Hemodynamics evaluation method and device based on mechanical circulation support equipment

Abstract

The embodiment of the invention provides a hemodynamics evaluation method and device based on mechanical circulation support equipment, the method is applied to electronic medical equipment, and the method comprises the steps that a multi-scale model in which a cardiovascular system of a patient is coupled with the mechanical circulation support equipment is constructed, the multi-scale model comprises a branch model of a branch artery of the aorta of the patient; calculating a target state value of the branch model through the multi-scale model based on a set current operation mode of the mechanical cycle support equipment; and by taking the target state value as a dynamic boundary condition and adopting a preset analysis model, evaluating hemodynamic parameters of the branch artery represented by the branch model. By applying the scheme provided by the embodiment, the blood flow data evaluation accuracy can be improved.

Description

Technical Field

[0001] This application relates to the field of medical device technology, and in particular to a hemodynamic assessment method and apparatus based on mechanical circulatory support equipment. Background Technology

[0002] Mechanical circulatory support devices are medical devices that use mechanical pumps to replace or assist the heart's pumping function, maintaining blood circulation and organ perfusion, and providing transitional support or long-term treatment for patients with cardiopulmonary failure. Their core objectives are to improve hemodynamics, reduce cardiac workload, and buy time for cardiac recovery, decision-making, or organ transplantation. Currently, there is an urgent need for an assessment protocol for mechanical circulatory support devices to improve hemodynamics. Summary of the Invention

[0003] The purpose of this application is to provide a hemodynamic assessment method and apparatus based on mechanical circulatory support devices to improve assessment accuracy. The specific technical solution is as follows: In a first aspect, embodiments of this application provide a hemodynamic assessment method based on a mechanical circulatory support device, the method being applied to an electronic medical device, the method comprising: A multi-scale model coupling the patient's cardiovascular system with mechanical circulatory support equipment is constructed, wherein the multi-scale model includes a branch model of the patient's aortic branch arteries; Based on the current operating mode of the mechanical cycle support equipment, the target state value of the branch model is calculated through the multi-scale model; Using the target state value as a dynamic boundary condition, a preset analysis model is employed to evaluate the hemodynamic parameters of the branch arteries represented by the branch model.

[0004] In one embodiment of this application, the calculation of the target state value of the branch model based on the current operating mode of the set mechanical cycle support equipment through the multi-scale model includes: Based on the current operating mode of the established mechanical cycle support equipment, the initial state value of the branch model is calculated through the multi-scale model; Using the initial state value as the initial value, an iterative calculation method is adopted. Based on the historical state value determined by the previous iteration step and the specific parameters of the branch model, the state value of the branch model is iteratively updated for each iteration step. The specific parameters include the outlet near-end drag, outlet far-end drag and compliance of the branch model. The state value that meets the preset convergence condition is determined as the target state value.

[0005] In one embodiment of this application, the target state value includes the instantaneous flow rate value and outlet pressure value of the branch model. The iterative update of the branch model's state value for each iteration step, based on the historical state value determined by the previous iteration step and the specific parameters of the branch model, includes: Calculate the state value of the branch model within each iteration step using the following expression: in, The instantaneous flow rate at the current iteration step. This represents the exit pressure value for the current iteration step. For the compliance of the branching model, For the near-end resistance at the exit of the branch model, This refers to the resistance at the distal end of the branch artery's outlet.

[0006] In one embodiment of this application, the aforementioned branch arteries include the brachial artery, left common carotid artery, left subclavian artery, superior mesenteric artery, celiac artery, inferior mesenteric artery, left common iliac artery, right common iliac artery, left renal artery, and right renal artery.

[0007] In one embodiment of this application, the aforementioned hemodynamic parameters include wall shear stress and instantaneous shear oscillation shear index.

[0008] Secondly, embodiments of this application provide a hemodynamic assessment device based on a mechanical circulatory support device, the device being applied to an electronic medical device, the device comprising: The model building module is used to build a multi-scale model of the patient's cardiovascular system coupled with mechanical circulatory support equipment, wherein the multi-scale model includes a branch model of the patient's aortic branch arteries; The state calculation module is used to calculate the target state value of the branch model based on the current operating mode of the set mechanical cycle support equipment through the multi-scale model; The information evaluation module is used to evaluate the hemodynamic parameters of the branch arteries represented by the branch model using the target state value as a dynamic boundary condition and a preset analysis model.

[0009] In one embodiment of this application, the aforementioned state calculation module includes: The state calculation submodule is used to calculate the initial state value of the branch model based on the current operating mode of the set mechanical cycle support equipment through the multi-scale model. The state update submodule is used to update the state value of the branch model at each iteration step using the initial state value as the initial value and an iterative calculation method based on the historical state value determined by the previous iteration step and the specific parameters of the branch model. The specific parameters include the proximal drag of the branch model, the distal drag of the branch model, and compliance. The state determination submodule is used to determine the state value that meets the preset convergence condition as the target state value.

[0010] In one embodiment of this application, the target state value includes the instantaneous flow rate value and outlet pressure value of the branch model. The state update submodule is specifically used to calculate the state value of the branch model within each iteration step according to the following expression: in, The instantaneous flow rate at the current iteration step. This represents the exit pressure value for the current iteration step. For the compliance of the branching model, For the near-end resistance at the exit of the branch model, This refers to the resistance at the distal end of the branch artery's outlet.

[0011] In one embodiment of this application, the aforementioned branch arteries include the brachial artery, left common carotid artery, left subclavian artery, superior mesenteric artery, celiac artery, inferior mesenteric artery, left common iliac artery, right common iliac artery, left renal artery, and right renal artery.

[0012] In one embodiment of this application, the aforementioned hemodynamic parameters include wall shear stress and instantaneous shear oscillation shear index.

[0013] Thirdly, embodiments of this application provide an electronic medical device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; When a processor executes a program stored in memory, it implements the steps of the method described in the first aspect above.

[0014] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method described in the first aspect above.

[0015] As can be seen from the above, the solution provided in this application can, on the one hand, construct a multi-scale model to realistically simulate the dynamic environment of the coupling between the cardiovascular system and the mechanical circulatory support device; on the other hand, it can evaluate hemodynamic information using target state values ​​as dynamic boundary conditions. The target state values ​​reflect the dynamic response information of branch arteries to the mechanical circulatory support device. By using the above-mentioned target state values ​​as dynamic boundary conditions, the evaluated hemodynamic parameters can be made to better fit the actual dynamic situation. In summary, the solution provided in this embodiment can improve the accuracy of the evaluation results.

[0016] Of course, implementing any product or method of this application does not necessarily require achieving all of the advantages described above at the same time. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other embodiments can be obtained based on these drawings.

[0018] Figure 1 A schematic flowchart of the first hemodynamic assessment method based on a mechanical circulatory support device provided in this application embodiment; Figure 2 A schematic diagram of the structure of a branch artery in the aorta provided in this application embodiment; Figure 3 A schematic diagram of a hemodynamic assessment result provided for an embodiment of this application; Figure 4 A schematic flowchart illustrating the second hemodynamic assessment method based on a mechanical circulatory support device provided in this application embodiment; Figure 5 A schematic diagram of a hemodynamic assessment device based on a mechanical circulatory support device provided in this application embodiment; Figure 6 This is a schematic diagram of the structure of an electronic medical device provided in an embodiment of this application. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art based on this application are within the scope of protection of this application.

[0020] First, it should be noted that the mechanical circulatory support devices in this application include ventricular catheter pumps, intra-aortic balloon counterpulsation devices, ECMO (Extracorporeal Membrane Oxygenation), etc., and can also be a combination of ECMO and ventricular catheter pumps, or a combination of ECMO and intra-aortic balloon counterpulsation devices.

[0021] The subject of this application is an electronic medical device, which can be a control host of a mechanical circulation support device or an electronic device independent of the mechanical circulation support device.

[0022] This application is applied to a simulation environment to evaluate hemodynamics by simulating the dynamic environment of mechanical circulatory support devices coupled with the heart.

[0023] This application can be applied in different testing environments, such as evaluating the hemodynamic parameters of a single implanted mechanical circulatory support device and optimizing the structural performance of the device based on the evaluation results; it can also evaluate the hemodynamic parameters of different mechanical circulatory support devices separately, and use the evaluation results to compare the therapeutic effects of different mechanical circulatory support devices on cardiopulmonary function in order to determine the best treatment plan.

[0024] The following describes the solutions provided in the embodiments of this application.

[0025] See Figure 1 , Figure 1 This is a flowchart illustrating the first hemodynamic assessment method based on a mechanical circulatory support device provided in this application embodiment. The method includes the following steps S101-S103.

[0026] Step S101: Construct a multi-scale model coupling the patient's cardiovascular system with mechanical circulatory support equipment.

[0027] The aforementioned multi-scale model includes a branch model of the aorta's branch arteries. The aorta's branch arteries are branches of the main systemic circulation arteries, responsible for distributing blood from the aorta to all organs of the body.

[0028] by Figure 2 For example, Figure 2 The branch model is shown, which simulates the various branches of the aorta, including the brachial artery, left common carotid artery, left subclavian artery, superior mesenteric artery, celiac artery, inferior mesenteric artery, left common iliac artery, right common iliac artery, left renal artery, and right renal artery.

[0029] Specifically, a three-dimensional structural model of the aorta and a three-dimensional structural model of the mechanical circulatory support device of the patient's cardiovascular system can be constructed first using three-dimensional software. Then, a structural model coupled with the above two three-dimensional structural models can be constructed. This structural model can adopt a ternary lumped parameter model.

[0030] Step S102: Based on the current operating mode of the set mechanical cycle support equipment, calculate the target state value of the branch model through a multi-scale model.

[0031] The current operating mode of the mechanical circulatory support device is preset and includes the device's operating parameters. For example, when the mechanical circulatory support device is a ventricular catheter pump, the operating parameters include the pump blood flow pattern and the current rotation speed. The pump blood flow pattern includes constant flow and pulsatile flow. The key difference between constant flow and pulsatile flow is that pulsatile flow is synchronized with the cardiac cycle, while constant flow is not. When the mechanical circulatory support device is an intra-aortic balloon counterpulsation device, the operating parameters include the counterpulsation ratio. When the mechanical circulatory support device is an ECMO, the operating parameters include the current rotation speed.

[0032] The aforementioned target state values ​​reflect the state information of the branch arteries represented by the branch model, and can comprehensively reflect the cardiac pumping efficiency, vascular delivery capacity, and peripheral tissue perfusion status. Target state values ​​may include the instantaneous flow rate and outlet pressure values ​​of the branch model.

[0033] One approach to determining the target state value is to utilize the mapping relationship between the operating modes of the mechanical cyclic support equipment included in the multi-scale model and the state values ​​of the branch model to determine the state value corresponding to the current operating mode, which is then used as the target state value of the branch model.

[0034] Other implementation methods for calculating the target state value can be found in the following sections. Figure 4 The corresponding implementation examples will not be described in detail here.

[0035] Step S103: Using the target state value as the dynamic boundary condition, and employing a preset analysis model, evaluate the hemodynamic parameters of the branch arteries represented by the branch model.

[0036] The aforementioned pre-defined analytical model is primarily used to solve for blood flow data in the bifurcation model, thereby obtaining hemodynamic parameters. This pre-defined analytical model can be the Navier-Stokes model, employing the finite volume method to describe fluid motion and using the SIMPLE algorithm for solution.

[0037] The aforementioned hemodynamic parameters reflect the blood flow in the branch arteries represented by the branch model, and the assessed hemodynamic parameters are matched to different test scenarios. For example, in the simulation scenario of ventricular catheter pump, hemodynamic parameters include wall shear stress and transient shear oscillation shear index. Wall shear stress is used as an indicator to assess the risk of thrombosis and rupture in the arterial system, while the transient shear oscillation shear index is used to indicate the area of ​​atherosclerosis. In the simulation scenario of ECMO combined with catheter pump or intra-aortic balloon counterpulsation device, hemodynamic parameters include wall shear stress, harmonic index, velocity, and flow rate. The assessment results of the hemodynamic parameters can be found in [reference needed]. Figure 3 The diagram shown is shown in the image.

[0038] Since the evaluation results reflect the hemodynamic information of the branch arteries represented by the branch model under the current operating mode, different operating modes can be set for the mechanical circulatory support equipment, the hemodynamic information under different operating modes can be compared, and the operating mode corresponding to the best effect can be selected as the operating mode for the patient.

[0039] As can be seen from the above, by applying the solution provided in this embodiment, on the one hand, a multi-scale model is constructed to realistically simulate the dynamic environment of the coupling between the cardiovascular system and the mechanical circulatory support device; on the other hand, the target state value is used as a dynamic boundary condition to evaluate hemodynamic information. The target state value reflects the dynamic response information of the branch model to the mechanical circulatory support device. By using the above-mentioned target state value as a dynamic boundary condition, the evaluated hemodynamic parameters can be made to better fit the actual dynamic situation. In summary, the solution provided in this embodiment can improve the accuracy of the evaluation results.

[0040] The foregoing Figure 1 In the corresponding embodiment, step S102, the target state value can be calculated not only using the aforementioned implementation method, but also using steps S402-S404 described below. Based on this, see... Figure 4 , Figure 4 A flowchart illustrating the second hemodynamic assessment method based on a mechanical circulatory support device provided in this application embodiment, the method comprising: Step S401: Construct a multi-scale model of the patient's cardiovascular system coupled with mechanical circulatory support equipment.

[0041] Among them, the aforementioned multi-scale model includes a branch model of the patient's aorta branch arteries.

[0042] The above step S401 is the same as the aforementioned step S101, and will not be repeated here.

[0043] Step S402: Based on the current operating mode of the set mechanical cycle support equipment, calculate the initial state value of the branch model through a multi-scale model.

[0044] The initial state value reflects the initial response of the branch model to the state value of the current operating mode. Using the mapping relationship between the operating mode and the state value reflected by the multi-scale model, the state value corresponding to the current operating mode is determined as the initial state value.

[0045] Step S403: Using the initial state value as the initial value, and employing an iterative calculation method, based on the historical state value determined by the previous iteration step and the specific parameters of the branch model, iteratively update the state value of the branch model for each iteration step.

[0046] Specific parameters include proximal effluent resistance, distal effluent resistance, and compliance in the branching model. Different branching models for different arterial types correspond to different specific parameters, as listed in Table 1 below.

[0047] Artery <![CDATA[Outlet proximal resistance (10 7 Pa·s·m -3 )]]> <![CDATA[Outlet distal resistance (10 8 Pa·s·m -3 )]]> <![CDATA[Compliance (10 -10 ·m 3 ·Pa -1 )]]> Brachial artery 5.192 10.608 8.697 celiac artery 11.762 7.573 12.184 Inferior mesenteric artery 74.017 46.225 1.996 left common carotid artery 19.152 52.213 1.767 left common iliac artery 5.915 10.174 9.069 Left renal artery 34.138 5.395 17.102 Left subclavian artery 9.882 13.018 7.087 right common iliac artery 5.915 10.174 9.069 Right renal artery 34.138 5.395 17.102 superior mesenteric artery 17.435 5.510 16.745 Table 1 The iteration step size is preset, such as 0.01s or 0.02s.

[0048] This step uses an iterative method to calculate the state value. By using the iterative calculation method, the historical state value of each iteration is considered, so that the final calculated state value can better fit the dynamic environment of the actual branch artery, thereby improving the calculation accuracy.

[0049] In one embodiment of this application, for each iteration step, the state value of the branch model within each iteration step can be calculated according to the following expression: in, The instantaneous flow rate at the current iteration step. This represents the exit pressure value for the current iteration step. For the compliance of the branching model, For the near-end resistance at the exit of the branch model, This refers to the resistance at the distal end of the branch artery's outlet.

[0050] Step S404: Determine the state value that meets the preset convergence condition as the target state value.

[0051] The preset convergence condition can be a preset number of iterations. When the preset convergence condition is met, the iteration is determined to end, and the state value calculated in the last iteration is the state value that meets the preset convergence condition. The above state value is determined as the target state value.

[0052] Step S405: Using the target state value as the dynamic boundary condition, and employing a preset analysis model, evaluate the hemodynamic parameters of the branch arteries represented by the branch model.

[0053] Step S405 is the same as step S103 described above, and will not be repeated here.

[0054] Corresponding to the above-mentioned hemodynamic assessment method based on mechanical circulatory support equipment, this application also provides a hemodynamic assessment device based on mechanical circulatory support equipment.

[0055] See Figure 5 , Figure 5 This application provides a schematic diagram of a hemodynamic assessment device based on a mechanical circulatory support device. The device is applied to electronic medical devices and includes: The model building module 501 is used to build a multi-scale model of the patient's cardiovascular system coupled with the mechanical circulatory support device, wherein the multi-scale model includes a branch model of the branch arteries of the patient's aorta. The state calculation module 502 is used to calculate the target state value of the branch model based on the current operating mode of the set mechanical cycle support equipment through the multi-scale model. The information evaluation module 503 is used to evaluate the hemodynamic parameters of the branch arteries represented by the branch model using the target state value as a dynamic boundary condition and a preset analysis model.

[0056] As can be seen from the above, the solution provided in this embodiment can, on the one hand, construct a multi-scale model to realistically simulate the dynamic environment of the coupling between the cardiovascular system and the mechanical circulatory support device; on the other hand, it evaluates hemodynamic information using target state values ​​as dynamic boundary conditions. The target state values ​​reflect the dynamic response information of branch arteries to the mechanical circulatory support device. By using the above-mentioned target state values ​​as dynamic boundary conditions, the evaluated hemodynamic parameters can be made to better fit the actual dynamic situation. In summary, the solution provided in this embodiment can improve the accuracy of the evaluation results.

[0057] In one embodiment of this application, the state calculation module 502 includes: The state calculation submodule is used to calculate the initial state value of the branch model based on the current operating mode of the set mechanical cycle support equipment through the multi-scale model. The state update submodule is used to update the state value of the branch model at each iteration step using the initial state value as the initial value and an iterative calculation method based on the historical state value determined by the previous iteration step and the specific parameters of the branch model. The specific parameters include the proximal drag of the branch model, the distal drag of the branch model, and compliance. The state determination submodule is used to determine the state value that meets the preset convergence condition as the target state value.

[0058] By using an iterative calculation method, considering the historical state values ​​of each iteration, the final calculated state values ​​can better reflect the dynamic environment of the actual branch artery, thereby improving the calculation accuracy.

[0059] In one embodiment of this application, the target state value includes the instantaneous flow rate value and outlet pressure value of the branch model. The state update submodule is specifically used to calculate the state value of the branch model within each iteration step according to the following expression: in, The instantaneous flow rate at the current iteration step. This represents the exit pressure value for the current iteration step. For the compliance of the branching model, For the near-end resistance at the exit of the branch model, This refers to the resistance at the distal end of the branch artery's outlet.

[0060] In one embodiment of this application, the aforementioned branch arteries include the brachial artery, left common carotid artery, left subclavian artery, superior mesenteric artery, celiac artery, inferior mesenteric artery, left common iliac artery, right common iliac artery, left renal artery, and right renal artery.

[0061] In one embodiment of this application, the aforementioned hemodynamic parameters include wall shear stress and instantaneous shear oscillation shear index.

[0062] Corresponding to the hemodynamic assessment method based on mechanical circulatory support devices described above, this application provides an electronic medical device, see [link to relevant documentation]. Figure 6 , Figure 6 This is a schematic diagram of the structure of an electronic medical device provided in an embodiment of this application. The electronic medical device includes a processor 601, a communication interface 602, a memory 603, and a communication bus 604. The processor 601, the communication interface 602, and the memory 603 communicate with each other through the communication bus 604. Memory 603 is used to store computer programs; When the processor 601 executes the program stored in the memory 603, it implements the steps of the hemodynamic assessment method based on the mechanical circulatory support device described above.

[0063] The communication bus mentioned in the controller above can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus.

[0064] The communication interface is used for communication between the aforementioned controller and other devices.

[0065] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0066] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0067] In another embodiment provided in this application, a computer-readable storage medium is also provided, which stores a computer program. When the computer program is executed by a processor, it implements the hemodynamic assessment method and steps based on the mechanical circulatory support device provided in the embodiments of this application.

[0068] In another embodiment provided in this application, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to execute the hemodynamic assessment method and steps based on the mechanical circulatory support device provided in the embodiments of this application.

[0069] As can be seen from the above, the solution provided in this embodiment can, on the one hand, construct a multi-scale model to realistically simulate the dynamic environment of the coupling between the cardiovascular system and the mechanical circulatory support device; on the other hand, it evaluates hemodynamic information using target state values ​​as dynamic boundary conditions. The target state values ​​reflect the dynamic response information of branch arteries to the mechanical circulatory support device. By using the above-mentioned target state values ​​as dynamic boundary conditions, the evaluated hemodynamic parameters can be made to better fit the actual dynamic situation. In summary, the solution provided in this embodiment can improve the accuracy of the evaluation results.

[0070] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state disk (SSD)).

[0071] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0072] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments of apparatus, electronic medical devices, and computer-readable storage media are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0073] The above description is merely a preferred embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application are included within the scope of protection of this application.

Claims

1. A hemodynamic assessment method based on a mechanical circulatory support device, characterized in that, The method is applied to electronic medical devices, and the method includes: A multi-scale model coupling the patient's cardiovascular system with mechanical circulatory support equipment is constructed, wherein the multi-scale model includes a branch model of the patient's aortic branch arteries; Based on the current operating mode of the mechanical cycle support equipment, the target state value of the branch model is calculated through the multi-scale model; Using the target state value as a dynamic boundary condition, a preset analysis model is employed to evaluate the hemodynamic parameters of the branch arteries represented by the branch model.

2. The method according to claim 1, characterized in that, The calculation of the target state value of the branch model based on the current operating mode of the established mechanical cycle support equipment, using the multi-scale model, includes: Based on the current operating mode of the established mechanical cycle support equipment, the initial state value of the branch model is calculated through the multi-scale model; Using the initial state value as the initial value, an iterative calculation method is adopted. Based on the historical state value determined by the previous iteration step and the specific parameters of the branch model, the state value of the branch model is iteratively updated for each iteration step. The specific parameters include the outlet near-end drag, outlet far-end drag and compliance of the branch model. The state value that meets the preset convergence condition is determined as the target state value.

3. The method according to claim 2, characterized in that, The target state values ​​include the instantaneous flow rate and outlet pressure values ​​of the branch model. The iterative update of the branch model's state values ​​for each iteration step, based on the historical state values ​​determined by the previous iteration step and the specific parameters of the branch model, includes: Calculate the state value of the branch model within each iteration step using the following expression: in, The instantaneous flow rate at the current iteration step. This represents the exit pressure value for the current iteration step. For the compliance of the branching model, For the near-end resistance at the exit of the branch model, This refers to the resistance at the distal end of the branch artery's outlet.

4. The method according to any one of claims 1-3, characterized in that, The branch arteries include the brachial artery, left common carotid artery, left subclavian artery, superior mesenteric artery, celiac artery, inferior mesenteric artery, left common iliac artery, right common iliac artery, left renal artery, and right renal artery.

5. The method according to any one of claims 1-3, characterized in that, The hemodynamic parameters include wall shear stress and instantaneous shear oscillation shear index.

6. A hemodynamic assessment device based on mechanical circulatory support equipment, characterized in that, The device is used in electronic medical devices, and the device includes: The model building module is used to build a multi-scale model of the patient's cardiovascular system coupled with mechanical circulatory support equipment, wherein the multi-scale model includes a branch model of the patient's aortic branch arteries; The state calculation module is used to calculate the target state value of the branch model based on the current operating mode of the set mechanical cycle support equipment through the multi-scale model; The information evaluation module is used to evaluate the hemodynamic parameters of the branch arteries represented by the branch model using the target state value as a dynamic boundary condition and a preset analysis model.

7. The apparatus according to claim 6, characterized in that, The state calculation module includes: The state calculation submodule is used to calculate the initial state value of the branch model based on the current operating mode of the set mechanical cycle support equipment through the multi-scale model. The state update submodule is used to update the state value of the branch model at each iteration step using the initial state value as the initial value and an iterative calculation method based on the historical state value determined by the previous iteration step and the specific parameters of the branch model. The specific parameters include the proximal drag of the branch model, the distal drag of the branch model, and compliance. The state determination submodule is used to determine the state value that meets the preset convergence condition as the target state value.

8. The apparatus according to claim 7, characterized in that, The target state values ​​include the instantaneous flow rate and outlet pressure value of the branch model. The state update submodule is specifically used to calculate the state value of the branch model within each iteration step according to the following expression: in, The instantaneous flow rate at the current iteration step. This represents the exit pressure value for the current iteration step. For the compliance of the branching model, For the near-end resistance at the exit of the branch model, This refers to the resistance at the distal end of the branch artery's outlet.

9. An electronic medical device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, when executing a program stored in memory, implements the method steps of any one of claims 1-5.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the method steps of any one of claims 1-5.

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