Individualized cerebral blood flow simulation method fusing cerebrovascular morphology and function

Abstract

The invention discloses an individualized cerebral blood flow simulation method fusing cerebrovascular morphology and function, which comprises the following steps: acquiring multi-modal medical image data of a target patient for three-dimensional reconstruction to obtain a cerebrovascular three-dimensional geometric model; accurately mapping a standard cerebrovascular domain map to the individualized brain tissue model, and accurately partitioning a cerebrovascular blood supply area by a weighting mechanism; setting boundary conditions according with physiological characterization according to geometrical morphological characteristics of cerebral vessels and functional information of brain tissues; and based on the cerebrovascular three-dimensional geometric model and the cerebral blood supply function area, performing numerical simulation on the flowing condition of blood flow in the cerebrovascular by utilizing a computational fluid mechanics method to obtain a blood flow analysis result. According to the method, the individualized cerebrovascular morphological boundary and the brain tissue functional area can be reconstructed, the cerebral blood flow numerical impedance parameters can be accurately distributed on the basis of the standard cerebrovascular domain map, and finally more accurate and individualized cerebral blood flow simulation according with individual physiological characteristics is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of cerebral blood flow simulation, and in particular to an individualized cerebral blood flow simulation method, system, terminal and computer-readable storage medium integrating cerebral vascular morphology and functionality. Background Art

[0002] Cerebral hemodynamics refers to the flow of blood in the cerebral vascular system, which is crucial to maintaining the normal function of brain tissue. The specificity and self-regulation of cerebral blood flow make accurate simulation of the flow process of cerebral blood flow a very challenging research topic.

[0003] Current cerebral blood flow simulation methods are based only on the geometric morphology of cerebral vessels, while ignoring functional information that is highly relevant to cerebral hemodynamics, such as brain tissue characteristics and vascular blood supply areas. This neglect leads to deviations between simulation results and actual cerebral blood flow states, especially when individual differences are significant.

[0004] The functionality of cerebral blood flow is determined by multiple factors, including the geometry of blood vessels, the functional requirements of the blood supply area, and the individual's physiological state. Traditional cerebral blood flow simulation methods mainly rely on morphological characteristics and fail to fully utilize the functional information contained in medical images. The limitations of this method are reflected in the difficulty in accurately predicting the blood flow distribution and cerebral blood flow regulation mechanism in different functional areas, especially when simulating cerebral blood flow changes under pathological conditions.

[0005] Existing cerebral blood flow simulation methods mainly rely on the three-dimensional cerebral vascular geometry reconstructed from medical images. The three-dimensional geometry of cerebral blood vessels is obtained through CTA or MRA. Then, the area surrounded by the vascular geometry is used as the calculation domain, and the inlet and outlet boundary conditions are applied. The computational fluid dynamics (CFD) method is used to numerically simulate cerebral blood flow. In the boundary condition method, the resistance and other parameters are currently allocated by the three-element lumped parameter method of the Windkessel model through the diameter or area of ​​each cerebral vascular outlet. This method simplifies the hemodynamics into several impedance units and determines the simulation parameters through morphological characteristics (such as the area of ​​the vascular outlet). However, since only the geometric characteristics of each outlet are considered, the functional information of the brain tissue is not considered, resulting in limitations in the simulation.

[0006] The existing technology has the following major limitations in cerebral blood flow simulation: insufficient consideration of individualized blood flow regulation mechanisms, difficulty in accurately reflecting the self-regulatory function of cerebral blood flow, inability to accurately capture the differentiated functional characteristics of the downstream vascular network of each cut-off outlet, lack of full utilization of brain tissue functional information, and the simulation results cannot accurately reflect the individualized blood flow regulation mechanism.

[0007] Therefore, the prior art still needs to be improved and developed. Summary of the invention

[0008] The main purpose of the present invention is to provide an individualized cerebral blood flow simulation method, system, terminal and computer-readable storage medium that integrates cerebral vascular morphology and functionality, aiming to solve the problem in the prior art that the individualized blood flow regulation mechanism is insufficiently considered in cerebral blood flow simulation and it is difficult to accurately reflect the self-regulation function of cerebral blood flow.

[0009] To achieve the above object, the present invention provides an individualized cerebral blood flow simulation method integrating cerebrovascular morphology and functionality, the individualized cerebral blood flow simulation method integrating cerebrovascular morphology and functionality comprising the following steps:

[0010] Acquire multimodal medical imaging data of a target patient, and perform three-dimensional reconstruction based on the multimodal medical imaging data to obtain a three-dimensional geometric model of cerebral blood vessels;

[0011] The standard cerebrovascular area atlas is accurately mapped to the individualized brain tissue model through geometric deformation, and a weighting mechanism of morphological features is introduced to accurately partition the cerebrovascular blood supply area.

[0012] According to the geometric morphological characteristics of cerebral vessels and the functional information of brain tissue, boundary conditions that conform to physiological characterization are set, and the blood flow impedance parameters are allocated at the first level according to the size of the individual cerebral vascular blood supply area. In the individual cerebral vascular blood supply area, the blood flow impedance parameters are allocated at the second level according to the morphological characteristics of the distal outlet of the cerebral vessels.

[0013] Based on the three-dimensional geometric model of cerebral blood vessels and the brain blood supply functional area, the flow of blood in the cerebral blood vessels is numerically simulated using computational fluid dynamics methods to obtain blood flow analysis results.

[0014] Optionally, the individualized cerebral blood flow simulation method integrating cerebrovascular morphology and function, wherein the step of acquiring multimodal medical imaging data of a target patient and performing three-dimensional reconstruction according to the multimodal medical imaging data to obtain a three-dimensional geometric model of cerebrovascular vessels, specifically includes:

[0015] Acquire multimodal medical imaging data of a target patient through MRA technology, wherein the multimodal medical imaging data includes imaging data of cerebral blood vessels and brain functional areas;

[0016] Medical image processing software is used to segment and classify the image data of cerebral blood vessels and brain functional areas, and the geometric morphological characteristics of cerebral blood vessels and the spatial distribution of brain tissue are extracted respectively. Three-dimensional reconstruction is performed based on the geometric morphological characteristics of cerebral blood vessels and the spatial distribution of brain tissue to obtain a three-dimensional geometric model of cerebral blood vessels.

[0017] Optionally, the individualized cerebral blood flow simulation method integrating cerebrovascular morphology and functionality, wherein the standard cerebrovascular field atlas is accurately mapped to the individualized brain tissue model through geometric deformation, and a weighting mechanism of morphological features is introduced to accurately partition the cerebrovascular blood supply area, specifically including:

[0018] Selecting a standard cerebral vascular area atlas suitable for cerebral hemodynamic simulation, wherein the standard cerebral vascular area atlas is used to provide standardized brain regional blood supply distribution information;

[0019] A non-rigid registration algorithm is used to obtain a deformation field T(x) so that the standard cerebrovascular field atlas S is aligned with the individualized 3D model I, and the deformed point x′ is defined as:

[0020] x′=T(x)=x+d(x);

[0021] Where x represents a point in the standard cerebrovascular domain atlas, and d(x) is the corresponding displacement vector, which represents the deformation of point x from the standard cerebrovascular domain atlas to the individualized brain tissue model;

[0022] The displacement of the B-spline deformation field is calculated through the control points and the spline function, which is defined as follows:

[0023]

[0024] Among them, P i represents the displacement of the control point, B i (x) represents the B-spline basis function of the i-th control point, and m is the number of control points;

[0025] In the registration process, a weighted mechanism of morphological features is introduced into the non-rigid registration algorithm to accurately partition the cerebral vascular blood supply area. The morphological weighted number E(d) that measures the quality and rationality of the deformation field d is:

[0026] E(d)=E data (d)+λE smooth (d);

[0027] Among them, E data (d) represents the data matching item, which is used to measure the matching degree between the deformed standard cerebrovascular domain atlas and the individualized brain tissue model. smooth (d) represents the smoothness term, which is used to limit the drastic change of deformation. The weight coefficient λ is used to balance the importance of the matching term and the smoothness term.

[0028] Optionally, the individualized cerebral blood flow simulation method integrating cerebrovascular morphology and functionality, wherein the boundary conditions that conform to physiological characterization are set according to the geometric morphological characteristics of the cerebrovascular vessels and the functional information of the brain tissue, the blood flow impedance parameters are firstly allocated according to the size of the individualized cerebrovascular blood supply area, and the second-level allocation is performed in the separate cerebrovascular blood supply area according to the morphological characteristics of the distal outlet of the cerebrovascular vessel, specifically including:

[0029] Calculate the total resistance R total And the total capacitance C total :

[0030]

[0031]

[0032] Among them, R total The total resistance of the cerebrovascular system is represented by the proximal resistance R p and distal resistance R d Add them together to get R total =R p +R d , P m It represents mean arterial pressure, which is calculated by the weighted average of systolic pressure SBP and diastolic pressure DBP. Pm = (SBP + 2 × DBP) / 3, Q total V represents total cerebral blood flow; b represents the total volume of blood in the systemic arterial system, and P represents cerebral blood pressure;

[0033] Calculate the blood flow of each blood supply area and divide the cerebral blood vessels into 7 areas D i (i=1,...,7), including the left anterior cerebral artery, the right anterior cerebral artery, the left middle cerebral artery, the right middle cerebral artery, the left posterior cerebral artery, the right posterior cerebral artery and other arterial regions. Based on the normal population samples in the statistical data and the individualized cerebrovascular tree, the D i Blood flow Q i , the formula is as follows:

[0034] Q i =α i Q total ,i=1,...,7,

[0035] Among them, α i Indicates each published blood supply area D i Percentage of total cerebral blood flow;

[0036] Calculate the resistance and capacitance of each blood supply area. For each blood supply area D i , according to the parallel characteristics of resistance, calculate the sub-resistance R iand sub-capacitor C i :

[0037]

[0038]

[0039] Calculate the resistance and capacitance of each outlet, in each blood vessel outlet area D i According to the outlet area A of each cerebral blood vessel contained in each outlet area j Calculate the resistance R of the corresponding outlet j and capacitor C j , the formula is as follows:

[0040]

[0041]

[0042] Where n represents the area D i The number of exits within A j represents the cross-sectional area of ​​the jth outlet.

[0043] Optionally, the individualized cerebral blood flow simulation method integrating cerebral vascular morphology and function, wherein the blood flow in the cerebral blood vessels is numerically simulated by using a computational fluid dynamics method based on the cerebral vascular three-dimensional geometric model and the brain blood supply functional area to obtain a blood flow analysis result, specifically includes:

[0044] Solving the Navier-Stokes equation, which is used to describe the flow behavior of fluid in blood vessels, discretizing the Navier-Stokes equation by finite element method or finite volume method, dividing the continuous blood flow domain into discrete grid units, performing numerical calculations on each grid unit, and obtaining the velocity distribution and pressure distribution of blood in coronary arteries and cerebral blood vessels, as well as the flow of blood in different branch vessels;

[0045] During the simulation process, the boundary conditions are defined in combination with the patient's personalized physiological parameters, and the blood flow velocity and pressure distribution are dynamically simulated to output the blood flow analysis results.

[0046] Optionally, in the individualized cerebral blood flow simulation method integrating cerebral vascular morphology and functionality, a three-dimensional unsteady incompressible Navier-Stokes equation is used as a control equation to describe the coronary blood flow:

[0047]

[0048] Where u represents the blood flow velocity, represents the Cauchy stress tensor, p represents pressure, μ represents the blood viscosity coefficient, I represents the 3×3 unit matrix, t represents time, represents the gradient operator, Ω represents the computational domain consisting of the 3D geometry of the blood vessel and the inlet and outlet boundaries;

[0049] When constructing the computational domain, the blood vessel is truncated and artificial boundary conditions are given on the truncation surface. Under the assumption of a rigid blood vessel wall, the boundary condition of ΓW at the blood vessel wall is:

[0050] u=0 on Γ W ;

[0051] The entrance of cerebral blood flow is located in the carotid artery. Clinical carotid ultrasound provides the blood flow velocity g during the complete cardiac cycle and applies it to the entrance boundary ΓI:

[0052] u=g on Γ I ;

[0053] The two-level boundary conditions are applied to the cerebrovascular outlet boundary ΓO. At time t, the time-varying blood pressure p at the kth cerebrovascular outlet is k (t):

[0054]

[0055] Among them, R k Represents resistance, Q k represents the volume flow rate through the kth outlet, C k Capacitance used to characterize arterial deformation, p k (0) and They represent the blood pressure at the outlet of the kth artery and the downstream distal pressure at the initial moment, represents the distal pressure downstream of the kth arterial outlet at time t, s represents the integral variable from time 0 to time t, which is used to reflect the cumulative effect in the dynamic process, τ k =R k C k .

[0056] Optionally, the individualized cerebral blood flow simulation method integrating cerebral vascular morphology and function, wherein, based on the cerebral vascular three-dimensional geometric model and the brain blood supply functional area, the blood flow in the cerebral blood vessels is numerically simulated using a computational fluid dynamics method to obtain a blood flow analysis result, and then further includes:

[0057] The blood flow analysis results were compared and validated with clinical data measured by transcranial Doppler ultrasound to evaluate the simulation accuracy.

[0058] In addition, to achieve the above-mentioned purpose, the present invention also provides an individualized cerebral blood flow simulation system integrating cerebrovascular morphology and functionality, wherein the individualized cerebral blood flow simulation system integrating cerebrovascular morphology and functionality comprises:

[0059] A three-dimensional reconstruction module is used to obtain multimodal medical imaging data of a target patient, and to perform three-dimensional reconstruction based on the multimodal medical imaging data to obtain a three-dimensional geometric model of cerebral blood vessels;

[0060] The atlas mapping module is used to accurately map the standard cerebrovascular domain atlas onto the individualized brain tissue model through geometric deformation, and introduces a weighting mechanism of morphological features to accurately partition the cerebrovascular blood supply area;

[0061] The boundary condition setting module is used to set boundary conditions that conform to physiological characteristics according to the geometric morphological characteristics of cerebral blood vessels and the functional information of brain tissue, and to perform primary allocation of blood flow impedance parameters according to the size of individualized cerebral blood vessel supply areas, and to perform secondary allocation in individual cerebral blood vessel supply areas according to the morphological characteristics of the distal outlet of the cerebral blood vessels;

[0062] The cerebral blood flow numerical simulation module is used to numerically simulate the flow of blood in the cerebral blood vessels based on the three-dimensional geometric model of the cerebral blood vessels and the brain blood supply functional area using the computational fluid dynamics method to obtain the blood flow analysis results.

[0063] In addition, to achieve the above-mentioned purpose, the present invention also provides a terminal, wherein the terminal includes: a memory, a processor, and an individualized cerebral blood flow simulation program that integrates cerebrovascular morphology and functionality, which is stored in the memory and can be run on the processor. When the individualized cerebral blood flow simulation program that integrates cerebrovascular morphology and functionality is executed by the processor, the steps of the individualized cerebral blood flow simulation method that integrates cerebrovascular morphology and functionality are implemented as described above.

[0064] In addition, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores an individualized cerebral blood flow simulation program that integrates cerebral vascular morphology and functionality, and when the individualized cerebral blood flow simulation program that integrates cerebral vascular morphology and functionality is executed by a processor, the steps of the individualized cerebral blood flow simulation method that integrates cerebral vascular morphology and functionality as described above are implemented.

[0065] In the present invention, the multimodal medical imaging data of the target patient is obtained, and a three-dimensional reconstruction is performed according to the multimodal medical imaging data to obtain a three-dimensional geometric model of cerebral blood vessels; the standard cerebral vascular field atlas is accurately mapped to the individualized brain tissue model through geometric deformation, and the weighted mechanism of morphological characteristics is introduced to accurately partition the cerebral blood supply area; according to the geometric morphological characteristics of the cerebral blood vessels and the functional information of the brain tissue, the boundary conditions that meet the physiological characterization are set, and the blood flow impedance parameters are first-level allocated according to the size of the individualized cerebral blood supply area, and in the separate cerebral blood supply area, the blood flow impedance parameters are second-level allocated according to the morphological characteristics of the distal outlet of the cerebral blood vessels; based on the three-dimensional geometric model of the cerebral blood vessels and the brain blood supply functional area, the flow of blood in the cerebral blood vessels is numerically simulated using the computational fluid dynamics method to obtain the blood flow analysis results. The present invention can not only reconstruct the individualized cerebral vascular morphological boundaries and brain tissue functional areas, but also accurately allocate the numerical impedance parameters of cerebral blood flow based on the standard cerebral vascular field atlas, and finally achieve a more accurate and personalized cerebral blood flow simulation that meets individual physiological characteristics. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 It is a flow chart of a preferred embodiment of the individualized cerebral blood flow simulation method integrating cerebral vascular morphology and function of the present invention;

[0067] Figure 2 It is a schematic diagram of reconstructing a three-dimensional geometric model of cerebral blood vessels and brain tissue based on nuclear magnetic resonance imaging in a preferred embodiment of the individualized cerebral blood flow simulation method integrating cerebral vascular morphology and function of the present invention;

[0068] Figure 3 It is a schematic diagram of dividing the blood supply area of ​​individualized brain tissue and pre-allocating the cerebral blood flow by using a standard cerebral vascular field atlas in a preferred embodiment of the individualized cerebral blood flow simulation method integrating cerebral vascular morphology and function of the present invention;

[0069] Figure 4 It is a structural diagram of a preferred embodiment of the individualized cerebral blood flow simulation system integrating cerebrovascular morphology and function of the present invention;

[0070] Figure 5 It is a structural diagram of a preferred embodiment of the terminal of the present invention. DETAILED DESCRIPTION

[0071] In order to make the purpose, technical solution and advantages of the present invention clearer and more specific, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0072] In order to improve the accuracy of the simulation, the present invention combines medical imaging and computational fluid dynamics technology to develop a cerebral blood flow simulation method that can integrate individualized cerebral vascular geometry and brain functional area information. This technology can not only reconstruct individualized cerebral vascular morphological boundaries and brain tissue functional areas, but also accurately allocate cerebral blood flow numerical impedance parameters based on standard cerebral vascular field maps, and finally achieve cerebral blood flow simulation that meets individual physiological characteristics. That is, through medical imaging data and computational fluid dynamics technology, accurate simulation of individual cerebral blood flow is achieved. This method not only takes into account the geometric morphological characteristics of cerebral vessels, but also incorporates the functional information of brain tissue into the simulation process to improve the accuracy and clinical relevance of the simulation results.

[0073] The individualized cerebral blood flow simulation method integrating cerebrovascular morphology and function described in the preferred embodiment of the present invention is as follows: Figure 1 As shown, the individualized cerebral blood flow simulation method integrating cerebral vascular morphology and function includes the following steps:

[0074] Step S10: Acquire multimodal medical image data of a target patient, and perform three-dimensional reconstruction based on the multimodal medical image data to obtain a three-dimensional geometric model of cerebral blood vessels.

[0075] Specifically, the multimodal medical imaging data of the target patient is obtained by MRA technology (Magnetic resonance angiography), and the multimodal medical imaging data includes cerebral blood vessels and brain functional area imaging data. MRA can not only clearly display the geometric morphological information of cerebral blood vessels provided by cerebral arteries, but also obtain information such as brain tissue volume, and provide basic data for the integration of brain functional areas and hemodynamics; the cerebral blood vessels and brain functional area imaging data are segmented and classified by medical image processing software, and the geometric morphological characteristics of cerebral blood vessels and the spatial distribution of brain tissue are extracted respectively, which is helpful to achieve more accurate hemodynamic analysis in subsequent cerebral blood flow simulation, and three-dimensional reconstruction is performed according to the geometric morphological characteristics of cerebral blood vessels and the spatial distribution of brain tissue to obtain a three-dimensional geometric model of cerebral blood vessels, such as Figure 2 As shown, Figure 2 The above shows the reconstruction of the 3D geometric model of cerebral blood vessels based on MRI images. Figure 2 The brain tissue is represented below. During the reconstruction process, the three-dimensional geometric reconstruction of cerebral blood vessels and brain tissue is separate. It can be considered that the areas of cerebral blood vessels and brain tissue are found separately from the image, and three-dimensional geometric reconstruction is performed separately.

[0076] The present invention utilizes multimodal medical imaging data such as CTA and magnetic resonance angiography (MRA) to perform three-dimensional reconstruction of individualized cerebral blood vessels and brain tissue. The purpose of image-based three-dimensional reconstruction is to obtain a three-dimensional model of cerebral blood vessels and brain tissue, wherein the three-dimensional model of cerebral blood vessels is the calculation area for cerebral blood flow simulation, and the three-dimensional model of brain tissue is to further divide the brain tissue into functional areas and provide quantitative parameters of the boundary conditions of cerebral blood flow simulation (the volume of different brain tissue functional areas); different brain tissue functional areas are marked, and the brain tissue reconstruction model is optimized based on individual physiological characteristics (such as age, gender, and genetic factors) to make it more consistent with the individual's physiological representation.

[0077] Step S20: accurately map the standard cerebrovascular area atlas onto the individualized brain tissue model through geometric deformation, and introduce a weighting mechanism of morphological features to accurately partition the cerebrovascular blood supply area.

[0078] Specifically, in order to achieve accurate zoning of cerebral vascular blood supply areas, the present invention proposes a mapping method based on a non-rigid registration algorithm. This method accurately maps the standard cerebral vascular field atlas to an individualized brain tissue model through geometric deformation, and introduces a weighting mechanism of morphological features in this process to ensure a high degree of consistency between the atlas and individual anatomical and functional characteristics (i.e., to ensure that the standard atlas can adapt to the anatomical differences of different individuals), thereby achieving accurate zoning of cerebral vascular blood supply areas.

[0079] First, a standard cerebral vascular area atlas suitable for cerebral hemodynamic simulation is selected. The standard cerebral vascular area atlas is used to provide standardized brain regional blood supply distribution information, covering the blood supply areas of major cerebral blood vessels, including the main distribution ranges of the anterior cerebral artery, middle artery and posterior cerebral artery.

[0080] Secondly, in order to accurately match the standard cerebrovascular domain atlas with the patient's individualized three-dimensional cerebrovascular model (i.e., the cerebrovascular three-dimensional geometric model), the present invention uses a non-rigid registration algorithm, such as a registration method based on B-spline or Thin Plate Spline (TPS). The goal of non-rigid registration is to obtain a deformation field T(x) so that the standard cerebrovascular domain atlas S is aligned with the individualized three-dimensional model I, and the deformed point x′ is defined as:

[0081] x′=T(x)=x+d(x);

[0082] Where x represents a point in the standard cerebrovascular field atlas, and d(x) is the corresponding displacement vector, which represents the deformation of point x from the standard cerebrovascular field atlas to the individualized brain tissue model. The displacement of the B-spline deformation field is calculated by the control points and the spline function, which is defined as follows:

[0083]

[0084] Among them, P i represents the displacement of the control point, B i (x) represents the B-spline basis function of the i-th control point, and m is the number of control points.

[0085] This registration technology can effectively handle the morphological differences between the individual and the standard atlas. Through deformation adjustment, the standard atlas and the anatomical structure of the individual brain tissue are kept highly consistent, ensuring the accurate mapping of each blood supply area in the individual model. In the registration process, the algorithm introduces a weighting mechanism for morphological features, giving higher weights to key parts (such as vascular bifurcation points, main blood supply arteries, etc.). This weighting mechanism gives priority to the geometric features of these key parts, ensuring that the correct pairing of cerebrovascular branch structures can be maintained even if deformation occurs during the mapping process. In the registration process, a weighting mechanism for morphological features is introduced in the non-rigid registration algorithm to accurately partition the cerebrovascular blood supply area. The morphological weighted number E(d) that measures the quality and rationality of the deformation field d is:

[0086] E(d)=E data (d)+λE smooth (d);

[0087] Among them, E data (d) represents the data matching item, which is used to measure the matching degree between the deformed standard cerebrovascular domain atlas and the individualized brain tissue model. smooth (d) represents the smoothing term, which is used to limit the drastic changes in deformation, and the weight coefficient λ is used to balance the importance of the matching term and the smoothing term. The weighting mechanism assigns higher weights to important parts (such as vascular bifurcation points) to ensure that the geometric features of these parts remain consistent during the mapping process, so that they conform to the shape and functional differences of individual cerebral blood vessels, thereby achieving accurate division of the blood supply area.

[0088] like Figure 3 As shown, Figure 3 Standard cerebrovascular atlas ( Figure 3 The left side of the image can be used to divide the blood supply area of ​​individual brain tissue ( Figure 3 and pre-distribute cerebral blood flow ( Figure 3 on the right side of the screen).

[0089] Through the above-mentioned mapping algorithm, the present invention can flexibly adapt the standardized cerebrovascular field atlas to the individualized anatomical structure, realize the accurate division of blood supply areas of brain functional areas, and provide a solid foundation for further cerebral hemodynamic analysis.

[0090] Step S30: according to the geometrical morphological characteristics of cerebral blood vessels and the functional information of brain tissue, boundary conditions that conform to physiological characterization are set, and the blood flow impedance parameters are allocated at the primary level according to the size of the individualized cerebral blood supply area. In the individual cerebral blood supply area, the blood flow impedance parameters are allocated at the secondary level according to the morphological characteristics of the distal outlet of the cerebral blood vessels.

[0091] Specifically, in numerical simulation of cerebral blood flow, accurately setting boundary conditions is the key. To this end, the present invention proposes a boundary condition setting method based on a two-level vascular resistance and compliance allocation algorithm, which not only takes into account the geometric characteristics of cerebral blood vessels, but also combines the functional information of brain tissue to achieve a cerebral blood flow simulation that is more in line with physiological characteristics. First, the blood flow impedance parameters are allocated at the first level according to the size of the individualized cerebral vascular blood supply area, and then in the individual cerebral vascular blood supply area, the second level is allocated according to the morphological characteristics of the distal outlet of the cerebral blood vessels.

[0092] The setting of boundary conditions directly affects the accuracy of numerical simulation of cerebral blood flow. To this end, the present invention designs a multi-level vascular resistance and compliance distribution algorithm, and combines functional information to set boundary conditions that are more in line with physiological characterization. The specific steps are as follows:

[0093] (1) Calculate the total resistance R total And the total capacitance C total :

[0094]

[0095]

[0096] Among them, R total The total resistance of the cerebrovascular system is represented by the proximal resistance R p and distal resistance R d Add them together to get R total =R p +R d , P m It represents mean arterial pressure, which is calculated by the weighted average of systolic pressure SBP and diastolic pressure DBP. Pm = (SBP + 2 × DBP) / 3, Q total V represents total cerebral blood flow; b represents the total blood volume in the systemic arterial system, and P represents cerebral blood pressure.

[0097] (2) Calculate the blood flow of each blood supply area:

[0098] The cerebral blood vessels are divided into 7 regions. i(i=1,...,7), including the left anterior cerebral artery (Left ACA), the right anterior cerebral artery (Right ACA), the left middle cerebral artery (Left MCA), the right middle cerebral artery (Right MCA), the left posterior cerebral artery (Left PCA), the right posterior cerebral artery (Right PCA) and other arterial regions. Based on the normal population samples in the statistical data and the individualized cerebrovascular tree, the D i Blood flow Q i , the formula is as follows:

[0099] Q i =α i Q total ,i=1,...,7,

[0100] Among them, α i Indicates each published blood supply area D i The percentage of total cerebral blood flow.

[0101] (3) Calculate the resistance and capacitance of each blood supply area (first-level distribution):

[0102] For each blood supply area D i , according to the parallel characteristics of resistance, calculate the sub-resistance R i and sub-capacitor C i :

[0103]

[0104] (4) Calculate the resistance and capacitance of each outlet (secondary distribution):

[0105] In each blood vessel outlet area D i (i.e. blood supply area), according to the outlet area A of each cerebral blood vessel contained in each outlet area j Calculate the resistance R of the corresponding outlet j and capacitor C j , the formula is as follows:

[0106]

[0107] Where n represents the area D i The number of exits within A j represents the cross-sectional area of ​​the jth outlet.

[0108] Step S40: Based on the three-dimensional geometric model of the cerebral blood vessels and the brain blood supply functional area, a computational fluid dynamics method is used to perform numerical simulation on the flow of blood in the cerebral blood vessels to obtain a blood flow analysis result.

[0109] Specifically, based on the three-dimensional model of cerebral blood vessels and the brain blood supply functional area obtained in the above steps, the computational fluid dynamics (CFD) method is used to perform numerical simulation of the blood flow in the cerebral blood vessels. The core of cerebral hemodynamic simulation is to solve the Navier-Stokes equations, which are used to describe the flow behavior of fluids in blood vessels (used to describe the conservation of momentum and mass of fluids, and are usually solved by numerical methods). In hemodynamics, solving the Navier-Stokes equations requires discretization. Commonly used methods include the finite element method (FEM) or the finite volume method (FVM), which discretizes the Navier-Stokes equations, divides the continuous blood flow domain into discrete grid units, and performs numerical calculations on each grid unit to obtain the blood velocity distribution and pressure in the coronary arteries and cerebral blood vessels. force distribution, and the flow of blood in different branch vessels; during the simulation process, the boundary conditions are defined in combination with the patient's personalized physiological parameters, and the blood flow velocity and pressure distribution are dynamically simulated (that is, the solution of the Navier-Stokes equation includes the velocity field and pressure field in the blood vessel. This means that by solving the equation, the blood velocity distribution and pressure distribution in complex vascular geometric structures such as coronary arteries and cerebral blood vessels can be obtained, as well as the blood flow in different branch vessels. During the simulation process, the boundary conditions are defined in combination with the patient's personalized physiological parameters (such as blood pressure, heart rate, etc.), and the blood flow velocity, pressure distribution, etc. are dynamically simulated), and the blood flow analysis results are output.

[0110] In this process, the present invention uses the three-dimensional incompressible Navier-Stokes equation to describe the flow of blood, and the above two-level boundary conditions. The specific process is as follows:

[0111] The present invention adopts the three-dimensional unsteady incompressible Navier-Stokes equation as the control equation to describe the coronary blood flow:

[0112]

[0113] Where u represents the blood flow velocity, represents the Cauchy stress tensor, p represents pressure, μ represents the blood viscosity coefficient, I represents the 3×3 unit matrix, t represents time, represents the gradient operator, and Ω represents the computational domain consisting of the 3D geometry of the blood vessel and the inlet and outlet boundaries.

[0114] In terms of boundary conditions, due to the complexity of cerebral blood vessels, the entire coronary artery network cannot be simulated under existing imaging technology and computing conditions. It is necessary to truncate the blood vessels when constructing the computational domain and give artificial boundary conditions on the truncation surface. Under the assumption of a rigid blood vessel wall, the boundary condition of ГW at the blood vessel wall is:

[0115] u=0 on Γ W ;

[0116] The entrance of cerebral blood flow is located in the carotid artery. Clinical carotid ultrasound provides the blood flow velocity g during the complete cardiac cycle and applies it to the entrance boundary ГI:

[0117] u=g on Γ I ;

[0118] The two-level boundary conditions are applied to the cerebral vascular outlet boundary ГO. At time t, the time-varying blood pressure p at the kth cerebral vascular outlet is k (t):

[0119]

[0120] Among them, R k Represents resistance, Q k represents the volume flow rate through the kth outlet, C k Capacitance used to characterize arterial deformation, p k (0) and They represent the blood pressure at the outlet of the kth artery and the downstream distal pressure at the initial moment, represents the distal pressure downstream of the kth arterial outlet at time t, s represents the integral variable from time 0 to time t, which is used to reflect the cumulative effect in the dynamic process, that is, how the previous blood flow conditions affect the blood pressure at the current moment, τ k =R k C k .

[0121] The present invention can simulate individualized dynamic changes in cerebral blood flow, especially under the functional states of different brain regions. The simulation results of the present invention will be compared and verified with clinical data measured by transcranial Doppler ultrasound to evaluate its accuracy improvement compared with traditional methods based only on cerebrovascular morphology.

[0122] Finally, in the present invention, a parallel computing algorithm is used to improve the efficiency of the numerical calculation of cerebral blood flow. Specifically, the area to be calculated is divided into multiple small blocks, just like splitting a complex large task into many smaller tasks. Then, these tasks are assigned to multiple computers or multi-core processors for simultaneous processing. This method not only speeds up the calculation speed, but also ensures that accurate blood flow analysis results can be obtained in a shorter time. In order to further optimize the calculation process, advanced algorithms and technologies are also used, such as the Newton-Krylov-Schwarz algorithm and RAS preprocessing technology, to solve the numerical calculation problem of cerebral blood flow faster and more efficiently.

[0123] The key points of the present invention are as follows:

[0124] (1) Individualized cerebral hemodynamic simulation method: This method is based on the morphological and functional data of individualized cerebral vessels, combined with medical imaging, computational fluid dynamics (CFD) and cerebrovascular field maps to achieve individualized cerebral blood flow numerical simulation.

[0125] (2) Brain tissue division and cerebral vascular blood supply area division based on functional information: Reconstruct individualized brain tissue through medical imaging data, and combine it with the cerebrovascular field atlas to complete the accurate division of cerebral vascular blood supply areas, and allocate cerebral blood flow impedance parameters based on these functional areas.

[0126] (3) Cerebral blood flow boundary condition setting with multi-level parameter allocation mechanism: Through the primary and secondary parameter allocation mechanisms, individualized cerebral blood flow simulation outlet parameter setting is achieved according to the geometric characteristics of brain tissue and vascular outlets and blood flow requirements, thus ensuring the accuracy and individualized characteristics of numerical simulation.

[0127] The main advantage of the technical solution of the present invention is that it comprehensively considers the geometric morphology of cerebral blood vessels and the functional information of brain tissue, and realizes a more personalized and accurate cerebral blood flow simulation. Through the improved atlas mapping algorithm and boundary condition setting method, the present invention can better reflect the physiological characteristics of individuals, especially when simulating cerebral blood flow changes under complex pathological conditions. In addition, the method also has strong scalability and can be applied to cerebral blood flow simulation under different ages, genders and pathological conditions, providing an important reference for personalized diagnosis and treatment of brain diseases.

[0128] The feasibility of the present invention has been verified through preliminary experiments and numerical simulations. The experimental results show that the simulation method is superior to the traditional cerebral blood flow simulation method in terms of accuracy and individual characteristics. Under the premise of using individualized cerebral vascular geometry and functional area information, the cerebral blood flow simulation results generated by this method are compared with the traditional method. Experiments show that the new simulation method has higher accuracy in blood flow distribution, pressure impedance and division of blood supply areas. The individualized cerebral vascular blood supply area division registered with the standard cerebral vascular field atlas is more in line with the individual's physiological characteristics, and can better reflect the individualized blood flow regulation mechanism compared with the standard fluid dynamics model. The simulation results of this method are compared and analyzed with some clinical transcranial Doppler ultrasound data. The results show that the model is more consistent with actual clinical observations in predicting blood flow change trends and blood supply areas. Especially under pathological conditions such as arterial stenosis, this method can more accurately simulate blood flow changes, proving its applicability under complex pathological conditions.

[0129] Furthermore, if Figure 4As shown, based on the above-mentioned individualized cerebral blood flow simulation method integrating cerebrovascular morphology and functionality, the present invention also provides an individualized cerebral blood flow simulation system integrating cerebrovascular morphology and functionality, wherein the individualized cerebral blood flow simulation system integrating cerebrovascular morphology and functionality comprises:

[0130] A three-dimensional reconstruction module 51 is used to obtain multimodal medical image data of a target patient, and perform three-dimensional reconstruction based on the multimodal medical image data to obtain a three-dimensional geometric model of cerebral blood vessels;

[0131] The atlas mapping module 52 is used to accurately map the standard cerebrovascular field atlas to the individualized brain tissue model through geometric deformation, and introduce a weighting mechanism of morphological features to accurately partition the cerebrovascular blood supply area;

[0132] The boundary condition setting module 53 is used to set boundary conditions that conform to physiological characteristics according to the geometric morphological characteristics of cerebral blood vessels and the functional information of brain tissue, and to perform primary allocation of blood flow impedance parameters according to the size of the individualized cerebral blood vessel supply area, and to perform secondary allocation according to the morphological characteristics of the distal outlet of the cerebral blood vessels in the individual cerebral blood vessel supply area;

[0133] The cerebral blood flow numerical simulation module 54 is used to perform numerical simulation on the blood flow in the cerebral blood vessels based on the cerebral blood vessel three-dimensional geometric model and the brain blood supply functional area by using the computational fluid dynamics method to obtain the blood flow analysis result.

[0134] Furthermore, if Figure 5 As shown, based on the above-mentioned individualized cerebral blood flow simulation method and system integrating cerebrovascular morphology and functionality, the present invention also provides a terminal accordingly, and the terminal includes a processor 10, a memory 20 and a display 30. Figure 5 Only some components of the terminal are shown, but it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0135] In some embodiments, the memory 20 may be an internal storage unit of the terminal, such as a hard disk or memory of the terminal. In other embodiments, the memory 20 may also be an external storage device of the terminal, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the terminal. Further, the memory 20 may also include both an internal storage unit of the terminal and an external storage device. The memory 20 is used to store application software and various types of data installed on the terminal, such as the program code of the installation terminal. The memory 20 may also be used to temporarily store data that has been output or is to be output. In one embodiment, the memory 20 stores an individualized cerebral blood flow simulation program 40 that integrates cerebrovascular morphology and functionality, and the individualized cerebral blood flow simulation program 40 that integrates cerebrovascular morphology and functionality can be executed by the processor 10, thereby realizing the individualized cerebral blood flow simulation method that integrates cerebrovascular morphology and functionality in the present application.

[0136] In some embodiments, the processor 10 may be a central processing unit (CPU), a microprocessor or other data processing chip, used to run the program code or process data stored in the memory 20, such as executing the individualized cerebral blood flow simulation method that integrates cerebral vascular morphology and functionality.

[0137] In some embodiments, the display 30 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, etc. The display 30 is used to display information on the terminal and to display a visual user interface. The components 10-30 of the terminal communicate with each other via a system bus.

[0138] In one embodiment, when the processor 10 executes the individualized cerebral blood flow simulation program 40 integrating cerebral vascular morphology and functionality in the memory 20, the steps of the individualized cerebral blood flow simulation method integrating cerebral vascular morphology and functionality as described above are implemented.

[0139] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores an individualized cerebral blood flow simulation program that integrates cerebral vascular morphology and functionality, and when the individualized cerebral blood flow simulation program that integrates cerebral vascular morphology and functionality is executed by a processor, the steps of the individualized cerebral blood flow simulation method that integrates cerebral vascular morphology and functionality are implemented as described above.

[0140] In summary, the present invention provides an individualized cerebral blood flow simulation method, system, terminal and storage medium that integrate cerebrovascular morphology and functionality. The method includes: acquiring multimodal medical imaging data of a target patient, performing three-dimensional reconstruction based on the multimodal medical imaging data, and obtaining a three-dimensional geometric model of cerebrovascular vessels; accurately mapping a standard cerebrovascular field atlas onto an individualized brain tissue model through geometric deformation, and introducing a weighted mechanism of morphological features to accurately partition the cerebrovascular blood supply area; setting boundary conditions that conform to physiological characterization based on the geometric morphological features of the cerebrovascular vessels and the functional information of the brain tissue, performing a primary allocation of blood flow impedance parameters based on the size of the individualized cerebrovascular blood supply area, and performing a secondary allocation in a separate cerebrovascular blood supply area based on the morphological features of the distal outlet of the cerebrovascular vessels; based on the three-dimensional geometric model of the cerebrovascular vessels and the brain blood supply functional area, using a computational fluid dynamics method to numerically simulate the flow of blood in the cerebrovascular vessels to obtain a blood flow analysis result. The present invention can not only reconstruct individualized cerebrovascular morphological boundaries and brain tissue functional areas, but also accurately allocate numerical impedance parameters of cerebral blood flow based on standard cerebrovascular field maps, ultimately achieving more accurate and personalized cerebral blood flow simulation that conforms to individual physiological characteristics.

[0141] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or terminal including the element.

[0142] Of course, those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing related hardware (such as a processor, a controller, etc.) through a computer program, and the program can be stored in a computer-readable storage medium that can be read by a computer, and the program can include the processes of the above-mentioned method embodiments when executed. The computer-readable storage medium can be a memory, a disk, an optical disk, etc.

[0143] It should be understood that the application of the present invention is not limited to the above examples. For ordinary technicians in this field, improvements or changes can be made based on the above description. All these improvements and changes should fall within the scope of protection of the claims attached to the present invention.

Claims

1. A personalized cerebral blood flow simulation method integrating cerebrovascular morphology and function, characterized in that: The individualized cerebral blood flow simulation method integrating cerebrovascular morphology and function includes: Acquiring multimodal medical imaging data of a target patient, and performing three-dimensional reconstruction based on the multimodal medical imaging data to obtain a three-dimensional geometric model of cerebral blood vessels; The standard cerebrovascular area atlas is accurately mapped to the individualized brain tissue model through geometric deformation, and a weighting mechanism of morphological features is introduced to accurately partition the cerebrovascular blood supply area. According to the geometric morphological characteristics of cerebral vessels and the functional information of brain tissue, boundary conditions that conform to physiological characterization are set, and the blood flow impedance parameters are allocated at the first level according to the size of the individual cerebral vascular blood supply area. In the individual cerebral vascular blood supply area, the blood flow impedance parameters are allocated at the second level according to the morphological characteristics of the distal outlet of the cerebral vessels. Based on the three-dimensional geometric model of cerebral blood vessels and the brain blood supply functional area, the flow of blood in the cerebral blood vessels is numerically simulated using computational fluid dynamics methods to obtain blood flow analysis results.

2. The individualized cerebral blood flow simulation method integrating cerebrovascular morphology and function according to claim 1, characterized in that: The method of acquiring multimodal medical image data of a target patient and performing three-dimensional reconstruction according to the multimodal medical image data to obtain a three-dimensional geometric model of cerebral blood vessels specifically includes: Acquire multimodal medical imaging data of a target patient through MRA technology, wherein the multimodal medical imaging data includes imaging data of cerebral blood vessels and brain functional areas; Medical image processing software is used to segment and classify the image data of cerebral blood vessels and brain functional areas, and the geometric morphological characteristics of cerebral blood vessels and the spatial distribution of brain tissue are extracted respectively. Three-dimensional reconstruction is performed based on the geometric morphological characteristics of cerebral blood vessels and the spatial distribution of brain tissue to obtain a three-dimensional geometric model of cerebral blood vessels.

3. The individualized cerebral blood flow simulation method integrating cerebrovascular morphology and function according to claim 1, characterized in that: The method accurately maps the standard cerebrovascular domain atlas onto the individualized brain tissue model through geometric deformation, and introduces a weighting mechanism of morphological features to accurately partition the cerebrovascular blood supply area, specifically including: Selecting a standard cerebral vascular area atlas suitable for cerebral hemodynamic simulation, wherein the standard cerebral vascular area atlas is used to provide standardized brain regional blood supply distribution information; A non-rigid registration algorithm is used to obtain a deformation field T(x) so that the standard cerebrovascular field atlas S is aligned with the individualized 3D model I, and the deformed point x′ is defined as: x′=T(x)=x+d(x); Where x represents a point in the standard cerebrovascular domain atlas, and d(x) is the corresponding displacement vector, which represents the deformation of point x from the standard cerebrovascular domain atlas to the individualized brain tissue model; The displacement of the B-spline deformation field is calculated through the control points and the spline function, which is defined as follows: Among them, P i represents the displacement of the control point, B i (x) represents the B-spline basis function of the i-th control point, and m is the number of control points; In the registration process, a weighted mechanism of morphological features is introduced into the non-rigid registration algorithm to accurately partition the cerebral vascular blood supply area. The morphological weighted number E(d) that measures the quality and rationality of the deformation field d is: E(d)=E data (d)+λE smooth (d); Among them, E data (d) represents the data matching item, which is used to measure the matching degree between the deformed standard cerebrovascular domain atlas and the individualized brain tissue model. smooth (d) represents the smoothness term, which is used to limit the drastic change of deformation. The weight coefficient λ is used to balance the importance of the matching term and the smoothness term.

4. The individualized cerebral blood flow simulation method integrating cerebrovascular morphology and function according to claim 1, characterized in that: According to the geometric morphological characteristics of cerebral vessels and the functional information of brain tissue, boundary conditions that conform to physiological characteristics are set, and blood flow impedance parameters are first-level allocated according to the size of the individualized cerebral vascular blood supply area. In the individual cerebral vascular blood supply area, second-level allocation is performed according to the morphological characteristics of the distal outlet of the cerebral vessels, specifically including: Calculate the total resistance R total And the total capacitance C total : Among them, R total The total resistance of the cerebrovascular system is represented by the proximal resistance R p and distal resistance R d Add them together to get R total =R p +R d , P m It represents mean arterial pressure, which is calculated by the weighted average of systolic pressure SBP and diastolic pressure DBP. Pm = (SBP + 2 × DBP) / 3, Q total V represents total cerebral blood flow; b represents the total volume of blood in the systemic arterial system, and P represents cerebral blood pressure; Calculate the blood flow of each blood supply area and divide the cerebral blood vessels into 7 areas D i (i=1,...,7), including the left anterior cerebral artery, the right anterior cerebral artery, the left middle cerebral artery, the right middle cerebral artery, the left posterior cerebral artery, the right posterior cerebral artery and other arterial regions. Based on the normal population samples in the statistical data and the individualized cerebrovascular tree, the D i Blood flow Q i , the formula is as follows: Q i =α i Q total ,i=1,...,7, Among them, α i Indicates each published blood supply area D i Percentage of total cerebral blood flow; Calculate the resistance and capacitance of each blood supply area. For each blood supply area D i , according to the parallel characteristics of resistance, calculate the sub-resistance R i and sub-capacitor C i : Calculate the resistance and capacitance of each outlet, in each blood vessel outlet area D i According to the outlet area A of each cerebral blood vessel contained in each outlet area j Calculate the resistance R of the corresponding outlet j and capacitor C j , the formula is as follows: Where n represents the area D i The number of exits within A j represents the cross-sectional area of ​​the jth outlet.

5. The individualized cerebral blood flow simulation method integrating cerebrovascular morphology and function according to claim 1, characterized in that: Based on the three-dimensional geometric model of the cerebral blood vessels and the brain blood supply functional area, the computational fluid dynamics method is used to perform numerical simulation on the flow of blood in the cerebral blood vessels to obtain blood flow analysis results, which specifically include: Solving the Navier-Stokes equation, which is used to describe the flow behavior of fluid in blood vessels, discretizing the Navier-Stokes equation by finite element method or finite volume method, dividing the continuous blood flow domain into discrete grid units, performing numerical calculations on each grid unit, and obtaining the velocity distribution and pressure distribution of blood in coronary arteries and cerebral blood vessels, as well as the flow of blood in different branch vessels; During the simulation process, the boundary conditions are defined in combination with the patient's personalized physiological parameters, and the blood flow velocity and pressure distribution are dynamically simulated to output the blood flow analysis results.

6. The individualized cerebral blood flow simulation method integrating cerebrovascular morphology and function according to claim 5, characterized in that: The three-dimensional unsteady incompressible Navier-Stokes equation is used as the governing equation to describe the coronary blood flow: Where u represents the blood flow velocity, represents the Cauchy stress tensor, p represents pressure, μ represents the blood viscosity coefficient, I represents the 3×3 unit matrix, t represents time, represents the gradient operator, Ω represents the computational domain consisting of the 3D geometry of the blood vessel and the inlet and outlet boundaries; When constructing the computational domain, the blood vessel is truncated and artificial boundary conditions are given on the truncation surface. Under the assumption of a rigid blood vessel wall, the boundary condition of ГW at the blood vessel wall is: u=0onΓ W ; The entrance of cerebral blood flow is located in the carotid artery. Clinical carotid ultrasound provides the blood flow velocity g during the complete cardiac cycle and applies it to the entrance boundary ГI: u = gon ΓI; The two-level boundary conditions are applied to the cerebral vascular outlet boundary ГO. At time t, the time-varying blood pressure p at the kth cerebral vascular outlet is k (t): Among them, R k Represents resistance, Q k represents the volume flow rate through the kth outlet, C k Capacitance used to characterize arterial deformation, p k (0) and They represent the blood pressure at the kth artery outlet and the downstream distal pressure at the initial moment, represents the distal pressure downstream of the kth arterial outlet at time t, s represents the integral variable from time 0 to time t, which is used to reflect the cumulative effect in the dynamic process, τ k =R k C k .

7. The individualized cerebral blood flow simulation method integrating cerebrovascular morphology and function according to claim 5, characterized in that: Based on the three-dimensional geometric model of the cerebral blood vessels and the brain blood supply functional area, the flow of blood in the cerebral blood vessels is numerically simulated using a computational fluid dynamics method to obtain a blood flow analysis result, and then further comprising: The blood flow analysis results were compared and validated with clinical data measured by transcranial Doppler ultrasound to evaluate the simulation accuracy.

8. An individualized cerebral blood flow simulation system integrating cerebrovascular morphology and function, characterized in that: The individualized cerebral blood flow simulation system integrating cerebrovascular morphology and function includes: A three-dimensional reconstruction module is used to obtain multimodal medical imaging data of a target patient, and to perform three-dimensional reconstruction based on the multimodal medical imaging data to obtain a three-dimensional geometric model of cerebral blood vessels; The atlas mapping module is used to accurately map the standard cerebrovascular domain atlas onto the individualized brain tissue model through geometric deformation, and introduces a weighting mechanism of morphological features to accurately partition the cerebrovascular blood supply area; The boundary condition setting module is used to set boundary conditions that conform to physiological characteristics according to the geometric morphological characteristics of cerebral blood vessels and the functional information of brain tissue, and to perform primary allocation of blood flow impedance parameters according to the size of individualized cerebral blood vessel supply areas, and to perform secondary allocation in individual cerebral blood vessel supply areas according to the morphological characteristics of the distal outlet of the cerebral blood vessels; The cerebral blood flow numerical simulation module is used to numerically simulate the flow of blood in the cerebral blood vessels based on the three-dimensional geometric model of the cerebral blood vessels and the brain blood supply functional area using the computational fluid dynamics method to obtain the blood flow analysis results.

9. A terminal, characterized in that: The terminal includes: a memory, a processor, and an individualized cerebral blood flow simulation program that integrates cerebral vascular morphology and functionality, which is stored in the memory and can be run on the processor. When the individualized cerebral blood flow simulation program that integrates cerebral vascular morphology and functionality is executed by the processor, the steps of the individualized cerebral blood flow simulation method that integrates cerebral vascular morphology and functionality are implemented as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores an individualized cerebral blood flow simulation program that integrates cerebral vascular morphology and functionality. When the individualized cerebral blood flow simulation program that integrates cerebral vascular morphology and functionality is executed by a processor, the steps of the individualized cerebral blood flow simulation method that integrates cerebral vascular morphology and functionality are implemented as described in any one of claims 1-7.

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