CN112683743B

CN112683743B - Platelet status analysis method, platelet status analysis device, electronic apparatus, and storage medium

Info

Publication number: CN112683743B
Application number: CN202110271263.6A
Authority: CN
Inventors: 高琪; 曾海翔; 刘星利; 魏润杰
Original assignee: Hangzhou Shengshi Technology Co ltd
Current assignee: Hangzhou Shengshi Technology Co ltd
Priority date: 2021-03-12
Filing date: 2021-03-12
Publication date: 2021-06-18
Anticipated expiration: 2041-03-12
Also published as: CN112683743A

Abstract

The application provides a platelet status analysis method, a platelet status analysis device, an electronic apparatus, and a storage medium, wherein the method comprises: obtaining the concentration distribution information of the deposited platelets in the target blood vessel according to a scalar transport equation of at least one component in the target blood vessel and the fluid field information in the target blood vessel; carrying out interpolation processing on the calculation grid of the target blood vessel according to the concentration distribution information to obtain interpolation information of the concentration distribution information on the grid surface of the calculation grid; obtaining the deposition rate information of the deposited platelets according to the interpolation information on the grid surface of the computational grid; and acquiring growth form information of the deposited platelets according to the deposition rate information of the deposited platelets. The platelet status analysis method provided by the application can improve the accuracy of the analysis result of the platelet status.

Description

Platelet status analysis method, platelet status analysis device, electronic apparatus, and storage medium

Technical Field

The embodiment of the application relates to the field of medical monitoring, in particular to a platelet status analysis method, a platelet status analysis device, an electronic device and a computer storage medium.

Background

Platelets (platelets) play an important role in physiological hemostasis, maintaining the integrity of blood vessel walls, and activation of platelets includes platelet adhesion, aggregation, and release. The research shows that the adhesion and aggregation of the platelets on the inner wall of the blood vessel to form platelet deposition are key factors for causing thrombus (thrombosis). In the related art, it is necessary to acquire growth morphology information of deposited platelets in order to analyze the physiological state of the platelets. However, the related art still has the problem of poor accuracy of analysis results.

Disclosure of Invention

The embodiment of the application provides a platelet state analysis method, a platelet state analysis device, an electronic device and a computer storage medium, which can improve the accuracy of an analysis result of a platelet state.

The platelet status analysis method provided by the embodiment of the application comprises the following steps:

acquiring concentration distribution information of deposited platelets in a target blood vessel according to a scalar transport equation of at least one component in the target blood vessel and fluid field information in the target blood vessel;

carrying out interpolation processing on the calculation grid of the target blood vessel according to the concentration distribution information to obtain interpolation information of the concentration distribution information on a grid surface of the calculation grid;

obtaining the deposition rate information of the deposited platelets according to the interpolation information on the grid surface of the computational grid and the normal vector information of the grid surface of the computational grid;

and acquiring growth form information of the deposited platelets according to the deposition rate information of the deposited platelets.

In one implementation, the grid type of the computing grid includes any one of the following grid types: structured grid, unstructured grid, hybrid grid.

In one implementation, the at least one component includes von willebrand factor.

In one implementation, the at least one component further comprises a component other than the von willebrand factor; the obtaining of the concentration distribution information of the deposited platelets in the target vessel according to the scalar transport equation of at least one component in the target vessel and the fluid field information in the target vessel comprises:

according to the fluid field information in the target blood vessel, sequentially solving scalar transport equations of the at least one component according to a preset sequence to obtain deposition rate information of the deposited platelets in the target blood vessel;

the preset order represents the order of solving the scalar transport equation of the von willebrand factor and then solving the scalar transport equations of the other components;

and acquiring the concentration distribution information of the deposited platelets in the target blood vessel according to the deposition rate information and the reaction time.

In one implementation, prior to the obtaining concentration distribution information of platelets deposited in the target vessel, the method further comprises:

determining reaction parameter information for a biochemical reaction associated with the von willebrand factor;

and acquiring a scalar transport equation of the von willebrand factor according to the reaction parameter information.

In one implementation, the at least one component includes the inhibitor of platelet activation; before the obtaining of the information on the concentration distribution of the platelets deposited in the target blood vessel, the method further comprises:

acquiring the deposition intensity information of the platelets, wherein the deposition intensity information of the platelets represents the ratio of the concentration value of the deposited platelets acquired last time to a preset reference value;

and obtaining a scalar transport equation of the platelet activation inhibitor according to the deposition intensity information of the platelets.

The platelet status analysis device provided in the embodiment of the present application includes:

the acquisition module is used for acquiring the concentration distribution information of the deposited platelets in the target blood vessel according to a scalar transport equation of at least one component in the target blood vessel and the fluid field information in the target blood vessel;

the analysis module is used for carrying out interpolation processing on the calculation grid of the target blood vessel according to the concentration distribution information to obtain interpolation information on the grid surface of the calculation grid;

the processing module is used for acquiring the deposition rate information of the platelet deposition according to the interpolation information on the grid surface of the computational grid and the normal vector information of the grid surface of the computational grid; and acquiring growth form information of the deposited platelets according to the deposition rate information of the deposited platelets.

In one implementation, the at least one component further comprises a component other than the von willebrand factor; the obtaining module is used for obtaining the concentration distribution information of the deposited platelets in the target blood vessel according to the scalar transport equation of at least one component in the target blood vessel and the fluid field information in the target blood vessel, and comprises:

according to the fluid field information in the target blood vessel, sequentially solving scalar transport equations of the at least one component according to a preset sequence to obtain deposition rate information of the deposited platelets in the target blood vessel; the preset order represents the order of solving the scalar transport equation of the von willebrand factor and then solving the scalar transport equations of the other components;

In one implementation, before the obtaining concentration distribution information of the deposited platelets in the target vessel, the obtaining module is further configured to:

In one implementation, the at least one component includes the inhibitor of platelet activation; before the acquiring concentration distribution information of the deposited platelets in the target blood vessel, the acquiring module is further configured to:

The embodiment of the present application provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the program, the platelet status analysis method provided by one or more of the foregoing technical solutions is implemented.

The embodiment of the application provides a computer storage medium, wherein a computer program is stored in the computer storage medium; the computer program can be executed to implement the platelet status analysis method provided by one or more of the above technical solutions.

Based on the platelet state analysis method provided by the application, the concentration distribution information of the deposited platelets in the target blood vessel is obtained according to a scalar transport equation of at least one component in the target blood vessel and the fluid field information in the target blood vessel; then, interpolation processing is carried out on the calculation grid of the target blood vessel according to the concentration distribution information, so that interpolation information on the grid surface of the calculation grid corresponding to the concentration distribution information can be obtained, and therefore, the deposition rate information of the deposited platelets is obtained according to the interpolation information on the grid surface of the calculation grid and the normal vector information of the grid surface of the calculation grid; and acquiring growth form information of the deposited platelets according to the deposition rate information of the deposited platelets. Therefore, the accuracy of the analysis result of the platelet status is improved.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.

Drawings

Fig. 1 is a schematic diagram of a platelet status analysis method provided in an embodiment of the present application;

FIG. 2 is a schematic illustration of a platelet deposition state provided in an embodiment of the present application;

FIG. 3 is a schematic diagram of another platelet status analysis method provided in an embodiment of the present application;

FIG. 4 is a schematic diagram of a three-dimensional structure of a target blood vessel according to an embodiment of the present application;

FIG. 5 is a schematic diagram of another platelet status analysis method provided in an embodiment of the present application;

FIG. 6 is a schematic illustration of another platelet deposition state provided by an embodiment of the present application;

fig. 7 is a schematic view of a platelet status analysis device according to an embodiment of the present application;

fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

The present application will be described in further detail below with reference to the accompanying drawings and examples. It should be understood that the examples provided herein are merely illustrative of the present application and are not intended to limit the present application. In addition, the following examples are provided as partial examples for implementing the present application, not all examples for implementing the present application, and the technical solutions described in the examples of the present application may be implemented in any combination without conflict.

Currently, in order to analyze the state of platelets, a coagulation test method and a fluid mechanics calculation method are mainly used. The blood coagulation test method is a detection test method of a blood coagulation function primary screen which is commonly used clinically, and is used for primary diagnosis of blood coagulation disorder diseases, monitoring of anticoagulant drugs and analysis of routine blood coagulation functions before operation. However, the blood coagulation test method centrifugally removes cellular components such as platelets and erythrocytes, resulting in inaccurate platelet status monitoring results. The current fluid mechanics calculation method only considers the activation effect of shear stress (shear stress) on blood platelets, neglects the involved biochemical reaction process of blood coagulation process inside blood, and causes larger error of calculation result.

Hereinafter, the platelet status analysis method according to the present application will be described in detail with respect to the problem of the related art that the accuracy of the result of the platelet status analysis is low.

Example one

Referring to fig. 1, the present application provides a platelet status analysis method, which may include the following steps:

step A101: and acquiring the concentration distribution information of the deposited platelets in the target blood vessel according to the scalar transport equation of at least one component in the target blood vessel and the fluid field information in the target blood vessel.

Here, the concentration distribution information of deposited platelets may include concentration values of deposited platelets within a calculation grid of the target blood vessel and spatial coordinate information of the calculation grid.

Illustratively, the fluid field information of the target vessel may include: velocity field information of the target vessel, pressure field information of the target vessel, and stress field information. Wherein, the velocity field information may include blood flow velocity information in a computational grid of the target blood vessel and spatial coordinate information of the computational grid; the pressure field information may comprise pressure information in a computational grid of the target vessel and spatial coordinate information of the computational grid. The stress field information may include shear stress versus shear rate of platelet deposition information.

It should be understood that the computational grid is a basic computational unit in a computational space, the computational fluid dynamics method disperses the computational space through the computational grid, iteratively solves a differential equation set formed by a Navier-Stokes equation and at least one component scalar transport equation, obtains flow field variables of a specified space and a specified time, and integrates to obtain the overall flow characteristic of the object bypassing. Blood in a blood vessel belongs to incompressible fluid, and the fluid generates remarkable wall shear stress at the blood vessel wall, and the wall shear stress promotes von willebrand factor to be attached to the inner wall of the blood vessel, so that the adhesion and aggregation of platelets on the inner wall of the blood vessel are influenced to form platelet deposition.

Illustratively, gridding software can be used to spatially disperse the three-dimensional structure information of the target blood vessel, so as to obtain a computational grid corresponding to the target blood vessel.

Illustratively, referring to table 1, the composition in the target vessel may include at least one of the following components: reactants, products, platelet-activation intermediates and platelet-activation inhibitors. Wherein the reactants may comprise at least one of the following components: von willebrand factor, unactivated platelets, activated platelets, the product being deposited platelets, and may include at least one of deposited unactivated platelets, deposited activated platelets, deposited immobilized platelets. Platelet-activating intermediates may include, thromboxane, adenosine diphosphate, prothrombin, thrombin. The platelet activation inhibitor may include antithrombin.

TABLE 1 compositional information of fluid in target vessel

In the context of table 1, the following,C _vWF 、C _RP 、C _AP、 C _TxA2 、C _ADP、 C _PT 、C _Ts 、C _RPd 、C _APd 、C _Aps 、C _ATrespectively showing the component concentration information corresponding to the components vWF, RP, AP, TxA2, ADP, PT, Ts, RPd, APd, APs and AT. Here, the component concentration information may be component concentration information at an initial time or component concentration information at a certain time of a calculation process. For example, the component concentration information at the initial time of the time step Δ t.

For example, when acquiring the velocity field information in the target blood vessel, 4D Flow Magnetic Resonance Imaging (MRI) may be used to perform a Magnetic Resonance scan on the target blood vessel, so as to acquire fluid data in the target blood vessel in multiple directions, and obtain a Magnetic Resonance image and spatial phase information of the target blood vessel. Three mutually perpendicular dimensions (x, y, z) are phase encoded and velocity field information of the target vessel is recorded. The velocity field information may reflect a vector distribution of blood flow velocities in the target vessel. Here, 4D flow magnetic resonance imaging is a technique of acquiring a magnetic resonance image of a fluid in three-dimensional space with time.

For example, the pressure poisson equation of the target blood vessel may be solved according to the velocity field information of the target blood vessel, so as to obtain pressure field information and stress field information in the target blood vessel, where the stress field information includes shear rate information of platelets deposited in the target blood vessel.

Further, the information of the concentration distribution of the deposited platelets in the target blood vessel is obtained according to the scalar transport equation of each reactant in the target blood vessel and the information of the fluid field in the target blood vessel. Here, the fluid field information in the target blood vessel may include a blood flow rate U, a shear rate of deposited platelets.

Illustratively, a scalar transport equation for each reactant in the target vessel may be solved based on the fluid field information in the target vessel to obtain concentration distribution information of the deposited platelets within the computational grid of the target vessel.

Illustratively, for a product in a target vessel, the scalar transport equation may take the form:

（1）

wherein,ρdenotes the blood density,. phi. denotes the product,. omega_φRepresenting the corresponding chemical reaction term of the product phi in a scalar transport equation.

Illustratively, for a reactant, platelet-activation intermediate, platelet-activation inhibitor in a target vessel, the scalar transport equation may take the form:

（2）

wherein,ρdenotes the blood density, # denotes any of the reactant, the platelet-activation intermediate, and the platelet-activation inhibitor, U denotes the blood flow rate, D denotes the diffusion coefficient for the reactant, # denotes ω_ψRepresenting the corresponding chemical reaction term in the scalar transport equation.

It will be appreciated that there are a number of different types of component psi involved in biochemical reactions in the target vessel, the different components psi corresponding to different chemical reaction terms ω in the scalar transport equation_ψ。

Chemical reaction term omega_ψThe value of (A) is influenced by a reaction coefficient, which may include femb, vol, kpdf, etc., wherein the reaction coefficient femb is used for characterizing the shear rate of platelet deposition, vol is used for characterizing the deposition intensity information of platelets (0 ≦ vol ≦ 1), kpdf is used for characterizing the deposition rate of platelets。

Step A102: and carrying out interpolation processing on the calculation grid of the target blood vessel according to the concentration distribution information to obtain interpolation information of the concentration distribution information on the grid surface of the calculation grid.

Here, the concentration distribution information is associated with the calculation mesh of the target blood vesselM _iAnd concentration information of platelets deposited on the computational grid of the target vesselC _iWhereinM _iidentification information for an ith computational mesh of the plurality of computational meshes for the target vessel,C _iand (4) calculating the concentration information of the corresponding deposited platelet of the ith calculation grid of the target blood vessel.

Illustratively, the concentration information of the deposited platelets and the maximum deposited concentration of platelets per unit volume corresponding to the ith calculation grid based on the target blood vessel (ii) ((ii))PLT _max) Information on the intensity of platelet deposition in the ith calculation grid is obtained.

Here, the sedimentation intensity information (vol) of platelets in the ith calculation grid may take the form:

（3）

wherein, C_RPd、C_APd、C_APsThe concentration information of the non-activated platelet RPd deposited, the activated platelet APd deposited and the solidified platelet APs deposited in the calculation grid are respectively corresponded.

It should be understood that in the ith calculation grid, the platelet sedimentation strength information vol plays an important role in platelet diffusion and aggregation. Concentration information of deposited platelets when the ith calculation grid isC _i= PLT _maxVol =1, and the concentration of deposited platelets reaches the maximum concentration of deposited platelets per unit volume in the ith calculation grid. In this case, the concentration of deposited platelets within the ith computational grid is saturated.

Furthermore, according to the deposition intensity information vol of the thrombocytes in the ith calculation grid, interpolation processing is carried out on the ith calculation grid of the target blood vessel, and interpolation information volref of the concentration distribution information of the deposited thrombocytes on the grid surface of the ith calculation grid is obtained.

Step A103: and acquiring the deposition rate information of the deposited platelets according to the interpolation information on the grid surface of the calculation grid and the normal vector information of the grid surface of the calculation grid.

Here, the deposition rate information of the deposited platelets may be first deposition rate information used for calculating growth morphology information of the deposited platelets.

Illustratively, the platelet deposition rate kpdf can be calculated according to the interpolation information volref of the concentration distribution information of the deposited platelets on the grid plane of the ith calculation grid and the normal vector fn of the grid plane of the ith calculation grid. Here, the deposition rate of platelets, kpdf, may take the form:

(4)

in practical applications, the following approximation method can be used to approximate the platelet deposition rate

When kpdf = 0; in that

When kpdf = 1000000.

(5)

And A104, acquiring growth form information of the deposited platelets according to the deposition rate information of the deposited platelets.

Here, the growth morphology information of the deposited platelets may include information of a chemical reaction surface forming the deposited platelets.

It is understood that the deposited platelet concentration distribution information and the deposited platelet growth morphology information are different in that the deposited platelet concentration distribution information includes a concentration value of deposited platelets in a calculation grid of a target blood vessel and spatial coordinate information of the calculation grid, and information of a chemical reaction surface forming the deposited platelets cannot be directly obtained based on the concentration distribution information.

Illustratively, based on the visualization process of the growth morphology information of the deposited platelets, the information of the chemical reaction surface forming the deposited platelets, which may be understood as the growth surface of the deposited platelets, may be presented in a visualized manner.

Illustratively, growth morphology information of the deposited platelets may be used to determine pathological characteristic information of the deposited platelets in the target vessel, e.g., associated pathological characteristic information of thrombus formation within the target vessel.

Illustratively, according to the deposition rate information and the reaction time of the deposited platelets in the target blood vessel, the growth morphology information of the deposited platelets at any time corresponding to the reaction time is acquired. Here, the reaction time may be a complete reaction period, or one time step Δ t among a plurality of time steps obtained by dividing the complete reaction period, or an accumulated time of the plurality of time steps.

For example, from the information of the deposition rate of the deposited platelets, the net increment of the deposition concentration of the deposited platelets in the calculation grid within each time step Δ t is obtained. And accumulating the net increment of the concentration information of the deposited platelets in the target blood vessel along with the time change delta t to obtain the total deposited value of the deposited platelets in the calculation grid of the target blood vessel.

Further, according to the total deposition value of the deposited platelets in the calculation grid of the target blood vessel and the space coordinate information of the calculation grid, the growth form information of the deposited platelets in the target blood vessel is obtained. As shown in fig. 2, in the circular channel corresponding to the target blood vessel, the first characteristic region 201 is used for characterizing the growth morphology information of the deposited platelets.

In the present example, the process of platelet deposition per time step is approximated as a steady state process where the deposition rate information of the product in the target vessel is kept constant at all times. Therefore, the net increment of the deposition concentration of the deposited platelets in the calculation grid in each time step can be obtained according to the information of the product of the deposition rate of the deposited platelets and the time step.

In practical applications, the steps a101 to a104 may be implemented by a Processor, and the Processor may be at least one of an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a Central Processing Unit (CPU), a controller, a microcontroller, and a microprocessor.

Based on the platelet state analysis method provided by the embodiment of the application, the concentration distribution information of the deposited platelets in the target blood vessel is obtained according to the scalar transport equation of at least one component in the target blood vessel and the fluid field information in the target blood vessel; then, interpolation processing is carried out on the calculation grid of the target blood vessel according to the concentration distribution information, so that interpolation information on the grid surface of the calculation grid corresponding to the concentration distribution information can be obtained, and therefore, the deposition rate information of the deposited platelets is obtained according to the interpolation information on the grid surface of the calculation grid and the normal vector information of the grid surface of the calculation grid; and acquiring growth form information of the deposited platelets according to the deposition rate information of the deposited platelets. Therefore, the accuracy of the analysis result of the platelet status is improved.

In one implementation, the interpolation information may be fitted to an inequality relationship based on interpolation information volref of concentration distribution information of deposited platelets on the grid plane of the ith calculation grid "x≤volref≤1，x∈[0,1]"the calculation grid is determined as a target calculation grid, and the grid is calculated according to the targetAnd (3) calculating information of space communication areas formed by a plurality of grids in the grid to acquire growth form information of the deposited platelets.

In the practical application of the method, the material is,xthe value of (b) can be flexibly set, for example,xand =0.6, determining a calculation grid in which the interpolation information satisfies an inequality relationship of "0.6 < volref ≦ 1" as a target calculation grid, and representing growth morphology information of the deposited platelets according to information of a spatially connected region formed by a plurality of calculation grids in the target calculation grid.

Here, the growth morphology information of the deposited platelets may be information of the growth trend surface of the deposited platelets.

It should be understood that the interpolation information volref indirectly represents the deposition intensity values of the platelets in the calculation grid, and for the calculation grid in which the interpolation information conforms to "volref 0.6" or more, the concentration of the deposited platelets in the calculation grid is much less than the maximum deposition concentration of the platelets per unit volumePLT _maxTherefore, the probability of the deposited platelets within a computational grid growing diffusively to an adjacent computational grid is low. For the calculation grid with interpolation information conforming to 'volref is more than 0.6 and less than or equal to 1', the concentration of the deposited platelets in the calculation grid gradually approaches the maximum concentration of the deposited platelets in the unit volumePLT _maxTherefore, the probability of a deposited platelet within a computational grid spreading to an adjacent computational grid is high.

In practical application, based onxThe calculation grids corresponding to the target blood vessel may be divided into a first type grid and a second type grid, wherein interpolation information of the first type grid is coincident "0≤volref≤x", the interpolation information of the second type of mesh is coincident"x＜volref≤1，x∈[0,1]”。

Exemplarily, will conform to "x＜volref≤1，x∈[0,1]"the grid surface corresponding to the space communication area formed by the second type grid is characterized as the growth trend surface of the deposited platelet in the target blood vessel.

Here, the growth trend surface may be understood as a chemical reaction surface that grows out-diffusion after the concentration of deposited platelets within the current computational grid reaches saturation.

Illustratively, the information characterizing the growth trend surface of the deposited platelets is based on interpolation information volref of the concentration distribution information of the deposited platelets on the grid plane of the i-th computation grid. According to the information of the growth trend surface of the deposited platelet, iterative calculation is carried out on the growth form information of the deposited platelet by combining a computational fluid mechanics method, and the growth form information of the deposited platelet at different moments in a certain time can be obtained.

In one implementation, the fluid field information in the target vessel may be obtained according to the model information of the target vessel, and referring to fig. 3, the method may include the following steps:

step A301: model information of the target blood vessel is acquired, and the model information comprises three-dimensional structure information of the target blood vessel, boundary condition information of a fluid field in the target blood vessel and component concentration information in the target blood vessel in platelet activation and deposition processes.

It is understood that the state of platelets is influenced by biochemical reactions between various components in the blood. The factors influencing biochemical reactions include the following: three-dimensional structural information of the target vessel, boundary condition information of a fluid field in the target vessel, and component concentration information in the target vessel during platelet activation and deposition.

Illustratively, as shown in fig. 4, the three-dimensional structural information of the target blood vessel is a circular pipe including an inlet 401, an outlet 402, and a wall 403. The length of the circular pipeline is 5mm, and the diameter of the circular pipeline is 0.9 mm. The inner wall of the circular canal presents a circular marking area 404, the diameter of the marking area 404 being 0.03mm, which is used to characterize the wound site inside the blood vessel.

It is understood that a wound site inside a blood vessel is susceptible to platelet aggregation, thereby forming a platelet precipitate. The wound site inside the blood vessel corresponds to the deposition site of the platelets on the inner wall of the circular duct.

For example, when acquiring the three-dimensional structure information of the target blood vessel, a computed tomography angiography method or a nuclear magnetic resonance method may be used to acquire medical image data related to the target blood vessel, and based on the medical image data related to the target blood vessel, three-dimensional space point cloud information of the target blood vessel may be acquired, and a poisson surface reconstruction algorithm may be used to acquire the three-dimensional structure information of the smooth and closed target blood vessel. Or reading the medical model description language, calling the three-dimensional structure model of the blood vessel, and setting parameters of the three-dimensional structure model of the blood vessel to obtain the three-dimensional structure information of the target blood vessel.

In the embodiment of the present application, the inner wall of the circular pipeline adopts the non-slip boundary condition information, and at this time, the initial value of the fluid field of the circular pipeline may be consistent with the fluid field of the inlet of the circular pipeline. Here, the no-slip condition means that there is no relative slip between the fluid and the solid wall, and the flow velocity of the fluid is zero near the wall surface of the pipe.

For example, the mesh division software may be used to perform mesh division on the three-dimensional structure of the target blood vessel, perform spatial discretization on the three-dimensional structure information of the target blood vessel to obtain a computational mesh corresponding to the target blood vessel, and import the computational mesh corresponding to the target blood vessel into a computing system for analyzing the platelet status.

Here, the mesh type of the computation mesh may employ any one of the following mesh types: structured grid, unstructured grid, hybrid grid. The structural grid can accurately simulate the boundary layer flow, and the non-structural grid has better structural adaptability to complex structures. In the hybrid mesh, a structured mesh is adopted for a simple symmetric structure, and an unstructured mesh is adopted for an asymmetric structure with a complex structure.

In the embodiment of the application, the analysis method of the platelet state is optimized, the dependency on the computational grid structure is eliminated, and the computational domain can be discretized into a structured grid or an unstructured grid.

Illustratively, the boundary condition information of the fluid field in the target vessel includes: blood flow rate 0.02m/s, pressure information 0 Pa. Here, the blood flow rate may be a blood flow rate of the circular tube inlet, and the pressure information may be pressure information of the circular tube outlet.

Illustratively, referring to Table 2, for a fluid in a target vessel, the component concentrations of the fluidThe information may include: vWF concentration 1.88E+05nmolm ^-3RP concentration 3.0E+14(PLTm ^-3)PLTm ^-3AP concentration 3.0E+12(PLTm ^-3)PLTm ^-3PT concentration 1.1E+06 nmolm ^-3AT concentration 2.844E+06 nmolm ^-3。

TABLE 2 component concentration information of reactants in target blood vessels

Step A302: and solving a momentum equation of the target blood vessel according to the model information to obtain the velocity field information of the target blood vessel, wherein the velocity field information comprises blood flow velocity information and shear rate information of the deposited platelets.

Here, the momentum equation of the target blood vessel may take the following form:

（5）

wherein,volinformation on the intensity of platelet deposition, ρ is the blood density,Urepresenting the blood flow rate, t representing time, ∇_PIndicating the gradient of pressure, ∇_τRepresenting the divergence of the shear stress in the fluid field, g representing the acceleration of gravity,Findicating the resistance to blood impact with the deposited platelets.

Illustratively, the shear rate of the deposited platelets in the flow field is calculated from the velocity field information of the target vessel.

Here, the shear rate of platelet deposition may take the form:

（6）

where a1 and a2 are coefficients, mag represents a modulus operation, and τ represents shear stress in the fluid field.

Step A303: and solving a pressure Poisson equation of the target blood vessel according to the velocity field information of the target blood vessel to obtain pressure field information in the target blood vessel.

Here, the pressure poisson equation for the target vessel may take the form:

（7）

where HbyA represents the off-diagonal elements of the equation coefficient matrix divided by the main diagonal elements, A_diagA main diagonal element representing a coefficient matrix +_pRepresenting the gradient of pressure.

step B1: and sequentially solving scalar transport equations of the at least one component according to a preset sequence according to the fluid field information in the target blood vessel to obtain the deposition rate information of the deposited platelets in the target blood vessel.

Here, the deposition rate information of the deposited platelets may be second deposition rate information used for calculating concentration distribution information of the deposited platelets. The preset order represents the order of solving the scalar transport equation of the remaining components in turn, based on solving the scalar transport equation of von willebrand factor.

It should be understood that the first deposition rate information and the second deposition rate information are different in the effect of the first deposition rate information and the second deposition rate information, and the first deposition rate information is used for calculating growth morphology information of deposited platelets, reflecting the deposition rate value of a chemical reaction surface forming the deposited platelets and spatial coordinate information of the chemical reaction surface. The second deposition rate information is used for calculating to obtain concentration distribution information of the deposited platelets, and reflecting the deposition rate value of the deposited platelets in the calculation grid of the target blood vessel and the space coordinate information of the calculation grid.

For example, the preset order may be: vWF → RP → AP → RPd → APd → APs → ADP → TxA2 → PT → Ts → AT.

Step B2: and acquiring the concentration distribution information of the deposited platelets at any time in the reaction time according to the deposition rate information and the reaction time.

Here, as for the implementation process of step B2, reference may be made to step a101 above, which is not described herein again.

step C1: reaction parameter information for a biochemical reaction associated with von willebrand factor is determined.

Here, see Table 1, the chemical reaction terms ω associated with von Willebrand factor_ψ=kτ∙H(τ-τ_C)∙C_vWFWherein the reaction coefficient k τ =0.05,

，τ_C=15。

step C2: and obtaining a scalar transport equation of the von willebrand factor according to the reaction parameter information.

Here, based on the reaction parameter information for determining the biochemical reaction associated with von Willebrand factor, the chemical reaction term ω associated with von Willebrand factor can be obtained_ψ=kτ∙H(τ-τ_C)∙C_vWFFurther, will ω_ψ=kτ∙H(τ-τ_C)∙C_vWFSubstituting into equation (2) above, a scalar transport equation for von willebrand factor is obtained, as follows:

（8）

in the embodiment of the present application, the platelet status analysis method takes into consideration the promotion effect of hemophilia factors on platelet activation under high shear stress, and introduces new reaction components and reaction parameters, thereby improving the accuracy of the platelet status analysis result.

In one implementation, the at least one component includes the inhibitor of platelet activation; before the acquiring the information of the concentration distribution of the deposited platelets in the target blood vessel, the method may further include the steps of:

step D1: and acquiring the deposition intensity information of the platelets, wherein the deposition intensity information of the platelets represents the ratio of the concentration value of the deposited platelets acquired last time to a preset reference value.

Here, the concentration value of the deposited platelets obtained last time may be concentration information of the deposited platelets corresponding to the ith calculation grid of the target blood vessel, and the preset reference value may be a maximum deposited concentration of platelets per unit volume ((maximum deposited concentration of platelets per unit volume) ((ii)PLT _max). Regarding the implementation process of step D1, reference may be made to step a102 above, which is not described herein again.

It should be understood that each time step Δ t corresponds to the concentration information of the deposited platelets corresponding to the ith calculation grid of one target blood vessel, and in practical applications, the concentration information of the deposited platelets corresponding to the ith calculation grid of the target blood vessel may be iteratively calculated within each time step Δ t. The concentration value of the deposited platelet obtained last time can be understood as the concentration information of the deposited platelet corresponding to the ith calculation grid of the target blood vessel corresponding to the last time step Δ t.

Step D2: and obtaining a scalar transport equation of the platelet activation inhibitor according to the deposition intensity information of the platelets.

Here, referring to Table 1, the chemical reaction term ω of the platelet activation inhibitor_ψ= tao ∙ epslin ∙ Ts, wherein the reaction coefficient epslin = 0.00911.

Here, based on the reaction parameter information for determining the biochemical reaction associated with the platelet activation inhibitor, the chemical reaction term ω associated with von Willebrand factor can be obtained_ψ=-tao∙epslion∙Ts, and further, ω_ψSubstitution of = tao ∙ epslion ∙ Ts into equation (2) above yields the scalar transport equation for von willebrand factor as follows:

（9）

in the embodiment of the application, in consideration of the distribution characteristics of the platelet activation inhibitor, a scalar transport equation of a new platelet activation inhibitor is constructed according to the platelet deposition fraction, so that the stability of the computational fluid dynamics method is improved, and accordingly, the accuracy of the analysis result of the platelet state is improved.

Based on the same technical concept as the previous embodiment, referring to fig. 5, the platelet status analysis method provided in the embodiment of the present application may include the following steps:

step A501: and obtaining model information of the blood pump, wherein the model information comprises three-dimensional structure information of the blood pump, boundary condition information of a fluid field in the blood pump and component concentration information in the blood pump in platelet activation and deposition processes.

Here, the platelet status analysis method provided in the embodiment of the present application is described in detail with reference to a blood pump as an analysis object, and in practical applications, the analysis object may be a target blood vessel, a target organ, or a biological implantation device similar to a blood pump, and the target blood vessel may be a partial blood vessel tissue in a biological organ or a complete blood vessel tissue, which is not limited in the embodiment of the present application.

Illustratively, fluid fields in the blood pump are simulated by using fluid mechanics calculation software, and in the simulation, the time step Δ T is set to 100ns, and the preset time value T is set to 90 s. The preset time value corresponds to a complete reaction period. Here, the process of platelet deposition is approximately treated as a steady state process in each time step Δ t time.

Step A502: and solving a momentum equation of the blood pump according to the model information of the blood pump to obtain the fluid field information of the blood pump.

Step A503: and sequentially calculating a scalar transport equation of each reactant in the blood pump according to a preset solving sequence according to the fluid field information in the blood pump to obtain the deposition rate information of the deposited platelets.

Step A504: and obtaining the net increment of the deposition concentration of the deposited platelets in the calculation grid in each time step according to the product information of the deposition rate information of the deposited platelets and the time step.

Illustratively, within a time step Δ t, sequentially solving scalar transport equations of each component according to a preset sequence to obtain the deposition rate information of the deposited platelets in the blood pump; and repeatedly executing the steps in the next time step based on a preset solving strategy, thereby obtaining the concentration distribution information of the deposited platelets.

Step A505: and judging whether the calculation result meets a preset calculation strategy or not.

Illustratively, in the solution strategy of the computing system, the termination time of the simulation calculation is set, and whether to repeatedly execute the steps a501 to a504 is determined according to the judgment result of whether the calculation time of the simulation calculation reaches the termination time. And stopping the calculation if the calculation time of the simulation calculation reaches the termination time. Otherwise, the above steps a501 to a504 are repeatedly performed.

For example, in the solution strategy of the computing system, whether the computing time reaches the preset time value 90s is judged, and the computing is stopped when the computing time reaches the preset time value 90 s. Otherwise, the above steps are repeatedly executed.

Illustratively, in the solution strategy of the computing system, the time step Δ t at the beginning of each cycle is automatically adjusted by a preset courant number. For example, the preset coulomb number may be set to 10.

Step A506: and accumulating the net value of the concentration information of the deposited platelets in the blood pump along with the change of time to obtain the growth form information of the deposited platelets.

Here, regarding the implementation process of step a501 to step a506, refer to step a301 to step a303, which are not described herein again.

Example two

The platelet status analysis method provided by the embodiment of the present application will be described below based on the same technical concept as the previous embodiment, in conjunction with the problem of platelet deposition caused by trauma inside the blood vessel.

(1) Acquiring three-dimensional structural information of the cardiovascular system, boundary condition information of a fluid field in the cardiovascular system and component concentration information of fluid in the cardiovascular system.

Here, the cardiovascular three-dimensional structure information represents a circular channel, and as shown in fig. 4, the cardiovascular three-dimensional structure information represents a circular channel including an inlet 401, an outlet 402, and a wall 403. The length of the circular pipeline is 5mm, and the diameter of the circular pipeline is 0.9 mm.

Illustratively, the boundary condition information of the fluid field in the cardiovascular system includes: blood flow rate 0.02m/s, pressure information 0 Pa. Here, the blood flow rate may be a blood flow rate of the circular tube inlet, and the pressure information may be pressure information of the circular tube outlet.

For example, referring to table 2, for a fluid in the cardiovascular, the component concentration information of the fluid may include: vWF concentration 1.88E+05nmolm ^-3RP concentration 3.0E+14PLTm ^-3AP concentration 3.0E+12 PLTm ^-3PT concentration 1.1E+06 nmolm ^-3AT concentration 2.844E+06 nmolm ^-3。

(2) And carrying out space dispersion on the three-dimensional structure information of the cardiovascular by adopting grid processing software.

(3) And solving a cardiovascular momentum equation according to the boundary condition information of the fluid field and the component concentration information of the reactant to obtain cardiovascular velocity field information. Here, the velocity field information includes blood flow velocity information.

Illustratively, to ensure that the residuals of the cardiovascular momentum equations fall below 0.00001, the solution strategy of the computing system may be configured to perform multiple iterations of the calculations during the calculation of the momentum equations. For example, the number of iterative calculations of the momentum equation may be set to 7 within the same time step.

(4) And solving a pressure Poisson equation according to the cardiovascular speed field information to obtain the cardiovascular pressure field information and stress field information.

Here, the stress field information includes shear rate information of deposited platelets.

Illustratively, to ensure that the residual error of the pressure poisson equation falls below 0.00001, the solution strategy of the computing system may be configured to perform a plurality of internal iteration calculations during the calculation of the pressure poisson equation. For example, the number of inner iteration calculations of the pressure poisson equation may be set to 14 within the same time step.

(5) And sequentially solving scalar transport equations of the 11 components participating in the reaction in the processes of platelet activation and deposition to obtain the deposition rate information of the deposited platelets in the computational grid of the cardiovascular system.

Here, the information of the chemical reaction items of the 11 components participating in the reaction is shown in table 3, or table 4. In table 3, chemical reaction terms of the respective components of the non-characteristic wall surface of the target blood vessel are shown, and in table 4, chemical reaction terms of the respective components of the characteristic wall surface of the target blood vessel are shown. femb and fembb represent the shear rates of the deposited platelets corresponding to the non-characteristic wall surface and the characteristic wall surface, respectively.

Here, the characteristic wall surface and the non-characteristic wall surface together form a wall surface of the target blood vessel, wherein the characteristic wall surface may be a wall surface corresponding to a wound position inside the blood vessel. The wound site inside the blood vessel corresponds to the deposition site of the platelets on the inner wall of the circular duct. Such as the marked area 404 in fig. 4.

It is understood that the wall surface corresponding to the wound site inside the blood vessel tends to secrete a large amount of von willebrand factor, and platelet aggregation occurs in the characteristic wall surface, thereby forming a platelet precipitate.

In the embodiment of the application, the wall surface of the target blood vessel is divided into a non-characteristic wall surface and a characteristic wall surface, different calculation parameters are adopted for the non-characteristic wall surface and the characteristic wall surface, the characteristic wall surface can be a wall surface corresponding to a wound position in the blood vessel, and the important function of von willebrand factor on the characteristic wall surface on the deposited platelets is considered, so that the growth form information of the deposited platelets in the target blood vessel can be accurately obtained.

TABLE 3 chemical reaction terms of various components of the non-characteristic wall surface of the target blood vessel

TABLE 4 chemical reaction terms of various components of the characteristic wall of the target vessel

Illustratively, in the model information of the cardiovascular vessel, name information of the boundary mesh corresponding to the feature wall is read, and identification information of the feature wall of the cardiovascular vessel is extracted based on the keyword. And acquiring the information of all computational grids contained in the characteristic wall surface according to the identification information of the characteristic wall surface.

Further, based on the information of all computational grids contained in the characteristic wall, the generation or consumption rate of the 11 components is sequentially solved.

(6) And acquiring the concentration distribution information of the deposited platelets according to the deposition rate information of the deposited platelets in the computational grid of the cardiovascular system.

Illustratively, the deposition rate information for three products in the cardiovascular system (RPd, APd, APs) is multiplied by the time step Δ t to obtain the net increase in the deposition concentration of the product at the "feature wall" for each time step.

Further, the net added values of the platelet sedimentation concentration in the calculation grids contained in the feature wall surfaces in different time steps are accumulated to obtain the total platelet sedimentation value in the calculation grids contained in the feature wall surfaces. And acquiring the concentration distribution information of the deposited platelets in the calculation grids contained in the characteristic wall surface according to the total deposition value of the platelets in the calculation grids contained in the characteristic wall surface.

(7) And acquiring growth form information of the deposited platelets through interpolation information of the concentration distribution information of the deposited platelets on the grid surface of the calculation grid.

EXAMPLE III

The platelet status analysis method provided by the embodiment of the present application is described below based on the same technical concept as the previous embodiment, in combination with the problem of platelet deposition on the inner wall of the blood pump conduit.

(1) And acquiring three-dimensional structure information of the blood pump, boundary condition information of a fluid field in the target blood vessel and component concentration information of fluid in the target blood vessel. The three-dimensional structure information of the blood pump mainly comprises an inlet, an outlet, an inner wall and a pump body. In consideration of the turbulent effect during the rotation of the blood pump, the operating rotation speed of the blood pump may be set to 25000rpm during the platelet status analysis.

For example, referring to table 3, for a fluid operating in a blood pump, the component concentration information for the fluid may include: vWF concentration 1.88E +05(nmolm ^-3) RP concentration 3.0E + 14: (PLTm ^-3) AP concentration 3.0E + 12: (PLTm ^-3) PT concentration 1.1E + 06: (nmolm ^-3) AT concentration 2.844E + 06: (nmolm ^-3)。

(2) And carrying out space dispersion on the three-dimensional structure information of the blood pump by adopting mesh division software.

(3) And solving a momentum equation according to the boundary condition information of the fluid field and the component concentration information of the reactant to obtain the speed field information in the blood pump. Here, the velocity field information includes blood flow velocity information.

(4) And solving a pressure Poisson equation according to the speed field information in the blood pump to obtain pressure field information and stress field information in the blood pump. Here, the stress field information includes shear rate information of deposited platelets.

(5) And sequentially solving scalar transport equations of the 11 components participating in the reaction in the platelet activation and deposition processes to obtain the deposition rate information of the platelets deposited in the blood pump calculation grid.

Here, the information of the chemical reaction items of the 11 components participating in the reaction is shown in table 5, or table 6. Wherein, table 5 shows the chemical reaction terms of various components of the non-characteristic wall surface of the blood pump, and table 6 shows the chemical reaction terms of various components at the characteristic wall surface of the blood pump.

Here, the wall surface of the blood pump is immersed in the blood tissue for a long period of time, and since the wall surface of the blood pump lacks an anticoagulant substance, the entire wall surface of the blood pump can be defined as a characteristic wall surface. In practical application, the chemical reaction term corresponding to the characteristic wall surface in table 6 can be used for calculation.

In the embodiment of the application, the wall surface of the blood pump is immersed in blood tissues for a long time, and the wall surface of the blood pump is lack of anticoagulation substances and is easy to be attached with von willebrand factor, so the wall surface of the blood pump adopts the calculation parameters according with the physiological medical condition, and the growth form information of the deposited platelets in the blood pump can be accurately acquired.

TABLE 5 chemical reaction terms of various components of the non-characteristic wall of blood pumps

TABLE 6 chemical reaction terms of various components of the characteristic wall of blood pumps

(6) And obtaining the concentration distribution information of the deposited platelets according to the deposition rate information of the deposited platelets in the calculation grid of the blood pump.

(7) And acquiring growth form information of the deposited platelets according to the interpolation information of the concentration distribution information of the deposited platelets on the grid surface of the calculation grid.

Illustratively, as shown in fig. 6, the image information of the second feature region 601 represents the growth morphology information of the deposited platelets on the feature wall surface, that is, the growth morphology information of the deposited platelets on the feature wall surface reflects the spatial position information of the main deposition region of the platelets. Further, according to the space position information of the main deposition area of the blood platelets, the rotating shaft and the root of the blade of the blood pump are determined to be high-risk structure areas, and then the functional structure of the high-risk structure areas in the blood pump product is improved.

Example four

Based on the same technical concept as the previous embodiment, referring to fig. 7, the platelet status analysis device 700 provided in the embodiment of the present application may include:

an obtaining module 701, configured to obtain concentration distribution information of platelets deposited in a target blood vessel according to a scalar transport equation of at least one component in the target blood vessel and fluid field information in the target blood vessel;

an analysis module 702, configured to perform interpolation processing on the concentration distribution information in a computational grid of the target blood vessel to obtain interpolation information of the concentration distribution information on a grid surface of the computational grid;

a processing module 703, configured to obtain deposition rate information of the platelet deposit according to interpolation information on a grid surface of the computational grid and normal vector information of the grid surface of the computational grid;

In one implementation, the at least one component further comprises a component other than the von willebrand factor; the obtaining module 701 is configured to obtain information on concentration distribution of platelets deposited in a target blood vessel according to a scalar transport equation of at least one component in the target blood vessel and fluid field information in the target blood vessel, and includes:

In one implementation, before the acquiring concentration distribution information of platelets deposited in the target blood vessel, the acquiring module 701 is configured to:

In one implementation, the at least one component includes the inhibitor of platelet activation; before the acquiring the information on the concentration distribution of the platelets deposited in the target blood vessel, the acquiring module 701 is configured to:

EXAMPLE five

Based on the same technical concept as the foregoing embodiment, referring to fig. 8, an electronic device 800 provided in an embodiment of the present application may include: a memory 810 and a processor 820; wherein,

a memory 810 for storing computer programs and data;

a processor 820 for executing the computer program stored in the memory to implement any one of the platelet status analysis methods in the foregoing embodiments.

In practical applications, the memory 810 may be a volatile memory (volatile memory), such as RAM; or a non-volatile memory (non-volatile memory), illustratively a ROM, a flash memory, a Hard Disk Drive (HDD) or a Solid-State Drive (SSD); or a combination of the above types of memories. The memory 810 may provide instructions and data to the processor 820.

The foregoing description of the various embodiments is intended to highlight various differences between the embodiments, and the same or similar parts may be referred to each other, which are not repeated herein for brevity

The methods disclosed in the method embodiments provided by the present application can be combined arbitrarily without conflict to obtain new method embodiments.

Features disclosed in various product embodiments provided by the application can be combined arbitrarily to obtain new product embodiments without conflict.

The features disclosed in the various method or apparatus embodiments provided herein may be combined in any combination to arrive at new method or apparatus embodiments without conflict.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, and for example, the division of the unit is only one logical function division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of grid units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, all functional units in the embodiments of the present application may be integrated into one processing module, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.

Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer readable storage medium, and when executed, the program performs the steps including the method embodiments.

The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and all the changes or substitutions should be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A platelet status analysis method comprising:

acquiring concentration distribution information of deposited platelets in a target blood vessel according to a scalar transport equation of at least one component in the target blood vessel and fluid field information in the target blood vessel; the at least one component includes a reactant, a product, a platelet-activation intermediate, and a platelet-activation inhibitor;

2. The method of claim 1, wherein the computational grid comprises any one of the following grid types:

structured grid, unstructured grid, hybrid grid.

3. The method of claim 1, wherein the reagent comprises von willebrand factor.

4. The method of claim 3, wherein obtaining the information on the concentration distribution of the deposited platelets in the target vessel based on the scalar transport equation of the at least one component in the target vessel and the information on the fluid field in the target vessel comprises:

the predetermined order represents an order in which the scalar transport equation of the von willebrand factor is solved first, and then the scalar transport equations of the other components of the at least one component are solved;

5. The method of claim 4, wherein prior to said obtaining concentration profile information of platelets deposited in said target vessel, said method further comprises:

6. The method of claim 1, wherein prior to said obtaining concentration distribution information of platelets deposited in said target vessel, said method further comprises:

7. A platelet status analysis device, comprising:

the acquisition module is used for acquiring the concentration distribution information of the deposited platelets in the target blood vessel according to a scalar transport equation of at least one component in the target blood vessel and the fluid field information in the target blood vessel; the at least one component includes a reactant, a product, a platelet-activation intermediate, and a platelet-activation inhibitor;

the analysis module is used for carrying out interpolation processing on the calculation grid of the target blood vessel according to the concentration distribution information to obtain interpolation information of the concentration distribution information on the grid surface of the calculation grid;

8. The apparatus of claim 7, wherein the computational grid comprises any one of the following grid types:

structured grid, unstructured grid, hybrid grid.

9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the platelet status analysis method of any one of claims 1 to 6 when executing the program.

10. A computer storage medium storing a computer program; characterized in that the computer program is executable to implement the platelet status analysis method according to any one of claims 1 to 6.