A non-invasive measurement method and device for portal vein pressure gradient

Abstract

This application is applicable to the field of computational fluid dynamics and provides a method and device for non-invasively measuring portal vein pressure gradient. The method comprises: obtaining a three-dimensional model of the portal vein, a three-dimensional model of the hepatic vein, the portal vein inlet blood flow velocity, and the hepatic vein outlet blood flow velocity of the liver to be evaluated based on an image of the liver to be evaluated; constructing fluid control equations based on the three-dimensional models of the portal vein and the hepatic vein; solving the fluid control equations based on the portal vein inlet blood flow velocity, the three-dimensional model of the portal vein, the hepatic vein outlet blood flow velocity, and the three-dimensional model of the hepatic vein to obtain the portal vein inlet blood flow pressure and the hepatic vein outlet blood flow pressure; and determining the portal vein pressure gradient based on the portal vein inlet blood flow pressure and the hepatic vein outlet blood flow pressure. This method can improve the low accuracy of non-invasive measurement of portal vein pressure gradient.

Description

Technical Field

[0001] The present application belongs to the field of computational fluid dynamics technology, and in particular relates to a method and device for non-invasively measuring portal vein pressure gradient. Background Art

[0002] Cirrhosis is a common, chronic, progressive liver disease, characterized by diffuse liver damage caused by the long-term or repeated effects of one or more etiologies. In the early stages of cirrhosis, due to the liver's strong compensatory function, there may be no obvious symptoms. In the later stages, liver damage and portal hypertension (PHT) are the main manifestations. The portal vein pressure gradient is an important indicator for assessing the presence of portal hypertension.

[0003] Currently, in the existing portal vein pressure gradient measurement methods, the liver vascular models used for numerical simulation are mostly one-dimensional models and simplified three-dimensional models. Their research scope is limited to the portal vein trunk, and the influence of blood flow status in vascular branches on the portal vein pressure gradient is ignored. Therefore, the measurement accuracy of the portal vein pressure gradient is low. Summary of the Invention

[0004] The embodiments of the present application provide a method and device for non-invasively measuring portal vein pressure gradient, which are used to improve the problem of low measurement accuracy of portal vein pressure gradient in related technologies.

[0005] In a first aspect, embodiments of the present application provide a method for non-invasively measuring portal vein pressure gradient, comprising:

[0006] Based on the image of the liver to be evaluated, a three-dimensional model of the portal vein, a three-dimensional model of the hepatic vein, the blood flow velocity at the entrance of the portal vein, and the blood flow velocity at the exit of the hepatic vein are obtained;

[0007] constructing a fluid control equation of the portal vein based on a three-dimensional model of the portal vein, and constructing a fluid control equation of the hepatic vein based on a three-dimensional model of the hepatic vein;

[0008] According to the portal vein inlet blood flow velocity and the three-dimensional model of the portal vein, the portal vein flow control equation is solved to obtain the portal vein inlet blood flow pressure;

[0009] According to the hepatic vein outlet blood flow velocity and the three-dimensional model of the hepatic vein, the fluid control equation of the hepatic vein is solved to obtain the hepatic vein outlet blood flow pressure;

[0010] The portal vein pressure gradient is determined by the portal vein inlet blood pressure and the hepatic vein outlet blood pressure.

[0011] In a possible implementation of the first aspect, solving the portal vein flow control equation based on the portal vein inlet blood flow velocity and the three-dimensional model of the portal vein to obtain the portal vein inlet blood flow pressure includes:

[0012] Determine the boundary conditions of the portal vein entrance according to the blood flow velocity at the portal vein entrance;

[0013] The first Darcy equation was constructed based on the three-dimensional model of the portal vein;

[0014] Solve the first Darcy equation to obtain the portal vein outlet blood pressure;

[0015] According to the blood flow pressure at the portal vein outlet, the boundary condition of the portal vein outlet is determined;

[0016] According to the portal vein inlet boundary condition, the portal vein outlet boundary condition and the preset portal vein vascular wall boundary condition, the portal vein fluid control equation is solved to obtain the portal vein inlet blood flow pressure.

[0017] In a possible implementation of the first aspect, solving the portal vein flow control equation based on the portal vein inlet boundary condition, the portal vein outlet boundary condition, and the preset portal vein vascular wall boundary condition to obtain the portal vein inlet blood flow pressure includes:

[0018] Finite element method and backward Euler scheme are used to numerically discretize the portal vein flow control equations and obtain the first sparse nonlinear equation system;

[0019] The Newton-Krylov-Schwarz algorithm is used to solve the first sparse nonlinear equation group according to the portal vein inlet boundary conditions, the portal vein outlet boundary conditions and the preset portal vein vascular wall boundary conditions to obtain the portal vein inlet blood flow pressure.

[0020] In a possible implementation of the first aspect, a Newton-Krylov-Schwarz algorithm is used to solve a first sparse nonlinear equation system based on the portal vein inlet boundary condition, the portal vein outlet boundary condition, and a preset portal vein vascular wall boundary condition to obtain the portal vein inlet blood flow pressure, including:

[0021] On the supercomputing platform, the Newton-Krylov-Schwarz algorithm is used to solve the first sparse nonlinear equation group according to the portal vein inlet boundary conditions, portal vein outlet boundary conditions and preset portal vein vascular wall boundary conditions to obtain the portal vein inlet blood flow pressure.

[0022] In a possible implementation of the first aspect, solving the fluid control equation of the hepatic vein based on the hepatic vein outlet blood flow velocity and the three-dimensional model of the hepatic vein to obtain the hepatic vein outlet blood flow pressure includes:

[0023] Determine the boundary conditions of the hepatic vein outlet according to the blood flow velocity at the hepatic vein outlet;

[0024] The second Darcy equation was constructed based on the three-dimensional model of the hepatic vein;

[0025] Solve the second Darcy equation to obtain the blood flow velocity at the inlet of the hepatic vein;

[0026] According to the blood flow velocity at the entrance of the hepatic vein, the boundary conditions at the entrance of the hepatic vein are determined;

[0027] According to the inlet boundary condition of the hepatic vein, the outlet boundary condition of the hepatic vein and the preset vascular wall boundary condition of the hepatic vein, the fluid control equation of the hepatic vein is solved to obtain the outlet blood flow pressure of the hepatic vein.

[0028] In a possible implementation of the first aspect, solving the hepatic vein flow control equation based on the hepatic vein inlet boundary condition, the hepatic vein outlet boundary condition, and the preset hepatic vein vascular wall boundary condition to obtain the hepatic vein outlet blood flow pressure includes:

[0029] The finite element method and backward Euler scheme are used to numerically discretize the fluid flow equations of the hepatic vein, and the second sparse nonlinear equation system is obtained;

[0030] The Newton-Krylov-Schwarz algorithm is used to solve the second sparse nonlinear equation group according to the inlet boundary conditions of the hepatic vein, the outlet boundary conditions of the hepatic vein and the preset vascular wall boundary conditions of the hepatic vein to obtain the outlet blood flow pressure of the hepatic vein.

[0031] In a possible implementation of the first aspect, a Newton-Krylov-Schwarz algorithm is used to solve a second sparse nonlinear equation set based on the inlet boundary condition of the hepatic vein, the outlet boundary condition of the hepatic vein, and a preset hepatic vein vascular wall boundary condition to obtain the outlet blood flow pressure of the hepatic vein, including:

[0032] On the supercomputing platform, the Newton-Krylov-Schwarz algorithm was used to solve the second sparse nonlinear equation group according to the inlet boundary conditions of the hepatic vein, the outlet boundary conditions of the hepatic vein, and the preset vascular wall boundary conditions of the hepatic vein to obtain the outlet blood flow pressure of the hepatic vein.

[0033] In a second aspect, an embodiment of the present application provides a non-invasive measurement device for portal vein pressure gradient, comprising:

[0034] an acquisition module, configured to acquire, based on an image of the liver to be evaluated, a three-dimensional model of the portal vein, a three-dimensional model of the hepatic vein, a blood flow velocity at the inlet of the portal vein, and a blood flow velocity at the outlet of the hepatic vein;

[0035] A construction module, configured to construct a fluid control equation of the portal vein based on a three-dimensional model of the portal vein, and to construct a fluid control equation of the hepatic vein based on a three-dimensional model of the hepatic vein;

[0036] A first calculation module is used to solve the portal vein fluid control equation according to the portal vein inlet blood flow velocity to obtain the portal vein inlet blood flow pressure;

[0037] a second calculation module for solving the fluid control equation of the hepatic vein according to the blood flow velocity at the outlet of the hepatic vein and the three-dimensional model of the hepatic vein to obtain the blood flow pressure at the outlet of the hepatic vein;

[0038] The third calculation module is used to determine the pressure gradient of the portal vein according to the inlet blood flow pressure of the portal vein and the outlet blood flow pressure of the hepatic vein.

[0039] In a third aspect, an embodiment of the present application provides an electronic device, including a processor, which is coupled to a memory, and the processor is used to execute a computer program or instruction stored in the memory, so that the electronic device executes the method in the first aspect.

[0040] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program. When the computer program runs on an electronic device, the electronic device executes the method in the first aspect.

[0041] In a fifth aspect, an embodiment of the present application provides a chip comprising a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the method in the first aspect is implemented.

[0042] In a sixth aspect, an embodiment of the present application provides a computer program product, which, when executed on a terminal device, enables the electronic device to execute the method in the first aspect.

[0043] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0044] In the embodiment of the present application, a real three-dimensional model of the portal vein and hepatic vein can be obtained by acquiring a real liver CT image. By establishing the fluid control equation through the three-dimensional model, the blood flow in the portal vein and hepatic vein can be restored more accurately and completely, thereby improving the accuracy of portal vein pressure measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0046] Figure 1 1 is a flow chart of a method for measuring portal vein pressure gradient provided in an embodiment of the present application;

[0047] Figure 2 A schematic diagram of the structures of the portal vein and hepatic vein provided in the embodiments of the present application;

[0048] Figure 3 This is a schematic diagram of the mesh division of the portal vein and hepatic vein provided in an embodiment of the present application;

[0049] FIG4( a ) is an ultrasound image of the portal vein and hepatic vein provided in an embodiment of the present application;

[0050] FIG4( b ) is a diagram of portal vein inlet velocity extraction provided in an embodiment of the present application;

[0051] FIG4( c ) is a diagram of the rapid extraction of the hepatic vein outlet provided in an embodiment of the present application;

[0052] FIG5( a ) is an image of the portal vein and hepatic vein of Case 1 provided in the Examples of the present application;

[0053] FIG5( b ) is a portal vein pressure gradient diagram of Case 1 provided in the Examples of the present application;

[0054] FIG6( a ) is an image of the portal vein and hepatic vein of Case 2 provided in an embodiment of the present application;

[0055] FIG6( b ) is a graph showing the temporal variation of the portal vein entry point in Case 2 provided in an embodiment of the present application;

[0056] FIG6( c ) is a graph showing the temporal variation of the hepatic vein exit point in Case 2 provided in an embodiment of the present application;

[0057] FIG6( d ) is a curve diagram of portal vein pressure gradient change in Case 2 provided in the Examples of the present application;

[0058] FIG6( e ) is a time-averaged portal vein pressure gradient diagram of Case 2 provided in the Examples of the present application;

[0059] Figure 7 A schematic diagram of the scalability and parallel efficiency test of the numerical algorithm provided in the embodiment of the present application;

[0060] Figure 81 is a schematic diagram of the parallel efficiency test results of the numerical algorithm provided in the embodiment of the present application;

[0061] Figure 9 Schematic diagram of pressure distribution of the numerical simulation results of portal vein and hepatic vein blood flow pressure provided in the embodiments of the present application;

[0062] Figure 10 This is a flow chart of the portal vein pressure gradient measurement device provided in an embodiment of the present application;

[0063] Figure 11 Schematic diagram of the structure of the portal vein pressure gradient measurement device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0064] In the following description, specific details such as specific system structures and techniques are provided for purposes of illustration rather than limitation to facilitate a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obscuring the description of the present application with unnecessary detail.

[0065] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0066] It will also be understood that the term "and / or" used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0067] As used in this specification and the appended claims, the term "if" can be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0068] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0069] References to "one embodiment" or "some embodiments" in this specification mean that a particular feature, structure, or characteristic described in conjunction with that embodiment is included in one or more embodiments of the present application. Thus, phrases such as "in one embodiment," "in some embodiments," "in other embodiments," and "in other embodiments" appearing in various places in this specification do not necessarily refer to the same embodiment, but rather mean "one or more but not all embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0070] The device described in the title may include a non-invasive measurement device for portal vein pressure gradient, an electronic device, a readable storage medium, a chip, and a computer product.

[0071] The portal vein pressure gradient measurement technology can be used to monitor the portal vein pressure gradient value in patients with cirrhosis. Due to changes in the liver structure and vascular function of patients with cirrhosis, the blood flow resistance of the portal vein system and the portal vein blood flow increase, which will lead to increased portal vein pressure. The portal vein pressure gradient value is a measure of portal hypertension. The normal portal vein pressure gradient (PPG) range is 3-5 mmHg. When the portal vein pressure gradient is greater than 5 mmHg, it is defined as portal hypertension. When the portal vein pressure gradient is greater than 10 mmHg, it is clinically significant portal hypertension. In order to monitor the measurement value of patients with cirrhosis, their portal vein pressure gradient needs to be measured. When the patient's portal vein pressure gradient is directly measured, there are not only problems of large trauma and high risk, but also the measurement accuracy is not high enough.

[0072] Therefore, the present application provides a method for non-invasively measuring the portal vein pressure gradient. By restoring the portal vein and hepatic vein in the liver through real images and establishing a three-dimensional model, the fluid control equation is established through the three-dimensional model, which can more accurately and completely restore the flow of blood in the portal vein and hepatic vein, thereby improving the accuracy of portal vein pressure measurement.

[0073] The following is an illustrative description of the non-invasive method for measuring portal vein pressure gradient provided by the present application with reference to the accompanying drawings and specific embodiments.

[0074] Figure 1 This is a flow chart of a method for non-invasively measuring portal vein pressure gradient provided in an embodiment of the present application. The execution subject of this method can be a computer application. Figure 1 , the method comprises the following steps:

[0075] Step 101: acquiring a three-dimensional model of the portal vein and the hepatic vein of the liver to be evaluated, a blood flow velocity at the inlet of the portal vein, and a blood flow velocity at the outlet of the hepatic vein according to an image of the liver to be evaluated;

[0076] In this embodiment, the liver image is a computed tomography (CT) image. The liver image can be obtained by taking a CT image of the patient's abdomen, or by obtaining it from a cooperating hospital, which is not limited here.

[0077] The embodiments of the present application do not limit the method of obtaining a three-dimensional model through images.

[0078] In one possible implementation, the method for obtaining a three-dimensional model may specifically include the following steps:

[0079] Step 110: Acquire the portal vein and the hepatic vein from the liver CT image to be evaluated.

[0080] For example, a CT image of the liver can be Figure 2 As shown in (a) of FIG, in order to construct the three-dimensional model of the portal vein and hepatic vein of the liver, the portal vein image and the hepatic vein image are first extracted from the CT image of the liver to be evaluated. For example, the liver segmentation image can be extracted from the CT image of the liver using Mimics (Materialise's Interactive Medical Image Control System) software. The liver segmentation image can be as follows: Figure 2 As shown in (b), it includes portal vein and hepatic vein.

[0081] Step 120: Perform geometric repair and smoothing processing on the portal vein and the hepatic vein.

[0082] In order to make the obtained portal vein and hepatic vein more restored, the portal vein and hepatic vein need to be geometrically repaired and smoothed.

[0083] In one possible implementation, Geomagic (Geomagic Spark, forward-inverse hybrid design) software can be used to perform geometric repair and smoothing on the extracted portal vein and hepatic vein to obtain the following: Figure 2 (c) shows the portal vein and hepatic vein vascular maps after repair.

[0084] Step 130: Meshing the portal vein and the hepatic vein to obtain three-dimensional models of the portal vein and the hepatic vein.

[0085] For example, the ICEM module (a module in Ansys that can be used for mesh design) in Ansys (a finite element method computer design program) can be used to mesh the portal vein and the hepatic vein to obtain three-dimensional models of the portal vein and the hepatic vein.

[0086] For example, the ICEM module can be used to divide the portal vein and hepatic vein into unstructured tetrahedral meshes. Unstructured means that the internal points in the mesh area do not have the same adjacent units, and tetrahedral means that the shape of each mesh is a tetrahedron. Figure 2 The portal vein and hepatic vein images after repair shown in (c) are divided into grids, and the following can be obtained: Figure 3 The grid diagram shown in Figure 1. Figure 3 (a) shows the portal vein mesh diagram. The corresponding 3D model includes the coordinates of each grid point in the portal vein's unstructured tetrahedral mesh. As can be seen, the portal vein has a single inlet and multiple outlets, with small outlet diameters typically on the millimeter scale.

[0087] like Figure 3 (b) shows the hepatic vein mesh diagram. The corresponding 3D model includes the coordinates of each grid point in the unstructured tetrahedral mesh of the hepatic vein. As can be seen, the hepatic vein has multiple inlets and a single outlet, with a small inlet diameter, typically on the millimeter scale.

[0088] The blood flow velocity at the portal vein inlet and the hepatic vein outlet can be extracted from the outer contours of the acquired ultrasound image using Origin software. Origin is a scientific graphics and data analysis software. Figure 4(a) shows the ultrasound images of the portal vein and hepatic vein. After extraction using Origin software, the blood flow velocity at the portal vein inlet is shown in Figure 4(b), and the blood flow velocity at the hepatic vein outlet is shown in Figure 4(c).

[0089] Step 102: constructing a fluid control equation of the portal vein based on the three-dimensional model of the portal vein, and constructing a fluid control equation of the hepatic vein based on the three-dimensional model of the hepatic vein.

[0090] In mathematics, fluid control equations are mostly systems of equations coupled from nonlinear partial differential equations. Specifically, fluid flow generally satisfies three basic laws: the law of conservation of mass, Newton's second law, and the law of conservation of energy. Equations that reflect the flow state of a fluid are referred to as fluid control equations. In the embodiments of this application, any fluid control equation that can reflect the flow state of blood flow can be constructed and solved, and this application does not impose any restrictions on this.

[0091] In a possible implementation, the portal vein and the hepatic vein may use the same flow control equation or different flow control equations. The following uses the same flow control equation as an example for exemplary description.

[0092] Because blood flow in the portal and hepatic veins resembles an incompressible Newtonian fluid—a fluid whose density does not change during flow—the non-steady-state incompressible Navier-Stokes (NS) equations are used to describe the flow state of blood in the portal and hepatic veins.

[0093] Exemplarily, the fluid control equation of the portal vein is constructed based on the three-dimensional model of the portal vein, as shown in the following formula:

[0094]

[0095] Among them, u1 represents the blood flow velocity in the portal vein, t represents time, represents the partial derivative of the blood flow velocity u1 in the portal vein with respect to time t, ρ represents the density of blood, represents the gradient or divergence operator, and σ represents the Cauchy stress tensor. Ω1 represents the spatial domain of the portal vein fluid control equation, that is, the space where the three-dimensional model of the portal vein is located. (0, T1] represents the time domain of the portal vein fluid control equation, and T1 represents the cycle length. The calculation of σ in the portal vein fluid control equation satisfies the following formula:

[0096] σ=﹣p1I+2με(u1)

[0097] Where p1 represents the blood flow pressure in the portal vein, I represents the 3×3 unit matrix, μ represents the dynamic viscosity, and ε(u1) represents the strain tensor. The calculation of ε(u1) satisfies the following formula:

[0098]

[0099] in, represents the transpose of u1.

[0100] The initial conditions of the portal vein flow control equation are:

[0101] u1(x,0)=u a

[0102] In one possible implementation, u a It can be 0, that is, 0 can be used as the initial value of u1 for solution.

[0103] It should be understood that among the various physical quantities involved in the above portal vein fluid control equation, the blood flow velocity u1 and the pressure p1 are unknown quantities in the equation, that is, the physical quantities to be solved in the embodiment of the present application.

[0104] The fluid control equation of the hepatic vein is constructed based on the three-dimensional model of the hepatic vein, as shown in the following equation:

[0105]

[0106] Where, u2 represents the blood flow velocity in the hepatic vein, t represents time, represents the partial derivative of the blood flow velocity u2 in the hepatic vein with respect to time t, ρ represents the density of blood, represents the gradient or divergence operator, and σ represents the Cauchy stress tensor. Ω2 represents the spatial domain of the hepatic vein fluid control equation, that is, the space where the three-dimensional model is located. (0, T2] represents the time domain of the hepatic vein fluid control equation, and T2 represents the cycle length. The calculation of σ in the hepatic vein fluid control equation satisfies the following formula:

[0107] σ=﹣p2I+2με(u2)

[0108] Where p2 represents the pressure of blood flow in the hepatic vein, I represents the 3×3 unit matrix, μ represents the dynamic viscosity, and ε(u2) represents the strain tensor. The calculation of ε(u2) satisfies the following formula:

[0109]

[0110] in, represents the transpose of u2.

[0111] The initial conditions of the flow control equations of the hepatic vein are:

[0112] u2(x,0)=u b

[0113] In one possible implementation, u b It can be 0, that is, 0 can be used as the initial value of u2 for solution.

[0114] It should be understood that among the various physical quantities involved in the above-mentioned hepatic vein fluid control equation, the blood flow velocity u2 and the pressure p2 are unknown quantities in the equation, that is, the physical quantities to be solved in the embodiment of the present application.

[0115] Step 103: Solve the portal vein flow control equation according to the portal vein inlet blood flow velocity and the three-dimensional model of the portal vein to obtain the portal vein inlet blood flow pressure.

[0116] In order to solve the above portal vein flow control equation, boundary conditions need to be set to limit the flow control equation.

[0117] The boundary condition of the portal vein entrance can be obtained from the blood flow velocity at the portal vein entrance. In one possible implementation, the boundary condition of the portal vein entrance can be:

[0118] u1=u0onΓ I ×(0,T1]

[0119] Where u0 represents the extracted blood flow velocity at the portal vein entrance, Γ I represents the entrance of the portal vein, and (0, T1] represents the portal vein calculation time domain.

[0120] Because the portal vein has a single inlet and multiple outlets, its outlet diameter is relatively small, typically on the order of millimeters. Its blood flow velocity cannot be directly measured using ultrasound, and therefore its boundary conditions cannot be directly measured. Currently, related technologies typically use empirical values to determine the boundary conditions required for portal vein outlet blood flow velocity across different patients. This fails to account for individual differences, resulting in low measurement accuracy.

[0121] In order to obtain more accurate boundary conditions of the portal vein outlet, the present application calculates the boundary conditions of the portal vein outlet based on the three-dimensional model of the portal vein. For example, the following first Darcy equation is constructed based on the three-dimensional model of the portal vein:

[0122]

[0123] Where S0 represents the preset water release coefficient of the tissue, q1 represents the pressure of the blood flow at the portal vein outlet, v1 represents the velocity of the blood flow at the portal vein outlet, f is the source term, which can be taken as 0, and K represents the permeability tensor of the porous medium. Represents the partial derivative of the pressure q1 of blood flow at the portal vein outlet with respect to time t.

[0124] By solving the first Darcy equation above, q1 is obtained. It should be understood that the obtained q1 represents the pressure values of different points. According to the coordinate position of the sampling point of each outlet in the three-dimensional model, the pressure value corresponding to each outlet is obtained from q1. For example, if there are K outlets, K outlet pressures are obtained based on q1, which are expressed as q 11 ,q 12 ...q 1k The boundary condition of the kth exit (k is an integer between 1 and K) among the K exits can be expressed as:

[0125]

[0126] Among them, q 1k is the blood flow pressure at the kth outlet obtained by the first Darcy equation, represents the kth portal vein outlet.

[0127] In one possible implementation, assuming that the blood flow velocity in the portal vein wall is 0, that is, assuming that the blood flow does not pass through the vessel wall, the boundary condition at the portal vein wall can be set as:

[0128] u1=0onΓ w ×(0,T1]

[0129] After obtaining the boundary conditions of the portal vein fluid control equation, the portal vein fluid control equation can be solved according to the portal vein inlet boundary conditions, the portal vein outlet boundary conditions and the preset portal vein vascular wall boundary conditions to obtain the portal vein inlet blood flow pressure.

[0130] In one possible implementation, the portal vein flow control equations may be numerically discretized to obtain a first sparse nonlinear equation system. This first sparse nonlinear equation system is then solved based on the portal vein inlet boundary conditions, the portal vein outlet boundary conditions, and preset portal vein vascular wall boundary conditions to obtain the portal vein inlet blood flow pressure.

[0131] For example, the portal vein flow control equations can be numerically discretized in both the time and space domains. For example, the portal vein flow control equations can be discretized in the space domain using the P1-P1 finite element method, and in the time domain using the implicit backward Euler method. The two P1s refer to the use of the P1 finite element method for both the blood flow velocity u1 and the pressure p1, respectively. Specifically, the P1 finite element method refers to first-order linear discretization.

[0132] In one possible implementation, a Newton-Krylov-Schwarz (NKS) algorithm may be used to solve the first sparse nonlinear equation system. The NKS algorithm includes an inexact Newton method (Newton), a Krylov subspace iteration method (Krylov), and an overlapping Schwarz algorithm (Schwarz). Exemplarily, the NKS algorithm includes the following processing steps:

[0133] Step 310: Solve the first sparse nonlinear equation system using the inexact Newton method.

[0134] In the iterative process of solving the inexact Newton method, the grid sequence method and nonlinear preprocessing technology can be used to make the nonlinear iterative process of this step have grid-independent convergence; and for the Jacobian matrix in the inexact Newton method, the polychromatic sorting finite difference method, automatic differentiation technology, JFNK (Jacobian-free Newton-Krylov) method or explicit generation strategies are used to construct and generate it.

[0135] Step 320: Use the Krenov subspace iteration method to solve the linear equations in the inexact Newton method.

[0136] Specifically, in this step, the generalized minimal residual algorithm (GMRES) is used to solve the linear equations with asymmetric matrices in the inexact Newton method.

[0137] Step 330: construct a preconditioner in the linear system of equations using the domain decomposition method.

[0138] Specifically, in this embodiment, an overlapping Schwarz algorithm is used to construct a preconditioner to accelerate the linear solution in step 320. Specifically, the preconditioner can be constructed by adjusting the extended additive Schwarz algorithm or the restricted additive Schwarz algorithm.

[0139] The embodiment of the present application processes the sparse nonlinear system through the NKS algorithm, thereby improving the computational efficiency of the computer in solving the fluid control equation.

[0140] In order to improve parallel efficiency, the Tianhe-2A supercomputer platform can be used to solve the first sparse nonlinear equations.

[0141] In this embodiment, after solving the portal vein flow control equation, the pressure p1 obtained includes the pressure value of any point in the portal vein grid. Therefore, based on the coordinate position in the three-dimensional portal vein model, the pressure of any point at the portal vein entrance can be extracted from p1.

[0142] Step 104: Solve the fluid control equation of the hepatic vein according to the blood flow velocity at the outlet of the hepatic vein and the three-dimensional model of the hepatic vein to obtain the blood flow pressure at the outlet of the hepatic vein.

[0143] In the embodiment of the present application, the same algorithm can be used to solve the fluid control equation.

[0144] In order to solve the above-mentioned fluid control equation of the hepatic vein, boundary conditions need to be set to limit the fluid control equation.

[0145] The boundary condition of the hepatic vein outlet can be obtained from the blood flow velocity at the hepatic vein outlet. In one possible implementation, the boundary condition of the hepatic vein outlet can be:

[0146] p2=QRonΓ o ×(0,T2]

[0147] Where Q represents the blood flow rate, which can be obtained by the blood flow velocity at the hepatic vein outlet, R is the resistance of blood flow in the given hepatic vein, and Γ o represents the outlet of the hepatic vein, and (0, T2] represents the time domain of the hepatic vein calculation.

[0148] Because the hepatic veins have multiple inlets and a single outlet, their inlet diameters are relatively small, typically on the order of millimeters. Blood flow velocity cannot be directly measured using ultrasound, and therefore, the boundary conditions cannot be directly measured. Currently, the required boundary conditions for hepatic vein inlet blood flow velocity are typically set based on empirical values, using the same empirical values for all patients. This fails to account for individual differences, resulting in low measurement accuracy.

[0149] In order to obtain more accurate boundary conditions at the hepatic vein inlet, the present application calculates the boundary conditions at the hepatic vein inlet based on the three-dimensional model of the hepatic vein. For example, the following second Darcy equation is constructed based on the three-dimensional model of the hepatic vein:

[0150]

[0151] Where S0 represents the preset water release coefficient of the tissue, q2 represents the blood pressure at the hepatic vein inlet, v2 represents the blood velocity at the hepatic vein inlet, f is the source term, which can be taken as 0, and K represents the permeability tensor of the porous medium. Represents the partial derivative of the pressure q2 of blood flow in the hepatic vein with respect to time t.

[0152] By solving the second Darcy equation above, v2 is obtained. It should be understood that the obtained v2 represents the velocity values of different points. According to the coordinate position of the sampling point of each entrance in the three-dimensional model, the velocity value corresponding to each entrance is obtained from v2. For example, if there are K entrances, K entrance velocities are obtained based on v2, which are respectively expressed as v 21 、v 22 ……v 2k The boundary condition of the kth (k is an integer between 1 and K) entrance among the K exits can be expressed as:

[0153]

[0154] Among them, v k is the blood flow velocity at the kth inlet obtained by the second Darcy equation, Indicates the entrance of the hepatic vein.

[0155] In one possible implementation, assuming that the blood flow velocity in the hepatic vein wall is 0, that is, assuming that the blood flow does not pass through the vessel wall, the boundary condition at the hepatic vein wall can be set as:

[0156] u2=0onΓ w×(0,T2]

[0157] After obtaining the boundary conditions of the hepatic vein fluid control equation, the hepatic vein fluid control equation can be solved according to the inlet boundary conditions of the hepatic vein, the outlet boundary conditions of the hepatic vein and the preset vascular wall boundary conditions of the hepatic vein to obtain the outlet blood flow pressure of the hepatic vein.

[0158] In one possible implementation, the fluid control equations of the hepatic vein may be numerically discretized to obtain a second sparse nonlinear equation system. This second sparse nonlinear equation system is then solved based on the inlet boundary conditions of the hepatic vein, the outlet boundary conditions of the hepatic vein, and preset vascular wall boundary conditions of the hepatic vein to obtain the outlet blood flow pressure of the hepatic vein.

[0159] For example, the hepatic vein flow control equations can be numerically discretized in both the time and space domains. For example, the hepatic vein flow control equations can be discretized in the space domain using the P1-P1 finite element method, and in the time domain using the implicit backward Euler method. The two P1s refer to the use of the P1 finite element method for both the blood flow velocity u2 and the pressure p2, respectively. Specifically, the P1 finite element method refers to first-order linear discretization.

[0160] The embodiment of the present application processes the sparse nonlinear equations through the NKS algorithm, thereby improving the computational efficiency of the computer in solving the fluid control equations. The description of the NKS algorithm in 103 above is provided and will not be repeated here.

[0161] In order to improve parallel efficiency, the Tianhe-2A supercomputer platform can be used to solve the second sparse nonlinear equations.

[0162] In this embodiment, the pressure p2 obtained by solving the hepatic vein flow control equation includes the pressure value at any point in the hepatic vein grid. Therefore, the pressure at any point at the hepatic vein outlet can be extracted from p2 based on the coordinate position in the three-dimensional hepatic vein model.

[0163] Step 105: Determine the pressure gradient of the portal vein according to the inlet blood flow pressure of the portal vein and the outlet blood flow pressure of the hepatic vein.

[0164] Specifically, after the blood pressure at the portal vein inlet and the blood pressure at the hepatic vein outlet are solved in the above steps 103 and 104, the blood pressure at the portal vein inlet is subtracted from the blood pressure at the hepatic vein outlet to obtain the portal vein pressure gradient value.

[0165] The accuracy of the gradient value obtained by the non-invasive measurement method of portal vein pressure provided in this application is exemplified below in combination with simulated data from two cases.

[0166] Figure 5(a) shows images of the portal vein and hepatic vein in Case 1. Using the method provided in an embodiment of the present application, the blood flow pressure in the portal vein and hepatic vein at a specific time point was calculated. The pressures of four sample points, A1, A2, A3, and A4, were extracted at the portal vein entrance, and the pressures of four sample points, B1, B2, B3, and B4, were extracted at the hepatic vein exit. As shown in Figure 5(b), the pressure difference between points A1 and B1 was 4.87, the pressure difference between points A2 and B2 was 4.71, the pressure difference between points A3 and B3 was 4.62, and the pressure difference between points A4 and B4 was 4.17. Since the normal value of the portal vein pressure gradient is within 5 mmHg, it can be seen that the portal vein pressure gradient values in Case 1 were all within the normal range.

[0167] Figure 6(a) shows images of the portal vein and hepatic vein in Case 2. Using the method provided in an embodiment of the present application, after calculating the blood flow pressure in the portal vein and hepatic vein over multiple time periods, the pressures at four sample points (C1, C2, C3, and C4) were extracted at the portal vein entrance. A curve showing the pressure values at C1, C2, C3, and C4 changing over time is shown in Figure 6(b). At the hepatic vein exit, the pressures at four sample points (D1, D2, D3, and D4) were extracted. A curve showing the pressure values at D1, D2, D3, and D4 changing over time is shown in Figure 6(c).

[0168] The pressure difference curves over time are shown in Figure 6(d) by subtracting C1 from D1, C2 from D2, C3 from D3, and C4 from D4. As shown in Figure 6(e), over the three time periods, the average time-pressure difference between C1 and D1 is 4.28, the average time-pressure difference between C2 and D2 is 3.75, the average time-pressure difference between C3 and D3 is 4.08, and the average time-pressure difference between C4 and D4 is 3.78. Since the normal value of the portal vein pressure gradient is within 5 mmHg, it can be seen that the portal vein pressure gradient values in Case 2 are all within the normal range.

[0169] From the test results of the above two cases, it can be seen that after using the method provided in the embodiment of the present application to solve the portal vein blood flow pressure and the hepatic vein blood flow pressure and obtain the portal vein pressure gradient, by comparing with the portal vein pressure gradient obtained by the test, it can be seen that the solved portal vein pressure gradient and the portal vein pressure gradient obtained by the experiment are both within the normal value range. Therefore, the method for obtaining the portal vein pressure gradient provided in the present application is accurate.

[0170] The following experiments illustrate the scalability and parallel efficiency of the non-invasive portal vein pressure gradient measurement method provided in this application to obtain the gradient value.

[0171] This application tests the scalability and parallel efficiency of the algorithm on the Guangzhou supercomputer "Tianhe-2". Figure 7 As shown in (a) in the figure, it is a line graph of the number of processor cores and computing time. Through testing, it can be seen that as the number of processor cores increases, the computing time decreases and is consistent with the ideal value. Figure 7 (b) is a line graph showing the number of processor cores and their speedup ratio. The test shows that as the number of processor cores increases, the speedup ratio of the numerical simulation approaches the ideal speedup ratio.

[0172] like Figure 8 The figure shows the parallel efficiency test results of the non-invasive portal vein pressure gradient measurement method provided by this application. Assuming the number of processor cores (np) is 360, 720, and 1080, the number of nonlinear iterations (Newton), the number of linear iterations (GMRES), computation time (Time), memory (Memory), speedup (Speedup), and parallel efficiency (Efficiency) are calculated. The number of nonlinear iterations is the number of times the first sparse nonlinear equation system is solved using the inexact Newton method in step 310, and the number of linear iterations is the number of times the linear equation system in the inexact Newton method is solved using the Krenov subspace iteration method in step 320.

[0173] pass Figure 8It can be seen that when the preset number of processor cores is 360, the number of nonlinear iterations is calculated to be 3.80, the number of linear iterations is 185.24, the calculation time is 51.96 seconds, the memory used is 265.55 bytes, the speedup ratio is 1, and the parallel efficiency is 100%. When the preset number of processor cores is 720, the number of nonlinear iterations is calculated to be 3.70, the number of linear iterations is 179.32, the calculation time is 27.84 seconds, the memory used is 118.76 bytes, the speedup ratio is 1.86, and the parallel efficiency is 94%. When the preset number of processor cores is 1080, the number of nonlinear iterations is calculated to be 3.70, the number of linear iterations is 185.46, the calculation time is 20.98 seconds, the memory used is 111.94 bytes, the speedup ratio is 2.48, and the parallel efficiency is 83%. Since a higher parallel efficiency value indicates higher parallel efficiency, it can be seen that the noninvasive portal vein pressure gradient measurement method provided in this application achieves high parallel efficiency when assuming 360, 720, and 1080 processor cores, respectively. Therefore, the noninvasive portal vein pressure gradient measurement method provided in this application has high parallel efficiency.

[0174] The non-invasive method for measuring portal vein pressure gradient provided by the above embodiment has the following advantages:

[0175] (1) By acquiring real liver CT images, a three-dimensional model of the portal vein and hepatic vein is obtained. By establishing the fluid control equation through the three-dimensional model, the blood flow in the portal vein and hepatic vein can be restored more accurately and completely, thereby improving the accuracy of portal vein pressure measurement.

[0176] (2) The Darcy equation is used to simulate the boundary conditions of the portal vein outlet and the hepatic vein inlet, avoiding the influence of empirical parameters on the numerical simulation results and making the portal vein pressure gradient measurement results closer to the true value.

[0177] (3) Using the fully implicit and fully coupled method to solve the NS equations simulating portal vein and hepatic vein blood flow can improve the calculation accuracy of the equations and ensure mass conservation.

[0178] (4) The NKS algorithm is used to calculate sparse nonlinear equations, which has high parallel efficiency on supercomputing platforms, improves the computational efficiency of nonlinear iteration and linear iteration, and reduces the calculation time.

[0179] (5) Based on the fluid dynamics properties of blood, other fluid dynamics parameters of blood, such as blood shear stress, can be calculated from the blood flow velocity and pressure obtained through the technical solution provided by this application, so as to prevent and diagnose liver vascular diseases.

[0180] It should be understood that, provided there is no logical conflict, the above-mentioned embodiments can be combined with each other to meet actual application requirements. The specific embodiments or implementation plans obtained by these combinations still fall within the scope of protection of this application.

[0181] Corresponding to the non-invasive measurement method of portal vein pressure gradient described in the above embodiment, Figure 10 A schematic structural diagram of a non-invasive measurement device for portal vein pressure gradient provided in one embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown.

[0182] See also Figure 10 As shown, the portal vein pressure gradient non-invasive measurement device comprises:

[0183] An acquisition module 1010 is configured to acquire a three-dimensional model of the portal vein, a three-dimensional model of the hepatic vein, a blood flow velocity at the inlet of the portal vein, and a blood flow velocity at the outlet of the hepatic vein of the liver to be evaluated based on an image of the liver to be evaluated;

[0184] A construction module 1020 is configured to construct a fluid control equation of the portal vein based on the three-dimensional model of the portal vein, and to construct a fluid control equation of the hepatic vein based on the three-dimensional model of the hepatic vein;

[0185] A first calculation module 1030 is configured to solve the portal vein flow control equation according to the portal vein inlet blood flow velocity to obtain the portal vein inlet blood flow pressure;

[0186] A second calculation module 1040 is configured to solve the flow control equation of the hepatic vein according to the blood flow velocity at the hepatic vein outlet and the three-dimensional model of the hepatic vein to obtain the blood flow pressure at the hepatic vein outlet;

[0187] The third calculation module 1050 is configured to determine the pressure gradient of the portal vein according to the blood flow pressure at the inlet of the portal vein and the blood flow pressure at the outlet of the hepatic vein.

[0188] Optionally, the first calculation module 1030 includes:

[0189] A first construction unit is configured to determine a boundary condition at the entrance of the portal vein according to a blood flow velocity at the entrance of the portal vein;

[0190] a second construction unit, configured to construct a first Darcy equation based on the three-dimensional model of the portal vein;

[0191] a first solving unit, for solving the first Darcy equation to obtain the blood flow pressure at the portal vein outlet;

[0192] a third construction unit, configured to determine an outlet boundary condition of the portal vein according to the outlet blood flow pressure of the portal vein;

[0193] The second solving unit is used to solve the portal vein fluid control equation according to the portal vein inlet boundary condition, the portal vein outlet boundary condition and the preset portal vein vascular wall boundary condition to obtain the portal vein inlet blood flow pressure.

[0194] Optionally, the second solving unit includes

[0195] A discrete unit is used to numerically discretize the fluid control equation of the portal vein using a finite element method and a backward Euler scheme to obtain a first sparse nonlinear equation group;

[0196] The solving unit is used to solve the first sparse nonlinear equation group according to the portal vein inlet boundary condition, the portal vein outlet boundary condition and the preset portal vein vascular wall boundary condition by using the Newton-Krylov-Schwarz algorithm to obtain the portal vein inlet blood flow pressure.

[0197] Optionally, the discrete unit includes using the Newton-Krylov-Schwarz algorithm on a supercomputing platform to solve the first sparse nonlinear equation group according to the portal vein inlet boundary condition, the portal vein outlet boundary condition and the preset portal vein vascular wall boundary condition to obtain the portal vein inlet blood flow pressure.

[0198] Optionally, the second calculation module 1040 includes:

[0199] A first construction unit is configured to determine an outlet boundary condition of the hepatic vein according to an outlet blood flow velocity of the hepatic vein;

[0200] a second construction unit, configured to construct a second Darcy equation based on the three-dimensional model of the hepatic vein;

[0201] The first solving unit is used to solve the second Darcy equation to obtain the blood flow velocity at the inlet of the hepatic vein;

[0202] a third construction unit, configured to determine a boundary condition at the entrance of the hepatic vein according to a blood flow velocity at the entrance of the hepatic vein;

[0203] The second solving unit is used to solve the fluid control equation of the hepatic vein according to the inlet boundary condition of the hepatic vein, the outlet boundary condition of the hepatic vein and the preset vascular wall boundary condition of the hepatic vein to obtain the outlet blood flow pressure of the hepatic vein.

[0204] Optionally, the second solving unit includes:

[0205] A discrete element is used for numerically discretizing the fluid control equation of the hepatic vein by using a finite element method and a backward Euler scheme to obtain a second sparse nonlinear equation group;

[0206] The solving unit is used to solve the second sparse nonlinear equation group according to the inlet boundary condition of the hepatic vein, the outlet boundary condition of the hepatic vein and the preset vascular wall boundary condition of the hepatic vein by using the Newton-Krylov-Schwarz algorithm to obtain the outlet blood flow pressure of the hepatic vein.

[0207] Optionally, the solving unit includes using the Newton-Krylov-Schwarz algorithm on a supercomputing platform to solve the second sparse nonlinear equation group according to the inlet boundary condition of the hepatic vein, the outlet boundary condition of the hepatic vein and the preset vascular wall boundary condition of the hepatic vein to obtain the outlet blood flow pressure of the hepatic vein.

[0208] The process of each module in the non-invasive measurement device for portal vein pressure gradient provided in the embodiment of the present application realizing its own function can be specifically referred to the aforementioned Figure 1 The description of the illustrated embodiment and other related method embodiments will not be repeated here.

[0209] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of this application. Their specific functions and technical effects can be found in the method embodiment section and will not be repeated here.

[0210] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0211] The non-invasive measurement method of portal vein pressure gradient provided in the embodiments of the present application can be applied to terminals such as mobile phones, tablet computers, wearable devices, vehicle-mounted devices, augmented reality (AR) / virtual reality (VR) devices, laptop computers, ultra-mobile personal computers (UMPCs), netbooks, and personal digital assistants (PDAs). The embodiments of the present application do not impose any restrictions on the specific type of terminal.

[0212] For example, the terminal can be a station (STAION, ST) in a WLAN, a cellular phone, a cordless phone, a Session Initiation Protocol (SIP) phone, a Wireless Local Loop (WLL) station, a Personal Digital Assistant (PDA) device, a handheld device with wireless communication capabilities, a computing device or other processing device connected to a wireless modem, a vehicle-mounted device, a vehicle networking terminal, a computer, a laptop computer, a handheld communication device, a handheld computing device, a satellite wireless device, a wireless modem card, a TV set-top box (STB), customer premise equipment (CPE) and / or other devices for communicating on a wireless system and a next-generation communication system, such as a terminal in a 5G network or a terminal in a future evolved Public Land Mobile Network (PLMN) network, etc.

[0213] Figure 11 This is a schematic diagram of the structure of a terminal device provided by an embodiment of the present application. Figure 11 As shown, the terminal device 11 of this embodiment includes: at least one processor 1110 ( Figure 11 Only one is shown), memory 1120, memory 1120 stores a computer program 1130 that can be run on processor 1110. When processor 1110 executes computer program 1130, the steps of the embodiment of the method for calculating the flow field of blood flow in each blood vessel described above are implemented, such as Figure 1 Alternatively, when the processor 1110 executes the computer program 1130, the functions of the modules / units in the above-mentioned device embodiments are realized, for example, Figure 10 The functions of modules 1010 to 1050 are shown.

[0214] The terminal device 11 may include, but is not limited to: a processor 1110 and a memory 1120. Those skilled in the art will understand that Figure 11 It is only an example of the terminal device 11 and does not constitute a limitation of the terminal device 11. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the terminal device 11 may also include an input sending device, a network access device, a bus, etc.

[0215] The processor 1110 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0216] In some embodiments, the memory 1120 may be an internal storage unit of the terminal device 11, such as a hard disk or memory of the terminal device 11. The memory 1120 may also be an external storage device of the terminal device 11, such as a plug-in hard disk equipped on the terminal device 11, a smart media card (SMC), a secure digital (SD) card, a flash memory card, etc. The memory 1120 may also include both an internal storage unit of the terminal device 11 and an external storage device. The memory 1120 is used to store an operating system, application programs, a boot loader, data, and other programs, such as the program code of the computer program 1130. The memory 1120 may also be used to temporarily store data that has been sent or is about to be sent.

[0217] In addition, those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units in the various embodiments of the present application can be integrated into a processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0218] An embodiment of the present application also provides an electronic device, characterized in that it includes a processor, the processor is coupled to a memory, and the processor is used to execute a computer program or instruction stored in the memory, so that the electronic device implements the steps in the above-mentioned various method embodiments.

[0219] An embodiment of the present application provides a computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program, and when the computer program runs on an electronic device, the electronic device executes the steps in the above-mentioned various method embodiments.

[0220] An embodiment of the present application provides a chip, characterized in that the chip includes a processor and a memory, the memory stores a computer program, and when the computer program is executed by the processor, the steps in the above-mentioned various method embodiments are implemented.

[0221] An embodiment of the present application provides a computer program product, characterized in that when the computer program product is run on a terminal device, the electronic device executes the steps in the above-mentioned various method embodiments.

[0222] It should be understood that the processor mentioned in the embodiments of the present application may be a central processing unit (CPU), or may be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0223] It should also be understood that the memory mentioned in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct RAM bus random access memory (DR RAM).

[0224] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0225] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0226] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0227] In the embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the system embodiments described above are merely schematic. For example, the division of the modules or units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0228] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0229] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0230] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program, when executed by the processor, can implement the steps of the above-mentioned various method embodiments. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include at least: any entity or device capable of carrying the computer program code to a large-screen device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electric carrier signal, a telecommunication signal and a software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0231] Finally, it should be noted that the above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A method for non-invasive measurement of portal vein pressure gradient, characterized in that: include: Obtain the portal and hepatic venous vessels from the image of the liver to be evaluated; performing geometric repair on the portal vein and the hepatic vein, and performing smoothing on the portal vein and the hepatic vein, respectively, to obtain a processed portal vein and a processed hepatic vein; Meshing the processed portal vein and the processed hepatic vein to obtain a three-dimensional model of the portal vein and a three-dimensional model of the hepatic vein; Obtaining the inlet blood flow velocity of the portal vein and the outlet blood flow velocity of the hepatic vein according to the image of the liver to be evaluated; constructing a fluid control equation of the portal vein according to the three-dimensional model of the portal vein, and constructing a fluid control equation of the hepatic vein according to the three-dimensional model of the hepatic vein; determining an inlet boundary condition of the portal vein according to the inlet blood flow velocity of the portal vein; constructing a first Darcy equation based on the three-dimensional model of the portal vein; Solving the first Darcy equation to obtain the blood flow pressure at the portal vein outlet; determining an outlet boundary condition of the portal vein according to the outlet blood flow pressure of the portal vein; Solving the portal vein flow control equation according to the portal vein inlet boundary condition, the portal vein outlet boundary condition, and the preset portal vein vascular wall boundary condition to obtain the portal vein inlet blood flow pressure; determining an outlet boundary condition of the hepatic vein according to the outlet blood flow velocity of the hepatic vein; constructing a second Darcy equation based on the three-dimensional model of the hepatic vein; Solving the second Darcy equation to obtain the blood flow velocity at the inlet of the hepatic vein; determining a boundary condition at the inlet of the hepatic vein according to the blood flow velocity at the inlet of the hepatic vein; Solving the fluid control equation of the hepatic vein according to the inlet boundary condition of the hepatic vein, the outlet boundary condition of the hepatic vein, and the preset vascular wall boundary condition of the hepatic vein to obtain the outlet blood flow pressure of the hepatic vein; The pressure gradient of the portal vein is determined according to the inlet blood flow pressure of the portal vein and the outlet blood flow pressure of the hepatic vein.

2. The method for non-invasive measurement of portal vein pressure gradient according to claim 1, characterized in that: Solving the portal vein flow control equation according to the portal vein inlet boundary condition, the portal vein outlet boundary condition, and the preset portal vein vascular wall boundary condition to obtain the portal vein inlet blood flow pressure includes: Numerically discretizing the portal vein fluid control equations using a finite element method and a backward Euler scheme to obtain a first sparse nonlinear equation group; The Newton-Krylov-Schwarz algorithm is used to solve the first sparse nonlinear equations according to the portal vein inlet boundary condition, the portal vein outlet boundary condition and the preset portal vein vascular wall boundary condition to obtain the portal vein inlet blood flow pressure.

3. The method for non-invasive measurement of portal vein pressure gradient according to claim 2, characterized in that: The Newton-Krylov-Schwarz algorithm is used to solve the first sparse nonlinear equations according to the portal vein inlet boundary condition, the portal vein outlet boundary condition, and the preset portal vein vascular wall boundary condition to obtain the portal vein inlet blood flow pressure, including: On a supercomputing platform, the Newton-Krylov-Schwarz algorithm is used to solve the first sparse nonlinear equations according to the portal vein inlet boundary condition, the portal vein outlet boundary condition and the preset portal vein vascular wall boundary condition to obtain the portal vein inlet blood flow pressure.

4. The method for non-invasive measurement of portal vein pressure gradient according to claim 1, characterized in that: Solving the fluid control equation of the hepatic vein according to the inlet boundary condition of the hepatic vein, the outlet boundary condition of the hepatic vein, and the preset vascular wall boundary condition of the hepatic vein to obtain the outlet blood flow pressure of the hepatic vein includes: Numerically discretizing the fluid control equations of the hepatic vein using a finite element method and a backward Euler scheme to obtain a second sparse nonlinear equation group; The Newton-Krylov-Schwarz algorithm is used to solve the second sparse nonlinear equations according to the inlet boundary condition of the hepatic vein, the outlet boundary condition of the hepatic vein, and the preset vascular wall boundary condition of the hepatic vein to obtain the outlet blood flow pressure of the hepatic vein.

5. The method for non-invasive measurement of portal vein pressure gradient according to claim 4, characterized in that: The Newton-Krylov-Schwarz algorithm is used to solve the second sparse nonlinear equations according to the inlet boundary condition of the hepatic vein, the outlet boundary condition of the hepatic vein, and the preset vascular wall boundary condition of the hepatic vein to obtain the outlet blood flow pressure of the hepatic vein, including: On a supercomputing platform, the Newton-Krylov-Schwarz algorithm is used to solve the second sparse nonlinear equations according to the inlet boundary condition of the hepatic vein, the outlet boundary condition of the hepatic vein, and the preset vascular wall boundary condition of the hepatic vein to obtain the outlet blood flow pressure of the hepatic vein.

6. A non-invasive measurement device for portal vein pressure gradient, characterized in that: include: an acquisition module configured to acquire a portal vein and a hepatic vein from an image of the liver to be evaluated; perform geometric repair on the portal vein and the hepatic vein, respectively, and perform smoothing on the portal vein and the hepatic vein, respectively, to obtain a processed portal vein and a processed hepatic vein; perform meshing on the processed portal vein and the processed hepatic vein, respectively, to obtain a three-dimensional model of the portal vein and a three-dimensional model of the hepatic vein; and acquire, based on the image of the liver to be evaluated, a blood flow velocity at an inlet of the portal vein and a blood flow velocity at an outlet of the hepatic vein; a construction module, configured to construct a fluid control equation of the portal vein based on the three-dimensional model of the portal vein, and to construct a fluid control equation of the hepatic vein based on the three-dimensional model of the hepatic vein; a first calculation module, configured to determine an inlet boundary condition of the portal vein based on the inlet blood flow velocity of the portal vein; construct a first Darcy equation based on the three-dimensional model of the portal vein; solve the first Darcy equation to obtain the outlet blood flow pressure of the portal vein; determine the outlet boundary condition of the portal vein based on the outlet blood flow pressure of the portal vein; and solve the fluid control equation of the portal vein based on the inlet boundary condition of the portal vein, the outlet boundary condition of the portal vein, and a preset vascular wall boundary condition of the portal vein to obtain the inlet blood flow pressure of the portal vein; a second calculation module, configured to determine an outlet boundary condition of the hepatic vein according to the outlet blood flow velocity of the hepatic vein; and construct a second Darcy equation according to the three-dimensional model of the hepatic vein; Solving the second Darcy equation to obtain the inlet blood flow velocity of the hepatic vein; determining the inlet boundary condition of the hepatic vein based on the inlet blood flow velocity of the hepatic vein; solving the fluid control equation of the hepatic vein based on the inlet boundary condition of the hepatic vein, the outlet boundary condition of the hepatic vein, and a preset vascular wall boundary condition of the hepatic vein to obtain the outlet blood flow pressure of the hepatic vein; The third calculation module is configured to determine the pressure gradient of the portal vein according to the inlet blood flow pressure of the portal vein and the outlet blood flow pressure of the hepatic vein.

7. An electronic device, characterized in that: The electronic device comprises a processor coupled to a memory, wherein the processor is configured to execute a computer program or instruction stored in the memory, so that the electronic device implements the method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is run on an electronic device, the electronic device is caused to perform the method according to any one of claims 1 to 5.

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