculature, which inflates the prognostic diagnosis for improvement of the subject's condition after stenotic vessel swelling. Evaluate whether the effect affects the incidence of complications that result from itself.
The terms "FFR" and "FFR index" in all grammatical forms are used throughout this specification and claim to represent the indices described above, and in the background art section, a small pressure transducer over the stenosis. It does not represent only the FFR index, which is referred to as an invasive measurement with the insertion of a guide wire equipped with. In some cases-especially when differences between certain types of FFRs and FFR-like indices are explained-subscripts are used to distinguish them, for example, for FFRs derived from pressure measurements. Is FFR<sub>pressure</sub>, And / or FFR if FFR is represented with respect to flow determination<sub>flow</sub>Is used.
Acquisition of Data for Building a Vascular Model In some embodiments, the data for modeling the vascular system comprises medical imaging data.
In some embodiments of the invention, the data is from a minimally invasive angiographic image, eg, an X-ray image. In some embodiments, the angiographic image is two-dimensional (2-D). In some embodiments, 2-D angiographic images taken from different viewing angles are combined to include, for example, three-dimensional (3-D) data from a viewing angle of 2, 3, 4, or more. To generate.
In some embodiments, the data is data from a computed tomography (CT) scan. It should be noted that with today's technology, angiographic images achieve finer resolution than CT scans. Models of the vasculature constructed based on angiographic images are potentially more accurate than models based on CT scans, whether they are one-dimensional (1-D) tree models or full 3-D models. And potentially provides a more accurate vascular assessment.
Speed of Results An object in some embodiments of the invention relating to real-time use is the fast calculation of vascular models and the fast calculation of anatomical and / or functional parameters thereof, thereby providing real-time diagnostic intent. Return feedback for decisions.
In some embodiments of the invention, feedback regarding making an intervention decision (eg, in a particular area or all) is provided in three broad categories: "intervention.<u style="single">Suggestion</u>, "Do not intervene<u style="single">Suggestion</u>",and"<u style="single">Suggestion</u>It can be divided into "none". As appropriate, feedback will be presented in such a format. Classification as appropriate is itself a graph, category description, and / or another output with multiple output states, continuous range output states, or any number of states in between. Performed by a doctor, based on the index provided. Moreover, in some embodiments of the invention, diagnostic feedback is readily relevant to indices already established in the field, such as scoring methods such as FFRpressure, SYNTAX scores, or alternative methods of vascular evaluation. By generating an index that is attached (and potentially interchangeable with it), it is associated with and / or easily relevant to clinical outcomes.
In some embodiments of the invention, vascular tree construction is optimized for the generation of vascular segment pathways, eg, vascular segment centerlines. From this stage (or from the results of another process that produces a vascular tree where the location of vascular spread is easily determined), the calculation for the determination of one or more diagnostically significant indices is an appropriate index. Potentially very fast as long as the goal is sought.
Another object in some embodiments of the invention relating to real-time use with respect to the selection of appropriate index goals is to generate a diagnostic index that is sufficiently accurate to be used as a clinical decision-making tool. However, it is the use of flow parameters that can be calculated very quickly given a vascular tree. One aid to obtaining such an index is that, in some embodiments, deep vascular trees (3, 4, or more branches) are available, thereby resulting in a large spread of the vascular network. Resistance to overall flow can be calculated with respect to the effect on flow through a particular segment in both narrowed (narrowed) and non-stenotic (spreaded) conditions. In some embodiments, X-ray angiographic images are constructed as described herein, but are potentially available from other imaging methods such as rotary angiography and / or CT angiography. A well-defined vascular tree, which is constructed as it is, is used as an input for image-based FFR calculations. "Clearly defined" comprises having, for example, 3, 4, or more vascular bifurcation depths. In addition or alternatively, "clearly defined" is, for example, 5%, 10%, 15%, or another larger, smaller, or intermediate range of true vessel widths. It has sufficient imaging resolution to model vessel width with internal accuracy.
In some embodiments of the invention, treatment<u style="single">Suggestion</u>Focusing on the generation of images guides the selection of image analysis methods, which makes it easier to provide fast diagnostic feedback. In particular, in some specific embodiments, the goal is to perform an analysis of whether a particular angiogenic intervention restores clinically meaningful blood flow. When creating a vascular model, it is a potential advantage to focus on modeling measurable parameters that target changes in clinical intervention, which is the effect of the proposed treatment (if any). It is because of these changes that you can feel. Moreover, such concentration allows, as appropriate, simplification and / or neglect of unchanged and / or equivalent parameters, at least to the extent that they do not affect the desired outcome of treatment. .. Thus, for example, potentially any dynamic flow modeling does not need to reach the diagnostic index of vascular function.
In some embodiments of the invention, it is useful for PCI and / or CABG (Coronary Artery Bypass Transplantation).<u style="single">Suggestion</u>An analysis sufficient to generate an analysis comprises the analysis of one or more features that are easily determined as a local function of 1-D parameters such as vascular segment location. For example, vascular resistance is affected by many variables that can be potentially treated by careful consideration of the fluid dynamics of the system, but has a strong dependency on the variable of vessel diameter. Vascular diameter is then the goal of treatment options such as stent implantation. In addition, the vessel diameter itself (and / or related metrics such as vessel radius, cross-sectional area, and / or cross-sectional profile) can be calculated at high speed from image data along a pathway with a description of vessel segment location.
In addition, the potential benefits of vascular models that are optimized for centerline determination are that, for example, less clinically significant details, such as calculations related to vessel wall shape, are avoidable and / or The point is that it can be postponed. In some embodiments, the vessel centerline constitutes the central framework of the final model. The same vessel centerline (and / or approximations thereof) is a landmark in one phase of the process of constructing a 3-D coordinate system where the 2-D image in which the 3-D vessel tree is modeled is registered. It is a potential advantage to use as a feature that results in. Potentially, this eliminates the need to determine a second feature set. Potentially, using the same features set for both the registration and the model basis avoids some calculations, as this reduces the asymmetry between the registration features and the model features. , Inconsistencies due to image artifacts are eliminated.
In some embodiments of the invention, a relatively modest computing resource (eg, a PC with a commercially available multi-core CPU and four midrange GPU cards-corresponding to about 8-12 teraflops of raw computing power). By using, the complete processing period from the receipt of the image to the availability of diagnostically useful metrics such as FFR is about 2 to 5 minutes. Using this type of equipment on a 5 minute time scale, in some embodiments, centerline division of about 200 input images takes about 0.5 minutes in processing time and about conversion to a 3-D model. 4 minutes, about 10-30 seconds for the remaining tasks such as FFR calculation, which depends on the calculated tree spread. Note that further reductions in processing time are expected as long as the typical processing capacity cost per teraflop continues to decrease. In addition, the division of processing tasks into multiprocessors and / or multicores can, of course, be achieved by dividing the work along vascular boundaries, for example, by dividing the work into several processing resources based on spatial location. .. In some embodiments of the present invention, the calculation for reconstructing the vascular tree and calculating the flow index comprises less than about 1 K. In some embodiments, the calculation comprises less than about 5,000 trillion, 2,000 trillion, 1,000 trillion, 500 trillion, or intermediate, greater than, or lesser number of operations.
Another object in some embodiments of the present invention is the integration of automatic vascular parameterization from imaging to clinical workflow. In some embodiments, this integration is interactive in that it provides an interaction between the results of the automatic imaging process and / or control and other aspects of the catheter insertion procedure when the procedure is in progress. Is. For example, in some embodiments of the invention, medical professionals manually say that one of the two branches of the vascular tree is a likely first candidate for vascular intervention, such as PCI. It can be decided from a rough inspection by. In some embodiments of the invention, the first candidate branch can be selected so that, for example, the process of determining the FFR index for that branch completes faster than the calculation for the second branch. Potentially, this allows decision making to be made earlier and / or with shorter interruptions in the procedure being performed on the patient.
In some embodiments of the invention, the tree treatment is fast enough that two, three, or more imaging methods can be performed and analyzed within the course of a single session with the patient. is there. A single session comprises, for example, an intervention that opens a stenosis within it, for example, a period in which part of the catheter and / or guide wire remains in part of the vascular tree, this time. Is, for example, 30 minutes to 1 hour, or a shorter, longer, or intermediate time. FFR<sub>pressure</sub>Is typically determined, for example, in conjunction with an injection of adenosine to maximize the patient's vascular system. However, the safe frequency of adenosine injections is limited, and therefore methods of determining an index equivalent to FFR without such injections offer potential benefits. The second imaging session is potentially valuable, for example, to verify the results of stent implantation, which is commonly performed at the level of positioning verification for current stent implantation. Potentially, vascular self-regulation after stenting results in changes in vessel width, which allows the second imaging session to advise further stenting and / or remain advisable. Can help determine if.
In some embodiments, the results of the intensive steps of the calculation can be used as the basis for further image-based recalculations and / or exponential recalculations. For example, an already calculated vascular tree can be used as the basis for registration of one or more images of the vascular system after implantation without the need to reacquire a complete image set.
Some embodiments of the invention provide a user interface to a computer, eg, a graphical user interface such that one or more interactive user commands are supported. As appropriate, for example, one or more user commands can be used to focus the image processing target on one or more selected branches of the subject's vascular system. As appropriate, one or more commands are available to modify one aspect of the vascular model (eg, to model the non-stenotic state of a stenotic vessel). To select and / or compare vascular models from multiple image sets as appropriate (eg, image sets taken at completely different times in the procedure and / or images with a display of the heart at different heart rate periods). One or more commands are available.
Features of some exemplary vascular models In some embodiments of the invention, the vascular model comprises a tree model, optionally a 3-D tree model. However, the spatial dimensions of the model are appropriately adjusted at different anatomical levels and / or processing steps to meet the requirements of the application. For example, 2-D images are appropriately combined to extract 3-D vascular tree information that allows identification and construction of 1-D vascular segment models. The 1-D segment model is then logically linked, in some embodiments, according to its connectivity, with or without preserving other spatial relationship details. In some embodiments, the spatial information is compressed or encoded, for example, by approximating the cross-section region with parameters of circle (diameter), ellipse (major / minor axis), or other representation. In some embodiments, the region along the vascular tree is non-spatial information such as flow resistance, calculated flow rate, elasticity, and / or sampled and / or expanded vascular segment region, and / or It has other dynamic or static properties associated with the nodes of the vascular tree.
In some embodiments, the tree model comprises a tree data structure with nodes linked by curved segments. Nodes are associated with vascular branches (eg, bi-branch or tri-branch or multi-branch), and curved segments are associated with vascular segments. The curved segment of the tree is also referred to below as the branch, and the entire tree portion distal to the branch is referred to as the crown. Thus, the tree model comprises a description of the vascular system in which, in some embodiments of the invention, the nodes of the tree are assigned to vascular branches and the branches of the tree are assigned to the vascular segments of the vascular system.
In some embodiments, sample points along the branches are associated with vessel diameter information. In such an embodiment, the trees are linked together to form a 3-D structure containing information related to local size, shape, branching, and other structural features at any point in the vascular tree. Can be thought of as being represented as a series of discs or poker chips (eg, circular or oval discs).
In some embodiments, the tri-branch and / or multi-branch is systematically transformed into a combination of bi-branches. As appropriate, for example, the tri-branch is transformed into two bi-branches. It is claimed that the term "branch" in all grammatical forms is used throughout this specification to mean bi-branch, tri-branch, or multi-branch.
In some embodiments, the tree model comprises characteristic data associated with sample points along each branch in the model and / or aggregated for the entire branch and / or for its extensions. Characteristic data include, for example, arrangement, orientation, cross section, radius, and / or diameter of blood vessels. In some embodiments, the tree model comprises flow characteristics at one or more of these points.
In some embodiments, the tree model comprises geometric data measured along the vascular centerline of the vasculature.
In some embodiments, the vasculature model comprises a 3-D model, eg, a 3-D model that can be obtained from a CT scan and constructed from a series of 2-D angiographic images taken from different angles.
In some embodiments, the vasculature model comprises 1-D modeling of vascular segments along the centerline of a series of vessels in the vasculature.
In some embodiments, the vasculature tree model comprises data for a segment represented by 1-D that describes the segment to be divided into two or more segments.
In some embodiments, the model has three-dimensional data associated with a 1-D aggregate of points, such as data about the cross-sectional area at each point, data about the 3-D orientation of the segment, and / or branching. Contains a collection of data along a segment of the blood vessel, including data on the angle of the part.
In some embodiments, the vasculature model is used to calculate a physical model of fluid flow, including physical properties such as pressure, flow rate, flow resistance, shear stress, and / or flow velocity.
Performing calculations for 1-D aggregates of points, such as calculating resistance to fluid flow, performs such calculations using a complete 3-D model that includes all voxels in the vascular system. Note that it is potentially quite efficient in comparison.
Calculation of Blood Vessel Model With reference to FIG. 13, this is a flow diagram illustrating an exemplary overview of the steps in vascular model construction according to some exemplary embodiments of the invention.
FIG. 13 is used as an overview of an exemplary vascular tree reconstruction method, first introduced as an overview and then described in more detail below.
In block 10, in some embodiments, images, eg, about 200 images, are acquired, eg, divided into four imaging devices. In some embodiments, the acquired image is obtained by X-ray angiography. The potential benefits of using X-ray angiography include the general availability of devices for stereoscopic X-ray angiography in catheterization rooms where diagnostic and interventional procedures are performed by state-of-the-art technology. .. X-ray angiographic images also potentially have a relatively high resolution compared to alternative imaging methods such as CT.
In block 20, in some embodiments, the blood vessel centerline is extracted. The vascular centerline has several properties that make this centerline a useful reference for other stages of vascular tree remodeling. The properties utilized in some embodiments of the present invention will optionally include:
The centerline is a feature that can be determined from a 2-D image, which allows individual images to be related to each other in 3-D with their use.
By definition, the vascular centerline is distributed throughout the imaging region of interest when the goal is to reconstruct a 3-D vascular model. Therefore, they are used as attractive candidates for reference points in the reconstructed imaging region.
The blood vessel centerline can be determined automatically, for example, based on easily divided image characteristics, without prior human selection, as described below.
The vascular centerline was taken from different perspectives, for example in the 2-D image itself and / or by back projection along the rays into 3-D space so that their homology can be easily identified. Even images are extended features that preserve sufficient similarity between images and are found in different image projections at ray intersections (and / or intersections between extended volumes based on back-projection rays). Identify homologous goals.
The spatial ordering of the samples along the centerline is preserved between the images, even though the centerline itself is distorted by viewing angles and / or motion artifacts. This further facilitates the comparison used, for example, for 3-D reconstruction.
The centerline provides a convenient reference system for organizing and / or analyzing features related to position along blood vessels. For example, by using the distance along the centerline as a reference, morphological features such as diameter and / or functional features such as flow resistance are represented as functions within a simplified 1-D space. obtain.
Centerline intersections provide a convenient means of describing vascular bifurcations, and / or vascular trees are treated separately from each other as appropriate, and / or further simplified, for example, for the purpose of functional analysis of flow characteristics. Divide into different segments.
In addition or alternative, in some embodiments, another type of image feature is identified. As appropriate, the image feature is, for example, the placement of the bifurcation of the vessel, the minimum radius within the constricted vessel (radius locally reduced compared to the surrounding vascular region). As appropriate, image features generally lack self-identity in translation in any direction (less than a predetermined threshold of self-identity, eg, always higher than, or always higher than, the threshold of intensity difference). Any composition of image pixels with a pattern of intensity (within the range of criteria for not being statistically significant), eg, a bend or bifurcation such as a corner.
In block 30, in some embodiments, a correspondence is found between the extracted vascular centerlines in individual 2-D images. These correspondences more generally indicate the relationship between 2-D images. In addition to that, or alternative, another feature that is generally identifiable within multiple 2-D images is the basis for finding correspondences. Such correspondence is generally not uniquely revealed by a priori-determined transformations from the imaging system and / or patient-related calibration information. The potential advantage of using the centerline to find the correspondence is that its most notable feature in the blood vessel image (the blood vessel itself) is the basis for the decision.
In some embodiments of the invention, the surface corresponding to the shape of the subject's heart uses, for example, a cardiovascular pattern to determine the projection of the heart surface onto a different 2-D image plane, and then the shell volume. It is defined by calculating. As appropriate, this surface is used as a constraint for the detection of corresponding image features. In some embodiments, image data constraints and / or other sources of additional information are used in the process of reconstructing the vascular tree. For example, one or more knowledge base (atlas-based) constraints can be applied, for example, by limiting recognized vessel positions to those within the range of expected vessel positions and / or branch composition. .. Also, for example, temporal information is the filling of the position along the vascular tree. It is available in some embodiments of the invention based on time). The filling time is used in some embodiments, for example, to determine and constrain relative vascular location (position along the extent of the vascular tree). In some embodiments, filling times are also used to establish homology between vascular features in different 2-D images (the same filling time is used at the vantage point of all images in the homologous arrangement). Should be seen). In addition, or alternative, filling times are used in some embodiments of the invention to constrain the vascular topology.
In block 40, in some embodiments, the vessel centerline is mapped to the 3-D coordinate system. In some embodiments, mapping is consistent with a set of optimization criteria, such as epipolar geometry constraints, and / or with vascular points for which 3-D positions have already been determined. It comprises identifying pairs of homologous centerline positions in different 2-D images that best meet the conditions of.
In block 50, in some embodiments, the vessel diameter is estimated. In some embodiments, the vessel diameter is calculated over the sample points of the selected 2-D projection and extrapolated over the entire circumference of the vessel. In some embodiments, the diameter over multiple projection angles is determined. In some embodiments, the projection is selected from a single acquired image, optionally an image in which the blood vessels are visible at their longest and / or without intersections. As appropriate, the projection is composited from two or more 2-D images.
Application of Vascular Trees The computational procedure of this embodiment potentially requires reduced computation for conventional techniques that employ computational fluid dynamics simulation and analysis. Computational fluid dynamics has been recognized to require substantial computational power and / or time. For example, if a fluid dynamics simulation is run on a standard PC, it will take several days as CPU time. This time is somewhat reduced by using supercomputers that apply parallel processing, but such computing platforms are generally not available for such dedicated use in medical facilities. The computational procedure of this embodiment is not based on hydrodynamic simulations and therefore does not require a supercomputer and is based on ordinary off-the-shelf components, eg, on a computing platform configured as a standard PC. Can be implemented in.
The inventors of the present invention have found that the tree model according to some embodiments of the present invention is less than 60 minutes or less than 50 minutes or less than 40 minutes or less than 30 minutes or 20 minutes since the 2-D image was received by the computer. We have found that it can be configured within minutes or less than 5 minutes or less than 2 minutes. This time is potentially dependent on the available computing resources, but the inventors are available with ordinary commercial computing hardware (eg, total computing power in the range of about 8-12 teraflops). It was found that the execution time of 2 to 5 minutes could be sufficiently reached.
This allows an efficient combination of calculation and treatment in some of this embodiment of the invention, where the tree model allows the subject to be placed on a therapeutic surface (eg, bed) for catheter insertion. Generated as appropriate while fixed. In some embodiments of the invention, the tree model is generated while the subject has a catheter in his vascular system. In some embodiments of the invention, the vasculature has at least one catheter other than an angiographic catheter (eg, a cardiac catheter or an intracranial catheter), where the image is taken while the catheter is in the vasculature. Is processed and a tree is generated.
The use of the calculated vascular tree is intended in clinical settings for further processing and / or decision making. A potential advantage of methods and / or systems for fast determination of vascular trees is that the patient being imaged can respond immediately for further procedures-perhaps as-is on the catheter insertion table-automatic assistance during Its usefulness in "real-time" applications that allow functional diagnostic and / or treatment decisions to be made.
Examples of such real-time applications include blood flow determination and / or vascular status scoring.
FFR In some embodiments of the invention, the model calculated from the original imaging data is treated as a "stenosis model", which potentially places the stenosis in the patient's vascular (cardiovascular) system. It is so called to reflect it. In some embodiments, this stenosis model is used to calculate an index of vascular function. The index can also indicate the need for revascularization. Representative examples of indices suitable for embodiments of the present invention include, without limitation, FFR.
In some embodiments, the index is calculated based on the volume of the crown or other vascular parameters in the stenosis model and the contribution of the stenotic vessel to resistance to blood flow within the crown. In some embodiments, the FFR index is the flow resistance of a stenotic vessel in a vascular model containing a stenotic vessel and the flow resistance of an expanded version of the same vessel in a similar vascular model in which the stenotic vessel is mathematically dilated. Calculated as a ratio.
In some embodiments, the index is calculated as the ratio of the flow resistance of a stenotic vessel within the vascular model to the flow resistance of adjacent similar healthy vessels within the vascular model. In some embodiments, this ratio has a different geometry between the constricted vessel and the adjacent vessel, as described in the section "Generating a model of the physical properties of the vascular system" below. Is multiplied by a constant that takes into account.
In some embodiments, a first tree model of the vasculature is generated based on actual patient measurements, optionally including constrictions in one or more arrangements of the patient's blood vessels, of the patient's vascular system. A second tree model is generated, appropriately modified so that at least one of the stenosis arrangements is modeled as after revascularization, and the index indicating the need for revascularization is in the first model. It is generated based on comparing the physical properties with the physical properties in the second model.
In some embodiments, actual pressure and / or flow measurements are used to calculate the physical properties of the model (s) and / or the exponents described above.
In some embodiments, actual pressure and / or flow measurements are not used to calculate the physical properties of the model (s) and / or the exponents described above.
It should be noted that the resolution of angiographic images is typically higher than the resolution typically obtained by 3-D techniques such as CT. In some embodiments, the model constructed from the higher resolution angiographic image is essentially of higher resolution, resulting in greater geometric accuracy and / or of smaller vessels than the CT image. Calculations that allow the use of geometric properties and / or use vascular branches distal to the stenosis for more generation or bifurcation downstream from the stenosis compared to CT images. to enable.
Vascular Condition Scoring In some embodiments of the invention, automatic determination of parameters based on vascular images is used to calculate a vascular disease score. In some embodiments, the imaged blood vessel is a cardiovascular vessel.
In some embodiments of the invention, the heart disease score is calculated according to the SYNTAX score calculation method. In some embodiments, the heart disease score is calculated by an alternative, derivative, and / or successor vascular condition scoring tool (VSST) of the SYNTAX score. Alternative VSST approaches potentially, for example, SYNTAX the "functional SYNTAX score" (physiological measurements-eg, another measure of blood flow capacity, vascular elasticity, vascular self-regulating capacity, and / or vascular function). Includes (integrate with score-like tools) or "clinical SYNTAX scores" (integrate clinical variables-eg, patient history and / or systemic and / or organ-specific test results-with SYNTAX score-like tools). Examples are AHA classification of the coronary tree segments modified for the ARTS study, Leaman score, ACC / AHA lesion classification system, total occlusion classification system. (total occlusion Also includes a classification system) and / or a Duke and ICPS classification system for bifurcation lesions.
In some embodiments, the 2D image from the angiography procedure is converted to a 3D image, the lesion in the blood vessel is identified, entered as a VSST parameter, and into a fast objective SYNTAX score during the procedure. To reach. In some embodiments, the VSST parameters are determined directly from the 2D image. Thus, for example, a 2-D image having a determined spatial relationship with, and optionally with, the vascular segment identified in the 3-D vascular model, is identified in the vascular model (and as appropriate). The vascular geometry properties that are subsequently linked to positions in the vascular segment) are analyzed.
In some embodiments of the invention, the automatically determined values are supplied as parameters to the VSST, such as the SYNTAX score, in real time during the catheter insertion procedure or after imaging.
Potentially, the time reduction in VSST calculation can be achieved by allowing the patient to remain catheterized for possible PCI (percutaneous coronary intervention) treatment while waiting for a shorter period of time, and / or treatment decision. It has the advantage of reducing the need for recathetering of patients who are temporarily released from the operating room holding the patient. Potentially, reduced scoring time and / or effort leads to increased use of VSST, such as SYNTAX scores, as a tool for clinical decision making.
Generating a Geometric Model of the Vascular System Image Acquisition Then with reference to FIG. 14, this provides an exemplary overview of the details of the steps in vascular model construction, according to some exemplary embodiments of the invention. It is a flow chart to be done. Details are also described in the additional diagrams referenced in the process of sequentially executing the blocks of Figure 14 below.
At block 10, multiple 2-D data images are acquired. In some embodiments of the invention, the data image is simultaneously acquired from a plurality of vantage points, such as 2, 3, 4, or more vantage points (cameras) for imaging. In some embodiments, the image is acquired, for example, at a frame rate of 15 Hz, 30 Hz, or another, lower, higher, or intermediate frame rate. In some embodiments, the number of frames acquired for each vantage point for imaging is approximately 50 frames (200 frames total for four vantage points for imaging). In some embodiments, the number of frames per vantage point for imaging is, for example, 10, 20, 40, 50, 60, 100, or another, larger, smaller, or intermediate number. Is. In some embodiments of the present invention, the number of heartbeat cycles included in the imaging period is about 3-4 heartbeat cycles. In some embodiments, the number of cardiac cycles is, for example, 3-4, 3-5, 4-6, 5-10, or another range with the same, smaller, larger, or intermediate range boundaries. Heart rate cycle.
Then with reference to FIG. 1, this shows the original image 110 and the flange filtered image 120 processed by some exemplary embodiments of the invention.
The original image 110 shows a typical angiographic 2-D image.
When using two or more 2-D projections of a subject's blood vessels, for example cardiovascular, two or more 2-D projections should be performed simultaneously or at least during the same period of the heartbeat cycle. Note that is a potential advantage and therefore the 2-D projections are of the same vessel shape.
Deviations between 2-D projections can result from heart and / or respiration and / or patient movement between 2-D projection frames.
In some embodiments, the ECG output is used to select the same cardiac phase within a 2-D projection frame to reduce deviations that may result from a lack of cardiac phase synchronization.
In some embodiments, another cardiac / pulse synchronization means, such as an ECG output, or a visible light pulse monitor, provides a 2-D projection frame to reduce deviations that may result from a lack of cardiac synchronization. Used to select the same cardiac phase within. As appropriate, cardiac synchronous outputs are recorded with a time scale, and the corresponding time scales are used to record when images of the vascular system are captured. In some embodiments of the invention, the time of acquisition with respect to the cycle of physiological kinetics is used to determine candidates for mutual registration. For example, image registration is optionally performed using an image dataset containing images taken in periods near the heart rate cycle. In some embodiments, registration is performed multiple times across different sets of period-adjacent datasets, so that registered landmarks are iteratively transformed into a common 3-D coordinate system with respect to position. Will be done.
In some embodiments, the 2-D projection frame is selected to be the end of diastole of the cardiac cycle. In some embodiments, the temporal and / or temporal order in which the 2-D projection frames are acquired is used to perform registration between the images captured in the periods of adjacent movement cycles. In some embodiments, the image that has been registered from the first period to the second period is then reregistered into the third and / or further period, thereby. Images taken in widely separated periods of the heart rate cycle can be registered against each other.
In some embodiments, the heart is imaged under the influence of intravenous adenosine, which potentially exaggerates the difference between the normal and abnormal segments. As appropriate, imaging with and without adenosine potentially allows the determination of the (vasodilatory) effect of adenosine itself and thus provides information on vascular compliance and / or self-regulatory status.
Extraction of Centerline Next, referring to FIG. 15, it shows a schematic representation of an exemplary arrangement configuration 1500 of imaging coordinates for an imaging system, according to some exemplary embodiments of the present invention.
Several different spatial relationships of the imaging arrangement configuration are used in determining the 3-D relationship of the image data in the 2-D image set.
In some embodiments, the image coordinate systems 1510, 1520, and the associated image planes 1525, 1530, describe how images taken of the same subject at different positions relate to each other. , That information is used to reconstruct 3-D information about the subject. In some embodiments of the invention, these coordinates reflect the axis of C-arm rotation of the angiographic imaging device. In some embodiments, the coordinate plane 1515 of the subject (eg, lying on bed 1505) is also used as part of the 3-D reconstruction.
This system configuration information is typically documented in DICOM (image) files and / or elsewhere, but with sufficient accuracy and / or accuracy for useful reconstruction of the coronary arterial tree. It is not compensated to reflect the actual position and orientation of the. In particular, the bed axis is potentially out of alignment with the room coordinate system, the axis of C-arm rotation is potentially non-intersecting with the isocenter and / or non-orthogonal, and / or the detector. The axes are potentially misaligned in the plane.
In block 20-return to Figure 14-the centerline of the vascular tree is extracted from the acquired 2-D image. In some embodiments of the invention, image filtering by anisotropic diffusion 21 comprises part of a processing operation that precedes centerline extraction. Anisotropic diffusion of a 2d grayscale image reduces image noise while preserving the edges of the area-smoothing along the edges of the image and removing noise gaps. In some embodiments, the basis of the method used is that introduced by Weickert's "A Scheme for Coherence-Enhancing Diffusion Filtering with Optimized Rotation Invariance" and / or "Anisotropic Diffusion in Image Processing" (Thesis 1996). Is similar to.
Next, referring to FIG. 16, this is a simplified flow diagram of a processing operation involving anisotropic diffusion according to some exemplary embodiments of the present invention.
The operation is described for a single image for some embodiments of the invention. In block 21A, the Hesse transformation is calculated from every pixel in the Gaussian smoothed input image (the Hesse transformation is related to the second derivative of the image data and takes the form of edge detection). At block 21B, the Hesse transformed image is smoothed, for example, by a Gaussian filter. In block 21C, the eigenvectors and eigenvalues of the smoothed Hesse transformed image are calculated. The resulting eigenvalues are generally larger when the original image contains edges, and the eigenvectors corresponding to the larger eigenvalues describe the direction in which the edges run. In addition to or as an alternative, another edge detection method as known in the art is used.
In block 21D, in some embodiments of the invention, a diffuse image is calculated. A finite difference scheme is used to perform the diffusion, in which some embodiments use eigenvectors as the diffusion tensor direction.
In block 21E, in some embodiments, a determination is made as to whether the time limit for diffusion (eg, a certain number of iterations that results in the desired level of image filtering) has been reached. If not, the flow chart returns to block 21A and continues. If so, the flow diagram ends and the flow continues within a higher level flow diagram, eg, the flow diagram of FIG.
At block 22, in some embodiments of the invention, a flange filter is applied based on the eigenvectors of the Hessian matrix, which comprises calculating the probability that the image region is within the blood vessel. Flange filtering is described, for example, by Frangi et al., "Multiscale vessel enhancement filtering", Medical Image Computing and Computer-Assisted Intervention-MICCA '98. By a non-limiting example, the flange filtered image 120 (FIG. 1) shows the original image 110 after image processing with the flange filter. In some embodiments, another filter, such as a threshold filter, or a hysteresis threshold filter, is used, whereby the pixels of the image are identified as belonging within the image region of the blood vessel.
At block 23, in some embodiments of the invention, the image is processed to produce a black-and-white shape that represents the arrangement of blood vessels in the angiographic projection image. In some embodiments, the hysteresis threshold filter is performed on the flange filter output with high and low thresholds. First, the algorithm shows pixels that are brighter than the higher threshold (eg, for image 120), and these are labeled as vascular pixels. In the second step, the algorithm labels a pixel as a blood vessel, which has a brightness higher than a low threshold and is also connected to a pixel that has already been labeled as a blood vessel pixel across the image.
A potential disadvantage of flange filters is the presence of a bulb-like shape at the vascular junction that interferes with accurate detection. In some embodiments, a region growth algorithm is used to extract these regions as an improvement only with hysteresis thresholding. The thresholded black-and-white and grayscale images obtained by anisotropic diffusion are provided with inputs to this algorithm.
A square extension is performed on the black and white image and the result is subtracted from the original black and white image. This subtracted image has a 1 pixel wide frame along which the growth of the area of the vessel labeling pixel is examined. The value (brightness) of the pixels in this frame is locally compared to the brightness of the existing vascular pixels to the periphery. High relative results lead to expansion. As appropriate, this process is repeated until no vascular pixels are found.
In block 24, in some embodiments, a thinning convolution is applied, which thins the black and white image segment down to a straight line representing the blood vessel centerline.
In some embodiments, blocks 21-24 are performed on an image-by-image basis (eg, sequential, interleaved, and / or parallel). Assuming sequential processing in block 25, if there are still images to process, the next image is selected in block 26 and processing continues from block 21 again.
If not, centerline extraction is complete in some embodiments of the invention. Next, referring to FIG. 2, this shows a 2-D tree 218 with a pale blood vessel centerline overlaid on top of the original image 110 of FIG. 1, according to an exemplary embodiment of the invention.
Motion Compensation In some embodiments of the present invention, the process of finding the centerline correspondence follows block 30 (Fig. 14). The goal of finding a centerline correspondence is to find a correspondence between different 2-D images (potentially from different angles, but at the point of imaging the same area of space), and therefore the target vasculature. 3-D reconstruction can be done.
At block 31, operations are performed for motion compensation and / or imaging position artifact compensation.
With ideal calibration information (for example, each image plane is completely identified with respect to a common axes) and no artifacts due to motion or other positioning errors, enough 2-D images in 3-D space. By back-projecting to, there is a potential cross-ray that uniquely defines the extent of the vessel centerline in 3-D (eg, the ray S in Figure 20B).<sub>1</sub>-P<sub>1</sub>And S<sub>2</sub>-P<sub>2</sub>) Is generated. In fact, deviations between images result from, for example, respiration, voluntary movements of the patient, and inaccurate and / or unclear phase fixation of imaging exposure to the cardiac cycle. Solving this problem without increasing the amount of calculation is a goal in some embodiments of the operation for motion compensation. Calibration errors potentially introduce other forms of image position artifacts.
In some embodiments of the invention, this procedure compensates for breathing and / or movement of other patients. As appropriate, this comprises iteratively repeating the detection of the corresponding image feature for different subsets of the angiographic image and updating the image correction parameters in response to the repeated detection.
Next, referring to FIG. 17A, this is a simplified flow diagram of a processing operation, including motion compensation, according to some exemplary embodiments of the invention.
In block 31A, in some embodiments of the invention, a subset (s) of images in which the 2-D centerline is identified are selected for processing. The centerline is extended in block 31B as appropriate, and the centerline back projection to 3-D is performed in block 31C based on the currently best known projection parameters for each image (first, these). Is, for example, a parameter expected based on the known configuration of the imaging device). The resulting projected volume is skeletonized in some embodiments to form a "consensus centerline" at block 31D. At block 31E, the consensus centerline is back-projected into the coordinate system of the 2-D image, which includes those that were not used to form the consensus centerline. At block 31F, adjust the projection parameters for the 3-D centerline within each 2-D image so that it fits more accurately with the centerline found within the image itself. This adjustment is used to adjust the projection parameters associated with each image. In 31G, in some embodiments, a decision is made whether to repeat this procedure for different image subsets in order to improve the overall quality of the projection fit. The decision to repeat is based on, for example, a given number of iterations, the metric measurement quality of the fit (such as the average distance between the closest points in the centerline projection), or another criterion. If so, the flow diagram returns to block 31A and continues. Otherwise, the flow diagram ends and the flow continues within a higher level of operational ordering, eg, the ordering of Figure 14.
By the inventors of the present invention, it has been found that such an iterative process can significantly reduce one or more of the effects of respiration, patient movement, and cardiac phase difference.
Next, referring to FIG. 17B, this is a simplified flow diagram of a processing operation, including alternative or additional methods of motion compensation, according to some exemplary embodiments of the invention.
In some embodiments of the invention, at block 31H, features within the reference image R are identified based on feature detection methods known in the art. Such image features generally lack self-identity, for example, in vascular bifurcations and origins of coronary vascular trees, placement of the smallest radius within constricted vessels, and / or translation in any direction. The composition of image pixels with a pattern of intensity-for example, corner-like bends or branches. Similar features (presumed to be homologous to the features of the reference image) are identified in the remaining image F.
In some embodiments of the invention, at block 31I, the image at F is then registered for image R. For example, the best-known projection parameters for image F are used to transform within the best-known projection plane for image R, and then, for example, shift, rotation, and / or scaling parameters. Optimized to obtain improved fits using epipolar geometry to calculate. As appropriate, the registration comprises the application of a geometric strain function. A distortion function is, for example, a function of the first, second, or other order of two image plane coordinates. In addition, or alternative, the strain function comprises parameters that describe the adjustment of node points defined in the image coordinate plane for registration. In some embodiments, the most well-known projection parameters are the same and a geometric distortion function is applied.
In some embodiments, the operation at block 31I comprises image correction parameter calculations based on the identified corresponding image features. The correction parameters typically describe, for example, translation and / or rotation of the coordinate system of a particular image. Based on the calculated parameters, the angiographic images are registered so as to provide a geometric correspondence between them. In some embodiments of the invention, some images are registered with respect to one of the images. For example, if the corresponding image feature is identified by N images (eg, N = 2, 3, 4, or more), then one of the images can be selected as a criterion, but the registration is For the remaining N-1 angiographic images, each of those remaining images is applied so as to geometrically correspond to a single angiographic image selected as a reference. In some embodiments, for example, another registration scenario is performed.
In block 31J, in some embodiments, candidate feature locations of identified features that are expected to be contained within a shell-like volume near the surface of the heart (particularly vascular features) are within such volume. Is filtered based on whether it really applies to. This shell-like volume calculation is described, for example, with respect to FIGS. 18A-18C.
At block 31K, in some embodiments, a decision is made whether to repeat this procedure for different image subsets in order to improve the overall quality of the projection fit. For example, a repeating decision is made as described for block 31G. If so, the flow diagram returns to block 31H and continues. Otherwise, the flow diagram ends and the flow continues within a higher level of operational ordering, eg, the ordering of Figure 14.
Cardiac Surface Constraints Then, referring to FIGS. 18A-18B, this is a "heart shell" for ignoring bad ray crossings from the calculated correspondence between images, according to some exemplary embodiments of the invention. The mode of calculation of the constraint condition is shown.
Also, referring to FIG. 18C, this is a simplified flow diagram of a processing operation, including constraining the pixel correspondence within a volume near the surface of the heart, according to some exemplary embodiments of the invention. is there.
In some imaging procedures, a "large enough" number of projections is potentially unavailable, and therefore the error in the determined position of the ray intersection potentially prevents convergence to the correct output. .. At block 32, in some embodiments of the invention, operations that reduce the effect of this source (and / or other sources) of positional error are performed based on cardiac surface constraints.
At block 32A, according to some embodiments of the invention, an image with features expected to be within the projected contour of the heart is selected. In some embodiments, the feature is a representation of the coronary artery 452, which takes a course on the surface of the heart. In some embodiments, the previously determined vascular centerline 451 has identified features. In block 32B, in some embodiments, the convex hull 450 defined by the blood vessel centerline 451 is determined. This convex hull represents the shape of the heart as projected into the plane of the selected 2-D image (if it is covered by the identified arterial centerline) so that it can be seen with the naked eye. In block 32C, in some embodiments, a decision is made as to whether another image should be selected to determine the projection of the heart shell from different angles. The number of images for which the convex hull of the heart shape is calculated is at least two, which allows 3-D localization of the heart shell, as appropriate, more images, as appropriate, all available images. Is used to determine the heart shell. If another image is added, the flow diagram follows block 32A, otherwise the flow continues to block 32D.
In block 32D, in some embodiments, the 3-D convex hull position (heart shell) is, for example, the most well-known projection for the intersection of each 2-D image plane and / or 3-D polyhedron. Determined from the various available 2-D convex hull projections by using the parameters. Such surfaces may be imaged using techniques known in the art, including, without limitation, polyhedra stitching, based on the description presented herein. .. In block 32E, in some embodiments, the cardiac shell is expanded to a volume where the amount of expansion is determined, for example, to accommodate the error limits expected to fit in the "true" vascular region. To.
At block 32F, in some embodiments, candidate 3-D positions of vascular centerline points off the heart shell are excluded. The flow diagram of FIG. 17C ends and the flow continues within a higher level of operational ordering, for example the ordering of FIG.
Identification of Homology Next, with reference to FIGS. 19A-19D, this shows the identification of homology between vascular branches according to some exemplary embodiments of the invention.
Also, referring to FIG. 19E, this is a simplified flow diagram of a processing operation, including identifying homologous regions along vascular bifurcations, according to some exemplary embodiments of the invention.
In block 33A, in some embodiments, the base 2-D image is selected for homology determination. The initial base selection is optional as appropriate. In block 33B, in some embodiments, the vessel centerline in one of the remaining images is projected in the plane of the base image. For example, the exemplary vessel centerline 503 in FIG. 19A is from a base image having a base coordinate system 504. The vessel centerline 501 taken from another image with a different coordinate system 502 is shown as being converted to the coordinate system 504 as the centerline 501B (translated in one direction for clarity in FIG. 19A). In Figure 19B, the two centerlines are overlaid to show their general similarity and the differences in some artifacts when bifurcating.
Note that in block 33C, in some embodiments, the projected vessel centerline 501B is dynamically expanded (501C), and the intersection with the vessel centerline of the base image occurs first, for example, all Continue until homology is identified. Dynamic expansion comprises, for example, gradually expanding the centerline by applying morphological operators to the pixel values of the image. In some embodiments, another method, such as the nearest neighbor algorithm, is used (in addition or alternative) to determine the correspondence. FIG. 19D shows an example of the correspondence between points on the blood vessel centerline at the end point of any of the minimum distance lines 515 and 510.
In block 33D, in some embodiments, a decision is made as to whether another image should be selected for extension to the current base image. If selected, the flow diagram follows block 33B. If not selected, block 33E makes a decision as to whether another base image should be selected. If selected, the flow diagram follows block 33A. If not selected, the flow diagram ends and the flow continues within a higher level of operational ordering, eg, the ordering of FIG.
Operations in block 30 (eg, subblocks 31, 32, 33) that find centerline correspondences between different 2-D images that allow the images to be reconstructed into a 3-D model of the vascular system. -And, more specifically, in some embodiments, it will be understood that it is an operation that performs the function of finding a correspondence between the blood vessel centerlines in a 2-D image. It will be appreciated that this function may be performed, based on the teachings of the description of the present invention, by modifications of the methods described and / or by other methods familiar to those skilled in the art. For example, whenever image A is projected, mapped, or transformed in some other way within the coordinate space of image B, in some embodiments, those transformations are reversed ( Instead, it transforms B), or the transformation can be both transformations into a common coordinate space. Also, for example, features and / or arrangements near features named in describing the operation (eg, vascular boundaries with respect to the blood vessel centerline), in some embodiments, are part of the task of finding a correspondence. Available to perform. In addition, the operations used to refine the results (including intermediate results) as a whole are optional in some embodiments, and in addition or alternative to, the results (including intermediate results) Other operations to be refined can potentially be determined by one of ordinary skill in the art, working under the description herein. These examples of modifications are not exhaustive, but rather show that the methods of providing embodiments of the present invention are broad.
Considering the consequences of the operations more commonly described in relation to blocks 20 and 30, progress towards at least two related but separate goals is, in some embodiments, shared intermediate results. Calculated based on -blood vessel centerline-. The first goal is to find the spatial relationships that the acquired 2-D images relate to a common 3-D imaging region. In principle, a number of possible reference features can be selected from 2-D images as the basis for this determination, but using the centerline of the vascular tree as a reference is a potential advantage. In particular, the determination of the vascular tree in this 3-D space is itself a second goal, and therefore, in some embodiments, the feature for mutual registration of images is the vascular model itself. It is also a feature used as a skeleton of. This is a potential advantage over the speed of calculation by reducing the need to make separate determinations of features for image registration, and vascular features as such. This is because the registration between vascular features is the basis for the transformation of the image data in which those same features are reconstructed, so the resulting vascular model has potential for accuracy, accuracy, and / or consistency. Advantages.
In 3-D mapping block 40, in some embodiments of the invention, 3-D mapping of 2-D centerlines is performed. In some embodiments, at block 41, the 3-D mapping begins with the identification of the optimal projection pair. If several different images are obtained, there are potentially several different (albeit homologous) projections of each region of the vessel centerline into 3-D space, each with a different 2-D image. Based on pairs.
Next, referring to FIG. 20A, this shows a simplified flow diagram of a processing operation, including selecting projection pairs along the blood vessel centerline, according to some exemplary embodiments of the invention. .. Upon entering block 41, an initial segment with a vessel centerline is selected along with an initial homology group of points on the centerline along it (eg, points from the endpoint) in different 2-D images.
In block 41A, in some embodiments of the invention, a point P on the blood vessel centerline.<sub>1</sub>(Corresponding to some homology groups at point P on the centerline) are selected from the first base image. In block 42B, in some embodiments, the other point P to find the location of the 3-D spatial phase.<sub>2</sub>... P<sub>N</sub>But P<sub>1</sub>Is selected from the homology group P to pair with.
Then, referring to FIG. 20B, this is the epipolar determination of the 3-D target position from the 2-D image position and its geometric relationship in space, according to some exemplary embodiments of the invention. It is a schematic representation.
Point P associated with image plane 410<sub>1</sub>Is the point P<sub>2</sub>Matched with, using the principles of epipolar geometry, placement in 3-D space P<sub>1,2</sub>To determine. Simply put, Source S<sub>1</sub>From point P through the target area<sub>1</sub>The ray leading to is S<sub>2</sub>It is on plane 417, which is also determined by exiting and crossing it. The continuation of these lines of intersection intersect plane 412 along the epipolar straight line 415.
In block 41C, in some embodiments, the points are evaluated for their relative suitability as optimally available projection pairs to extend the vessel centerline in 3-D space.
In some embodiments of the invention, the criterion for optimal selection of projection points is the distance of the projected points from their associated epipolar straight line. Ideally, each point P<sub>2</sub>... P<sub>N</sub>Is S<sub>2</sub>... S<sub>N</sub>Placed on the epipolar straight line corresponding to the epipolar plane defined by. However, some errors may remain due to imaging position artifacts-for example, the artifacts described for calibration and / or movement-so the point Pi is P.<sub>1</sub>Already determined to be homologous to, but deviated from its associated epipolar plane 418 and therefore away from its associated epipolar straight line 419 by a distance of 420. As appropriate, the projection point closest to its associated epipolar line for a given homology group is scored as the most suitable projection point for dilating the vessel centerline.
In some embodiments of the invention, one or more criteria for optimal selection of projection points relate to the continuity of expansion that the projected points result from from the already determined projected points. For example, a set of points along the vessel centerlines 421A, 421B can be used to determine the expected distance to the next expansion point in the current direction of expansion 423 and / or 3-D space. .. In some embodiments, projection points that more accurately match one or more of these or other geometric criteria are scored as correspondingly more appropriate choices.
In some embodiments, multiple criteria are weighted together and the selection of the best projection pair is based on the weighted result.
At block 41D, it is determined whether different base points within the homology group should be selected. If selected, the next base point is selected and further projection and evaluation continues from block 41A. If not selected, the point with the optimal (most suitable of the available selections) score to be included in the 3-D vessel centerline is selected. The flow diagram of FIG. 20A ends and the flow continues within a higher level of operational ordering, eg, the ordering of FIG.
In block 42, in some embodiments, the current vascular segment centerline is extended according to the points specified by the identified optimal pair of projections.
Vascular centerline determination follows 43 in some embodiments, where it is determined whether another sample (homologous group) should be evaluated for the current vascular centerline. If evaluated, the operation continues by selecting the next sample in block 44 and continues re-entering block 41. If not evaluated, a decision is made at block 45 whether the last vascular segment centerline has been determined. If not evaluated, the next segment is selected at 46 and processing continues with the first sample of that segment at block 41. When evaluated, the flow follows, in some embodiments, the vessel diameter estimation at block 50.
Estimating Blood Vessel Diameter Next, referring to FIG. 21, this is to generate an edge graph 51 and find a connection path along the edge graph 52, according to some exemplary embodiments of the invention. It is a simplified flow chart of the processing operation including.
Entering block 51, in some embodiments, an edge graph is determined. In block 51A, in some embodiments, a 2-D centerline projection is selected that maps to an arrangement relative to the arrangement of the intensity values of the 2-D imaging data. As appropriate, the selected projection is one in which the blood vessels are projected at maximum length. As appropriate, the selected projection is one in which one vessel does not intersect another vessel. In some embodiments, the projection is selected according to the partial region of the 2-D centerline of the vascular segment, for example, to have maximum length and / or non-intersection characteristics within the partial region. In some embodiments of the invention, images from orthogonal projections (and / or projections with another defined angular relationship) are selected.
In block 51B, in some embodiments, the starting vessel width (eg, radius) is estimated. The starting width is determined, for example, by generating an orthogonal profile to the centerline and selecting the peak of the weighted sum of the first and second derivatives of the image intensity along this profile.
In block 51C, in some embodiments, orthogonal profiles are created for points along the centerline, eg, for points sampled at intervals approximately equal to the vessel start width. The exact choice of spacing is not important. The use of radii as spacing is generally appropriate to obtain sufficient resolution for diameter estimation.
In block 51D, in some embodiments, the orthogonal profile to the sampled points is assembled in a rectangular frame, somewhat as if the 3-D centerline convolution was straightened, which assembles the orthogonal profile through the centerline. Make a parallel arrangement.
Once in block 52, in some embodiments, a connection path is then found along the vascular edge. In block 52A, in some embodiments, a first side (vascular edge) is selected for route tracking. In some embodiments, in block 52B, the path is appropriately assisted by the Dijkstra algorithm family, by minimizing the energy corresponding to the weighted sum of the first and second horizontal derivatives. It can be found along the edge at a distance of approximately the initial radius. If the second side is not calculated in block 52C, the flow diagram selects the second side in block 52D and branches to repeat the operation of 52B.
In some embodiments, following block 53 in FIG. 14, the centerline is reset to the middle of the two vascular walls that have just been determined. At block 55, in some embodiments it is determined whether this is the last centerline to process. Otherwise, in some embodiments, the next segment is selected in block 56 and processing continues to block 51. If so, in block 54, in some embodiments, a decision is made as to whether the procedure should be repeated. If it should be repeated, the first segment is selected for the second iteration and the operation continues to block 51. If not, the flow chart of FIG. 14 ends.
Construction of a segment-node representation of the vascular tree Next, referring to FIG. 3A, is image 305 of the coronary vascular tree model 310 produced by one exemplary embodiment of the invention.
Also referring to FIG. 3B, this is an image of the coronary vessel model 315 of FIG. 3A to which the dendrogram tag 320 was added according to an exemplary embodiment of the invention.
Note that tag 320 is just one exemplary method for tracking branches in a tree model.
In some embodiments of the invention, after reconstruction of a vascular tree model, such as a coronary arterial tree, from angiographic images, the tree model is appropriately divided into several branches, the branches of which are bifurcated. It is defined as a section of blood vessels between (eg, along a reference system established by the blood vessel centerline). The branches are numbered, for example, according to their formation in the tree. Branch points (nodes) can be determined in some embodiments of the invention in terms of the centerline representation of the skeleton connecting in more than two directions.
In some embodiments of the invention, the branch topology comprises dividing the vascular tree model into clearly distinguishable branches along the branch structure. In some embodiments, the branch topology comprises recombination of branches, for example, by lateral branches and / or branches of blood vessels.
Next, referring to FIG. 3C, this is a simplified diagram of the coronary vascular tree tree model 330 produced by one exemplary embodiment of the invention.
For some aspects of applying the vascular tree model to coronary artery diagnosis and / or functional modeling, in order to simplify the calculation of vascular tree characteristics (in the case of the present invention, for further illustration) of spatial location. It is useful to abstract some details.
In some embodiments, the tree model is represented by a 1-D sequence, for example, the 9-branch tree in Figure 3C is represented by a 9-element sequence, i.e. a = [0 1 1 2 2 3 3 4 4], which is a list of tree nodes in breadth-first order.
In some embodiments, in the reconstruction process, the spatial arrangement and radius of the segments in each branch is sampled at small distances, eg, every 1 mm, or in the range of 0.1 mm to 5 mm.
In some embodiments, the branches corresponding to the vascular segments between the modeled bifurcations correspond to vascular segments of 1 mm, 5 mm, 10 mm, 20 mm, 50 mm and even longer lengths.
In some embodiments, sampling at small distances increases the accuracy of the vascular geometric model, thereby increasing the accuracy of the flow characteristics calculated based on the geometric measurement results.
In some embodiments, the tree model is a reduced tree, restricted to a single segment of blood vessels, between two consecutive bifurcations of the vasculature. In some embodiments, the reduction is a reduction to a bifurcation region, optionally with a constriction.
Measuring flow from a time intensity curve in an angiography sequence In some embodiments, physical properties such as pressure and / or flow rate, and / or flow resistance, and / or shear stress, and / or flow velocity A physical model of fluid flow within the coronary vascular tree, including, is calculated.
In one exemplary embodiment, techniques based on the results of analysis of concentration distance time curves are used. These techniques work well in pulsatile conditions. An exemplary concentration-distance-time curve technique is a concentration-distance curve matching algorithm.
By using the techniques described above, the concentration of contrast agent, such as iodine, present at a particular distance along the vascular segment, across the vascular cavity perpendicular to the centerline, pixels in the angiography map (s). Obtained by integrating the intensity. The optimum shift is found in the distance axis between continuous concentration distance curves. The blood flow velocity is then calculated by dividing the shift by the time interval between the curves. Some variations of the above techniques have been reported in the following references, the contents of which are incorporated herein by reference. Four above-mentioned treatises by Seifalian et al., Above-mentioned paper by Hoffmann et al., Name "Determination of operating and average blood flow rates from digital angiograms of vessel phantoms using distance-density curves", above-mentioned paper by Shpilfoygel et al., Name "Comparison of" methods for prompting "Angiographic blood flow measurement", a paper by Holdsworth et al., Named "Quantitative angiographic blood flow measurement using pulsed intra-arterial injection".
Measuring the flow using other modality In some embodiments, the flow is calculated from ultrasonic measurements. Some modifications of the ultrasound technique described above have been reported in the literature described above, the contents of which are incorporated herein by reference. The above-mentioned paper by Kenji Fusejima, named "Noninvasive Measurement of Coronary Artery Blood Flow Using Combined Two-Dimensional and Doppler Echocardiography", the paper by Carlo Caiati et al., Named "New Noninvasive Method for Coronary Flow Reserve Assessment: "Contrast-Enhanced Transthoracic Second Harmonic Echo Doppler", a paper by Harald Lethena et al., Named "Validation of noninvasive assessment of coronary flow velocity reserve in the right coronary artery-A comparison of transthoracic echocardiographic results with intracoronary Doppler flow wire measurements", Paolo Vocia et al. Paper by, named "Coronary flow: "A new asset for the echo lab?", Review paper by Patrick Meimoun et al., Named "Non-invasive assessment of coronary flow and coronary flow reserve by transthoracic Doppler echocardiography: a magic tool for the real world", and paper by Carlo Caiati et al. , Name "Detection, location, and severity assessment of left anterior descending coronary artery stenoses by means of contrast-enhanced transthoracic harmonic echo Doppler".
In some embodiments, other modalities that measure flow rates within the coronary vascular tree are used. Exemplary modality includes MRI flow measurement and SPECT (single photon emission computed tomography), or gamma camera, flow measurement.
Note that in some embodiments, a blood flow model is constructed based on the geometric measurement results obtained from the images of the vascular system, without the use of flow or pressure measurements.
Note that in some embodiments, the flow measurement is used to verify the flow characteristics calculated based on a model constructed on the basis of geometric measurement results.
Note that in some embodiments, the pressure measurement is used to verify the flow characteristics calculated based on a model constructed on the basis of geometric measurement results.
An exemplary embodiment that produces a model in which stenosis is modeled as if it were revascularized-stenosis swelling In some embodiments, the blood vessel is regenerated as if it were a healthy structure. The structure is estimated. Such a structure is referred to as an inflated structure, as if the stenotic vessel had been regenerated to its original normal diameter.
In some embodiments, the technique is used as described in the following references, the contents of which are incorporated herein by reference. A paper by Tuinenburg et al., Named "Dedicated bifurcation analysis: basic principles", a paper by Tomasello et al., A paper named "Quantitative Coronary Angiography in the Interventional Cardiology", and a paper by Janssen et al., Named "New approaches for the assessment of vessel sizes in quantitative (" cardio-) vascular X-ray analysis ".
The stenosis dilation procedure is implemented separately and appropriately for each one of the 2-D projections. In some cases, the stenosis may occur in the area near the bifurcation, and in some cases, the stenosis may occur along the blood vessel. Next, the stenosis and dilation procedure in the two cases will be described separately.
If the stenosis is not located in the bifurcation region, it is sufficient to assess the flow rate in the diseased vessel. The proximal and distal coronary vascular segments of the stenosis are relatively disease-free and are referred to as reference segments. The algorithm optionally calculates the coronary vascular edge by interpolating the disease-free coronary vascular segments located proximal and distal to the stenotic region at the edge of the stenotic region. The algorithm appropriately reconstructs the reference coronary vascular segment as if it were disease-free.
In some embodiments, the technique involves calculating the mean diameter of the vascular cavity within a reference segment located upstream and downstream of the lesion.
When the stenosis is located in the bifurcation region, two exemplary bifurcation models, a T-branch model and a Y-branch model, are defined.
A T- or Y-shaped bifurcation model is detected by appropriately analyzing the arterial contours of the three vascular segments connected to the bifurcation. The calculation of the flow model for the diameter of an inflated healthy blood vessel is based on calculating as if each of the three segments connected to the bifurcation had a healthy diameter. Such calculations ensure that both proximal and distal major (interpolated) reference diameters are based on the arterial diameter outside of the bifurcated core.
The reference diameter function of the bifurcated core is appropriately based on the reconstruction of smooth transitions between proximal and distal vessel diameters. As a result, the reference diameter of the entire main section can be displayed as a function consisting of three different reference lines linked together.
Examples of Generating Models of Physical Properties of the Vascular System Next, some exemplary embodiments of methods for generating models of physical properties of the vascular system will be described.
An exemplary vasculature used in the rest of the description below is the coronary vasculature.
In some embodiments of the invention, a one-dimensional model of the vascular tree is used to assess the FFR index in the stenotic branches of the vascular tree, thereby constricting before and optionally after stenting. Estimate the flow rate at the branch.
In some embodiments of the invention, a one-dimensional model of the vascular tree is used to assess the FFR index in the stenotic branch of the vascular tree, thereby stenosis before and optionally after stent swelling. Estimate the flow rate at the branch.
Based on a maximum peak flow rate of 500 mL / min and an artery diameter of 5 mm, the maximum Reynolds number of the flow is as follows.<maths num="1"><img file="JP6636331B2_D0001.tif" /></maths>
The above calculation assumes laminar flow. Laminar flow, for example, assumes that the blood is a uniform Newtonian fluid. Another assumption made as appropriate is that the flow within the vascular branch is 1-D, which occurs over the entire cross section of the vessel.
Based on these assumptions, the pressure drop within each segment of the vascular tree is approximated by the Poiseuille equation in a straight tube.<maths num="2"><img file="JP6636331B2_D0002.tif" /></maths>
Where R<sub>i</sub>Is the viscous resistance to the flow of vascular segments. The slight loss due to vascular bifurcation, stenosis and curvature is added in series as additional resistors, as appropriate, according to Darcy-Weisbach's equation:<maths num="3"><img file="JP6636331B2_D0003.tif" /></maths><maths num="4"><img file="JP6636331B2_D0004.tif" /></maths>
Where K<sub>i</sub>Is the corresponding loss factor.
Then referring to FIG. 4, this is generated by an exemplary embodiment of the invention along the branches of the coronary vascular tree model 330 shown in FIG. 3C as a function of the distance along each branch. 9 series of figures 901 to 909 showing the radius of the blood vessel segment. Relative distances along the vascular segment are plotted in the X direction (horizontal direction) and relative radii are plotted in the Y direction (vertical direction).
The resistance of a branch to flow is calculated as the sum of the resistance of each segment along the branch.<maths num="5"><img file="JP6636331B2_D0005.tif" /></maths>
Or<maths num="6"><img file="JP6636331B2_D0006.tif" /></maths>
The resistor array corresponding to the example shown in Figure 3C is R<sub>s</sub>= [808 1923 1646 1569 53394 10543 55341 91454 58225], where the resistance to flow is in units mmHg * s / mL.
The above resistance is for stenotic vessels, as indicated by the peak of 91454 [mmHg * s / mL] in the resistance sequence.
The resistance sequence for a tree model without stenosis is appropriately calculated based on quantitative coronary angiography (QCA) to remove stenosis with an area of more than 50%.
In some embodiments, a tree model without stenosis is calculated by appropriately replacing the stenotic vessel with a dilated vessel, i.e., a geometric measurement of the stenotic vessel section is appropriate for the dilated vessel. Replaced by measurement.
In some embodiments, the geometric data (diameter and / or cross-sectional area) used for the inflated vessel is that of an arrangement just proximal to the stenotic arrangement and no arrangement just distal to the stenotic arrangement. It is the maximum value of the geometric data of the stenotic blood vessel.
In some embodiments, the geometric data (diameter and / or cross-sectional area) used for the inflated vessel is that of an arrangement just proximal to the stenotic arrangement and no arrangement just distal to the stenotic arrangement. It is the minimum value of the geometric data of the stenotic blood vessel.
In some embodiments, the geometric data (diameter and / or cross-sectional area) used for the inflated vessel is that of an arrangement just proximal to the stenotic arrangement and no arrangement just distal to the stenotic arrangement. Average of geometric data of stenotic vessels.
In some embodiments, the geometric data (diameter and / or cross-sectional area) used for the dilated vessel is no stenosis between the proximal arrangement of the stenotic arrangement and the distal arrangement of the stenotic arrangement. Calculated as a linear function of vascular geometric data, i.e., the swelling value is calculated taking into account the distance of the stenotic arrangement from the proximal arrangement and from the distal arrangement.
The stented, also referred to as inflated resistance sequence for the example shown in FIG.<maths num="7"><img file="JP6636331B2_D0007.tif" /></maths>
The peak resistance, which was 91454 [mmHg * s / mL], is replaced by 80454 [mmHg * s / mL] in the inflated or stented model.
Then, referring to FIG. 5, this is all generated by some exemplary embodiments of the invention, the coronary arterial tree model 1010, the combination matrix 1020 showing the wig tags, and the combination matrix showing the wig resistance. Indicates 1030.
The tree model is an exemplary tree model with nine branches tagged with branch numbers 0, 1a, 1b, 2a, 2b, 3a, 3b, 4a, and 4b.
The combinatorial matrix 1020 contains nine rows 1021 to 1029, which contain data on the nine streamlines, that is, the nine paths that the fluid takes as it flows through the tree model. Five lines 1025-1029 contain data for five complete streamlines of dark text for five paths all the way to the exit of the tree model. The four lines 1021 to 1024 contain data for light-colored text, partial streamlines for four paths that are not fully expanded within the tree model and do not go all the way to the exit of the tree model.
The combinatorial matrix 1030 shows rows for the same tree model as shown in the combinatorial matrix 1020, and the branch resistances are placed in the cells of the matrix corresponding to the branch tags in the combinatorial matrix 1020.
After calculating the resistance of each branch, a streamline is defined from the base point of the tree, branch 0, to each exit. To track streamlines, the branches that make up each streamline are listed in a combinatorial matrix, for example, as shown in FIG.
In some embodiments, the defined streamlines are further numbered, as shown in FIG.
Then, referring to FIG. 6, this was generated according to an exemplary embodiment of the invention, the tags correspond to streamlines, tags 1101-1105 numbered the exits of tree model 1100, A tree model 1100 of the vasculature is shown.
The pressure drop along the streamline j is calculated as the sum of the pressure drops in each of the component branches (i) according to the following equation.<maths num="8"><img file="JP6636331B2_D0008.tif" /></maths>
However, each branch has a different flow rate Q<sub>i</sub>Is when you have.
Based on the principle of conservation of mass at each branch, the flow rate at the mother branch is the sum of the flow rates at the daughter branch. For example:<maths num="9"><img file="JP6636331B2_D0009.tif" /></maths>
So, for example, the pressure drop along the streamline terminating at branch 4a is:<maths num="10"><img file="JP6636331B2_D0010.tif" /></maths>
Where Q<sub>j</sub>Is the flow rate along the streamline j, ER<sub>4,j</sub>Is the sum of the common resistances of streamline j and streamline 4. The global equation is appropriately formalized for the pressure drop along the streamline j as follows.<maths num="11"><img file="JP6636331B2_D0011.tif" /></maths>
For trees with k exit branches, i.e. for k complete streamlines, a set of k linear equations is used as appropriate.<maths num="12"><img file="JP6636331B2_D0012.tif" /></maths>
Here, index 1 ... k represents a streamline in the tree, and Q<sub>1</sub>... Q<sub>k</sub>Represents the flow rate at the corresponding outlet branch. The k × k matrix A consists of the elements ER and is calculated from the combination matrix. For example, for the five streamline trees shown in Figure 6, the ER matrix is:<maths num="13"><img file="JP6636331B2_D0013.tif" /></maths><maths num="14"><img file="JP6636331B2_D0014.tif" /></maths>
Next, referring to FIG. 23, this shows an exemplary bifurcated structure with recombination branches, according to some exemplary embodiments of the invention. In some embodiments of the invention, side branches and / or branches of blood vessels are provided and the branches are recombined in the tree.
In some embodiments of the invention, streamlines 2302, 2303 with loops may be modeled, for example, loops with branch segments 2a and 4c, separated from branch segment 2b, and then recombined. Or loops are equipped with recombination of branch segments 5a and 5b. In some embodiments of the invention, the necessary terms corresponding to branches are written to reflect that vascular resistance operates in parallel. So, for example, the pressure drop along streamline 2302 can be written as:<maths num="15"><img file="JP6636331B2_D0015.tif" /></maths>
In some embodiments, fluid pressure measurements, such as blood pressure measurements, are made. Given fluid pressure boundary condition (P<sub>in</sub>And P<sub>out_i</sub>) Based on the vector<maths num="16"><img file="JP6636331B2_D0016.tif" /></maths>
Is defined and Q<sub>i</sub>Is calculated as follows.<maths num="17"><img file="JP6636331B2_D0017.tif" /></maths>
For example, for a constant pressure drop of 70 mmHg between the base point and all outlets, the following flow distribution between outlets is calculated.
Q = [1.4356, 6.6946, 1.2754, 0.7999, 1.4282], where the unit of flow rate is mL / s. The result is the output of the above method and is shown in FIG.
Next, referring to FIG. 7, this is a simplified diagram of the vascular tree model 1210 produced by one exemplary embodiment of the invention, with the branch resistance R at each branch.<sub>i</sub> 1220 [mmHg * s / mL] and the calculated flow rate Q at each streamline outlet<sub>i</sub> Contains 1230 [mL / s].
In some embodiments, two models of the tree are calculated-the first model has stenosis, which is appropriately measured for a particular patient and the second model has no stenosis. FFR is calculated for each branch using the following formula.<maths num="18"><img file="JP6636331B2_D0018.tif" /></maths>
For example, for the tree described above, the FFR calculated for each of the nine branches is:<maths num="19"><img file="JP6636331B2_D0019.tif" /></maths>
The FFR calculated above is the flow rate Q<sub>S</sub>, Q<sub>N</sub>(FFR<sub>flow</sub>= Q<sub>S</sub>/ Q<sub>N</sub>) Directly expressed as the distal P of the pressure difference for stenosis<sub>d</sub>And Proximal P<sub>a</sub>FFR (FFR) derived from pressure measurement calculated based on<sub>pressure</sub>= P<sub>d</sub>/ P<sub>a</sub>Note that there is a clear distinction in the decisions from). Moreover, rather than comparing two variables of a fixed system state, this is a comparison of two clearly distinguishable states of the system.
FFR<sub>pressure</sub>For large differences in pressure measurements across stenotic lesions (eg, FFR)<sub>pressure</sub>If 0.75) is found, it means that removing the lesion removes substantial resistance to flow, which in turn results in a substantial increase in blood flow. "Substantially" means, in this case, "well medically valuable". This chain of reasoning is FFR<sub>flow</sub>Relies on simplifying assumptions about the pressure and resistance remaining in the vascular system that differ in detail from those described above.
However, the two indexes are closely related in what they describe. FFR is therefore defined as the ratio of maximal blood flow within a stenotic artery to maximal blood flow when the same artery is normal-although this is generally measured by the pressure difference in a fixed system state. Therefore, FFR<sub>flow</sub>And FFR<sub>pressure</sub>Can be characterized as the same desirable information, an index that arrives in different ways, that is, what fraction of the flow, at least in principle, can be restored by intervention in a particular region of the cardiovascular system.
FFR by the site<sub>pressure</sub>Acceptance is also related to the correlation between experience and clinical outcome. Therefore, FFR describes the vascular system in terms familiar to healthcare professionals.<sub>pressure</sub>There is a potential benefit to providing an alternative to. An index provided by the FFR estimates the potential for restoration of blood flow after treatment. Therefore, FFR<sub>flow</sub>-At least as long as this has a flow rate ratio-FFR, even if it arrives by different routes<sub>pressure</sub>As strictly as it is, it directly relates to parameters of medical interest.
Also, FFR<sub>pressure</sub>About FFR<sub>flow</sub>The goal of determining is, in some embodiments of the invention, a guide to making a medical decision by supplying an index that is fast calculable and easily interpretable. Medical professionals seeking diagnostic assistance find that interventions bring about medically meaningful changes in perfusion.<sub>flow</sub>It is potentially sufficient to be determined by a vascular index such as. The ratio index is an example of an index that compactly represents such changes. Also, by describing an index that represents the potential for change, FFR<sub>flow</sub>Is FFR<sub>pressure</sub>Note that, as it is, it potentially reduces the effects of error and / or strain on the absolute determination of vascular perfusion properties.
Quality of Results Then, referring to FIG. 24, this is the FFR index (FFR) for some exemplary embodiments of the invention.<sub>pressure</sub>) And image-based FFR index (FFR)<sub>flow</sub>), As a function of its average, the Brand Altman plot 2400.
In an exemplary graph, the mean difference between the FFR index and the image-based FFR2415 is -0.01 (N = 34 lesions, from 30 patients), with two standard deviation lines 2420, 2425 being 0.05 and -0.08. Can be found. The straight lines 2405, 2410 are typically cuts between the "non-treated" FFR (FFR> 0.80), preferably the "treated" FFR (FFR <0.75) and the intermediate FFR value (0.075 FFR 0.80). Mark off. In linear correlation, R<sup>2</sup>The value was 0.85. The specificity was found to be 100%.
These validation results indicate that image-based FFRs are potentially direct substitutions of FFRs calculated from pressure measurements.
In some embodiments of the invention, an image-calculated FFR and baseline FFR (eg, an FFR measured by pressure before and after actual stent implantation, or a control before and after actual stent implantation). The relationship with FFR) as measured by flow rate has approximately, for example, 90%, 95%, 100% specificity, or another intermediate or smaller specificity. R that describes the correlation with baseline FFR<sup>2</sup>The value is about, eg, 0.75, 0.80, 0.85, 0.90, or another larger, smaller, or intermediate value.
Some exemplary implementations for calculating exponents In some embodiments of the invention, image processing techniques and numerical calculations are functionally equivalent to the blood flow reserve ratio (FFR (pressure)) derived by pressure. Physiological index that is (eg, FFR)<sub>flow</sub>) Is combined to determine. In some embodiments, the functional equivalence is direct, and in some embodiments, the functional equivalence is an additional calibration factor (eg, offset to vessel width, change in blood viscosity, or simply the equivalence factor. And / or represents a function). The integration of the techniques described above potentially allows for a minimally invasive assessment of blood flow upon insertion of a diagnostic catheter, providing an appropriate estimate of the functional significance of coronary artery lesions.
In some embodiments of the invention, a novel physiological index makes it possible to potentially assess the need for percutaneous coronary intervention, making real-time diagnostic and interventional decisions. It is a physiological index that helps to make it. Minimally invasive methods potentially prevent unnecessary risk to the patient and / or reduce the time and / or cost of angiography, hospitalization, and / or follow-up treatment.
In some embodiments, the geometrical properties of the patient's vasculature, including its vascular tree and also with a single vessel, are equivalent in terms of application to current invasive FFR methods. Hemodynamic information (for example, FFR)<sub>flow</sub>) And a scientific model based on patient data is realized.
In addition, this model potentially allows us to examine the combination of 3D reconstruction of blood vessels and numerical flow analysis to determine functional significance for coronary artery lesions.
Some embodiments of the invention perform 1-D reconstruction of one or more coronary segment and / or branches and computational / numerical flow analysis during coronary angiography to perform arterial arteries. Evaluate pressure, flow rate, and / or flow resistance in parallel.
Some embodiments of the invention perform 3-D reconstruction of one or more coronary segment and / or branches and computational / numerical flow analysis during the performance of coronary angiography to perform arterial arteries. Evaluate pressure, flow rate, and / or flow resistance in parallel.
In an embodiment of the invention in which the vascular function index is calculated based solely on the stenosis model, resistance R contributed by stenosis to the total resistance of the crown of the lesion<sub>S</sub>Is evaluated. Crown volume V distal to the stenosis<sub>crown</sub>Is also calculated. Then the FFR index (FFR)<sub>resistance</sub>), But R<sub>S</sub>And V<sub>crown</sub>It can be calculated as a function that decreases with. Representative examples of such functions include, without limitation,:<maths num="20"><img file="JP6636331B2_D0020.tif" /></maths>
Where P<sub>a</sub>Is the aortic pressure, P<sub>0</sub>Is the precapillary pressure and k is the scaling law factor that can be adapted to the aortic pressure. FFR<sub>resistance</sub>The calculation of is as follows.
Next, referring to FIG. 8, this is a simplified flow diagram of an exemplary embodiment of the present invention. This embodiment is particularly useful when vascular function indices such as FFR are calculated based on two models of the vascular system.
FIG. 8 shows some parts of the method according to an exemplary embodiment. This method involves receiving at least two 2-D angiographic images of a portion of the patient's coronary artery (1810) and reconstructing a 3-D tree model of the coronary system (1815). , If there is a lesion, include the lesion.
Flow analysis of blood flow and, as appropriate, arterial pressure along the segment of interest is based on a tree model and, as appropriate, other available hemodynamic measurements such as aortic pressure and / or amount of infused contrast agent.
The exemplary embodiment just described potentially results in a minimally invasive physiological index indicating the functional significance of coronary artery lesions.
Illustrative methods are appropriately performed while performing coronary angiography, and calculations are appropriately performed while performing coronary angiography, which results in a minimally invasive physiological index in real time. Brought to you.
Next, referring to FIG. 9, this is a simplified flow diagram of another exemplary embodiment of the invention.
Figure 9 shows the generation of a tree model of the subject's vascular system, and the stenosis model is the geometry of the subject's vascular system at one or more locations along the vascular centerline of at least one branch of the subject's vascular system. Acquiring the flow characteristics of a stenosis model (1915) with objective measurements (1910) and generating a second model of similar spread of the patient's vascular system as a stenosis model (1920) For vascular evaluation, including obtaining flow characteristics (1925), calculating an index indicating the need for vascular regeneration based on the flow characteristics in the stenosis model and the flow characteristics in the normal model (1930). Here's how to do it.
Next, referring to FIG. 10, this is a simplified flow diagram of yet another exemplary embodiment of the invention.
Figure 10 shows a tree model of a subject's vascular system using multiple 2-D images of the subject's vascular system (2010) and at least some of the multiple captured 2-D images. And here, the tree model comprises a geometric measurement of the subject's vascular system at one or more locations along the vascular centerline of at least one branch of the subject's vascular system (2015). A method for vascular evaluation is shown, including generating a model of the flow characteristics of the first tree model (2020).
Spread of the coronary tree model In some embodiments, the spread of the first stenosis model includes the stenosis, a section of blood vessels proximal to the stenosis, and a section of blood vessels distal to the stenosis. The spread is just right.
In one such embodiment, the spread of the first model is, in some cases, a segment of blood vessels between the bifurcations, including a stenosis within the segment. In some cases, the spread includes the bifurcation and the sections of blood vessels located proximal and distal to the stenotic bifurcation, especially if the stenosis is at the bifurcation.
In some embodiments, the extent to which the first model extends proximally to the stenosis within a single segment ranges from about 1 or 2 mm to about 20 to 50 mm, and / or the end of the segment itself. Up to.
In some embodiments, the extent to which the first model extends distally to the stenosis within a single segment ranges from about 1 or 2 mm to about 20 to 50 mm, and / or the end of the segment itself. Up to.
In some embodiments, the extent to which the first model extends distal to the stenosis is measured by the bifurcation of the blood vessel. In some embodiments, the first model extends distal to the stenosis by only one or two branches, and in some embodiments, as many as three, four, or five branches. Only expand by more branches. In some embodiments, the first model extends distal to the stenosis as long as the resolution of the imaging process allows the distal portion of the vascular system to be discerned.
The second model, which has the same spread as the first model, is appropriately generated by inflating the stenosis as if the stenosis had been revascularized and returned to its normal diameter.
Generating a model of the physical properties of the vasculature In an exemplary implementation, the proximal arterial pressure P<sub>a</sub>Given [mmHg], the flow rate Q through the segment of interest<sub>s</sub>[mL / s] is the geometry of the segment of interest, including the results of the concentration-distance-time curve analysis and the diameter d (l) [cm] and / or volume V (l) [ml] as a function of segment length, as appropriate. Derived from the concentration of iodine contrast agent, based on scientific explanation.
In some embodiments, blood flow is modeled using a transthoracic eclipse, or other modality such as MRI or SPECT, especially in the case of large vessels such as the left anterior descending coronary artery (LAD). Can be measured to obtain.
For a given segment, the total resistance of the segment (R)<sub>t</sub>[mmHg * s / mL]) is calculated by dividing the arterial pressure by the flow rate as appropriate.<maths num="21"><img file="JP6636331B2_D0021.tif" /></maths>
Here R<sub>t</sub>Corresponds to all resistors, P<sub>a</sub>Corresponds to arterial pressure, Q<sub>s</sub>Corresponds to the flow rate through the vascular segment.
From the geometric description of the segment, the local resistance R of the stenosis within the segment<sub>s</sub>[mmHg * s / mL] is estimated. R<sub>s</sub>To estimate, use an empirical look-up table and / or use a function as described in the Kirkeeide literature above, and / or one of the methods of cumulative sum of Poiseuille's resistance. It can be done in one or more.<maths num="22"><img file="JP6636331B2_D0022.tif" /></maths>
Here, the integral spans the segment (dl) samples, where d is the arterial diameter of each sample as appropriate, and μ is 0.035 g · cm.<sup>-1</sup> S<sup>-1</sup>, Appropriately blood viscosity.
The downstream resistance of the segment is as follows:<sub>n</sub>Calculated for [mmHg * s / mL].<maths num="23"><img file="JP6636331B2_D0023.tif" /></maths>
Normal flow rate Q through a non-stenotic segment<sub>n</sub>[mL / s] is calculated for the example as follows.<maths num="24"><img file="JP6636331B2_D0024.tif" /></maths>
Here, Q<sub>n</sub>Is the input flow rate to the segment, P<sub>a</sub>Is the pressure proximal to the segment, R<sub>n</sub>Is the resistance to flow by the blood vessels distal to the segment.
Blood flow reserve ratio (FFR)<sub>contrast-flow</sub>Another form of) is, as appropriate, derived as the ratio of the measured flow rate through the constricted segment to the normal flow rate through the non-stenotic segment.<maths num="25"><img file="JP6636331B2_D0025.tif" /></maths>
In some embodiments, the FFR index (eg, FFR)<sub>contrast-flow</sub>) And other indices that indicate the potential effect of angiogenesis are calculated using the data described below.
Proximal artery pressure P<sub>a</sub>Total inlet flow rate Q through the origin of a blood vessel, such as the origin of a coronary artery, where [mmHg] is measured<sub>total</sub>[ml / s] is appropriately derived from the concentration of the contrast medium (iodine, etc.) based on the analysis result of the concentration distance time curve. In some embodiments, especially for large vessels such as the left anterior descending artery (LAD) coronary artery, flow rates are recorded as appropriate using transthoracic eclipse and / or other modalities such as MRI and SPECT. Will be done.
Subject's specific anatomy, including one or more of the following:
Geometric description of arterial diameter along the vascular tree segment, eg, generation of up to 3-4 as a function of segment length dl [cm], geometric description of arterial length along the vascular tree segment (L)<sub>i</sub>[cm])), for example, up to 1-2 generations downstream of the segment of interest, and cumulative crown length (L) downstream of the segment of interest.<sub>crown</sub>[cm]), L<sub>crown</sub>= ΣL<sub>i</sub>, Geometric description of arterial volume along the vascular tree segment (V)<sub>i</sub>[ml])), for example, up to 1-2 generations downstream of the segment of interest, and cumulative crown volume (V) downstream of the segment of interest.<sub>crown</sub>[ml]), V<sub>crown</sub>= ΣV<sub>i</sub>, Myocardial mass (LV mass) distribution M [ml] for the arterial segment of interest (in some embodiments, the LV mass is calculated, for example, using a transthoracic ectopler), and above. Normal flow through the segment through anatomical parameters as described (no stenosis) Q<sub>n</sub>Criteria parameter K or function F that correlates with [mL / s], eg<maths num="26"><img file="JP6636331B2_D0026.tif" /></maths>
Using the above data, indices indicating the potential effect of angiogenesis, such as the FFR index, are calculated as appropriate by performing the following calculations for each vascular segment of consideration.
From the geometric parameters of the tree, such as length, volume, mass, and / or diameter, the normal flow rate Q within the segment<sub>n</sub>Is obtained from the arterial pressure, the resistance (R) distal to the segment<sub>n</sub>, [MmHg * s / mL]), for example, R<sub>n</sub>= P<sub>a</sub>/ Q<sub>n</sub>From the geometric shape calculated by, the local resistance R of the stenosis in the segment R<sub>s</sub>[mmHg * s / mL] is estimated using, for example, one or more of the following methods: look-up tables, empirical functions as described in the Kirkeeide literature above, and / Or the cumulative sum of Poiseuille resistance R<sub>s</sub>= (128μ) / π (dl) / (d<sup>4</sup>), Where the integral spans the samples of the segment (dl), d is the arterial diameter of each sample, μ is 0.035 g · cm<sup>-1</sup> S<sup>-1</sup>Total resistance R to the segment, which is the blood viscosity as appropriate<sub>t</sub>[mmHg * s / mL] is R<sub>t</sub>= R<sub>n</sub>+ T<sub>s</sub>Flow rate Q through the constriction segment, calculated as<sub>s</sub>[mL / s] is Q<sub>s</sub>= P<sub>a</sub>/ R<sub>t</sub>Indexes such as blood flow reserve ratio (FFR) to segment, calculated as, are appropriately FFR = Q.<sub>s</sub>/ Q<sub>n</sub>Is calculated as.
Checking whether the above calculation is correct, the cumulative flow in the tree is Q as appropriate<sub>total</sub>= ΣQ<sub>i</sub>It can be done by checking if it matches the total flow rate measured as in.
In some embodiments, in the spread of the first model, this includes stenosis, distal as far as the resolution of the imaging modality that produced the vascular model allows, and / or several branches, eg, 3-4. It spreads to the distal side of the stenosis by the branch. In some embodiments, the number of bifurcations is limited by the resolution at which the vessel width can be determined from the image. For example, branching sequence cutoffs have been set and vessel width is no longer determinable within 5%, 10%, 15%, 20% accuracy, or another greater, smaller, or intermediate accuracy range. .. In some embodiments, sufficient accuracy is not available, for example, due to insufficient imaging resolution in the original image. The availability of multiple measurable branches is a potential advantage for a more complete reconstruction of detailed vascular resistance within the coronary vessels of the stenosis. It should be noted that with the latest technology, CT scans generally have lower resolution than X-ray angiographic imaging, reducing the availability of vessels capable of determining vascular resistance.
In an exemplary implementation, the total inlet flow rate through the origin of the coronary artery is derived from the concentration of contrast agent and, as appropriate, the particular anatomy of the subject.
In some embodiments, the anatomical data is appropriately described in the vascular tree segment, a geometric description of the arterial diameter along the vascular segment distal to the constriction by up to 3-4 branches. Includes a geometric description of arterial length along, a geometric description of arterial volume along a tree segment, and / or a myocardial mass (LV mass) distribution for the arterial segment of interest.
In some embodiments, the data attached to the anatomical structure is, as appropriate, a geometric description of the arterial diameter along the vascular segment distal to the constriction, along the vascular tree segment, as the imaging modality allows. Includes a geometric description of arterial length, a geometric description of arterial volume along the tree segment, and / or myocardial mass (LV mass) distribution for the arterial segment of interest.
In some embodiments, the LV mass is optionally calculated by using a transthoracic Echo Doppler.
In some embodiments, reference scaling parameters or functions are used that correlate anatomical parameters with normal flow through a non-stenotic segment.
In some embodiments, the spread of the first model comprises a stenotic vessel, the second model comprises a similar spread of the vasculature, and a healthy vessel resembles a stenotic vessel.
FFR index (FFR<sub>2-segment</sub>) Is appropriately calculated from the ratio of the measured flow rate in the stenotic blood vessel to the flow rate in the adjacent healthy blood vessel. In some embodiments, the index is adjusted by the ratio between the total length of the vessel within the crown of the stenotic vessel and the healthy vessel. The crown of a blood vessel is defined herein as a partial tree that branches off from the blood vessel. The total length of the coronary section is appropriately derived from the 3-D reconstruction of the coronary arterial tree.
Then referring to FIG. 11, this is a simplified drawing 2100 of the vasculature containing stenotic vessel 2105 and non-stenotic vessel 2107.
FIG. 11 shows two blood vessels that are candidates for reference to the results of comparing the flow characteristics of the stenotic blood vessel 2105 and the non-stenotic blood vessel 2107. FIG. 11 also shows the stenotic crown 2115 and the non-stenotic crown 2117.
The two vessels in Figure 11 appear to be particularly good candidates for comparison, as they both appear to have similar diameters and both appear to have similar crowns. Please note that.
Due to the scaling law, there is a linear relationship between the normal flow rate Q in the artery and the overall length of the blood vessel in its crown. This relationship holds for both adjacent healthy vessels and stenotic vessels. For healthy blood vessels:<maths num="27"><img file="JP6636331B2_D0027.tif" /></maths>
here<maths num="28"><img file="JP6636331B2_D0028.tif" /></maths>
Is the flow rate of healthy blood vessels, k is the correlation coefficient, and L<sup>h</sup>Is the total length of the coronary system of healthy blood vessels.
Similarly, the stenotic blood vessels are as follows.<maths num="29"><img file="JP6636331B2_D0029.tif" /></maths>
here<maths num="30"><img file="JP6636331B2_D0030.tif" /></maths>
Is the flow rate of the stenotic vessel, k is the correlation coefficient, and L<sup>s</sup>Is the total length of the coronary system of stenotic vessels.
FFR<sub>2-segment</sub>Is defined in some embodiments as the ratio of the flow rate in a stenotic artery during hyperemia to the flow rate in the same artery in the absence of stenosis (normal flow rate), as described in Equation 6.3 below. To. The above relationship yields results for FFR, which is calculated as the ratio between the flow rates measured in both vessels divided by the ratio between the total length of each crown.
Note that the scaling law also defines the relationship between normal flow and total crown volume. In some embodiments, the index or FFR divides the above-mentioned ratio between the measured flow rates in the diseased and healthy arteries by the ratio between the total volume of each crown of the stenotic and normal vessels, respectively. , 3/4 power is calculated.<maths num="31"><img file="JP6636331B2_D0031.tif" /></maths>
here,<maths num="32"><img file="JP6636331B2_D0032.tif" /></maths>
Is the existing flow rate within the stenotic vessel as measured by the method described herein.<maths num="33"><img file="JP6636331B2_D0033.tif" /></maths>
Is the existing flow rate in a healthy blood vessel as measured by the method described herein, L.<sup>s</sup>Is the total length of the crown of the stenotic vessel, L<sup>h</sup>Is the total crown of a healthy blood vessel.
The scaling law also defines the relationship between normal flow and total crown volume.<maths num="34"><img file="JP6636331B2_D0034.tif" /></maths>
here<maths num="35"><img file="JP6636331B2_D0035.tif" /></maths>
Is the flow rate of healthy blood vessels, kv is the correlation coefficient, and V<sub>h</sub>Is the total volume of the coronary system of healthy blood vessels.
Similarly, the stenotic blood vessels are as follows.<maths num="36"><img file="JP6636331B2_D0036.tif" /></maths>
here<maths num="37"><img file="JP6636331B2_D0037.tif" /></maths>
Is the flow rate of the stenotic blood vessel, k<sub>v</sub>Is the correlation coefficient, V<sub>h</sub>Is the total volume of the coronary system of stenotic vessels.
The FFR is, as appropriate, calculated from the above-mentioned ratio of measured flow rates in diseased and healthy vessels divided by the ratio of the total volume of each crown to the 3/4 power.<maths num="38"><img file="JP6636331B2_D0038.tif" /></maths>
Where V<sub>h</sub>And V<sub>s</sub>Is measured by using a 3-D model of the vascular system, in a non-limiting example.
Hardware Implementation Example With reference to FIG. 12A, this is a simplified diagram of the hardware implementation of the system for vascular evaluation constructed by one exemplary embodiment of the invention.
An exemplary system in Figure 12A includes:
A computer 2210 that is functionally connected to two or more imaging devices 2205, two or more imaging devices 2205 for capturing multiple 2-D images of the patient's vascular system (2209).
Computer 2210, as appropriate, receives data from multiple imaging devices 2205 and uses at least some of the multiple captured 2-D images to generate a tree model of the patient's vascular system, where. The tree model comprises geometric measurements of the patient's vascular system at one or more locations along the vascular centerline of at least one branch of the patient's vasculature to generate a model of the flow characteristics of the tree model. It is composed of.
In some embodiments, a synchronization unit (not shown) is used to supply a synchronization signal to the imaging device 2205 to synchronize the capture of 2-D images of the patient's vascular system.
Then referring to FIG. 12B, this is a simplified diagram of another hardware implementation of the system for vascular evaluation constructed by one exemplary embodiment of the invention.
An exemplary system in Figure 12B includes:
One imaging device 2235 for capturing multiple 2-D images of the patient's vascular system and a computer 2210 functionally connected to the imaging device 2235 (2239).
In the exemplary embodiment of FIG. 12B, the imaging device 2235 is configured for 2-D to acquire images from two or more directions with respect to the subject. The orientation and placement of the imaging device 2235 with respect to the subject and / or with respect to the fixed frame of reference is recorded as appropriate and may be one-dimensional (1-D) from the 2-D image taken from the imaging device 2235 as appropriate. Helps generate a vascular tree model, whether in three dimensions (3-D).
Computer 2210, as appropriate, receives data from multiple imaging devices 2235 and uses at least some of the multiple captured 2-D images to generate a tree model of the patient's vascular system, where. The tree model comprises geometric measurements of the patient's vascular system at one or more locations along the vascular centerline of at least one branch of the patient's vasculature to generate a model of the flow characteristics of the tree model. It is composed of.
In some embodiments, as appropriate, at the same time in the cardiac cycle, a synchronization unit (not shown) to supply a synchronization signal to the imaging device 2235 to synchronize the uptake of 2-D images of the patient's vascular system. Is used.
In some embodiments, the computer 2210 accepts the subject's ECG signal (not shown) and selects a 2-D image from the imaging device 2235 according to the ECG signal, eg, selecting a 2-D image in the same cardiac phase. To do.
In some embodiments, the system of FIG. 12A or 12B comprises an image registration unit that detects the corresponding image feature in a 2-D image, calculates image correction parameters based on the corresponding image feature, and image feature. Register the 2-D image so that it corresponds geometrically.
In some embodiments, the image feature is appropriately selected as the origin of the tree model and / or the placement of the smallest radius within the constricted vessel and / or the bifurcation of the vessel.
Example System for Vascular Condition Scoring Next, with reference to FIG. 22, this is a simplified schematic of the automated VSST scoring system 700 according to some exemplary embodiments of the present invention.
In FIG. 22, the wide white path (eg, path 751) represents a simplified path for data processing through the system. The wide black path (eg, path 763) represents one or more data connections to the system user interface 720. The black path data content is labeled by superimposing trapezoidal blocks.
The vascular tree reconstructor 702 receives image data 735 from one or more imaging systems or system connection networks 730 in some embodiments of the invention. The stenosis determinant 704, in some embodiments, determines the presence of a stenotic vascular lesion based on a reconstructed vascular tree. In some embodiments, the metric module 706 determines additional metrics related to the disease state of the vascular tree based on the reconstructed vascular tree and / or the determined stenosis arrangement and other measurements.
In some embodiments, the metric extractor 701 comprises the functionality of a vascular tree reconstructor 702, a stenosis determinant 704, and / or a metric module 706. In some embodiments, the metric extractor 701 can operate to receive image data 735 and then extract multiple vascular condition metrics that are suitable, for example, as inputs to the parameter synthesizer 708. ..
In some embodiments, the parameter synthesizer 708 "answers" vascular condition scoring questions, and / or in some other way maps to a particular operation of the VSST scoring procedure, a subscore with parameters. Convert the determined parameters to values (for example, true / false values).
In some embodiments, the subscore extractor 703 comprises the functions of a vascular tree reconstructor 702, a stenosis determinant 704, a metric module 706, and / or a parameter synthesizer 708. In some embodiments, the subscore extractor 703 comprises the functionality of the metric extractor 701. In some embodiments, the subscore extractor 703 receives image data 735 and then extracts one or more VSST subscores that are suitable as inputs to the score calculator 713.
The parameter finalizer 710, in some embodiments, ensures that the parameter data provided is complete and correct enough to proceed to final scoring. In some embodiments, corrections to the automatically determined parameters are determined in the finalizer 710, as appropriate, under the supervision of an operator made through the system user interface 720. In some embodiments, the missing portion of the automatically supplied parameter data is filled, for example by user input from the system user interface 720, or, for example, from another diagnostic system, or access to clinical data. It is done by other parameter data 725 provided by the allowed network.
In some embodiments, the score synthesizer 712 synthesizes a finalized output into a weighted score output 715 based on the determined parameters for the score. Scores are available, for example, on the system user interface to network resource 730.
In some embodiments of the invention, the score calculator 713 comprises the functionality of the parameter finalizer 710 and / or the score synthesizer 712. In some embodiments, score calculator 713 receives the synthesized parameters and / subscores (eg, from parameter synthesizer 708 and / or subscore extractor 703) and converts them to VSST score output 715. It is operational.
In some embodiments of the invention, intermediate results of the process (eg, reconstructed vascular tree, various metrics determined from it, and / or parameter determination) are stored in the storage device of System 700 (not shown). Stored in persistent or temporary storage on and / or on network 730.
The scoring system 700 is described in some embodiments of the present invention in the context of a module implemented as a programming function of a digital computer. Basic system architecture, in a variety of ways with an embodiment of the present invention, for example, single-process or multiprocessor is implemented as a client-server process running as a scan applications, and / or the same or different on a computer hardware system It will be understood to get. In some embodiments of the invention, the system is implemented in code executed by a general purpose processor. In some embodiments, some or all of the functionality of one or more modules is achieved by another dedicated hardware component, such as an FPGA, or ASIC.
To provide an example of a client-server configuration, the subscore extractor 703 is a server process (or server) on one or more remote machines on the client computer that implements modules such as the score calculator 713 and the user interface 720. Implemented as a group of implementation processes). It will be appreciated that other divisions of the module (or further divisions within the module) described herein are included by some embodiments of the invention. The potential advantage of such a split is that it allows the hardware to be shared among multiple end users, for example, while performing parts of the fast dedicated hardware that require a large amount of scoring computation. By doing so, economies of scale can be realized. Such a distributed architecture also has potential advantages for maintenance and / or delivery of new software versions.
Potential Benefits of Embodiments of the Invention Some exemplary embodiments of the invention minimize invasiveness, i.e. they can refrain from searching the coronary arteries with guidewires. Therefore, the risk to the patient is minimized compared to the invasive FFR catheter procedure.
An exemplary embodiment of the invention makes it possible to measure a reliable index during catheter insertion, processing angiographic data after the catheter insertion procedure, and / or additional in a catheter insertion procedure such as a guide wire. Note that it provides a cost-effective means of potentially eliminating the need for equipment and / or materials associated with catheter insertion procedures such as adenosine. Note that other potential savings include savings in hospitalization costs after a more appropriate treatment decision.
An exemplary embodiment of the invention is to experiment with different post-expansion vascular cross sections in different post-expansion models of the vasculature and select the appropriate stent for the subject based on the desired flow characteristics of the post-expansion model. Allows you to do.
An exemplary embodiment of the invention, as appropriate, automatically identifies the geometric properties of the vessel, defines the contour of the vessel, and is appropriately associated with the vessel, corresponding to current invasive FFR methods. Provides relevant hemodynamic information.
One embodiment of the present invention appropriately produces an index indicating the need for coronary vascular regeneration. Minimally invasive embodiments of the present invention potentially prevent unnecessary risk to the patient and potentially reduce the total time and cost of angiography, hospitalization and follow-up treatment.
The system constructed by one exemplary embodiment of the present invention potentially makes it possible to shorten the diagnostic angiography procedure. Unwanted coronary interventions in and / or in the future in angiography are also potentially prevented. Also, the method according to one exemplary embodiment of the invention allows for the assessment of vascular problems in other arterial regions, such as the carotid, renal, and affected vessels of the extremities, as appropriate.
It should be noted that the resolution of angiographic images is typically higher than the resolution typically obtained by 3-D techniques such as CT. Models constructed from higher resolution angiographic images are inherently higher resolution, resulting in greater geometric accuracy and / or the use of smaller vascular geometry than CT images. It enables and / or allows calculations using vascular branches distal to the stenosis for more generation or bifurcation downstream from the stenosis compared to CT images.
A short list of potential non-invasive FFR benefits. One or more of these have been realized in some embodiments of the invention and are as follows:
Non-invasive methods that do not endanger patients, calculation methods without additional time or invasive equipment, benefits of prognostic diagnosis in "borderline" and multivessel lesions, to assess the need for coronary vascular regeneration Methods for assessing and / or optimizing vascular regeneration procedures that provide a reliable index, strategies to save costs on catheterization, hospitalization, and follow-up treatments, unnecessary coronary interventions following angiography Prevent, "one-stop shop" comprehensive lesion assessment.
Another advantage of some embodiments of the present invention is the ability to generate a tree model within a short period of time. This is an exponent, especially but not always, also within a short period of time (for example, less than 60 minutes, less than 50 minutes, or 40 minutes from the time the 2-D image was received by the computer. Allows you to calculate an index (eg, FFR) that indicates vascular function for less than, or less than 30 minutes, or less than 20 minutes. Preferably, the exponent is calculated while the subject remains stationary on the treatment surface for catheter insertion. Such a fast calculation of the index allows the physician to make an assessment of the lesion being diagnosed during the catheterization procedure, thereby allowing a quick decision on appropriate treatment for that lesion. It is advantageous. Physicians can determine the need for treatment while in the catheter insertion chamber and do not have to wait for offline analysis.
The additional benefits of fast index calculation are reduced risk to the patient, the ability to calculate the index without the need for drugs or invasive equipment, and reduced time to perform coronary diagnostic procedures. Includes the benefits of established prognostic diagnosis in borderline lesions, reduced costs, reduced number of unnecessary coronary interventions, and reduced amount of subsequent procedures.
In this "game" of assessing the hemodynamic severity of each lesion, non-real-time solutions are often not an option to consider. Physicians need to know whether to treat lesions in the catheterization room and cannot afford to wait for offline analysis. CT-based solutions are also part of a different "game", but that is because the use of cardiac CT scans is low compared to PCI procedures, and the solution is angiography, both temporally and spatially. It is considerably lower than the law.
Another point to emphasize is that online image-based FFR assessments, unlike invasive assessments, potentially allow assessment of borderline lesions and are not necessarily limited to the percentage of hospitals assessed today. Because the risk to the patient (eg by passing through the guide wire) and the cost are considerably lower.
During the life of the patent maturing from this application, it is expected that many relevant methods and systems for imaging the vascular system will be developed, and the scope of terms describing imaging is all such new. It is intended to include technology a priori.
As used herein, the word "about" refers to 10%.
"Prepare", "prepare", "include", "include", "have", and their inflected forms mean "include, but not limited".
The phrase "consisting of" means "including limited".
The phrase "consisting of essentially" means that the composition, method, or structure includes additional materials, steps, and / or parts, but the composition for which additional materials, steps, and / or parts are claimed. Only if it does not substantially change the basic and novel properties of the method or structure.
As used in the original English text of this specification, the singular forms "a", "an", and "the" referent to multiple referents unless the context clearly dictates otherwise. Including. For example, the phrase "compound" or "at least one compound" may include multiple compounds, including mixtures thereof.
The term "example" or "exemplary" is used herein to mean used as an example, case, or example. Embodiments described as "examples" or "exemplary" are not necessarily construed to be preferred or advantageous over other embodiments, and / or exclude the incorporation of features from other embodiments. , Don't do that.
The phrase "as appropriate" is used herein to mean "provided in some embodiments and not in other embodiments." Certain embodiments of the invention may include multiple "optional" features as long as such features do not conflict.
As used herein, the term "method" is known or known to practitioners of chemistry, pharmacology, biology, biochemistry, and medicine, without limitation. Methods and means for completing a given task, including methods, means, techniques, procedures and procedures, methods, means, techniques, procedures and procedures that are easily developed. , Techniques, procedures, and procedures.
Throughout the application, various embodiments of the invention may be presented in a range format. It will be appreciated that the description of the range form is for convenience only and should not be construed as an inflexible limitation on the scope of the invention. Therefore, the description of the range should be considered as having all possible subranges disclosed in particular as well as individual numerical values within that range. For example, descriptions of ranges such as 1 to 6 are specifically disclosed as 1 to 3, 1 to 4, 1 to 5, 2 to 4, 2 to 6, 3 to 6, and so on. It should be considered to have a subrange, and even individual numbers within that range, such as 1, 2, 3, 4, 5, and 6. This applies regardless of the breadth of range.
Whenever a numerical range is specified herein, it is intended to include the number (fraction or integer) cited within the specified range. The first specified number and the second specified number are "in the range / range between" and the first specified number "from" the second specified number "in the range / range". The wording is used interchangeably herein and is intended to include the first and second indicated numbers and all fractions and integers between them.
For clarity, it will be appreciated that some features of the invention, described in the background context of the separate embodiments, can also be implemented in combination in a single embodiment. Conversely, for brevity, the various features of the invention, described in the context of a single embodiment, are also described separately, in appropriate subcombinations, or elsewhere in the invention. It can be provided as appropriate in the embodiment. Some of the features described in the background of the various embodiments should not be considered as essential features of these embodiments unless the embodiments become inoperable without these elements.
Although the present invention has been described in conjunction with its particular embodiment, it is clear to those skilled in the art that many alternatives, modifications, and modifications will be apparent. Accordingly, the invention is intended to include all such alternative, modified, and modified forms that fall within the spirit of the appended claims.
All publications, patents, and patent applications mentioned herein are specifically and individually instructed that their respective publications, patents, or patent applications are incorporated herein. Incorporated herein to the same extent as if. In addition, citations or identification of documents in this application shall not be construed as recognizing that such documents are available as prior art to the present invention. As long as section headings are used, these should not be construed as necessary restrictions.<u style="single">The inventions described in the claims of the original application of the present application are described below.</u><u style="single"> [1] Receiving the first vascular model of the cardiovascular system,</u><u style="single"> Determining at least one characteristic based on the first vascular model representing the flow through the stenotic segment of the vasculature.</u><u style="single"> Generating a second vascular model and</u><u style="single"> Elements corresponding to the first blood vessel model and</u><u style="single"> With at least one modified form, including a difference in at least one characteristic of the flow,</u><u style="single"> A method for vascular evaluation, comprising calculating a flow index comparing the first model with the second model.</u><u style="single"> [2] The difference in at least one characteristic of the flow comprises a difference between at least one characteristic of the flow through the constricted segment and the characteristic of the flow in the corresponding segment of the second model [1]. ] The method described in.</u><u style="single"> [3] The method according to [1], wherein the first blood vessel model is calculated based on a plurality of 2-D angiographic images.</u><u style="single"> [4] The angiographic image has sufficient resolution to allow vascular width determination to be made within 10% of the vascular segment according to at least a third bifurcation from the major human coronary artery. The method described in [3].</u><u style="single"> [5] The method according to [1], wherein the flow index comprises a prediction of increased flow that can be achieved by intervention to remove the stenosis from the stenosis segment.</u><u style="single"> [6] The comparative flow index is described in any one of [1] to [5], which is calculated based on the ratio of the corresponding flow characteristics of the first blood vessel model and the second blood vessel model. Method.</u><u style="single"> [7] The method according to any one of [1] to [6], wherein the comparative flow index is calculated based on the ratio of the corresponding flow characteristics of the narrowed segment and the non-stenotic segment.</u><u style="single"> [8] The method according to any one of [1] to [7], comprising reporting the comparative flow index as a single number per constriction.</u><u style="single"> [9] The method according to any one of [1] to [8], wherein the at least one characteristic of the flow comprises a flow rate.</u><u style="single"> [10] The comparative flow index comprises an index representing a blood flow reserve index having a ratio of the maximum flow through the stenotic vessel to the maximum flow through the stenotic vessel from which the stenosis has been removed [9]. ] The method described in.</u><u style="single"> [11] The method according to any one of [9] to [10], wherein the comparative flow index is used in determining a recommendation for angiogenesis.</u><u style="single"> [12] The method according to [10], wherein the comparative flow index has a value indicating a capacity for restoring the flow by removing the stenosis.</u><u style="single"> [13] The first and second vascular models include connected branches of vascular segment data, each of which is associated with a corresponding vascular resistance to flow [1]-[12]. The method according to any one of the above.</u><u style="single"> [14] The method described in [13], wherein the first vascular model does not include a detailed 3-D description in the radial direction of the vessel wall.</u><u style="single"> [15] The second vascular model is described in any one of [1] to [13], which is a conventional model including a blood vessel having a relatively large diameter that replaces a stenotic blood vessel in the first vascular model. the method of.</u><u style="single"> [16] The second vascular model is a conventional model comprising normalized blood vessels obtained by normalizing stenotic blood vessels based on the characteristics of adjacent non-stenotic blood vessels [1] to [13]. The method according to any one item.</u><u style="single"> [17] The method according to any one of [1] to [13], wherein the at least one characteristic of the flow is calculated based on the characteristics of a plurality of vascular segments connected to the stenotic segment by the flow.</u><u style="single"> [18] The method according to any one of [1] to [17], wherein the characteristic of the flow comprises resistance to a fluid flow.</u><u style="single"> [19] In the first vascular model, further distinguishing a stenotic vessel from the crown of a vascular branch downstream of the stenotic vessel and calculating the resistance to fluid flow within the crown. Prepare,</u><u style="single"> Here, the method according to [18], wherein the flow index is calculated based on the volume of the crown and the contribution of the stenotic vessel to the resistance to fluid flow.</u><u style="single"> [20] The method according to any one of [1] to [19], wherein the first blood vessel model includes a representation of blood vessel positions in a three-dimensional space.</u><u style="single"> [21] The method according to any one of [1] to [20], wherein each vascular model corresponds to a portion of said vascular system between two consecutive bifurcations of the vascular system.</u><u style="single"> [22] The method according to any one of [1] to [20], wherein each vascular model corresponds to a part of the vascular system including a bifurcation of the vascular system.</u><u style="single"> [23] Each vascular model is described in any one of [1] to [20] corresponding to a portion of the vascular system that extends at least one branch of the vascular system beyond the stenotic segment. the method of.</u><u style="single"> [24] The method according to [23], wherein each vascular model corresponds to a portion of the vascular system that extends at least three branches of the vascular system beyond the stenotic segment.</u><u style="single"> [25] The method according to [3], wherein the vascular model comprises pathways along vascular segments, each of which is mapped along its extent to a position within the plurality of 2-D images.</u><u style="single"> [26] The method according to [1], further comprising acquiring an image of the cardiovascular system and constructing a first vascular model thereof.</u><u style="single"> [27] Each vascular model corresponds to a portion of the vascular system that extends distally as long as the resolution of the image is within 10% of the correct value to allow determination of vascular width [26]. Method.</u><u style="single"> [28] At least one of the first vascular model and the second vascular model is an artificially dilated vasculature at the time of acquisition of the image used to generate the at least one vascular model. The method described in [1], which is a model of.</u><u style="single"> [29] A computer that stores program instructions and, when the instructions are read by a computer, receives multiple 2-D images of the subject's vasculature and causes the computer to perform the method described in [1]. Computer software products with readable media.</u><u style="single"> [30] Received multiple 2-D images of some of the vascular system,</u><u style="single"> Converting the plurality of 2-Ds into a first vascular model of the vascular system,</u><u style="single"> At least one characteristic was determined based on the first vascular model representing the flow through the stenotic segment of the vasculature.</u><u style="single"> Elements corresponding to the first blood vessel model and</u><u style="single"> A second vascular model comprising at least one modified form comprising transforming said at least one characteristic of flow through a stenotic segment into a characteristic of flow as if passing through a corresponding segment where the effect of stenosis is reduced. To generate</u><u style="single"> A system for vascular evaluation comprising a computer configured to calculate a flow index that compares the first model with the second model.</u><u style="single"> [31] The system according to [30], wherein the computer is configured to calculate the flow index within 5 minutes of receiving the first blood vessel model.</u><u style="single"> [32] The system according to [30], wherein the computer is configured to calculate the flow index within 5 minutes of acquiring the 2-D image.</u><u style="single"> [33] The system according to [30], wherein the computer is located at a location remote from the imaging device.</u><u style="single"> [34] Receiving a vascular model of the cardiovascular system and</u><u style="single"> Determining at least a first flow characteristic based on the vascular model representing the flow through the stenotic segment of the vasculature and the coronary vessel to the stenotic segment.</u><u style="single"> Determining at least a second flow characteristic based on the vascular model representing the flow through the coronary vessel without being restricted by the stenotic segment.</u><u style="single"> A method for vascular evaluation comprising calculating a flow index comparing the first flow property with the second flow property.</u>
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| Notice of designation (change) of administrative judgeJAPANESE INTERMEDIATE CODE: C22C22 | C22 | |
| Notice of termination of reconsideration by examiners before appeal proceedingsAppealJAPANESE INTERMEDIATE CODE: C211C211 | C211 | |
| Re-examination (zenchi) completed and case transferred to appeal boardAppealJAPANESE INTERMEDIATE CODE: A912A912 | A912 | |
| Notice of transfer of a case for reconsideration by examiners before appeal proceedingsAppealJAPANESE INTERMEDIATE CODE: C21C21 | C21 | |
| Transfer to examiner for re-examination before appeal (zenchi)AppealJAPANESE INTERMEDIATE CODE: A911A911 | A911 | |
| Request for written amendment filedJAPANESE INTERMEDIATE CODE: A523A521 | A521 | |
| Trial request (containing other claim documents, opposition documents)OppositionJAPANESE INTERMEDIATE CODE: C60C60 | C60 | |
| Decision of refusalJAPANESE INTERMEDIATE CODE: A02A02 | A02 | |
| Request for written amendment filedJAPANESE INTERMEDIATE CODE: A523A521 | A521 | |
| Notification of reasons for refusalJAPANESE INTERMEDIATE CODE: A131A131 | A131 | |
| Report on retrievalJAPANESE INTERMEDIATE CODE: A971007A977 | A977 | |
| Request for written amendment filedJAPANESE INTERMEDIATE CODE: A523A521 | A521 | |
| Written request for application examinationJAPANESE INTERMEDIATE CODE: A621A621 | A621 |
Numbers
- Publication
- 6636331
- Application
- 2015552198
Titles2
- Japanese
- 血流予備量比の算出
- English
- Calculation of blood flow reserve ratio
Classification
- CPC, 29
- A61B5/02007
- G16H50/30
- A61B6/504
- A61B5/021
- A61B5/026
- A61B5/7289
- A61B2576/023
- A61B6/032
- A61B6/037
- A61B6/481
- A61B6/507
- A61B6/5217
- A61B6/541
- A61B8/06
- G06T7/0012
- G06T2200/04
- G06T2207/10072
- G06T2207/10116
- G06T2207/10132
- G06T2207/30101
- G06T2207/30104
- G06T2207/30172
- G06T7/00
- G06T17/00
- G16H50/50
- G16H30/20
- G16Z99/00
- A61B5/1075
- A61B6/5235
- IPC, 4
- A61B5 00
- A61B5 055
- A61B6 03
- G06T1 00
