Method, device and equipment for determining hemodynamic indexes of blood circulation system under action of acceleration field, medium and product

Abstract

The invention discloses a method, a device, equipment, a medium and a product for determining hemodynamic indexes of a blood circulation system under the action of an acceleration field, and relates to the technical field of hemodynamics, the method comprises the following steps: constructing a one-dimensional topological model and a 0-dimensional connection model of main artery and vein blood vessel networks, and assigning parameters to obtain a 0-1-dimensional coupling basic model; iteratively solving by combining the simplified model of the basic model, the objective function and the physiological measured data to obtain individualized model parameters of the subject, and assigning the individualized model parameters to the basic model; extracting geometric topology information of the blood vessel network of the concerned part based on iconography information and assigning the geometric topology information to a corresponding position of the 0-1-dimensional model; the acceleration equivalent to the real environment is applied, the individualized 0-1-dimensional model control equation of the subject is solved, the hemodynamic indexes of the blood circulation system under the action of the acceleration field are obtained, and the hemodynamic changes of the arteriovenous system and the blood supply conditions of all important organs of the subject under the action of the acceleration can be accurately and quantitatively evaluated.

Description

Technical Field

[0001] The present application relates to the field of hemodynamics technology, and in particular to a method, device, equipment, medium and product for determining hemodynamic indicators of a blood circulation system under the action of an acceleration field. Background Art

[0002] The acceleration and posture changes of the human body have a significant impact on the cardiovascular system, especially when the acceleration field of the subject changes, such as when standing upright, sitting, lying flat, taking off and landing, and in extreme cases such as manned space flight, which will lead to significant changes in cardiovascular function. In addition, due to the low venous pressure and relatively high compliance of venous blood vessels, the acceleration effect in the venous system on hemodynamic indicators will be more significant when the posture and acceleration field change compared with the arterial system. The most direct way to monitor the hemodynamic indicators is experimental measurement. For example, the human centrifuge experiment is the most preferred method for studying the physiological response of the human body to acceleration. Centrifuge testing can help monitor the physiological phenomena of the subject during time-varying acceleration, including heart rate, blood pressure, and arterial oxygen saturation. However, the experimental method is difficult to measure and costly, and it cannot provide sufficiently detailed information to reveal the state of the blood circulation system. In the case that many hemodynamic indicators cannot be measured due to measurement methods and ethical restrictions, and the complexity of human physiology, it has become a research hotspot to characterize the circulatory system through mathematical models and simulate the effects of various environmental factors on hemodynamics, which can quantitatively characterize the local and global hemodynamic information of the circulatory system. Human cardiovascular and cerebrovascular computational hemodynamic models have been proven to be useful and effective tools for analyzing physiological and mechanical mechanisms in the blood circulation system. Studies have shown that the flow of blood in the cardiovascular and cerebrovascular system follows the general laws of fluid mechanics, which provides a theoretical basis for constructing simulation models of the blood circulation system. For example, related studies have used the lumped parameter method to establish a mathematical model of the circulatory system (0-dimensional model). By modeling four heart chambers, systemic arteries and veins, the circulation of typical organs and the pulmonary circulation, and considering the autonomic regulation mechanism, they aim to focus on the changes in the response of brain and eye blood perfusion under acceleration, providing a fast method for estimating the changes in brain and eye blood flow under different accelerations (reference Variations of human cerebral and ocular blood flow during exposure to multi-axial accelerations). However, the lumped parameter model can only describe the overall characteristics of the hemodynamic changes in various parts of the subject, while the topological structure of the vascular system of important organs of the human body is complex, and the lumped parameter model cannot provide a detailed description of the hemodynamic characteristics of each vascular segment of the vascular system. In addition, studies have shown that gravity can cause significant changes in heart rate, blood pressure, flow rate and blood distribution due to changes in human posture. For example, venous flow rate in the legs can be almost halved when standing or sitting compared with the supine position, whereas it can be doubled when the head is tilted downward. Changes in body posture constitute a dynamic process because multiple control mechanisms in the human body are activated to maintain adequate blood perfusion when the orientation of the body position relative to the gravitational field changes.Based on the above background and technical issues, there is an urgent need for a model that comprehensively covers the topological structure, physiological characteristics and regulatory mechanisms of various parts of the circulatory system to study the dynamic effects of human hemodynamics under typical postures and accelerations, while reducing the consumption of computing resources.

[0003] Studies have shown that compared with 0D computational models, 1D mathematical models of the blood circulation system have the ability to reasonably predict the propagation of blood flow, blood pressure, and pulse waves, and can provide appropriate inlet / outlet boundary conditions for 3D fluid-structure interaction models. Most of the literature reported so far is related to 1D arterial models, and uses 0D models or structure tree models to define the outflow boundary conditions of 1D models. However, due to the particularity of the properties of the venous network itself (such as the vascular collapse phenomenon caused by the high compliance of the tube wall and the self-excited oscillation in the system, etc.), the number of related studies is limited. Therefore, a closed-loop cardiovascular system model that includes the topology of the vascular system of important organs throughout the body is established, and the influence of the acceleration field on blood flow is taken into account to predict the response of the global and local cardiovascular system to dynamic posture changes and acceleration field changes. At the same time, it can predict the supercritical phenomenon of the venous system under acceleration (that is, the blood flow rate may exceed the pulse wave propagation speed in some veins), which is of great significance in the evaluation of the physiological and pathological status of subjects and the hemodynamic status of pilots and astronauts. Summary of the invention

[0004] The purpose of this application is to provide a method, device, equipment, medium and product for determining hemodynamic indicators of the blood circulation system under the action of an acceleration field, which can accurately and quantitatively evaluate the hemodynamic changes of the arteriovenous system and the blood supply of various important organs of the subject under the action of acceleration.

[0005] To achieve the above objectives, this application provides the following solutions:

[0006] In a first aspect, the present application provides a method for determining hemodynamic indicators of a blood circulation system under the action of an acceleration field, comprising:

[0007] Based on the averaged statistical anatomical data of the population, a 1-dimensional hemodynamic topological model of the main arterial network and a 1-dimensional hemodynamic topological model of the main venous network of the human circulatory system were constructed respectively;

[0008] Constructing a connection model of the 1-dimensional hemodynamic topological model of the main arterial vascular network and the 1-dimensional hemodynamic topological model of the main venous vascular network based on physiological knowledge;

[0009] The connection model is characterized by using a lumped parameter model to obtain a closed-loop 0-1 dimensional coupling basic model of the human blood circulation system;

[0010] The 0-1 dimensional coupling basic model is assigned values ​​using the morphological data of the averaged vascular network of the population and the physiological data of the blood vessels in different parts;

[0011] Collect physiological data of subjects and imaging data of areas of interest;

[0012] Extracting a three-dimensional geometric model and topological structure information of a vascular network according to the imaging data;

[0013] Extracting lumen centerline and lumen cross-sectional area information from the three-dimensional geometric model of the vascular network, importing the lumen centerline and lumen cross-sectional area information into the 0-1 dimensional coupling basic model, and importing the topological connection relationship of each segment of the blood vessel into the 0-1 dimensional coupling basic model;

[0014] The 0-1 dimensional coupling basic model is simplified based on the anatomical structure and physiological characteristics of the human blood circulation system to obtain a lumped parameter model of the blood circulation system corresponding to the 0-1 dimensional coupling basic model;

[0015] constructing an objective function based on the lumped parameter model of the blood circulation system and the measured physiological data of the subject;

[0016] Iteratively solving the objective function using a parameter optimization algorithm to obtain individualized model parameters for the subject;

[0017] Assigning the subject-individualized model parameters to the 0-1 dimensional coupled basic model;

[0018] The acceleration information received by the subject is obtained, an acceleration field equivalent to the real environment is applied in the 0-1 dimensional coupling basic model after the subject's individualized model parameters are assigned, and the control equations of the 0-1 dimensional coupling basic model after the subject's individualized model parameters are assigned are solved to obtain the hemodynamic indicators of the blood circulation system under the action of the acceleration field.

[0019] Optionally, the method for determining hemodynamic indicators of the blood circulation system under the action of the acceleration field further includes between the step of "characterizing the connection model using a lumped parameter model to obtain a closed-loop 0-1 dimensional coupling basic model of the human blood circulation system" and the step of "assigning values ​​to the 0-1 dimensional coupling basic model using morphological data of the vascular network and physiological data of blood vessels at different locations":

[0020] The parameters of the 0-1 dimensional coupling basic model are regulated using the pressure reflex regulation model and the blood flow self-regulation model.

[0021] Optionally, the morphological data of the vascular network and the physiological data of blood vessels in different parts specifically include: the entrance and exit lumen area of ​​each segment of the blood vessel, the vascular length along its centerline, the impedance of the blood vessel to blood flow, vascular compliance, cardiac viscoelasticity and blood flow inertia indicators.

[0022] Optionally, the subject's physiological data includes: subject's age, heart rate, brachial artery blood pressure, cardiac output, vascular flow at the site of interest, and pulse wave velocity PWV of the circulatory system;

[0023] All of the above are patient-specific data that can be obtained through non-invasive methods.

[0024] Optionally, extracting the three-dimensional geometric model and topological structure information of the vascular network according to the imaging data specifically includes the following steps:

[0025] Segmenting and reconstructing the vascular network of the region of interest on the imaging data to obtain a three-dimensional geometric model of the vascular system of the region of interest;

[0026] Determine the centerline of the vascular network according to the three-dimensional geometric model, take points at intervals on the centerline, and obtain the local cross-sectional area of ​​the blood vessels at each point;

[0027] A one-dimensional pulse wave conduction model of the vascular system of the area of ​​interest was established based on the length of the center line of each vascular network, the cross-sectional area of ​​the segmental vascular entrances and exits, and the topological structure.

[0028] Optionally, the governing equation of the 0-1 dimensional coupled basic model after the subject-individualized model parameter assignment is expressed as follows:

[0029]

[0030] Where z represents the axial coordinate along the blood vessel, t represents time, A represents the cross-sectional area of ​​the blood vessel, Q represents blood flow, U represents the average axial blood flow velocity, P represents the average blood pressure on the cross-sectional area of ​​the lumen, ρ represents blood density, and F v represents the viscous friction force of the blood vessel wall per unit length on the blood, v is Poisson's ratio, g is the acceleration of gravity, θ is the angle between the blood vessel axis and the horizontal plane, P0 is the reference pressure when A=A0, E is the Young's modulus, σ is the blood vessel wall stress, A0 is the lumen cross-sectional area when the transmural pressure is P0, P e represents the external pressure of the blood vessel, h and r0 are the thickness and radius of the blood vessel wall at zero transmural pressure, respectively, P j and P j-1 Respectively represent C j and C j-1 Pressure at the unit; Q j and Q j+1Respectively represent from C j The flow rate in and out of the unit; R j and L j Respectively represent the connection C j and C j-1 Impedance and inertia coefficient, C j and C j-1 represent the vascular compliance at the j-th node and the j-1-th node respectively.

[0031] In a second aspect, the present application provides a device for determining hemodynamic indices of a blood circulation system under the action of an acceleration field, the device for determining hemodynamic indices of a blood circulation system under the action of an acceleration field comprising:

[0032] A 1-dimensional hemodynamic topological model construction module of the main arterial-main venous vascular network, which is used to construct a 1-dimensional hemodynamic topological model of the main arterial vascular network and a 1-dimensional hemodynamic topological model of the main venous vascular network of the human blood circulation system based on the averaged statistical anatomical data of the population;

[0033] A connection model construction module is used to construct a connection model of the 1-dimensional hemodynamic topological model of the main arterial vascular network and the 1-dimensional hemodynamic topological model of the main venous vascular network based on physiological knowledge, so as to obtain a closed-loop 0-1-dimensional coupling basic model of the human blood circulation system;

[0034] A first assignment module, used for assigning values ​​to the 0-1 dimensional coupling basic model using morphological data of the vascular network and physiological data of blood vessels at different locations;

[0035] A subject data collection module, used to collect the subject's physiological data and imaging data of the part of interest;

[0036] A geometric topological structure information extraction module, used to extract the geometric topological structure information of the vascular network according to the imaging data;

[0037] A second assignment module is used to extract the lumen centerline and lumen cross-sectional area information from the three-dimensional geometric model of the vascular network, and import the lumen centerline and lumen cross-sectional area information into the 0-1 dimensional coupling basic model, and import the topological connection relationship of each segment of the blood vessel into the 0-1 dimensional coupling basic model;

[0038] A subject simplified lumped parameter model acquisition module, used to simplify the 0-1 dimensional coupling basic model based on the anatomical structure and physiological parameters of the human blood circulation system to obtain a lumped parameter model of the blood circulation system corresponding to the 0-1 dimensional coupling basic model;

[0039] An objective function construction module, used for constructing an objective function based on the lumped parameter model of the blood circulation system and the physiological data of the subject;

[0040] An objective function solving module, used to iteratively solve the objective function using a parameter optimization algorithm to obtain individualized model parameters for the subject;

[0041] A third assignment module, used for assigning the subject's individualized model parameters to the 0-1 dimensional coupling basic model;

[0042] The hemodynamic index solving module is used to obtain the acceleration information received by the subject, apply an acceleration field equivalent to the real environment in the 0-1 dimensional coupling basic model after the individualized model parameters of the subject are assigned, and solve the control equations of the 0-1 dimensional coupling basic model after the individualized model parameters of the subject are assigned, so as to obtain the hemodynamic indexes of the blood circulation system under the action of the acceleration field.

[0043] In a third aspect, the present application provides a computer device, comprising: 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 steps of the method for determining hemodynamic indicators of the blood circulatory system under the action of an acceleration field as described in any one of the above.

[0044] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for determining hemodynamic indicators of the blood circulatory system under the action of an acceleration field as described above.

[0045] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the method for determining hemodynamic indicators of the blood circulatory system under the action of an acceleration field as described in any one of the above.

[0046] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0047] 1. Compared with the prior art methods for evaluating the hemodynamic effects of pilots and other subjects when they are subjected to acceleration changes, the 0-1 dimensional coupling basic model adopted in this application has better physiological matching than the concentrated parameters (0-dimensional model) commonly used by predecessors, and has a good balance between computing resources and computing accuracy. In addition, this application embeds the physiological regulation mechanism of the human body, and at the same time more comprehensively considers various types of physiologically realistic arterial terminal branch-venous terminal branch connection model architectures.

[0048] 2. This application integrates the advantage of the 0-dimensional model in that it can quickly determine the model parameters, constructs a 0-dimensional model corresponding to the 0-1 dimensional coupling basic model, and combines this model with a parameter optimization algorithm to perform local and global searches for the optimal solutions of the model parameters with clinical measured indicators as the target. The obtained model parameters are assigned to the centralized parameter part of the 0-1 dimensional geometric multi-scale model, and finally the circulatory system functional parameters corresponding to the patient's actual physiology are obtained. At the same time, an individualized parameter import port for the subject is developed, including the physiological parameters and the 1-dimensional vascular system morphological and topological parameters, which can perform an overall synchronous evaluation of the overall circulatory system and the local organ vascular system.

[0049] 3. Compared with most previous studies that only modeled the main arterial system in one dimension, this application characterized the venous system in the form of a one-dimensional model and rationally arranged the venous valve model in the entire venous network, while taking into account its actual anatomical number and position. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0051] Figure 1 A flow chart of a method for determining hemodynamic indicators of a blood circulation system under the action of an acceleration field provided in one embodiment of the present application;

[0052] Figure 2 This is a schematic diagram of a 0-1 dimensional coupling basic model of the human blood circulation system according to an embodiment of the present application;

[0053] Figure 3 This is a schematic diagram of the heart-lung model coupling according to an embodiment of the present application;

[0054] Figure 4 This is a schematic diagram of the arteriovenous connection mode of the human blood circulation system in one embodiment of the present application; Part A is a peripheral vascular connection model; Part B is a liver vascular connection model; Part C is an upper limb circulation connection model; Part D is a lower limb circulation connection model; Part E is a coronary circulation connection model; Parts F to I are cerebral circulation connection models;

[0055] Figure 5 This is a schematic diagram of a qualitative comparative analysis of blood flow / blood pressure characteristic waveforms at various parts of the blood circulation system (measured waveform vs. simulated waveform) in one embodiment of the present application;

[0056] Figure 6A schematic diagram of the relationship between the acceleration angles of a blood vessel segment with a cross-sectional area of ​​A and a length of z according to an embodiment of the present application;

[0057] Figure 7 This is a schematic diagram of a method for constructing an individualized cerebral artery 1D model based on medical imaging information according to an embodiment of the present application;

[0058] Figure 8 This is a blood pressure waveform diagram of the aorta, left internal carotid artery and left external iliac artery in supine, sitting and standing postures according to an embodiment of the present application;

[0059] Fig. 9 This is a graph showing the changing trends of simulated blood pressure, systolic blood pressure (SBP, dot-shaped identifier), diastolic blood pressure (DBP, triangle-shaped identifier), and mean arterial pressure (MAP, square-shaped identifier) ​​during the parabolic flight mode of an embodiment of the present application, and their comparison with the physiological measured data reported in the literature;

[0060] Fig.10 A schematic diagram of basic components of a centralized parameter model according to an embodiment of the present application;

[0061] Fig.11 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0062] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0063] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0064] See also Figure 1 , Figure 1 A flow chart of a method for determining hemodynamic indicators of a blood circulation system under an acceleration field provided in an embodiment of the present application, the method specifically comprises the following steps:

[0065] Step 1: Based on the averaged statistical anatomical data of the population, a one-dimensional hemodynamic topological model of the main arterial network and a one-dimensional hemodynamic topological model of the main venous network of the human circulatory system are constructed respectively.

[0066] Step 2: Based on physiological knowledge, a connection model of the 1-dimensional hemodynamic topological model of the main arterial vascular network and the 1-dimensional hemodynamic topological model of the main venous vascular network is constructed to obtain a closed-loop 0-1-dimensional coupling basic model of the human blood circulation system.

[0067] Among them, physiological knowledge mainly refers to knowledge related to human anatomy. For example, blood is pumped from the left ventricle into the aorta, part of the blood in the aorta flows to the brain, part flows to the left and right arms, and part flows to the abdomen. The bifurcation position of the vascular network in human anatomy and the mutual connection relationship are the physiological knowledge.

[0068] Specifically, a lumped parameter model is used to characterize the connection model.

[0069] See Figure 2 This application constructs a closed-loop multi-scale cardiovascular basic model. The basic model parameters are all population average data, including arterial / venous networks represented by 1D models and cardiopulmonary circulation and peripheral circulation represented by 0D models. The specific steps of model construction are:

[0070] The entire 1D arterial system includes the human body's aorta and major organ artery networks ( Figure 2 The entire 1D venous system includes the main branch veins and the main organ venous network ( Figure 2 The right part of the figure). The 0-dimensional model connects the end of the 1-dimensional artery model and the end of the 1-dimensional vein model. The interface is as follows: Figure 4 As shown. The 0-dimensional lumped parameter model based on the Windkessel-3 element model is used to connect the 1-dimensional terminal arteries and terminal veins, including arterioles, capillaries and venules. Based on physiological knowledge, the topological structures of the vascular networks of different organs (parts) are different. The artery-vein 0-dimensional connection model in the 0-1-dimensional coupling basic model includes six types of interface models, all of which are arteriole-capillary-venule models based on the Windkessel model, specifically: cardiopulmonary circulation (see Figure 3 ); vascular network in the form of single channel connection ( Figure 4 The liver vascular network ( Figure 4 Left / right upper limb vascular network ( Figure 4 C in the left / right lower limb vascular network ( Figure 4 D in the coronary circulation ( Figure 4 E in the cerebral vascular network ( Figure 4 F to I in the ).

[0071] In addition, in the population averaged basic model of this step, the present invention uses the pressure reflex model reported in the literature to regulate the main parameters of the 0-1 dimensional coupling basic model with reference to the autonomic nervous regulation of the actual physiological process. According to physiological knowledge, the 0-1 dimensional coupling basic model of the present invention includes two types of control mechanisms: (1) autonomic regulation mediated by sympathetic and parasympathetic nervous responses, affecting heart rate, cardiac contractility, peripheral vascular resistance and compliance; (2) mediated by responses to local changes in myogenic tension, metabolic demand and carbon dioxide concentration, affecting coronary circulation and cerebral circulation vascular resistance.

[0072] Among them, in the second mechanism, the blood circulation system of the coronary arteries and brain regions has the ability to maintain basic blood supply when the perfusion pressure changes, that is, the ability of automatic regulation of blood flow, which is a local automatic regulation mechanism rather than being regulated by nerves.

[0073] In the baroreflex regulation model, the sympathetic and parasympathetic nerve activities are regulated by the relationship between the sigmoidal function and the mean arterial pressure Pa. The first-order differential equation is used to model the changes of the controlled parameters in the cardiovascular system model, including heart rate, the contractility of the four ventricles, and the compliance and resistance of different organs. The specific steps are as follows:

[0074] The cardiovascular system control model includes short-term regulatory mechanisms that can last for minutes, including carotid sinus, aortic wall pressure receptors, peripheral circulation chemical receptors, autoregulatory mechanisms, and ischemic responses directly mediated by the central nervous system. The body receives information about changes in blood pressure from pressure receptors and chemical receptors, which are processed by the autonomic nervous system to regulate sympathetic and parasympathetic nerve activity. Sympathetic and parasympathetic nerve fibers further regulate the cardiovascular system by changing heart rate, maximum ventricular contractility (left ventricle and right ventricle), peripheral vascular resistance, and systemic venous unstressed blood volume. The premise for achieving the above neural regulatory activities is that the heart rate is controlled by both sympathetic and parasympathetic nerves, and other receptors are regulated only under the control of sympathetic fibers.

[0075] The autonomic regulation process is modeled as pressure regulation, including heart rate, cardiac contractility, peripheral vascular resistance and circulatory system compliance, and is defined as a function of mean arterial blood pressure. Alternatively, a first-order differential equation is defined as follows:

[0076]

[0077] Wherein, parameter X(t) is the controlled parameter (heart rate, cardiac contractility, peripheral vascular resistance and circulatory system compliance), X c (P a) is the set point function, τ represents the time constant, which characterizes the time required for the variable to achieve its full effect. For different variables, the corresponding τ value is also different. In reality, the heart rate data of the subject can be directly collected in a non-invasive and simple way and imported into the basic model in real time. Therefore, the heart rate is not modeled using the set point function.

[0078] Peripheral circulatory resistance and cardiac contractility respond to arterial blood pressure as follows:

[0079]

[0080] Use the sigmoidal function, parameter X max and X min It is the maximum and minimum value of the controlled parameter X(t). Combined with the characteristics of the sigmoidal function, it can effectively display the parameter saturation, so that the extreme value of the parameter corresponds to the maximum expansion and contraction of the blood vessel. In addition, the increase in vascular tension leads to a decrease in compliance to cope with the decrease in arterial blood pressure. The response of vascular compliance to arterial blood pressure has the following forms:

[0081]

[0082] The formula produces a decreasing sigmoidal curve (ie, for decreasing arterial pressure, X c (P a ) will increase), and the equation produces an increasing sigmoidal curve (i.e., for decreasing pressure, X c (P a ) value will decrease).

[0083] The present invention embeds the blood flow automatic regulation mechanism in the model to simulate the ability of the coronary circulation and cerebral vascular network microcirculation vessels (mainly the arterioles) to automatically respond to the reduction of blood flow and expand in a resting state (i.e., the blood flow automatic regulation function). The specific method is to reasonably reproduce the real physiological blood pressure-flow relationship of the coronary circulation and cerebral circulation based on the clinically measured perfusion pressure-blood flow curve through feedback regulation of the peripheral vascular impedance. The specific regulation method can select a negative feedback regulation mechanism or a PID regulation mechanism.

[0084] Coronary blood flow and cerebral blood flow can remain unchanged when the perfusion pressure changes within a certain range. This phenomenon reflects that the microcirculation in the relevant parts has the ability to maintain constant blood flow through myogenic, shear-dependent or compensatory vascular reactions, that is, the automatic regulation function of blood flow. For example, animal experimental studies have found that sudden changes in perfusion pressure can cause instantaneous changes in coronary blood flow, but the blood flow will spontaneously return to its original level after 30s to 2min through the regulation of coronary microcirculation. On the other hand, when the perfusion pressure deviates too much from its physiological range, the automatic regulation efficiency of coronary blood flow will be significantly reduced, resulting in a nonlinear relationship between blood flow and perfusion pressure. In the present invention, we embed a control mechanism in the coupling model to simulate the real-time dynamic response process of coronary artery and cerebral blood flow. Therefore, the present invention reproduces the automatic regulation function of blood flow in coronary microcirculation and cerebral microcirculation by extracting the stable relationship between coronary perfusion pressure and blood flow observed in animal experiments reported in the literature. Specifically, the automatic regulation function uses a fourth-order polynomial function to fit the animal experimental data set reported in the literature to characterize the relationship between coronary / cerebral perfusion pressure and blood flow. Considering that the autoregulation function of coronary / cerebral blood flow is mainly mediated by the arterioles in the microcirculation, the present invention adopts a proportional-integral-differential feedback control loop to automatically adjust the arteriolar impedance (i.e. Figure 4 R in E a ). For the needs of numerical calculation, the discretized arteriolar impedance PID control expression is:

[0085]

[0086] In the formula, R k and R k+1 represents the arterial impedance at the kth and k+1th iterations respectively; cor(k) is R k The correction function is calculated by the normalized mean blood flow (Q k , that is, the ratio of actual blood flow to baseline normal blood flow) and the perfusion pressure (P k ) corresponds to the target blood flow (Q R , that is, the blood flow autoregulation curve and P k The difference between the corresponding blood flow p , K i and K d It should be noted that, considering the differences in blood perfusion conditions of each myocardial layer and the stress state of microcirculatory blood vessels, the present invention performs blood flow feedback regulation on each myocardial layer respectively.

[0087] In the 0-1 dimensional coupling basic model of step 2, valves play an important role in controlling blood flow and maintaining normal heart function, especially venous valves, which play a vital role in keeping blood flowing back to the heart and preventing blood reflux in the venous system in the blood circulation system. The present invention takes into account the actual anatomical distribution of venous valves in the entire venous system, and describes the dynamic movement of venous valves based on the actual number and position of venous valves averaged by the statistical population. The valve model (including the heart valve model and the venous valve model) used in the present invention is as follows:

[0088] The static pressure drop across the valve is characterized by Bernoulli's equation:

[0089]

[0090] Where t is time, p1 and p2 represent the pressure on both sides of the valve, B is the Bernoulli impedance, q is the flow through the valve, ρ is the blood density, L represents the blood inertia, l eff and A eff are the effective valve flow path length and opening area, respectively.

[0091]

[0092] Among them, A eff (t) is the effective opening area of ​​the valve; Valve status index Aeff,max and A eff,min It is the maximum and minimum effective opening area that the valve can achieve.

[0093]

[0094] The formula can effectively simulate the dynamic characteristics of the valve. The instantaneous rate of change relative to time adopts the above valve opening form (assuming p1-p2>0), where K vo Characterizes the rate coefficient of valve opening. This formula shows that if the instantaneous pressure difference is large, the valve opening rate becomes larger. For a given pressure difference, when the valve approaches the fully open position, the opening rate slows down. Conversely, valve closure (occurring when p1-p2<0) is characterized by the following formula:

[0095]

[0096] Among them, K vc is the rate coefficient of valve closure.

[0097] The valve motion model used in the present invention consists of two coefficients K vo and K vcThe higher the value, the faster the valve opening and closing rate, while the lower the value, the slower the valve opening and closing rate.

[0098] Step 3: Assign values ​​to the 0-1 dimensional coupling basic model using the morphological data of the averaged vascular network of the population and the physiological data of blood vessels in different parts.

[0099] Specifically, the model parameters of the 0-1 dimensional coupling basic model are assigned according to the literature report data and the non-invasive physiological measurement data, including the morphological data of the vascular network and the physiological data of the blood vessels in different parts (the impedance of the blood vessels to the blood flow, the compliance of the blood vessels, the viscoelasticity of the heart, and the inertia index of the blood flow), so as to ensure that the hemodynamic simulation results of the model can obtain the blood flow characteristic pressure-flow waveform of each part averaged by the population (specifically, Figure 5 shown).

[0100] Step 4: Collect the subject's physiological data and imaging data of the area of ​​interest.

[0101] Among them, the physiological data include the subject's age, heart rate, brachial artery blood pressure, cardiac output, vascular flow in the area of ​​interest, and pulse wave velocity PWV physiological indicators.

[0102] Step 5: Extracting the three-dimensional geometric model and topological structure information of the vascular network based on the imaging data.

[0103] Step 6: Extract the lumen centerline and lumen cross-sectional area information from the three-dimensional geometric model of the vascular network, import the lumen centerline and lumen cross-sectional area information into the 0-1 dimensional coupling basic model, and import the topological connection relationship of each blood vessel segment into the 0-1 dimensional coupling basic model.

[0104] Steps 5 and 6 specifically involve constructing a three-dimensional model of the local vascular system based on the real computed tomography angiography image or magnetic resonance image of the organ / part of interest, extracting the lumen centerline and lumen cross-sectional area information, and importing the parameters into the corresponding parameter assignment positions in the 0-1 dimensional coupling basic model through the parameter port.

[0105] Taking cerebral arteries as an example, the specific extraction steps are as follows:

[0106] Segmenting and reconstructing the region of interest of the magnetic resonance image to obtain a three-dimensional geometric model of the vascular system at the site; determining the center line of the vascular network based on the three-dimensional geometric model, taking points at intervals on the center line, and obtaining the local cross-sectional area of ​​the blood vessels at each point;

[0107] A 1D pulse wave conduction model of the vascular system was established based on the length of the centerline of each vascular network, the cross-sectional area of ​​the segmental vascular inlet and outlet, and the topological structure (see Figure 7).

[0108] Step 7: Simplify the 0-1 dimensional coupling basic model based on the anatomical structure and physiological characteristics of the human blood circulation system to obtain a lumped parameter model of the blood circulation system corresponding to the 0-1 dimensional coupling basic model.

[0109] Step 8: Constructing an objective function based on the lumped parameter model of the blood circulation system and the physiological data of the subject.

[0110] Step 9: Use a parameter optimization algorithm to iteratively solve the objective function to obtain model parameters individualized for the subject.

[0111] Specifically, a centralized parameter model of the blood circulation system corresponding to the 0-1 dimensional basic model is constructed based on the anatomical structure and physiological characteristics of the human blood circulation system. The target optimization function is set in combination with the human physiological data obtained by actual measurement. The model parameters individualized by the patient are obtained by using the parameter optimization algorithm and assigned to the corresponding parameter part of the 0-1 dimensional model. The present invention provides two feasible parameter optimization schemes:

[0112] (1) In the case where a small number of clinical target physiological values ​​can be obtained, a 0-dimensional cardiovascular system concentrated parameter model is constructed and combined with a parameter optimization algorithm such as the Nelder-Mead algorithm. Based on the numerical calculation results of the model and the individualized data obtained in step S05, a parameter optimization objective function is established; the model is calibrated through numerical iteration to achieve individualized correspondence between the cardiovascular function parameters of the model and the patient.

[0113] (2) In cases where a large number of clinical target physiological values ​​are available, a 0-dimensional centralized parameter model of the cardiovascular system is constructed. By combining local identifiability, Bayesian estimation, and maximum a posteriori simplex optimization, a multi-level estimation algorithm, i.e., based on prior information, can significantly reduce the posterior variance of parameter estimation and improve the accuracy of parameter estimation.

[0114] Step 10: Assign the subject-individualized model parameters to the 0-1 dimensional coupled basic model.

[0115] Step 11: Obtain the acceleration information received by the subject, apply an acceleration field equivalent to the real environment in the 0-1 dimensional coupling basic model after the individualized model parameters of the subject are assigned, and couple and solve the control equations of the 0-1 dimensional coupling basic model after the individualized model parameters of the subject, so as to obtain the hemodynamic indicators of the blood circulation system under the action of the acceleration field.

[0116] Among them, the hemodynamic indicators specifically include: the dynamic change information of the lumen cross-sectional area of ​​the blood vessels in each segment of the arterial system and venous system, blood pressure, and blood perfusion flow, as well as the real-time quantitative evaluation of the hemodynamic indicators when the acceleration changes.

[0117] Specifically, the hemodynamic effect of the human cardiovascular system can be used to simulate the blood flow of any artery or vein according to the following control equation:

[0118] The governing equations for the 1D model of hemodynamics in flexible vessels can be derived from the conservation of mass and momentum balance applied to both impermeable and deformable axisymmetric vessels:

[0119]

[0120] Wherein, z is the axial coordinate along the blood vessel, t represents time, A represents the cross-sectional area of ​​the blood vessel, U represents the average axial blood flow velocity, P represents the average blood pressure on the lumen cross section, ρ represents blood density, g represents gravitational acceleration, and in the present invention, g>0 represents that gravity acts in the positive direction of the z-axis coordinate, g<0 represents that gravity acts in the negative direction of the z-axis coordinate, and θ represents the angle between the blood vessel axis and the horizontal plane (e.g. Figure 6 shown), F v represents the friction force generated by the blood vessel wall per unit length on the blood; E represents Young's modulus, υ represents Poisson's ratio, h and r0 represent the thickness of the blood vessel wall and the radius of the blood vessel under zero transmural pressure, respectively, P0 represents the reference pressure when A=A0, P e The external pressure of the blood vessels.

[0121] Based on the 1D blood flow control equation, the related equations are further linearized to obtain a model that contains only three parameters and can characterize the blood flow state in a section of blood vessels, namely the concentrated parameter (0-dimensional) modeling method. In the model calculation, the 0-dimensional partial model equation is solved by the fourth-order Runge-Kutta method. The control equation follows the law of conservation of mass and momentum, and the corresponding control equations are defined at the pressure and flow nodes respectively (see Fig.10 ):

[0122]

[0123] Where P j and P j-1 Respectively represent C j and C j-1 The pressure at the unit; t represents time; Q j and Q j+1 Respectively represent from C j The flow rate in and out of the unit; R j and L j Respectively represent the connection C j and Cj-1 The impedance and inertia coefficient.

[0124] Through the above-mentioned determination method, the embodiment of the present application realizes the quantitative evaluation of the hemodynamic effects of the subject's cardiovascular and cerebrovascular blood circulation system (artery / venous) by integrating physiological measurements and numerical simulation. Especially when the subject is in an acceleration field environment and in the dynamic process of changes in body posture, the robustness of the model greatly improves the accuracy of the evaluation, and has strong ease of use and practicality.

[0125] The acceleration to which the human body is subjected and changes in its posture have a significant impact on the cardiovascular and cerebrovascular systems, especially when the acceleration field in which the subject is located changes, such as when standing upright, sitting, lying flat, or during airplane takeoff and landing, as well as in extreme cases such as in manned space flight, which can lead to significant changes in cardiovascular function. Figure 8 The simulated blood pressure waveforms of the aorta, left internal carotid artery and left external iliac artery in three postures of adult subjects, standing, sitting and lying, are displayed. The trend of blood pressure changes with posture is consistent with that reported in the literature. Fig. 9 The figure shows the continuous change waveform of the subject's blood pressure when the acceleration of the subject changes continuously (simulating the parabolic flight in the actual scene). The change trend is consistent with the literature report ( Fig. 9 The measured data of systolic, diastolic and mean pressure changes with acceleration are consistent with those shown in the table.

[0126] Based on the same inventive concept, the embodiment of the present application also provides a device for determining hemodynamic indices of a blood circulation system under the action of an acceleration field, which is used to implement the method for determining hemodynamic indices of a blood circulation system under the action of an acceleration field. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations of the embodiments of one or more devices for determining hemodynamic indices of a blood circulation system under the action of an acceleration field provided below can refer to the limitations of the method for determining hemodynamic indices of a blood circulation system under the action of an acceleration field above, and will not be repeated here.

[0127] In an exemplary embodiment, a device for determining hemodynamic indicators of a blood circulation system under the action of an acceleration field is provided, comprising:

[0128] A 1-dimensional hemodynamic topological model construction module of the main arterial-main venous vascular network, which is used to construct a 1-dimensional hemodynamic topological model of the main arterial vascular network and a 1-dimensional hemodynamic topological model of the main venous vascular network of the human blood circulation system based on the averaged statistical anatomical data of the population;

[0129] A connection model construction module is used to construct a connection model of the 1-dimensional hemodynamic topological model of the main arterial vascular network and the 1-dimensional hemodynamic topological model of the main venous vascular network based on physiological knowledge, so as to obtain a closed-loop 0-1-dimensional coupling basic model of the human blood circulation system;

[0130] A first assignment module is used to assign values ​​to the 0-1 dimensional coupling basic model using the morphological data of the averaged vascular network of the population and the physiological data of the blood vessels at different locations;

[0131] A subject data collection module, used to collect the subject's physiological data and imaging data of the part of interest;

[0132] A geometric topological structure information extraction module, used to extract a three-dimensional geometric model and topological structure information of a vascular network according to the imaging data;

[0133] A second assignment module is used to extract the lumen centerline and lumen cross-sectional area information from the three-dimensional geometric model of the vascular network, and import the lumen centerline and lumen cross-sectional area information into the 0-1 dimensional coupling basic model, and import the topological connection relationship of each segment of the blood vessel into the 0-1 dimensional coupling basic model;

[0134] A subject simplified lumped parameter model acquisition module, used to simplify the 0-1 dimensional coupling basic model based on the anatomical structure and physiological characteristics of the human blood circulation system, and obtain a lumped parameter model of the blood circulation system corresponding to the 0-1 dimensional coupling basic model;

[0135] An objective function construction module, used to construct an objective function based on the lumped parameter model of the blood circulation system and the measured physiological data of the subject;

[0136] An objective function solving module, used to iteratively solve the objective function using a parameter optimization algorithm to obtain individualized model parameters for the subject;

[0137] A third assignment module, used for assigning the subject's individualized model parameters to the 0-1 dimensional coupling basic model;

[0138] The hemodynamic index solving module is used to obtain the acceleration information received by the subject, apply an acceleration field equivalent to the real environment in the 0-1 dimensional coupling basic model after the individualized model parameters of the subject are assigned, and solve the control equations of the 0-1 dimensional coupling basic model after the individualized model parameters of the subject are assigned, so as to obtain the hemodynamic indexes of the blood circulation system under the action of the acceleration field.

[0139] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Fig.11 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data for determining hemodynamic indicators of the blood circulation system. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for determining hemodynamic indicators of the blood circulation system under the action of an acceleration field is implemented.

[0140] Those skilled in the art will understand that Fig.11 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0141] In an exemplary embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0142] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0143] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0144] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0145] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0146] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0147] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0148] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for determining hemodynamic indicators of a blood circulation system under the action of an acceleration field, characterized in that: The method for determining the hemodynamic index of the blood circulation system under the action of the acceleration field comprises: Based on the averaged statistical anatomical data of the population, a 1-dimensional hemodynamic topological model of the main arterial network and a 1-dimensional hemodynamic topological model of the main venous network of the human circulatory system were constructed respectively; Based on physiological knowledge, a connection model of the 1-dimensional hemodynamic topological model of the main arterial vascular network and the 1-dimensional hemodynamic topological model of the main venous vascular network is constructed to obtain a closed-loop 0-1-dimensional coupling basic model of the human blood circulation system; The 0-1 dimensional coupling basic model is assigned values ​​using the morphological data of the averaged vascular network of the population and the physiological data of the blood vessels in different parts; Collect physiological data of subjects and imaging data of areas of interest; Extracting a three-dimensional geometric model and topological structure information of a vascular network according to the imaging data; Extracting lumen centerline and lumen cross-sectional area information from the three-dimensional geometric model of the vascular network, importing the lumen centerline and lumen cross-sectional area information into the 0-1 dimensional coupling basic model, and importing the topological connection relationship of each segment of the blood vessel into the 0-1 dimensional coupling basic model; The 0-1 dimensional coupling basic model is simplified based on the anatomical structure and physiological characteristics of the human blood circulation system to obtain a lumped parameter model of the blood circulation system corresponding to the 0-1 dimensional coupling basic model; constructing an objective function based on the lumped parameter model of the blood circulation system and the measured physiological data of the subject; Iteratively solving the objective function using a parameter optimization algorithm to obtain individualized model parameters for the subject; Assigning the subject-individualized model parameters to the 0-1 dimensional coupled basic model; The acceleration information received by the subject is obtained, an acceleration field equivalent to the real environment is applied in the 0-1 dimensional coupling basic model after the subject's individualized model parameters are assigned, and the control equations of the 0-1 dimensional coupling basic model after the subject's individualized model parameters are assigned are solved to obtain the hemodynamic indicators of the blood circulation system under the action of the acceleration field.

2. The method for determining hemodynamic indicators of the blood circulation system under the action of an acceleration field according to claim 1, characterized in that: The method for determining hemodynamic indicators of the blood circulation system under the action of the acceleration field further includes, between the step of "characterizing the connection model using a lumped parameter model to obtain a closed-loop 0-1 dimensional coupling basic model of the human blood circulation system" and the step of "assigning values ​​to the 0-1 dimensional coupling basic model using morphological data of the vascular network and physiological data of blood vessels at different locations": The parameters of the 0-1 dimensional coupling basic model are regulated using the pressure reflex regulation model and the blood flow self-regulation model.

3. The method for determining hemodynamic indicators of the blood circulation system under the action of an acceleration field according to claim 1, characterized in that: The morphological data of the vascular network and the physiological data of blood vessels in different parts specifically include: the entrance and exit lumen area of ​​each segment of the blood vessel, the vascular length along its centerline, the impedance of the blood vessel to blood flow, vascular compliance, cardiac viscoelasticity and blood flow inertia index.

4. The method for determining hemodynamic indicators of the blood circulation system under the action of an acceleration field according to claim 1, characterized in that: The physiological data of the subject include: subject's age, heart rate, brachial artery blood pressure, cardiac output, vascular flow of the site of interest, and pulse wave velocity PWV of the circulatory system.

5. The method for determining hemodynamic indicators of the blood circulation system under the action of an acceleration field according to claim 1, characterized in that: Extracting the three-dimensional geometric model and topological structure information of the vascular network according to the imaging data specifically includes the following steps: Segmenting and reconstructing the vascular network of the region of interest on the imaging data to obtain a three-dimensional geometric model of the vascular system of the region of interest; Determine the centerline of the vascular network according to the three-dimensional geometric model, take points at intervals on the centerline, and obtain the local cross-sectional area of ​​the blood vessels at each point; A one-dimensional pulse wave conduction model of the vascular system of the area of ​​interest was established based on the length of the center line of each vascular network, the cross-sectional area of ​​the segmental vascular entrances and exits, and the topological structure.

6. The method for determining hemodynamic indexes of the blood circulation system under the action of an acceleration field according to claim 1, characterized in that: The expression of the control equation of the 0-1 dimensional coupling basic model after the individualized model parameter assignment of the subject is as follows: Where z represents the axial coordinate along the blood vessel, t represents time, A represents the cross-sectional area of ​​the blood vessel, Q represents blood flow, U represents the average axial blood flow velocity, P represents the average blood pressure on the cross-sectional area of ​​the lumen, ρ represents blood density, and F v represents the viscous friction force of the blood vessel wall per unit length on the blood, v is Poisson's ratio, g is the acceleration of gravity, θ is the angle between the blood vessel axis and the horizontal plane, P0 is the reference pressure when A=A0, E is the Young's modulus, σ is the blood vessel wall stress, A0 is the lumen cross-sectional area when the transmural pressure is P0, P e represents the external pressure of the blood vessel, h and r0 are the thickness and radius of the blood vessel wall at zero transmural pressure, respectively, P j and P j-1 Respectively represent C j and C j-1 Pressure at the unit; Q j and Q j+1 Respectively represent from C j The flow rate in and out of the unit; R j and L j Respectively represent the connection C j and C j-1 Impedance and inertia coefficient, C j and C j-1 represent the vascular compliance at the j-th node and the j-1-th node respectively.

7. A device for determining hemodynamic indicators of a blood circulation system under the action of an acceleration field, characterized in that: The device for determining hemodynamic indexes of the blood circulation system under the action of the acceleration field comprises: A 1-dimensional hemodynamic topological model construction module of the main arterial-main venous vascular network, which is used to construct a 1-dimensional hemodynamic topological model of the main arterial vascular network and a 1-dimensional hemodynamic topological model of the main venous vascular network of the human blood circulation system based on the averaged statistical anatomical data of the population; A connection model construction module is used to construct a connection model of the 1-dimensional hemodynamic topological model of the main arterial vascular network and the 1-dimensional hemodynamic topological model of the main venous vascular network based on physiological knowledge, so as to obtain a closed-loop 0-1-dimensional coupling basic model of the human blood circulation system; A first assignment module is used to assign values ​​to the 0-1 dimensional coupling basic model using the morphological data of the averaged vascular network of the population and the physiological data of the blood vessels at different locations; A subject data collection module, used to collect the subject's physiological data and imaging data of the part of interest; A geometric topological structure information extraction module, used to extract a three-dimensional geometric model and topological structure information of a vascular network according to the imaging data; A second assignment module is used to extract the lumen centerline and lumen cross-sectional area information from the three-dimensional geometric model of the vascular network, and import the lumen centerline and lumen cross-sectional area information into the 0-1 dimensional coupling basic model, and import the topological connection relationship of each segment of the blood vessel into the 0-1 dimensional coupling basic model; A subject simplified lumped parameter model acquisition module, used to simplify the 0-1 dimensional coupling basic model based on the anatomical structure and physiological characteristics of the human blood circulation system, and obtain a lumped parameter model of the blood circulation system corresponding to the 0-1 dimensional coupling basic model; An objective function construction module, used to construct an objective function based on the lumped parameter model of the blood circulation system and the measured physiological data of the subject; An objective function solving module, used to iteratively solve the objective function using a parameter optimization algorithm to obtain individualized model parameters for the subject; A third assignment module, used for assigning the subject's individualized model parameters to the 0-1 dimensional coupling basic model; The hemodynamic index solving module is used to obtain the acceleration information received by the subject, apply an acceleration field equivalent to the real environment in the 0-1 dimensional coupling basic model after the individualized model parameters of the subject are assigned, and solve the control equations of the 0-1 dimensional coupling basic model after the individualized model parameters of the subject are assigned, so as to obtain the hemodynamic indexes of the blood circulation system under the action of the acceleration field.

8. A computer device comprising: 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 steps of the method for determining hemodynamic indicators of the blood circulatory system under the action of an acceleration field as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for determining hemodynamic indicators of the blood circulation system under the action of an acceleration field described in any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method for determining hemodynamic indicators of the blood circulation system under the action of an acceleration field described in any one of claims 1 to 6 are implemented.

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