Blood pressure calculation method and device based on cross-scale fluid-structure coupling and considering nonlinear biomechanical characteristics of aorta

Abstract

The application discloses a blood pressure calculation method and equipment based on cross-scale fluid-solid coupling and considering nonlinear biomechanical characteristics of an aorta, and the method comprises the following steps: establishing a three-dimensional ideal aorta geometric model; establishing a zero-dimensional heart lumped parameter model to simulate the process that the heart pumps blood to the aorta inlet through periodic contraction and diastole; establishing a zero-dimensional three-element Windkessel model of small arteries to simulate blood flow microcirculation of peripheral small arteries; establishing a blood vessel wall biomechanical model containing residual stress of the aorta wall and active contraction of smooth muscle cells to obtain a pressure-radius relationship of the aorta wall as a fluid wall boundary condition to simulate the change process of the aorta radius in blood circulation; and coupling the three-dimensional ideal geometric model of the aorta, the zero-dimensional heart lumped parameter model and the zero-dimensional three-element Windkessel model to construct a cross-scale fluid-solid coupling system of hemodynamics, and the blood pressure in the aorta is calculated through iterative solution.

Description

Technical Field

[0001] This invention belongs to the fields of biomedical engineering and computational fluid dynamics, specifically relating to a blood pressure calculation method and device based on cross-scale fluid-structure interaction and considering the nonlinear biomechanical characteristics of the aorta. Background Technology

[0002] Endovascular aortic repair (EVAR) and artificial vascular graft replacement are first-line treatments for aortic diseases. However, due to the mismatch between the vascular implant and the biomechanical properties of the aorta, postoperative complications such as increased cardiac afterload, ascending aortic dilation, and myocardial thickening often occur. Therefore, achieving quantitative prediction of blood pressure, and thus analyzing the impact of aortic surgery on cardiac afterload, is crucial for evaluating the effectiveness of aortic treatment, optimizing treatment plans, and improving medical devices. Current blood pressure calculation techniques mainly rely on zero-dimensional fluid dynamics models or three-dimensional fluid dynamics (CFD) models, but both have significant limitations. Existing methods often use a zero-dimensional heart model to drive a three-dimensional aortic model unidirectionally, failing to achieve bidirectional energy feedback between the heart and aorta. This makes it difficult to ensure the dynamic consistency between inlet flow boundary conditions and outlet pressure boundary conditions, and the microcirculation modeling of peripheral arterioles often relies on empirical parameters, failing to accurately reflect the spatiotemporal dynamic characteristics under physiological conditions. Furthermore, traditional models generally neglect the residual stress of the aortic wall and the active contraction of smooth muscle cells, describing the mechanical behavior of the vascular wall only with passive hyperelastic constitutive models. This leads to a distortion of the pressure-radius relationship and makes it difficult to explain the differences in hemodynamic characteristics during cardiac systole and diastole, as well as individual differences.

[0003] In fluid-structure interaction (FSI) techniques, existing methods mostly employ explicit iterative strategies, requiring frequent exchanges of boundary conditions between the fluid and solid domains. This leads to low computational efficiency and frequent interruptions due to convergence issues. Furthermore, the settings for inlet flow rate and outlet pressure often deviate from the dynamic characteristics of physiological valves. These shortcomings make it difficult for existing techniques to meet the dual requirements of high accuracy and high efficiency in scenarios such as non-steady-state blood flow and cardiac work assessment, thus limiting their application in clinical diagnosis and biomechanical research. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and to propose a blood pressure calculation method and device based on cross-scale fluid-structure interaction and considering the nonlinear biomechanical characteristics of the aorta, so as to improve the accuracy and efficiency of blood pressure prediction.

[0005] In view of this, the present invention proposes a blood pressure calculation method based on cross-scale fluid-structure interaction and considering the nonlinear biomechanical properties of the aorta, comprising: Step S1: Establish a three-dimensional ideal aortic geometric model; Step S2: Based on the functional characteristics of the left atrium and left ventricle and the concept of time-varying elastic function, establish a zero-dimensional lumped parameter model of the heart to simulate the process of the heart pumping blood to the aortic inlet through periodic contraction and relaxation. Step S3: Establish a zero-dimensional ternary Windkessel model of arterioles to simulate the blood flow microcirculation of peripheral arterioles; Step S4: Establish a biomechanical model of the blood vessel wall that includes residual stress in the aortic wall and active contraction of smooth muscle cells, and obtain the pressure-radius relationship of the aortic wall as a fluid wall boundary condition to simulate the change process of the aortic radius in blood circulation. Step S5: Couple the three-dimensional ideal aortic geometric model, the zero-dimensional lumped parameter model of the heart, and the zero-dimensional ternary Windkessel model to construct a hemodynamic cross-scale fluid-structure interaction system. Calculate the blood pressure within the aorta through iterative solution.

[0006] Preferably, step 1 includes: A three-dimensional ideal aortic geometric model is established based on the inner radius, ascending aorta length, aortic arch radius, and descending aorta length under initial pressure.

[0007] Preferably, the zero-dimensional cardiac lumped parameter model is constructed based on circuit analogy and includes: a diode for simulating the function of the mitral and aortic valves, an inductor for simulating blood flow inertia, a resistor for simulating blood flow resistance, an elastic constant unit for describing the change of left atrial pressure with volume, and a time-varying elastic function unit for describing the periodic contraction and relaxation of the left ventricle.

[0008] Preferably, the zero-dimensional cardiac lumped parameter model is specifically as follows: The left atrium consists of a diode and a left atrial resistor. Left atrial inductance and left atrial elastic constant Composition; among which, , Left atrial volume, The left atrial volume under stress-free conditions. This refers to the pressure within the left atrial cavity; The left ventricle is determined by a time-varying elastic function. Left ventricular nonlinear resistance diodes, aortic valve resistors and aortic valve inductance Composition; among which, , , Left ventricular volume The left ventricular volume under stress-free conditions. This refers to the pressure within the left ventricle. It is a constant.

[0009] Preferably, the time-varying elastic function To further simplify:

[0010] in, This is the maximum elastic value. For the minimum elastic value, The time to reach the maximum value The remaining time from the start of diastole, where T is the length of the cardiac cycle and t represents time.

[0011] Preferably, the zero-dimensional ternary Windkessel model includes: a proximal resistance, a distal resistance, and a capacitor connected in series, wherein the capacitor is used to characterize the compliance of peripheral blood vessels.

[0012] Preferably, step S4, establishing the pressure-radius relationship of the aortic wall, includes: Calculate the residual deformation gradient using the residual deformation parameters of the aorta. and in-situ deformation gradient : , in, The residual deformation parameters of the aorta, which are load deformation gradients, include: the opening angle of the media and adventitia, the radius of curvature of the opening angle, the lateral bending angle, and the radius of curvature of the lateral bending angle. Substituting the constitutive equation and equilibrium equation, the radius of the aortic wall under different internal pressures is obtained, and the pressure-radius relationship of the aortic wall is obtained by fitting the function. The constitutive equation and equilibrium equation are as follows:

[0013]

[0014] Where W is the strain energy density function of the aorta, expressed as: and the sum of This represents the passive hyperelastic response of the matrix and elastin network, as well as the anisotropic passive response induced by collagen fibers. This represents the contribution of activated smooth muscle cells; For the Green-Lagrange strain tensor; For Lagrange multipliers; Represented as a second-order unit tensor; and These are the radial and circumferential stress components, respectively; The radius is [0, 1].

[0015] Preferably, step S5, which constructs a hemodynamic cross-scale fluid-structure interaction system, includes: The inlet flow rate at the next time step, calculated from the real-time inlet flow rate and pressure feedback of the zero-dimensional heart lumped parameter model based on the three-dimensional ideal geometric model, is used as the inlet boundary condition of the three-dimensional ideal geometric model. The outlet pressure at the next time step, calculated by the zero-dimensional ternary Windkessel model based on the real-time outlet flow and pressure feedback from the three-dimensional ideal geometric model, is used as the outlet boundary condition of the three-dimensional ideal geometric model. The pressure-radius relationship of the aortic wall is used as the fluid wall boundary condition for the three-dimensional ideal geometric model; By setting initial conditions and time steps, data exchange and collaborative solution of the zero-dimensional heart lumped parameter model, the three-dimensional ideal geometric model, and the zero-dimensional ternary Windkessel model are achieved.

[0016] Preferably, the method further includes: after step S5, calculating the pressure-volume loop of the left ventricle based on the solution results of the hemodynamic cross-scale fluid-structure interaction system; and calculating the stroke work of the heart based on the pressure-volume loop.

[0017] On the other hand, the present invention provides a computer device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described method.

[0018] Compared with the prior art, the advantages of the present invention are: 1. The method of cross-scale fluid-structure interaction using a zero-dimensional heart and small artery Windkessel model and a three-dimensional aortic model is more in line with normal physiological state, and the rationality of experimental results can be evaluated from the perspective of heart work.

[0019] 2. The aortic wall uses a moving boundary method to achieve implicit fluid-structure interaction between the vessel wall and the blood flow domain, simplifying the traditional two-way fluid-structure interaction method.

[0020] 3. By employing a hyperelastic constitutive model that includes both active and passive components, the influence of vascular wall components such as matrix, elastin, collagen fibers, and smooth muscle cells on blood flow is comprehensively considered. In addition, residual stress in the vascular wall is also introduced, further enhancing the accuracy of blood pressure prediction results. Attached Figure Description

[0021] Figure 1This is a flowchart illustrating the blood pressure calculation method of the present invention based on cross-scale fluid-structure interaction and considering the nonlinear biomechanical properties of the aorta. Figure 2 This is a schematic diagram of a three-dimensional ideal aorta model; Figure 3 This is a schematic diagram of a zero-dimensional lumped parameter model of the heart; Figure 4 This is a schematic diagram of a zero-dimensional ternary Windkessel model of a small artery; Figure 5 It is the aortic wall pressure-radius relationship; Figure 6 It is the aortic inlet pressure-time curve; Figure 7 It is the aortic outlet pressure-time curve; Figure 8 This is the left ventricular PV Loop curve. Detailed Implementation

[0022] This invention proposes a method and device for calculating blood pressure based on cross-scale fluid-structure interaction and considering the nonlinear biomechanical properties of the aorta, including: Step 1: Based on the geometric dimensions of the numerical simulation study, establish a three-dimensional ideal aortic geometric model; the geometric dimensions of the numerical simulation study include the inner radius, ascending aorta length, aortic arch radius, and descending aorta length under the initial pressure of the aortic model.

[0023] Step 2: Based on the functional characteristics of the left atrium and left ventricle and the concept of time-varying elastic function, establish a zero-dimensional lumped parameter model of the heart to simulate the process of the heart pumping blood to the aortic inlet through periodic contraction and relaxation; The functional characteristics of the left atrium and left ventricle are as follows: the left atrium receives oxygenated blood returning from the lungs and pumps it into the left ventricle through the mitral valve; while the left ventricle is the most powerful pumping chamber of the heart, responsible for pumping blood through the aortic valve into the aorta and delivering it to the whole body. Both work together to maintain normal blood circulation by opening and closing their valves, ensuring the orderly delivery of blood.

[0024] The time-varying elastic function can be considered as the constitutive equation of the left ventricle, which linearly relates the volume of the left ventricle to the intracardiac pressure of the left ventricle to simulate the pulsatile relaxation and contraction of the left ventricle, and is defined as follows:

[0025] in, This refers to the pressure within the left ventricle. Left ventricular volume This represents the left ventricular volume under stress-free conditions.

[0026] The time-varying elastic function can be simplified to the following form:

[0027] in, This is the maximum elastic value. For the minimum elastic value, The time to reach the maximum value The remaining time from the start of diastole, where T is the length of the cardiac cycle.

[0028] The zero-dimensional lumped-parameter model of the heart consists of electrical components such as diodes, resistors, and inductors, as well as the time-varying elastic function of the left ventricle and the elastic constant of the left atrium. The diodes simulate the functions of the mitral and aortic valves; the opening of these valves is determined by the negative pressure gradient in the direction of blood flow, and once opened, they remain open until reverse blood flow is detected. The resistors include the left atrial resistance. aortic valve resistance and left ventricular nonlinear resistance , It is a constant; inductance includes the left atrial inductance. and aortic valve inductance Left ventricular time-varying elastic function , Left ventricular volume Left ventricular volume under stress-free conditions; left atrial elastic constant. , Left atrial volume, This represents the left atrial volume under stress-free conditions.

[0029] Step 3: Establish a zero-dimensional ternary Windkessel model of the arteriole to simulate the microcirculation of peripheral arteriole blood flow; the zero-dimensional ternary Windkessel model consists of resistors and capacitors. The resistors include proximal resistors. and remote resistor Capacitance C represents peripheral arteriole compliance.

[0030] Step 4: Calculate the residual deformation gradient using the residual aortic deformation parameters. and in-situ deformation gradient , Substituting the load deformation gradient into the equilibrium equation and the constitutive equation including the active contraction of smooth muscle cells, the radius of the aortic wall under different internal pressures is obtained. The pressure-radius relationship of the aortic wall is obtained by fitting the function. This pressure-radius relationship is used as the boundary condition of the fluid wall to simulate the change process of the aortic radius in blood circulation. The residual deformation parameters of the aorta include the opening angle, radius of curvature of the opening angle, lateral bending angle, and radius of curvature of the lateral bending angle of the media and adventitia; the constitutive equation and equilibrium equation are as follows:

[0031]

[0032] in For in-situ deformation gradient; For the Green-Lagrange strain tensor; For Lagrange multipliers; Represented as a second-order unit tensor; and These are the radial and circumferential stress components, respectively; W is the radius; W is the strain energy density function of the aorta, represented by the passive component. and active components the sum of This represents the passive hyperelastic response of the matrix and elastin network, as well as the anisotropic passive response induced by collagen fibers. This represents the contribution of activated smooth muscle cells. The specific expression for W is shown below:

[0033]

[0034]

[0035]

[0036]

[0037]

[0038]

[0039]

[0040]

[0041] In the formula: , , , , , , , , , , , , Material parameters; Let C be the first invariant of the right Cauchy-Green strain tensor. and Let C be a pseudo-invariant of the right Cauchy-Green strain tensor.

[0042] Step 5: The three-dimensional aortic blood flow model is used to describe the propagation process of blood flow and blood pressure in the aorta, while the zero-dimensional heart lumped parameter model and the Windkessel blood flow model of the small arteries are used to describe the pumping of blood from the heart to the aortic inlet and the microcirculation process of blood flow in the peripheral small arteries, respectively. The parts are coupled with each other, and the data of each part are exchanged by setting the initial conditions and time steps, so as to realize the calculation and solution of the zero-dimensional-three-dimensional cross-scale fluid-structure interaction model. Zero-dimensional to three-dimensional cross-scale fluid-structure interaction refers to the following: At the inlet of the three-dimensional aortic model, when the aortic valve is closed, the aortic inlet flow is zero; when the aortic valve is open, the inlet flow at the beginning of each time step is calculated based on the flow-pressure relationship at the inlet boundary, thus achieving data exchange between the zero-dimensional heart model and the three-dimensional aortic model. At the outlet of the three-dimensional aortic model, the outlet pressure at the beginning of each time step is calculated based on the flow-pressure relationship at the outlet boundary, thus achieving data exchange between the zero-dimensional ternary Windkessel model of arterioles and the three-dimensional aortic model.

[0043] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0044] Example 1 Embodiments of this invention propose a blood pressure calculation method based on cross-scale fluid-structure interaction and considering the nonlinear biomechanical properties of the aorta. For example... Figure 1 As shown, it includes the following steps: 1. Establish a three-dimensional aortic model: Based on the geometric dimensions obtained from numerical simulation studies, establish a three-dimensional ideal aortic geometric model; In this embodiment, a three-dimensional ideal aortic model is established based on the geometric dimensions of the initial pressure: an inner radius of 9.84 mm, an ascending aorta length of 20 mm, an aortic arch radius of 20 mm, and a descending aorta length of 240 mm. Figure 2 As shown.

[0045] 2. Establish a zero-dimensional heart model: Based on the functional characteristics of the left atrium and left ventricle and the concept of time-varying elastic function, establish a zero-dimensional lumped parameter model of the heart to simulate the process of the heart pumping blood to the aortic inlet through periodic contraction and relaxation; In this embodiment, a zero-dimensional cardiac lumped parameter model is established based on the functional characteristics of the left atrium and left ventricle and the concept of time-varying elastic functions, as follows: Figure 3 As shown. The left atrium consists of a diode and a left atrial resistor. Left atrial inductance and left atrial elastic constant Composition; the left ventricle is composed of time-varying elastic functions Left ventricular nonlinear resistance diodes, aortic valve resistors and aortic valve inductance The heart is composed of several parts. The left atrium receives oxygenated blood returning from the lungs, pumps it into the left ventricle via the mitral valve, and the left ventricle then pumps the blood into the aorta via the aortic valve, distributing it throughout the body. The parameters of the zero-dimensional lumped parameter model of the heart are shown in Table 1.

[0046] Table 1. Parameters of the zero-dimensional cardiac lumped model

[0047] 3. Establish a zero-dimensional arteriole model: Establish a zero-dimensional ternary Windkessel model of arterioles to simulate the microcirculation of peripheral arteriole blood flow; In this embodiment, the zero-dimensional ternary Windkessel model consists of resistors and capacitors. The resistors include near-end resistors. and remote resistor Capacitance C represents peripheral arteriole compliance. The parameters of the zero-dimensional ternary Windkessel model are shown in Table 2.

[0048] Table 2 Parameters of the zero-dimensional ternary Windkessel model

[0049] 4. Solving the pressure-radius relationship of the blood vessel wall: By using the residual deformation parameters of the aorta, the residual deformation gradient and the in-situ deformation gradient are calculated. Substitute them into the constitutive equation and the equilibrium equation to obtain the radius of the aortic blood vessel wall under different internal pressures. The pressure-radius relationship of the aortic blood vessel wall is obtained by fitting the function. This pressure-radius relationship is used as the boundary condition of the fluid wall to simulate the change process of the aortic radius in blood circulation. In this embodiment, the residual deformation gradient is calculated based on the residual deformation parameters of the porcine aortic wall shown in Table 3. Then, by applying 1.2 times the axial tension of the blood vessel wall and the effect of blood pressure, the load deformation gradient was calculated. The total deformation gradient Substituting the constitutive equation and equilibrium equation, the pressure-radius relationship of the aortic wall can be obtained as follows: Figure 5 As shown.

[0050] Table 3 Residual Deformation Parameters of the Aortic Wall

[0051] 5. Zero-dimensional to three-dimensional cross-scale fluid-structure interaction calculation: The three-dimensional aortic blood flow model is used to describe the propagation process of blood flow and blood pressure in the aorta, while the zero-dimensional lumped parameter model of the heart and the Windkessel blood flow model of the arterioles are used to describe the pumping of blood from the heart to the aortic inlet and the microcirculation process of blood flow in the peripheral arterioles, respectively. The parts are coupled with each other, and the data of each part are exchanged by setting initial conditions and time steps, so as to realize the calculation and solution of the zero-dimensional to three-dimensional cross-scale fluid-structure interaction model; In this embodiment, the zero-dimensional heart model calculates the inlet flow rate at the beginning of each time step based on the flow-pressure relationship at the inlet boundary, serving as the inlet boundary condition for the three-dimensional aortic model; the zero-dimensional arteriole ternary Windkessel model calculates the outlet pressure at the beginning of each time step based on the flow-pressure relationship at the outlet boundary, serving as the outlet boundary condition for the three-dimensional aortic model; the pressure-radius relationship of the aortic wall serves as the fluid wall boundary condition for the three-dimensional aortic model. By setting initial conditions and time steps to exchange data from different parts, the calculation and solution of the zero-dimensional-to-three-dimensional cross-scale fluid-structure interaction model are achieved. The aortic inlet pressure-time curve and the aortic outlet pressure-time curve are plotted as follows: Figure 6 and Figure 7 As shown, the calculated pulse pressure for this individual was 38.37 mmHg. Furthermore, due to the use of a zero-dimensional lumped-parameter model of the heart, the PV Loop curve of the left ventricle can also be plotted, as shown below. Figure 8 As shown, the calculated work done by the heart per stroke (SW) is 0.7858 J.

[0052] Example 2 Embodiment 2 of the present invention provides a computer device comprising: at least one processor, a memory, at least one network interface, and a user interface. The various components of the device are coupled together via a bus system. It is understood that the bus system is used to enable communication between these components. In addition to a data bus, the bus system also includes a power bus, a control bus, and a status signal bus.

[0053] The user interface may include a display, keyboard, or clicking device (e.g., mouse, trackball, touchpad, or touchscreen).

[0054] It is understood that the memory in the embodiments disclosed in this application may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory may be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The memories described herein are intended to include, but are not limited to, these and any other suitable types of memory.

[0055] In some implementations, the memory stores elements such as executable modules or data structures, or subsets thereof, or extended sets thereof: operating systems and applications.

[0056] The operating system includes various system programs, such as the framework layer, core library layer, and driver layer, used to implement various basic business functions and handle hardware-based tasks. The application programs include various applications, such as media players and browsers, used to implement various application functions. Programs implementing the methods of the embodiments of this disclosure can be included in the application programs.

[0057] In the above embodiments, the processor can also execute the steps of the method of embodiment 1 by calling a program or instruction stored in the memory, specifically a program or instruction stored in an application program.

[0058] The method of Embodiment 1 can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by integrated logic circuits in the processor's hardware or by instructions in software form. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in Embodiment 1. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in Embodiment 1 can be directly implemented by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory; the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method.

[0059] It is understood that the embodiments described in this invention can be implemented in hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described in this application, or combinations thereof.

[0060] For software implementation, the technology of this invention can be implemented by executing the functional modules (e.g., procedures, functions, etc.) of this invention. The software code can be stored in memory and executed by a processor. The memory can be implemented in the processor or externally.

[0061] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to the embodiments, those skilled in the art should understand that modifications or equivalent substitutions to the technical solutions of the present invention do not depart from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A blood pressure calculation method based on cross-scale fluid-structure interaction and considering the nonlinear biomechanical properties of the aorta, comprising: Step S1: Establish a three-dimensional ideal aortic geometric model; Step S2: Based on the functional characteristics of the left atrium and left ventricle and the concept of time-varying elastic function, establish a zero-dimensional lumped parameter model of the heart to simulate the process of the heart pumping blood to the aortic inlet through periodic contraction and relaxation. Step S3: Establish a zero-dimensional ternary Windkessel model of arterioles to simulate the blood flow microcirculation of peripheral arterioles; Step S4: Establish a biomechanical model of the blood vessel wall that includes residual stress in the aortic wall and active contraction of smooth muscle cells, and obtain the pressure-radius relationship of the aortic wall as a fluid wall boundary condition to simulate the change process of the aortic radius in blood circulation. Step S5: Couple the three-dimensional ideal geometric model of the aorta, the zero-dimensional lumped parameter model of the heart, and the zero-dimensional ternary Windkessel model to construct a hemodynamic cross-scale fluid-structure interaction system. Calculate the blood pressure within the aorta through iterative solution.

2. The blood pressure calculation method based on cross-scale fluid-structure interaction and considering the nonlinear biomechanical properties of the aorta according to claim 1, characterized in that, Step 1 includes: A three-dimensional ideal aortic geometric model is established based on the inner radius, ascending aorta length, aortic arch radius, and descending aorta length under initial pressure.

3. The blood pressure calculation method based on cross-scale fluid-structure interaction and considering the nonlinear biomechanical properties of the aorta according to claim 1, characterized in that, The zero-dimensional cardiac lumped parameter model is constructed based on circuit analogy and includes: a diode for simulating the function of the mitral and aortic valves, an inductor for simulating blood flow inertia, a resistor for simulating blood flow resistance, an elastic constant unit for describing the change of left atrial pressure with volume, and a time-varying elastic function unit for describing the periodic contraction and relaxation of the left ventricle.

4. The blood pressure calculation method based on cross-scale fluid-structure interaction and considering the nonlinear biomechanical properties of the aorta according to claim 1, characterized in that, The zero-dimensional cardiac lumped parameter model is specifically as follows: The left atrium consists of a diode and a left atrial resistor. Left atrial inductance and left atrial elastic constant Composition; among which, ， Left atrial volume, The left atrial volume under stress-free conditions. This refers to the pressure within the left atrial cavity; The left ventricle is a time-varying elastic function Left ventricular nonlinear resistance diodes, aortic valve resistors and aortic valve inductance Composition; among which, ， ， Left ventricular volume The left ventricular volume under stress-free conditions. This refers to the pressure within the left ventricle. It is a constant.

5. The blood pressure calculation method based on cross-scale fluid-structure interaction and considering the nonlinear biomechanical properties of the aorta according to claim 4, characterized in that, The time-varying elastic function To further simplify: ， in, This is the maximum elastic value. For the minimum elastic value, The time to reach the maximum value The remaining time from the start of diastole, where T is the length of the cardiac cycle and t represents time.

6. The blood pressure calculation method based on cross-scale fluid-structure interaction and considering the nonlinear biomechanical properties of the aorta according to claim 1, characterized in that, The zero-dimensional ternary Windkessel model includes a series of proximal and distal resistances and a parallel capacitor, wherein the capacitor is used to characterize the compliance of peripheral blood vessels.

7. The blood pressure calculation method based on cross-scale fluid-structure interaction and considering the nonlinear biomechanical properties of the aorta according to claim 1, characterized in that, The establishment of the pressure-radius relationship of the aortic wall in step S4 includes: Calculate the residual deformation gradient using the residual deformation parameters of the aorta. and in-situ deformation gradient : ， in, The residual deformation parameters of the aorta, which are load deformation gradients, include: the opening angle of the media and adventitia, the radius of curvature of the opening angle, the lateral bending angle, and the radius of curvature of the lateral bending angle. Substituting the constitutive equation and equilibrium equation, the radius of the aortic wall under different internal pressures is obtained, and the pressure-radius relationship of the aortic wall is obtained by fitting the function. The constitutive equation and equilibrium equation are as follows: ， ， Where W is the strain energy density function of the aorta, expressed as: and The sum of This represents the passive hyperelastic response of the matrix and elastin network, as well as the anisotropic passive response induced by collagen fibers. This represents the contribution of activated smooth muscle cells; For the Green-Lagrange strain tensor; For Lagrange multipliers; Represented as a second-order unit tensor; and These are the radial and circumferential stress components, respectively; The radius is [0, 1].

8. The blood pressure calculation method based on cross-scale fluid-structure interaction and considering the nonlinear biomechanical properties of the aorta according to claim 1, characterized in that, Step S5, which constructs the hemodynamic cross-scale fluid-structure interaction system, includes: The inlet flow rate at the next time step, calculated from the real-time inlet flow rate and pressure feedback of the zero-dimensional heart lumped parameter model based on the three-dimensional ideal geometric model, is used as the inlet boundary condition of the three-dimensional ideal geometric model. The outlet pressure at the next time step, calculated by the zero-dimensional ternary Windkessel model based on the real-time outlet flow and pressure feedback from the three-dimensional ideal geometric model, is used as the outlet boundary condition of the three-dimensional ideal geometric model. The pressure-radius relationship of the aortic wall is used as the fluid wall boundary condition for the three-dimensional ideal geometric model; By setting initial conditions and time steps, data exchange and collaborative solution of the zero-dimensional heart lumped parameter model, the three-dimensional ideal geometric model, and the zero-dimensional ternary Windkessel model are achieved.

9. The blood pressure calculation method based on cross-scale fluid-structure interaction and considering the nonlinear biomechanical properties of the aorta according to claim 8, characterized in that, The method further includes: after step S5, calculating the pressure-volume loop of the left ventricle based on the solution results of the hemodynamic cross-scale fluid-structure interaction system; and calculating the stroke work of the heart based on the pressure-volume loop.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1 to 9.

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