Coronary heart disease risk assessment method and device, electronic equipment, storage medium and program product

Abstract

The application relates to a coronary heart disease risk assessment method and device, electronic equipment, a storage medium and a program product. The method comprises the following steps: acquiring a coronary CTA image of a subject; constructing a coronary artery and myocardium three-dimensional model based on the coronary CTA image; generating a subepicardial small-size coronary artery model and a myocardial small microvessel model based on the coronary artery and myocardium three-dimensional model; constructing a full coronary circulation model according to the coronary artery and myocardium three-dimensional model, the subepicardial small-size coronary artery model, the myocardial small microvessel model, coronary microcirculation, cardiopulmonary circulation and systemic circulation; and calculating the blood flow reserve fraction and the microcirculation resistance index of each coronary artery according to the full coronary circulation model, and generating an evaluation report. The technical scheme can improve the accuracy of coronary heart disease risk assessment.

Description

Technical Field

[0001] This application relates to the field of risk assessment technology, specifically to a method, device, electronic device, storage medium, and program product for assessing the risk of coronary heart disease. Background Technology

[0002] The main pathological mechanism of coronary artery disease (CAD) is the stenosis or dysfunction of the coronary arteries, leading to ischemic damage or necrosis of the myocardium. Therefore, accurately assessing the degree of myocardial ischemia is crucial for the clinical diagnosis and intervention selection of CAD. Currently, there are various imaging and functional examinations available clinically for indirect or direct assessment of myocardial ischemia, with relevant indicators including myocardial blood flow (MBF), fractional flow reserve (FFR), and index of microcirculatory resistance (IMR). Existing clinical guidelines recommend using the coronary artery stenosis rate as a basis, combined with the aforementioned functional indicators (FFR, IMR), to assess the functional status of the large vessels under the epicardium and the small / microvessels within the myocardium to determine whether surgical treatment is necessary. However, conducting a comprehensive and systematic examination faces challenges such as high cost, long processing time, and the risk of trauma. Therefore, there is an urgent need to develop a comprehensive, accurate, and non-invasive quantitative clinical decision support method. Summary of the Invention

[0003] This application provides a method, device, electronic device, storage medium, and program product for assessing the risk of coronary heart disease, which can improve the accuracy of coronary heart disease risk assessment.

[0004] According to a first aspect of the embodiments of this application, a method for assessing the risk of coronary heart disease is provided, comprising: acquiring coronary artery CTA images of a subject; constructing a 3D model of the coronary arteries and myocardium based on the coronary artery CTA images; generating a small-sized subepicardial coronary artery model and a microvascular model within the myocardium based on the 3D model of the coronary arteries and myocardium; constructing a whole coronary circulation model based on the 3D model of the coronary arteries and myocardium, the small-sized subepicardial coronary artery model, the microvascular model within the myocardium, the coronary microcirculation, the cardiopulmonary circulation, and the systemic circulation; and calculating the fractional flow reserve and microcirculation resistance index of each coronary artery based on the whole coronary circulation model, and generating an assessment report.

[0005] In one implementation, a small-sized coronary artery model and a microvascular model within the myocardium are generated based on a 3D model of the coronary artery and myocardium. This includes: generating small-sized coronary arteries and microvascular models within the epicardium based on the 3D model of the coronary artery and myocardium and a vascular constraint construction optimization algorithm, thereby obtaining the small-sized coronary artery model and the microvascular model within the epicardium. The vascular network of the small-sized coronary artery model and the microvascular model within the epicardium is a binary tree structure composed of cylindrical pipes. For each vascular branch, the flow rate and pressure of the parent vessel and the daughter vessel satisfy the mass flow rate conservation relationship and the energy conservation relationship, respectively, and the radii of the parent vessel and the daughter vessel satisfy the anatomical Murray's law.

[0006] In one implementation, based on a 3D model of the coronary arteries and myocardium and a vascular constraint construction optimization algorithm, small-sized subepicardial coronary arteries and intramyocardial microvessels are generated to obtain a model of small-sized subepicardial coronary arteries and a model of intramyocardial microvessels. This includes: using the terminal segments of each coronary artery in the 3D coronary artery model as the starting point for angiogenesis, confining the vascular growth region to the epicardial surface, and extending and growing coronary arteries within the epicardial surface to generate small-sized subepicardial coronary arteries, thus obtaining an initial model of small-sized subepicardial coronary arteries. The model is developed by switching the blood vessel growth region from the epicardial surface to the left ventricular myocardial wall. At the terminal portion of the small-sized coronary arteries under the epicardium, the blood vessel growth pattern is changed from growth along the epicardium to growth into the myocardium, generating intramyocardial microvessels and obtaining an initial intramyocardial microvessel model. Based on the blood vessel constraint construction optimization algorithm, for the initial small-sized coronary artery model under the epicardium and the initial intramyocardial microvessel model, the node coordinates and blood vessel direction of each segment of the blood vessel are iteratively adjusted. When the iteration converges, the small-sized coronary artery model under the epicardium and the intramyocardial microvessel model are output.

[0007] In one implementation, a complete coronary circulation model is constructed based on a 3D model of the coronary arteries and myocardium, a small-sized subepicardial coronary artery model, a microvascular model within the myocardium, the coronary microcirculation, the cardiopulmonary circulation, and the systemic circulation. This includes: meshing the 3D coronary artery model within the 3D coronary artery and myocardium model to generate a 3D epicardial coronary artery computational mesh model; or, extracting the vessel length and diameter along the course of each branch of the coronary artery from the 3D coronary artery model to construct a 1D epicardial coronary artery hemodynamic model; and, based on the small-sized subepicardial coronary artery model and the microvascular model within the myocardium, utilizing vessel length, diameter along the course, and topology, constructing a 0D or 1D model. A reduced-order model of small-sized subepicardial coronary arteries and intramyocardial vessels is constructed. Based on hemodynamic electrical simulation, a 0-dimensional systemic circulation hemodynamic model is constructed for coronary microcirculation, cardiopulmonary circulation, and systemic circulation. A complete coronary circulation model is constructed by bidirectionally coupling a 3-dimensional epicardial coronary artery computational grid model, a 0-dimensional or 1-dimensional reduced-order model of small-sized subepicardial coronary arteries and intramyocardial vessels, and a 0-dimensional systemic circulation hemodynamic model. Alternatively, a complete coronary circulation model is constructed by bidirectionally coupling a 1-dimensional epicardial coronary artery hemodynamic model, a 0-dimensional or 1-dimensional reduced-order model of small-sized subepicardial coronary arteries and intramyocardial vessels, and a 0-dimensional systemic circulation hemodynamic model.

[0008] In one embodiment, a 3D epicardial coronary artery computational mesh model, a 0D or 1D reduced-order model of small-sized epicardial coronary arteries and intramyocardial vessels, and a 0D systemic hemodynamic model are bidirectionally coupled to construct a whole coronary circulation model; or, a 1D epicardial coronary artery hemodynamic model, a 0D or 1D reduced-order model of small-sized epicardial coronary arteries and intramyocardial vessels, and a 0D systemic hemodynamic model are bidirectionally coupled to construct a whole coronary circulation model, including: acquiring myocardial CTP images, upper arm artery blood pressure, and heart rate of the subject; and bidirectionally coupling a 3D epicardial coronary artery computational mesh model, a 0D or 1D reduced-order model of small-sized epicardial coronary arteries and intramyocardial vessels, and a 0D systemic hemodynamic ...; and bidirectionally coupling a 3D epicardial coronary artery computational mesh model, a 0D or 1D reduced-order model of small-sized epicardial coronary arteries and intramyocardial vessels, and a 0D systemic hemodynamic model, including: acquiring myocardial CTP images, upper arm artery blood pressure, and heart rate; and bidirectionally coupling a 1D epicardial coronary artery computational mesh model, a 0D or 1D reduced-order model of small-sized epicardial coronary arteries and intramyocardial vessels, and a An initial whole coronary circulation model is constructed by bidirectionally coupling a 1D reduced-order model of small-sized subepicardial coronary arteries and intramyocardial vessels with a 0D systemic circulation hemodynamic model; or, an initial whole coronary circulation model is constructed by bidirectionally coupling a 1D epicardial coronary artery hemodynamic model, a 0D or 1D reduced-order model of small-sized subepicardial coronary arteries and intramyocardial vessels with a 0D systemic circulation hemodynamic model. Based on the subject's myocardial CTP image, upper arm artery blood pressure, heart rate, and the initial whole coronary circulation model, myocardial blood flow and arterial blood pressure are iteratively calculated, and the parameters of the initial whole coronary circulation model are adjusted to obtain the whole coronary circulation model.

[0009] In one implementation, a 3D model of the coronary artery and myocardium is constructed based on coronary CTA images, including: segmenting the arterial lumen, myocardium, bone, and soft tissue regions in the coronary CTA images according to the image grayscale values; constructing an initial 3D model of the coronary artery and myocardium using region growing and surface lofting algorithms for the arterial lumen and myocardium, the construction scope of the initial 3D model of the coronary artery and myocardium including: the aortic root, left main coronary artery, left anterior descending artery, circumflex artery, right coronary artery, and left ventricular myocardium; and performing surface smoothing processing on the initial 3D model of the coronary artery and myocardium to obtain the 3D model of the coronary artery and myocardium.

[0010] According to a second aspect of the embodiments of this application, a coronary artery disease risk assessment device is provided. The coronary artery disease risk assessment device includes: an acquisition module, a first construction module, an angiogenesis module, a second construction module, and an assessment report generation module. The acquisition module is used to acquire coronary artery CTA images of a subject. The first construction module is used to construct a 3D model of the coronary arteries and myocardium based on the coronary artery CTA images. The angiogenesis module is used to generate a small-sized subepicardial coronary artery model and a microvascular model within the myocardium based on the 3D model of the coronary arteries and myocardium. The second construction module is used to construct a complete coronary circulation model based on the 3D model of the coronary arteries and myocardium, the small-sized subepicardial coronary artery model, the microvascular model within the myocardium, the coronary microcirculation, the cardiopulmonary circulation, and the systemic circulation. The assessment report generation module is used to calculate the fractional flow reserve and microcirculation resistance index of each coronary artery based on the complete coronary circulation model and generate an assessment report.

[0011] According to a third aspect of the embodiments of this application, an electronic device is provided, including a memory and a processor, wherein the memory is used to store a computer program executable by the processor; and the processor is used to execute the computer program in the memory to implement the above-described coronary heart disease risk assessment method.

[0012] According to a fourth aspect of the embodiments of this application, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, can implement the above-described coronary heart disease risk assessment method.

[0013] According to a fifth aspect of the embodiments of this application, a computer program product is provided, including a computer program that, when executed by a processor, implements the above-described coronary heart disease risk assessment method.

[0014] The method described in this application has the following beneficial effects:

[0015] (1) Effectively reduces examination costs and avoids the risks of invasive measurements. This application only requires obtaining the subject's data through non-invasive measurement technology, which not only reduces examination costs but also effectively avoids the risk of complications that may be caused by invasive measurements.

[0016] (2) The assessment results have higher accuracy, stronger physiological significance and clinical application value. This application uses the vascular virtual generation method and geometric multi-scale modeling method to realize the integrated analysis of hemodynamic parameters of the whole coronary circulation, and considers the structure and function of intramyocardial vessels and the influence of systemic circulation on coronary blood flow, which can greatly improve the physiological significance and clinical application value of the assessment results.

[0017] (3) Provide richer information support for risk assessment of coronary heart disease. This application provides hemodynamic information covering epicardial coronary arteries and intramyocardial vessels. It can not only output FFR and IMR to quantitatively evaluate the functional impact of coronary artery stenosis and microcirculatory function, but also provide detailed hemodynamic information such as wall shear stress distribution and near-wall flow field characteristics for assessing plaque stability and adverse progression risk, thereby supporting clinical decision-making from multiple information dimensions. Attached Figure Description

[0018] The above and other objects, features, and advantages of exemplary embodiments of this application will become readily apparent from the following detailed description taken in conjunction with the accompanying drawings. Several embodiments of this application are illustrated in the drawings by way of example and not limitation, in which:

[0019] Figure 1 This is a flowchart illustrating a method for assessing the risk of coronary heart disease according to an exemplary embodiment.

[0020] Figure 2 This is a block diagram illustrating a coronary heart disease risk assessment device according to an exemplary embodiment.

[0021] Figure 3 This is a flowchart illustrating another method for assessing the risk of coronary heart disease according to another exemplary embodiment.

[0022] Figure 4 This is a coupled structural diagram of a 0-3D whole coronary circulation model according to an exemplary embodiment.

[0023] Figure 5 This is an example of an FFR contour map and an MBF contour map, as illustrated in an exemplary embodiment.

[0024] Figure 6 This is a 3D streamline of blood and a cloud map of hemodynamic parameters of the wall surface, according to an exemplary embodiment.

[0025] Figure 7 This is a simulated value of 17 segments of myocardial blood flow (MBF) in the left ventricle, as illustrated in an exemplary embodiment. sim ) and dynamic CTP measured value (MBF) ctp (Comparison diagram)

[0026] Figure 8 This is a model for calculating FFR (FFR) according to an exemplary embodiment. sim ) and clinically measured FFR (FFR) clin A comparison diagram.

[0027] Figure 9 This is a block diagram illustrating an electronic device according to an exemplary embodiment. Detailed Implementation

[0028] It should be understood that in the embodiments of this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0029] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0030] The following detailed description of some embodiments of this application is provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0031] One embodiment of this application provides a method for assessing the risk of coronary artery disease (CAD). This method, based on the acquisition of coronary computed tomography (CTA) and computed tomography perfusion (CTP) images, upper arm artery blood pressure, and heart rate, integrates coronary artery anatomy, local stenosis morphology, and microcirculatory function into hemodynamic analysis by combining virtual angiogenesis algorithms and geometric multi-scale modeling methods. It outputs indicators such as fractional flow reserve (FFR) and microcirculatory resistance index (IMR), providing quantitative information support for CAD risk assessment and clinical decision-making. Please refer to... Figure 1 This method for assessing the risk of coronary heart disease may include the following steps:

[0032] S101, acquire coronary CTA images of the subject.

[0033] In some embodiments, coronary CTA images and myocardial CTP images of the subject can be acquired using medical imaging equipment, and upper arm arterial blood pressure (including systolic pressure, diastolic pressure, and mean pressure) and heart rate can be measured using a sphygmomanometer under maximal congestion conditions.

[0034] S102, based on coronary CTA images, constructs a 3D model of the coronary arteries and myocardium.

[0035] In some embodiments, the subject's coronary CTA images can be input into medical image processing software such as Simvascular or Mimics to reconstruct a 3D geometric model of the coronary arteries and left ventricular myocardium.

[0036] In some embodiments, the refactoring step may include:

[0037] 1. Based on image grayscale values, the arterial lumen, myocardium, bone, and soft tissue regions are segmented. For the arterial lumen and myocardial tissue, algorithms such as region growing and surface lofting are used to construct initial 3D models of the coronary arteries and myocardium. These initial 3D models include initial 3D models of the coronary arteries and myocardium. The scope of the initial 3D models includes the aortic root, left main coronary artery, left anterior descending artery, circumflex artery, right coronary artery, and other major branches of the coronary arteries, as well as the left ventricular myocardium.

[0038] 2. The initial 3D models of the coronary artery and myocardium were smoothed to obtain 3D models of the coronary artery and myocardium, which include the 3D model of the coronary artery and the 3D model of the myocardium.

[0039] S103 generates a small-sized subepicardial coronary artery model and a microvascular model (i.e., intramyocardial micro / microvascular) model based on a 3D model of coronary arteries and myocardium.

[0040] In some embodiments, the small-sized subepidermal coronary arteries and intramyocardial microvessels that are difficult to distinguish in coronary CTA imaging can be completed based on the 3D model of coronary arteries and myocardium and the constrained constructed optimization (CCO) algorithm, so as to obtain the model of the small-sized subepidermal coronary arteries and the model of the intramyocardial microvessels, and thus obtain a complete coronary circulation model with complete anatomical structure and physiological characteristics.

[0041] In some embodiments, the vascular network can be modeled as a binary tree structure composed of cylindrical pipes based on the vascular constraint construction optimization algorithm. For each vascular branch, the flow rate and pressure of the parent vessel and the child vessel satisfy the mass flow rate conservation relationship and the energy conservation relationship, respectively, and the radii of the parent vessel and the child vessel follow the Murray's law of anatomy.

[0042] Formula (1)

[0043] Where Q represents the blood flow rate within the blood vessel. The flow rate of the mother vessel i is denoted as . Let be the flow rate of the j-th branch vessel from the parent vessel i. Let P be the intravascular pressure. The pressure at the inlet of the mother vessel i. R is the outlet pressure of the sub-vessel j. R is the flow resistance. Let be the flow resistance of the sub-vessel j. Let r be the radius of the vessel segment. The radius of the mother blood vessel. Let be the radius of sub-vessel j. The subscripts i and j represent sub-vessel j of the i-th segment of the blood vessel, where i and j are positive integers. The value range is [2.7, 3]. When given N... tot When constructing the vascular tree structure of root vessels, the exit locations of new terminal vessels must first be determined. This process is accomplished by generating pseudo-random points in geometric space, and the vascular tree structure is then optimized. The objective function for optimization is Equation (2), which is:

[0044] Formula (2)

[0045] Among them, V i Let m be the volume of the i-th segment of the blood vessel. i Let be the spatial coordinates of the midpoint of the i-th segment of the blood vessel. The spatial location weighting function is used to constrain the vascular growth region, penalizing vessels that deviate from the growth region and ensuring that large vessels are mainly distributed in the epicardial region, while small vessels and terminal vessels tend to be distributed on the endocardial side, thus making the generated vascular structure more anatomically consistent. The goal is to find the minimum value of the objective function T, compare vascular trees with different topological connections, and select the optimal configuration.

[0046] The specific steps mainly include:

[0047] 1. Using the terminal vessels of each blood vessel in the 3D model of coronary arteries and myocardium as the starting point for angiogenesis, the blood vessel growth area is limited to the epicardial surface of the 3D model of myocardium. Within this range, coronary arteries extend and grow, generating an initial small-sized subepicardial coronary artery model that is difficult to distinguish in coronary CTA imaging.

[0048] In some embodiments, the initial blood vessel growth region can be set as the epicardial surface of a 3D myocardial model, and a weighting function can be set. If the midpoint of the blood vessel is m i Landing outside the epicardial surface, weight By taking a larger value, penalties are imposed on vessels that extend beyond their boundaries, the location of bifurcation points is optimized, and it is ensured that vessels can only extend and grow within the area of ​​the epicardial surface.

[0049] In some embodiments, pseudo-random points can be generated within a defined epicardial surface as candidate exit locations for newly added peripheral vessels. New vessel branches extend from existing vessel ends to the candidate exit locations, constructing a binary tree branching structure. Each time a vessel branch is generated, the constraints are immediately verified, including verification of mass flow conservation, energy conservation, and Murray's law (anatomical law), i.e., verification according to formula (1). New vessel branches are continuously added to generate an initial small-sized subepardial coronary artery model.

[0050] 2. The blood vessel growth area was switched from the epicardial surface to the left ventricular myocardial wall of the 3D model of myocardium. At the terminal of the small coronary artery under the epicardium, the blood vessel growth pattern was changed from growing along the epicardium to growing into the myocardium, generating an initial microvascular model within the myocardium.

[0051] In some embodiments, the initial small-sized coronary artery terminals beneath the epicardium are used as the starting points for a new batch of angiogenesis. Pseudo-random points are generated within the left ventricular myocardium as candidate exit locations for newly formed terminal vessels, shifting the angiogenesis region from the epicardial surface to the interior of the left ventricular myocardial wall. The weights can be modified. By adjusting the weight values ​​corresponding to different myocardial layers, the distribution density of blood vessels in each layer is controlled, thereby achieving a higher blood vessel density closer to the endocardium. An initial binary tree network of small and microvessels within the myocardium is generated iteratively. Each time a blood vessel branch is generated, the constraints are immediately verified, including verifying the mass flow conservation relationship, energy conservation relationship, and Murray's law of anatomy, i.e., verification is performed according to formula (1). New blood vessel branches are continuously added to generate an initial model of small and microvessels within the myocardium.

[0052] 3. Based on the vascular constraint construction optimization algorithm, the optimization objective is to minimize the objective function (Equation (2)) for all generated vascular networks (initial subepicardial small coronary artery model and initial intramyocardial microvascular model). The node coordinates and vascular orientation of each segment of the blood vessel are iteratively adjusted to continuously correct the vascular network topology. Constraints are applied to each vascular bifurcation node, and the following is continuously verified during the iterative adjustment process: all parent and child blood vessels at the bifurcation positions satisfy the mass flow conservation relationship, energy conservation relationship, and the radii of parent and child blood vessels follow the Murray law of anatomy. Blood vessel configurations that violate physiological constraints are eliminated. When the objective function converges, the objective function no longer decreases significantly, and the optimization stops.

[0053] 4. Output small-sized subepicardial coronary artery models and intramyocardial microvascular models.

[0054] S104. Based on the 3D model of coronary arteries and myocardium, the model of small-sized coronary arteries under the epicardium, the model of small microvessels in the myocardium, the coronary microcirculation, the cardiopulmonary circulation, and the systemic circulation, a complete coronary circulation model is constructed.

[0055] In some embodiments, the 3D coronary artery model can be meshed using mesh generation software such as Ansys ICEM or Fluent meshing to generate a high-precision 3D epicardial coronary artery computational mesh model. Alternatively, medical image processing software such as Simvascular or Mimics can be used to extract the geometric parameters (including vessel length and diameter along the vessel) of each artery from the 3D coronary artery model to construct a 1D epicardial coronary artery hemodynamic model.

[0056] In some embodiments, based on the virtually generated small-sized subepidermal coronary artery model and intramyocardial microvascular model, a 0-dimensional or 1-dimensional reduced-order model of the small-sized subepidermal coronary artery and intramyocardial vessel that retains spatial coordinates can be constructed using vessel length, diameter along the vessel, and topology. Each vessel has 3-dimensional spatial coordinates, and hemodynamic calculation results (such as hemodynamic parameters such as pressure and flow rate) can be mapped to the corresponding vessel location or myocardial tissue.

[0057] In some embodiments, a 0-dimensional systemic circulatory hemodynamic model can be constructed based on hemodynamic electrical simulation methods for coronary microcirculation, cardiopulmonary circulation, and systemic circulation.

[0058] In some embodiments, an initial whole coronary circulation model can be obtained by bidirectional coupling based on a 3D epicardial coronary artery computational grid model or a 1D epicardial coronary artery hemodynamic model, a 0D or 1D reduced-order model of small-sized epicardial coronary arteries and intramyocardial vessels, and a 0D systemic circulation hemodynamic model.

[0059] In some embodiments, initial values ​​can be set for the parameters of the initial whole coronary circulation model based on recorded statistical data. Model parameters include: vascular resistance, vascular compliance, blood inertia, myocardial elasticity, myocardial viscoelasticity, valve Bernoulli resistance, etc.

[0060] In some embodiments, myocardial blood flow and arterial blood pressure can be iteratively calculated based on the subject's myocardial CTP image, upper arm arterial blood pressure, heart rate, and initial whole coronary circulation model, and the parameters of the initial whole coronary circulation model can be adjusted to obtain the whole coronary circulation model.

[0061] In some embodiments, myocardial blood flow (MBF) can be extracted from the subject's myocardial CTP images using software (such as commercial software, open-source software, or self-developed software). Combined with the subject's upper arm arterial blood pressure, a clinical dataset can be constructed as a comparison object for the calculation results of the whole coronary circulation model. An objective function can be established, using the error between the simulation output of the initial whole coronary circulation model and the clinically measured MBF and blood pressure as the optimization objective.

[0062] In some embodiments, computational fluid dynamics (CFD) software (such as ANSYS Fluent or OpenFOAM) can be used to solve the hemodynamic control equations of a 3D model of the coronary arteries and myocardium. The computer solvers of a 0D or 1D reduced-order model of small-sized epicardial coronary arteries and intramyocardial vessels and a 0D systemic circulation hemodynamic model can be embedded into the CFD software through a custom function. Blood flow and pressure data can be exchanged at the interface between the 3D model and the reduced-order model to complete the coupled solution of the 3D model and the reduced-order model. The blood velocity, pressure, flow rate and myocardial blood flow in the epicardial coronary arteries, intramyocardial vessels, coronary microcirculation, systemic circulation and cardiopulmonary circulation can be calculated iteratively.

[0063] For example, myocardial blood flow (MBF) can be calculated based on the blood flow in the blood vessels of the myocardium and the volume of the left ventricular myocardium.

[0064] Myocardial blood flow (MBF) = Outflow rate of intramyocardial vessels / Volume of myocardium in the vicinity of the outlet.

[0065] For example, systolic blood pressure, diastolic blood pressure, and mean blood pressure can be obtained from arterial blood pressure in the systemic circulation (such as blood pressure in the upper arm artery).

[0066] In some embodiments, hemodynamic calculations can be performed continuously for multiple cardiac cycles (the duration of which is set according to the subject's heart rate). A multi-objective optimization algorithm (such as NSGA-II or MOEA / D) is employed to optimize the multi-objective function, iteratively calculate myocardial blood flow and arterial blood pressure, iteratively adjust the parameters of the whole coronary circulation model, minimize the errors in MBF, systolic blood pressure, diastolic blood pressure, and mean blood pressure between the simulation results and clinical datasets, and find an optimal solution among the multiple objectives. The mathematical expression of the multi-objective function is:

[0067] min(f1(P),f2(P),f3(P),…,f n (P)

[0068] Among them, f1 to f n The error function represents the difference between the calculated and measured values ​​of parameters such as MBF, systolic blood pressure, and diastolic blood pressure. It can include the error functions between the calculated and measured values ​​of MBF, systolic blood pressure, diastolic blood pressure, and mean blood pressure. p is the vector of model parameters to be optimized.

[0069] In some embodiments, multiple cardiac cycles can be calculated cyclically. After the calculation converges, all hemodynamic results of the last cardiac cycle are saved for subsequent analysis.

[0070] S105 calculates the fractional flow reserve and microcirculation resistance index of each coronary artery based on the whole coronary circulation model, and generates a risk assessment report.

[0071] In some embodiments, the fractional flow reserve (FFR) and index of microcirculatory resistance (IMR) of each coronary artery can be calculated based on the blood velocity, pressure, and flow rate in the epicardial coronary arteries, intramyocardial vessels, coronary microcirculation, systemic circulation, and cardiopulmonary circulation obtained from the last iteration of the initial whole coronary circulation model, and a risk assessment report can be generated.

[0072] In some embodiments, hemodynamic data can be quantitatively analyzed to calculate the fractional flow reserve (FFR). For example, the mean aortic pressure and the mean pressure at the coronary artery stenosis (such as the mean pressure approximately 20 mm downstream of the coronary artery stenosis) can be extracted to calculate the FFR.

[0073] In some embodiments, the microcirculation resistance index (IMR) can be calculated. For example, the IMR can be calculated using the mean pressure at the distal end of the coronary artery and the mean blood flow time (such as the average time required for blood to flow from the inlet of the vessel to the pressure measurement point).

[0074] In some embodiments, the MBF extracted from the myocardial CTP image can be divided into 17 segments for quantitative analysis and evaluation based on the current standardized division method of the left ventricular myocardium.

[0075] In some embodiments, the calculation of plaque risk-related hemodynamic parameters may include: outputting velocity information within the coronary artery at different times and time-series data of wall shear stress (WSS) over a cardiac cycle, and calculating wall shear stress-related parameters characterizing plaque progression risk, such as time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), transverse wall shear stress (TransWSS), and topological shear variation index (TSVI).

[0076] In some embodiments, parameters of plaque progression risk can be visualized, including generating FFR and MBF cloud maps; drawing 3D streamlines of coronary blood flow and wall dynamic parameter cloud maps; and recording IMR of each branch in a table.

[0077] In some embodiments, a risk assessment report can be output, including a comprehensive assessment report that integrates FFR, IMR, MBF distribution, and wall shear stress parameters to assess the risk of myocardial ischemia, the causes of ischemia, and the risk of adverse plaque progression in patients with coronary heart disease, in order to assist in clinical diagnosis and treatment decisions.

[0078] Another embodiment of this application provides a coronary heart disease risk assessment device.

[0079] In some embodiments, such as Figure 2 As shown, the coronary heart disease risk assessment device 200 includes an acquisition module 201, a first construction module 202, an angiogenesis module 203, a second construction module 204, and an assessment report generation module 205.

[0080] The acquisition module 201 is used to acquire coronary CTA images of the subject. For specific applications of the acquisition module 201, please refer to [reference needed]. Figure 1 Step S101 in the process will not be described again here.

[0081] The first construction module 202 is used to construct a 3D model of the coronary arteries and myocardium based on coronary CTA images. For specific applications of the first construction module 202, please refer to [reference needed]. Figure 1 Step S102 in the process will not be described again here.

[0082] The angiogenesis module 203 is used to generate small-sized subepicardial coronary artery models and intramyocardial microvascular models based on 3D models of coronary arteries and myocardium. For specific applications of the angiogenesis module 203, please refer to [reference needed]. Figure 1 Step S103 in the process will not be described again here.

[0083] The second construction module 204 is used to construct a complete coronary circulation model based on the 3D models of coronary arteries and myocardium, the subepicardial small-sized coronary artery model, the intramyocardial microvascular model, the coronary microcirculation, the cardiopulmonary circulation, and the systemic circulation. For specific applications of the second construction module 204, please refer to [reference needed]. Figure 1 Step S104 in the process will not be described again here.

[0084] The assessment report generation module 205 is used to calculate the fractional flow reserve and microcirculatory resistance index of each coronary artery based on the whole coronary circulation model. For specific applications of the assessment report generation module 205, please refer to [reference needed]. Figure 1 Step S105 in the process will not be described again here.

[0085] The method and apparatus embodiments of this application can complement each other.

[0086] Example:

[0087] This application proposes a method for assessing coronary artery disease (CAD). Based on the acquisition of coronary CTA and myocardial CTP images, upper arm blood pressure, and heart rate from CAD patients, it employs a virtual vascular generation method and geometric multi-scale modeling to comprehensively incorporate coronary artery anatomy, local stenosis morphology, and microcirculatory function into coronary hemodynamic analysis. The method outputs indicators such as fractional flow reserve (FFR) and microcirculatory resistance index (IMR), providing quantitative information support for CAD risk assessment and clinical decision-making. The implementation process of this application is as follows: Figure 2 As shown.

[0088] The 3D models of coronary arteries and myocardium constructed in this application embodiment are 3D models, and the reduced-order model of intramyocardial vessels is a 0D (i.e., lumped parameter) model. However, those skilled in the art will understand that 1D models or other types of reduced-order models are also applicable to the characterization of coronary vascular networks, because these models have the ability to describe hemodynamic phenomena in large-scale vascular networks with low computational cost, and can be coupled with 3D or 0D models to form geometric multi-scale models, which have a similar role in this application.

[0089] refer to Figure 3 Another method for assessing the risk of coronary heart disease according to embodiments of this application may include the following steps:

[0090] Step 201: Data Acquisition

[0091] In some embodiments, coronary artery CTA images and myocardial CTP images of patients with coronary heart disease can be acquired to ensure that the image quality and resolution meet the requirements for geometric model reconstruction and key data extraction.

[0092] In some embodiments, a blood pressure monitor can be used to measure the blood pressure (such as upper arm artery systolic pressure, diastolic pressure, and mean pressure) and heart rate of patients with coronary heart disease.

[0093] Step 202: Reconstruction of 3D Models of Coronary Arteries and Myocardium

[0094] In some embodiments, medical image processing software can be used to segment coronary CTA images to construct high-precision 3D models of the coronary arteries and myocardium. The reconstruction scope of the 3D model of the coronary arteries and myocardium includes the aortic root, left main coronary artery, left anterior descending artery, circumflex artery, and right coronary artery, as well as the left ventricular myocardium.

[0095] Step 203: Virtual generation of blood vessels

[0096] In some embodiments, based on the 3D models of coronary arteries and myocardium, small-sized subepicardial coronary artery models and intramyocardial microvessel models that are difficult to distinguish in coronary CTA images can be virtually generated to obtain a complete coronary circulation model with intact anatomical structure and physiological characteristics.

[0097] Step 204: Construction of Hemodynamic Model

[0098] In some embodiments, the constructed 3D coronary artery model can be meshed to generate a high-precision 3D epicardial coronary artery computational mesh model. Alternatively, the vessel length and diameter along the course of each branch coronary artery can be extracted from the 3D coronary artery model to construct a 1D epicardial coronary artery hemodynamic model.

[0099] In some embodiments, a 0-dimensional reduced-order model of intramyocardial vessels, preserving spatial coordinates, can be constructed based on the generated subepidermal small coronary artery model and intramyocardial microvascular model, according to their geometric parameters (vessel length, diameter along the vessel) and topological structure. In this 0-dimensional reduced-order model of intramyocardial vessels, the viscous impedance (Rk) of each vessel is... 0D ), blood inertia coefficient (L) 0D ) and pipe wall compliance (C 0D The blood flow velocity (c0) can be obtained by integrating the blood vessel length (l), the blood vessel area along the length direction (A0), the blood density (ρ), the blood viscosity coefficient (μ), and the pulse wave velocity (c0) with formula (3). Formula (3) is:

[0100] dl, dl, dl formula (3)

[0101] Among them, R 0D For the viscous resistance of blood vessels, L 0D C is the blood inertia coefficient. 0D ρ is the vessel wall compliance. l is the vessel length. A0 is the vessel area along its length. ρ is the blood density. μ is the blood viscosity coefficient. c0 is the pulse wave velocity.

[0102] In some embodiments, a 0-dimensional systemic circulatory hemodynamic model is constructed for the coronary microcirculation, cardiopulmonary circulation, and systemic circulation based on hemodynamic electrical simulation.

[0103] In some embodiments, reference Figure 4 It can bidirectionally couple a 3D epicardial coronary artery computational mesh model, a 0D intramyocardial vessel reduced-order model, and a 0D systemic circulatory hemodynamic model to construct a closed-loop 0-3D whole coronary circulation model.

[0104] Step 205: Hemodynamic Calculation

[0105] In some embodiments, the cardiac cycle can be set according to the heart rate measured in step 201, and the myocardial blood flow (MBF) data extracted from the myocardial CTP image and the measured blood pressure can be used as a clinical dataset for patients with coronary heart disease; a target function can be established with the model parameters of the 0-3D whole coronary circulation model as independent variables and the relative difference between the model simulation results and the data in the clinical dataset as the dependent variable; the optimization objective is to minimize the error between the MBF and blood pressure output by the simulation and the MBF and upper arm blood pressure measured clinically.

[0106] In some embodiments, hemodynamic calculations can be performed continuously for multiple cardiac cycles. During this process, the model parameters of the 0-3D whole coronary circulation model are iteratively adjusted through a parameter optimization algorithm to minimize the objective function. The hemodynamic calculation results of the last cardiac cycle are then saved for subsequent analysis.

[0107] Step 206: Output of Risk Assessment Report

[0108] In some embodiments, the results of hemodynamic calculations can be post-processed to extract the mean aortic pressure (Pa) and the mean pressure at the coronary artery stenosis site (P). d1 The average pressure (such as about 20 mm downstream of the coronary artery stenosis) is used to calculate the FFR according to formula (4), which is:

[0109] FFR= Formula (4)

[0110] In some embodiments, the mean pressure (P) at the distal coronary artery (e.g., at 2 / 3 of the coronary artery length) can be extracted.d2 The average time (T) required for blood to flow from the inlet of the blood vessel to the pressure measurement point. mn IMR is calculated according to formula (5), which is:

[0111] IMR= P d2 ×T mn Formula (5)

[0112] In some embodiments, the MBF extracted from the myocardial CTP image can be divided into 17 segments for quantitative analysis and evaluation, based on the current standardized left ventricular myocardial segmentation method. For example... Figure 5 As shown, the software was used to generate FFR and MBF contour maps, and the IMR values ​​corresponding to the main branches of the coronary arteries were recorded in a table.

[0113] In some embodiments, the velocity information within the coronary arteries at different times and the WSS time history data within a cardiac cycle can be output. Wall shear stress-related parameters or indices such as TAWSS, OSI, TransWSS, and TSVI can be calculated, and the data can be visualized using software, outputting data such as... Figure 6 The 3D streamlines of blood and the cloud map of hemodynamic parameters of the wall shown intuitively display the blood flow status in the coronary artery and the distribution characteristics of parameters related to endothelial cell damage or plaque formation and adverse progression risk, such as high TAWSS, low TAWSS, high OSI, high TransWSS, and high TSVI.

[0114] Among them, TAWSS, OSI, TransWSS and TSVI can be calculated using formulas (6) to (9) respectively, and formulas (6) to (9) are as follows:

[0115] Formula (6)

[0116] Formula (7)

[0117] Formula (8)

[0118] Formula (9)

[0119] in, This is the instantaneous WSS vector. Let be the unit normal vector of the blood vessel wall. T is time.

[0120] In some embodiments, a risk assessment report can be generated, providing a one-stop output of multiple key indicators that are difficult to obtain comprehensively by existing detection methods, including FFR, IMR, TAWSS, OSI, TransWSS, and TSVI, to assist in clinical diagnosis and decision-making.

[0121] Table 1 shows the functional indicators of the major branches of the coronary arteries output by the 0-3D whole coronary circulation model.

[0122] Table 1

[0123]

[0124] In some embodiments, the reliability of the coronary artery disease risk assessment method of this application can be verified by using MBF measured by clinical CTP images and FFR measured by invasive pressure guidewire methods. The steps include:

[0125] (1) Patient recruitment and clinical data collection

[0126] In some possible implementations, patients with coronary heart disease can be recruited from the cardiology and radiology departments of medical institutions, and coronary CTA images, myocardial CTP images, and clinical data such as upper arm artery blood pressure and heart rate can be collected from these patients as described in the embodiments of this application.

[0127] (2) Invasive measurement of coronary FFR using a guidewire

[0128] In some possible implementations, invasive FFR measurement can be performed on the coronary arteries of patients with 50%–75% luminal stenosis within two weeks after a CT scan. For example, a clinically common pressure guidewire system can be used to measure central arterial blood pressure (P) after vasodilators have been injected to induce maximum congestion in the coronary microcirculation. a ) and blood pressure distal to the stenosis of the coronary arteries (P d2 (e.g., about 20 mm downstream of the coronary artery stenosis), the FFR value is calculated according to the aforementioned formula (4).

[0129] In some possible implementations, the calculated results can be tested for consistency and correlation with the measured values.

[0130] In this embodiment, the above-mentioned non-invasive CTA images, CTP images, and invasive FFR were measured in 6 patients with coronary heart disease. Hemodynamic modeling and numerical calculation were carried out according to the implementation plan of this application, and the MBF and FFR calculated by the model were statistically compared and analyzed with the clinical measured data.

[0131] Table 2 shows a comparison of the calculation results of the 0-3D whole coronary circulation model and the clinical experimental results.

[0132] Table 2

[0133]

[0134] Referring to Table 2, the MBF (MBF) of the 0-3D whole coronary circulation model was first calculated. sim ) and measured values ​​of clinical CTP images (MBF) ctp Perform a consistency check. Figure 7 MBF was showcased sim With MBF ctp The specific comparison results.

[0135] The results show that the MBF calculated by the 0-3D whole coronary circulation model is sim Compared with clinically measured MBF ctp The results were largely consistent in terms of spatial distribution and quantification of 17 myocardial segments, and the relative root mean square error (RRMSE) between the two was less than 7.5%.

[0136] Furthermore, referring to Table 2, the FFR (FFR) calculated by the 0-3D whole coronary circulation model integrating CTP data is... sim ) and clinically measured FFR (FFR) clin For example, to make a comparison, Figure 8 As shown, the FFR of 6 patients sim With FFR clin The correlation was significant (r=0.988, p<0.001), and the two models showed high consistency (RRMSE=1.65%). This comparative analysis demonstrates that the calculation results of the 0-3D whole coronary circulation model are in good agreement with clinically measured data, indicating that the 0-3D whole coronary circulation model can accurately reflect the actual physiological state of patients.

[0137] Embodiments of this application also propose an electronic device, including a processor and a memory; the memory is used to store a computer program executable by the processor; the processor is used to execute the computer program in the memory to implement the coronary heart disease risk assessment method of any of the above embodiments.

[0138] Embodiments of this application also propose a computer-readable storage medium that, when an executable computer program in the storage medium is executed by a processor, enables the implementation of the coronary heart disease risk assessment method of any of the above embodiments.

[0139] Embodiments of this application also propose a computer program product, including a computer program that, when executed by a processor, implements the coronary heart disease risk assessment method of any of the above embodiments.

[0140] Regarding the apparatus in the above embodiments, the specific manner in which the processor performs the operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0141] Embodiments of this application also provide an electronic device 600, such as... Figure 9As shown, the electronic device 600 includes a memory 601 and a processor 602. The memory 601 is used to store computer programs executable by the processor 602; the processor 602 is used to execute the computer programs in the memory 601 to implement the coronary heart disease risk assessment method provided in any of the above embodiments.

[0142] The electronic device 600 also includes a communication interface 603. The processor 602, memory 601, and communication interface 603 are connected via a communication bus and communicate with each other.

[0143] Processor 602 may be a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits used to control the execution of programs in the above scheme.

[0144] Communication interface 603 is used to communicate with other devices or communication networks, such as Ethernet, Radio Access Network (RAN), Wireless Local Area Networks (WLAN), etc.

[0145] The memory 601 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory may exist independently and be connected to the processor via a bus. The memory may also be integrated with the processor.

[0146] In this application, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance. The term "multiple" refers to two or more unless otherwise expressly defined.

[0147] The above description of the embodiments is intended to enable those skilled in the art to understand and apply this application. It will be apparent to those skilled in the art that various modifications can be easily made to these embodiments, and the general principles described herein can be applied to other embodiments without creative effort. Therefore, this application is not limited to the embodiments described herein, and any improvements and modifications made by those skilled in the art based on the disclosure of this application without departing from the scope and spirit of this application are within the scope of this application.

Claims

1. A method for assessing the risk of coronary heart disease, characterized in that, The methods for assessing the risk of coronary heart disease include: Obtain coronary CTA images of the subjects; Based on the coronary CTA images, a 3D model of the coronary arteries and myocardium was constructed; Based on the aforementioned 3D models of coronary arteries and myocardium, a small-sized subepicardial coronary artery model and a microvascular model within the myocardium are generated. Based on the aforementioned 3D model of coronary arteries and myocardium, the aforementioned small-sized coronary artery model under the epicardium, the aforementioned microvascular model within the myocardium, coronary microcirculation, cardiopulmonary circulation, and systemic circulation, a complete coronary circulation model is constructed. Based on the whole coronary circulation model, the fractional flow reserve and microcirculation resistance index of each coronary artery are calculated, and an evaluation report is generated.

2. The method for assessing the risk of coronary heart disease according to claim 1, characterized in that, The generation of a small-sized subepicardial coronary artery model and a small intramyocardial microvessel model based on the aforementioned 3D coronary artery and myocardial model includes: Based on the aforementioned 3D models of coronary arteries and myocardium, and the vascular constraint construction optimization algorithm, small-sized subepicardial coronary arteries and intramyocardial microvessels are generated, resulting in models of small-sized subepicardial coronary arteries and intramyocardial microvessels. The vascular networks of both models are binary tree structures composed of cylindrical pipes. For each vascular bifurcation, the flow rates of the parent and child vessels satisfy the mass flow rate conservation relationship, the pressures of the parent and child vessels satisfy the energy conservation relationship, and the radii of the parent and child vessels satisfy Murray's law of anatomy.

3. The method for assessing the risk of coronary heart disease according to claim 2, characterized in that, The process involves generating small-sized subepicardial coronary arteries and intramyocardial microvessels based on the 3D model of the coronary arteries and myocardium, and using a vascular constraint construction optimization algorithm. This results in a model of small-sized subepicardial coronary arteries and intramyocardial microvessels, including: Using the terminal portion of each coronary artery in the 3D model of the coronary artery and myocardium as the starting point for angiogenesis, the angiogenesis growth region is confined to the epicardial surface of the 3D model of the myocardium in the 3D model of the coronary artery and myocardium. Coronary arteries extend and grow within the epicardial surface to generate small-sized subepicardial coronary arteries, thus obtaining an initial small-sized subepicardial coronary artery model. The blood vessel growth region is switched from the epicardial surface to the left ventricular myocardial wall of the 3D myocardial model. At the terminal of the small coronary artery under the epicardium, the blood vessel growth pattern is changed from growth along the epicardium to growth into the myocardium to generate intramyocardial microvessels, thus obtaining an initial intramyocardial microvessel model. Based on the vascular constraint construction optimization algorithm, for the initial epicardial small-sized coronary artery model and the initial intramyocardial microvascular model, the node coordinates and vascular direction of each segment of the blood vessel are iteratively adjusted. When the iteration converges, the epicardial small-sized coronary artery model and the intramyocardial microvascular model are output.

4. The method for assessing the risk of coronary heart disease according to claim 1, characterized in that, The construction of a complete coronary circulation model based on the 3D model of the coronary arteries and myocardium, the subepicardial small-sized coronary artery model, the intramyocardial microvascular model, coronary microcirculation, cardiopulmonary circulation, and systemic circulation includes: The 3D model of the coronary artery in the 3D model of the coronary artery and myocardium is divided into a mesh to generate a 3D epicardial coronary artery computational mesh model; or, the vessel length and diameter along the course of each branch of the coronary artery are extracted from the 3D model of the coronary artery to construct a 1D epicardial coronary artery hemodynamic model. Based on the aforementioned small-sized subepidermal coronary artery model and the aforementioned intramyocardial microvascular model, 0-dimensional or 1-dimensional reduced-order models of small-sized subepidermal coronary arteries and intramyocardial vessels are constructed using vessel length, diameter along the vessel, and topology. Based on the hemodynamic electrical simulation method, a 0-dimensional systemic circulation hemodynamic model was constructed for the coronary microcirculation, cardiopulmonary circulation and systemic circulation; A complete coronary circulation model is constructed by bidirectionally coupling the 3D epicardial coronary artery computational mesh model, the 0D or 1D reduced-order model of small-sized epicardial coronary arteries and intramyocardial vessels, and the 0D systemic circulation hemodynamic model; or, a complete coronary circulation model is constructed by bidirectionally coupling the 1D epicardial coronary artery hemodynamic model, the 0D or 1D reduced-order model of small-sized epicardial coronary arteries and intramyocardial vessels, and the 0D systemic circulation hemodynamic model.

5. The method for assessing the risk of coronary heart disease according to claim 4, characterized in that, The method involves bidirectionally coupling the 3D epicardial coronary artery computational mesh model, the 0D or 1D reduced-order model of small-sized subepicardial coronary arteries and intramyocardial vessels, and the 0D systemic hemodynamic model to construct a whole coronary circulation model; or, bidirectionally coupling the 1D epicardial coronary artery hemodynamic model, the 0D or 1D reduced-order model of small-sized subepicardial coronary arteries and intramyocardial vessels, and the 0D systemic hemodynamic model to construct a whole coronary circulation model, including: Acquire myocardial CTP images, upper arm arterial blood pressure, and heart rate of the subject; An initial whole coronary circulation model is constructed by bidirectionally coupling the 3D epicardial coronary artery computational mesh model, the 0D or 1D reduced-order model of small-sized epicardial coronary arteries and intramyocardial vessels, and the 0D systemic circulation hemodynamic model; or, an initial whole coronary circulation model is constructed by bidirectionally coupling the 1D epicardial coronary artery hemodynamic model, the 0D or 1D reduced-order model of small-sized epicardial coronary arteries and intramyocardial vessels, and the 0D systemic circulation hemodynamic model. Based on the subject's myocardial CTP image, upper arm arterial blood pressure, heart rate, and the initial whole coronary circulation model, myocardial blood flow and arterial blood pressure are calculated iteratively, and the parameters of the initial whole coronary circulation model are adjusted to obtain the whole coronary circulation model.

6. The method for assessing the risk of coronary heart disease according to claim 1, characterized in that, The construction of a 3D model of the coronary arteries and myocardium based on the coronary CTA images includes: The coronary CTA image is segmented into arterial lumen, myocardium, bone, and soft tissue regions based on image grayscale values; For the arterial lumen and myocardium, region growing and surface lofting algorithms are used to construct an initial 3D model of the coronary artery and myocardium. The construction scope of the initial 3D model of the coronary artery and myocardium includes: the aortic root, left main coronary artery, left anterior descending branch, circumflex branch, right coronary artery and left ventricular myocardium. The initial 3D models of the coronary arteries and myocardium were smoothed to obtain 3D models of the coronary arteries and myocardium.

7. A device for assessing the risk of coronary heart disease, characterized in that, The coronary artery disease risk assessment device includes: an acquisition module, a first construction module, an angiogenesis module, a second construction module, and an assessment report generation module. The acquisition module is used to acquire coronary artery CTA images of the subject; The first construction module is used to construct a 3D model of the coronary arteries and myocardium based on the coronary CTA images; The angiogenesis module is used to generate a small-sized subepicardial coronary artery model and a microvascular model within the myocardium based on the 3D model of the coronary artery and myocardium. The second construction module is used to construct a whole coronary circulation model based on the 3D model of the coronary artery and myocardium, the small-sized coronary artery model under the epicardium, the microvascular model within the myocardium, the coronary microcirculation, the cardiopulmonary circulation, and the systemic circulation; The assessment report generation module is used to calculate the fractional flow reserve and microcirculation resistance index of each coronary artery based on the whole coronary circulation model, and generate an assessment report.

8. An electronic device, characterized in that, The device includes a memory and a processor, wherein the memory stores a computer program executable by the processor; and the processor executes the computer program in the memory to implement the coronary heart disease risk assessment method as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by a processor to implement the coronary heart disease risk assessment method as described in any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the coronary heart disease risk assessment method as described in any one of claims 1-6.

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