Clinical intervention analysis system for extracorporeal circulation based on three-dimensional simulation

Abstract

The application relates to the technical field of medical systems, in particular to a clinical intervention analysis system for extracorporeal circulation based on three-dimensional simulation, which constructs an individualized hemodynamic model by fusing patient images, physiological data and extracorporeal circulation parameters, accurately predicts the damage risk of a blood vessel wall, and provides quantitative support for clinical decision-making; meanwhile, the system constructs an individualized blood vessel tolerance model by integrating image, physiological and equipment data, realizes quantitative evaluation of fragile factors such as blood vessel calcification and plaque, and provides a basis for accurate early warning; based on real-time extracorporeal circulation parameters and blood flow simulation, the system can dynamically analyze the blood flow friction influence on blood vessels at different positions, and identify high damage risk areas in advance.

Description

Technical Field

[0001] This application relates to the field of medical system technology, and in particular to a three-dimensional simulation-based extracorporeal circulation clinical intervention analysis system. Background Technology

[0002] Cardiopulmonary bypass is a core supporting technology for cardiac surgery, but its non-physiological blood flow (such as non-pulsatile perfusion and blood dilution) can impact the patient's vascular system. Especially in vascular sites with potential lesions such as calcification and plaque, it may lead to serious complications such as intimal damage, plaque detachment, or even vascular rupture. Currently, clinical practice mainly relies on doctors' subjective risk assessment based on preoperative static imaging (such as CTA) and experience, lacking quantitative analysis of the biomechanical characteristics of the vascular wall, and even more so, the ability to dynamically assess risks in real time during surgery.

[0003] Current management methods have significant shortcomings: 1. Static assessment: Relying on preoperative imaging and experience-based judgment, it is impossible to quantify vascular fragility or dynamically update with intraoperative blood flow status; 2. Macroscopic monitoring: Intraoperative monitoring only monitors overall parameters such as mean arterial pressure and flow rate, and cannot perceive the local shear force and pressure fluctuations experienced by specific vascular segments (such as the cannulation site and aortic arch), making it difficult to achieve damage early warning; 3. Passive response: Interventions are mostly reactive measures after complications occur (such as adjusting cannulation and emergency repair), lacking proactive protection based on prediction; 4. Fragmented information: Risk-related information is scattered and lacks an integrated analysis and decision support platform. Summary of the Invention

[0004] To overcome the shortcomings and deficiencies of existing technologies, this application constructs an individualized hemodynamic model by integrating patient images, physiological data, and extracorporeal circulation parameters. This model accurately predicts the risk of vascular wall damage, providing quantitative support for clinical decision-making. Simultaneously, the system integrates imaging, physiological, and equipment data to construct an individualized vascular tolerance model, enabling quantitative assessment of vulnerable factors such as vascular calcification and plaque, providing a basis for accurate early warning. Based on real-time extracorporeal circulation parameters and blood flow simulation, the system can dynamically analyze the impact of blood flow friction on blood vessels at different locations, identifying high-risk damage areas in advance.

[0005] To achieve the above objectives, this application adopts the following technical solution: Firstly, this application provides a method for analyzing extracorporeal circulation clinical interventions based on three-dimensional simulation, including the following specific steps: Step 1: Obtain the operating status of the extracorporeal circulation device, and simultaneously obtain the blood vessel distribution, image information, and distance relative to the circulation location at each corresponding location; Step 2: Analyze the tolerance of blood vessels at each location based on the distribution of blood vessels and the image data at each location; Step 3: Analyze the impact of extracorporeal circulation on blood vessels based on the operation of the extracorporeal circulation device, blood flow, and the distance of blood vessels relative to the circulatory location; Step 4: Analyze the damage to blood vessels caused by extracorporeal circulation based on the effects of extracorporeal circulation on blood vessels and the tolerance of blood vessels at different locations. Step 5: Analyze the vascular damage results using extracorporeal circulation at each location and conduct health intervention and early warning for each location.

[0006] In one implementation of this application, the acquisition of the operating status of the extracorporeal circulation device, and the acquisition of the blood vessel distribution and status at each corresponding location, as well as the corresponding distance relative to the circulation location, includes the following specific details: S11. Obtain high-resolution CT or MRI images of the patient before surgery; the images should include enhanced angiography sequences to clearly show the morphology of blood vessels, and at the same time measure morphological parameters such as initial elasticity, diameter, curvature, and wall thickness of blood vessels through sensors. Among them, the initial elasticity is the average elastic modulus of blood vessels at corresponding locations for the corresponding age, medical history, and gender, which is obtained through historical records; used to analyze the vulnerability of blood vessels at each location. S12. Obtain the model of the cardiopulmonary bypass machine, pump head type, cannula type and size, as well as the target pump flow rate, speed, and negative pressure suction pressure operating parameters; used to analyze abnormal operation of the cardiopulmonary bypass machine and its impact on blood vessels; S13. Use medical image processing software to perform semi-automatic / automatic segmentation of the target vascular region, generate a patient-specific three-dimensional vascular model (including the aorta, cannulation location, and major branch arteries), virtually place the extracorporeal circulation cannula in the three-dimensional model, and determine its location according to the surgical plan.

[0007] In one implementation of this application, the analysis of vascular tolerance at various locations includes the following specific steps: S21. Obtain vascular images and assess vascular elasticity abnormalities based on the calcification distribution, plaque characteristics, and initial elasticity of the vascular wall in the vascular images. Among them, plaques are lesions such as hemorrhages identified by MRI. Specifically, the following steps are included: S211. Obtain images of each blood vessel and use image processing software to obtain the volume, density, and distribution of calcification in the blood vessel wall. The image processing software compares the image features on the blood vessel wall with previously identified calcification features using a similarity comparison method to obtain the region and characteristics of calcifications. It also obtains the average calcification volume, average density, and the proportion of the contact surface with the blood vessel interior to the area of ​​the blood vessel wall per unit distance. The calcification volume abnormality is obtained by dividing the average calcification volume by the safe calcification volume, the calcification density abnormality is obtained by dividing the average calcification density by the safe density, and the calcification influence abnormality is obtained by multiplying the calcification volume abnormality by the calcification density abnormality and then by the proportion of the contact surface with the blood vessel interior to the area of ​​the blood vessel wall. S212. Obtain the pixel features of each pixel in the image of the patch, and obtain the patch impact anomaly by the average of the standard deviations of the pixel values ​​of each point from the safe pixel values; S213. The internal influence abnormality coefficient is obtained by weighted summation of calcification influence abnormality and plaque influence abnormality. The initial elasticity abnormality is obtained by dividing the safe elasticity value by the initial elasticity of the corresponding blood vessel. The elasticity abnormality assessment result is obtained by multiplying the internal influence abnormality coefficient by the initial elasticity abnormality. S22. Analyze the abnormal vascular friction index based on the diameter, curvature, and wall thickness characteristics of the corresponding blood vessels; including the following specific steps: S221. Obtain the average diameter and wall thickness of the corresponding blood vessel. Divide the safe value of the average diameter and wall thickness of the corresponding blood vessel by the corresponding parameter to obtain the abnormality of the corresponding parameter. Divide the average curvature of the corresponding blood vessel by the safe value of curvature to obtain the curvature abnormality. S222. The abnormal diameter, abnormal wall thickness, and abnormal curvature are weighted and summed to obtain the vascular friction abnormality index; where the safety values ​​of the corresponding parameters are all set by medical personnel; and the weights of the weighted summation are obtained by fitting historical data. S23. The abnormal vascular elasticity assessment results are weighted and summed with the abnormal vascular friction index to obtain the abnormal vascular tolerance. The benefits of this step are: This step innovatively combines vascular morphological characteristics with pathological characteristics. By quantitatively calculating the abnormal elasticity and friction index, it achieves an objective and graded assessment of the fragility or tolerance of the blood vessels themselves. It changes the traditional subjective mode that relies on doctors' visual inspection and experience judgment, and can identify high-risk vascular segments earlier and more accurately.

[0008] In one implementation of this application, the effect of extracorporeal circulation on blood vessels includes the following specific aspects: S31. Obtain the operating parameters and fluctuations of the extracorporeal circulation device, and analyze the impact of abnormal operation of the circulation device by comparing the operating parameters with the safe range and the abnormal fluctuations. The impact of abnormal operation of the circulation equipment includes the following specific steps: The system acquires the set operating flow rate, speed, and negative pressure suction pressure of the circulating equipment; it also acquires the fluctuation value of the actual operation of the equipment in the previous stage relative to the set value, and obtains the fluctuation anomaly of the corresponding parameter by dividing the average of the absolute values ​​of the fluctuation values ​​of the corresponding parameter by the corresponding set value. The standard deviation of the operating parameters of the extracorporeal circulation device and the corresponding safe range of the parameters is obtained to obtain the comparative anomalies of the corresponding parameters. The fluctuation anomalies of the corresponding parameters are summed with the comparative anomalies of the corresponding parameters to obtain the operating anomalies of the corresponding parameters. The weighted sum of the operating anomalies of all parameters is multiplied by the device influence coefficient to obtain the impact of the operating anomalies of the circulation device. The device influence coefficient is obtained by linear fitting of historical data; the weights are obtained by analyzing the average importance of each anomaly in historical data and then fitting the data. S32. Analyze the abnormal effects of blood flow by examining blood flow patterns and the distance of blood vessels relative to circulatory locations; The analysis of abnormal blood flow includes the following specific steps: The flow rate of the corresponding blood vessel and its distance from the circulatory location are obtained. The distance effect is obtained by dividing the safe distance by the distance of the blood vessel relative to the circulatory location. The distance effect is multiplied by the distance attenuation coefficient to obtain the distance effect anomaly. The flow rate anomaly is obtained by dividing the blood vessel flow rate by the safe flow rate of the corresponding blood vessel. The blood flow effect anomaly is obtained by multiplying the flow rate anomaly by the distance effect anomaly. The safe flow rate of the corresponding blood vessel is the average flow rate of the corresponding blood vessel of healthy individuals of the corresponding age and gender. The distance attenuation coefficient is obtained by fitting the average value of historical experimental data. S33. The sum of the effects of abnormal operation of the circulatory equipment and the value 1 is multiplied by the abnormal blood flow effect to obtain the abnormal effect of extracorporeal circulation on blood vessels. The benefit of this step is that it correlates abnormal equipment operation with hemodynamic effects, and dynamically assesses the external impact of extracorporeal circulation on blood vessels. It not only focuses on the set parameters of the equipment, but also incorporates the fluctuations in actual operation, thereby capturing non-steady-state and instantaneous risk factors. This method, which combines equipment engineering parameters with physiological propagation models, makes the assessment of mechanical stress on blood vessels more real-time and predictive.

[0009] In one implementation of this application, the analysis of vascular damage caused by extracorporeal circulation includes the following specific details: The first step is to obtain information on the abnormal effects of cardiopulmonary bypass on blood vessels and the abnormalities in vascular tolerance; the two are then weighted and summed to obtain the damage analysis results of cardiopulmonary bypass on the corresponding blood vessels. The second step involves obtaining the damage analysis results for each blood vessel and comparing them with the corresponding damage analysis thresholds. Blood vessels with damage analysis thresholds greater than or equal to the thresholds are designated as damaged vessels and marked on the 3D model. Blood vessels with damage analysis thresholds less than the thresholds are designated as safe vessels. The advantage of this step is that it comprehensively and weights the intrinsic vulnerability of the blood vessels assessed in step two with the external impact intensity assessed in step three, ultimately obtaining quantitative damage analysis results. This achieves a leap from isolated factor analysis to systemic risk assessment, enabling more accurate prediction of which blood vessels are truly at risk of damage under a specific extracorporeal circulation protocol. Furthermore, it achieves automatic risk classification and visual labeling by comparing with the thresholds.

[0010] In one implementation of this application, the step of using extracorporeal circulation at various locations to analyze vascular damage and provide early warning for health intervention at each location includes the following specific steps: The location of damaged blood vessels during extracorporeal circulation is obtained and sent to medical staff, who then issue warnings for the corresponding locations. Based on the location of the damaged blood vessels, medical staff can choose to replan the circulation route and add anti-inflammatory drugs or endothelial protectants to the corresponding blood vessel locations.

[0011] Secondly, this application also provides a three-dimensional simulation-based extracorporeal circulation clinical intervention analysis system, including the following specific modules: The system includes a data acquisition module, a tolerance analysis module, an extracorporeal circulation effect module, a damage analysis module, and an intervention and early warning module. The acquisition module is used to acquire the operating status of the extracorporeal circulation device, and at the same time acquire the blood vessel distribution, image status, and distance relative to the circulation position at each corresponding location. The tolerance analysis module analyzes the tolerance of blood vessels at each location based on the blood vessel distribution and image conditions at each location. The extracorporeal circulation impact module analyzes the impact of extracorporeal circulation on blood vessels based on the operation of the extracorporeal circulation equipment, blood flow, and the distance of blood vessels relative to the circulation location. The damage analysis module performs damage analysis on blood vessels based on the effects of extracorporeal circulation on blood vessels and the tolerance of blood vessels at various locations. The intervention and early warning module provides health intervention and early warning for each location based on the analysis results of vascular damage through extracorporeal circulation at each location.

[0012] Thirdly, this application provides an electronic device comprising: a processor and a memory, wherein the memory stores a computer program that can be called by the processor, and the processor executes a three-dimensional simulation-based extracorporeal circulation clinical intervention analysis method by calling the computer program stored in the memory.

[0013] Fourthly, this application provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform a three-dimensional simulation-based extracorporeal circulation clinical intervention analysis method.

[0014] Compared with the prior art, this application has the following advantages: By integrating patient images, physiological data, and extracorporeal circulation parameters, an individualized hemodynamic model is constructed to accurately predict the risk of vascular wall damage, providing quantitative support for clinical decision-making. At the same time, by integrating imaging, physiological, and equipment data, the system constructs an individualized vascular tolerance model to achieve quantitative assessment of vulnerable factors such as vascular calcification and plaque, providing a basis for accurate early warning. Based on real-time extracorporeal circulation parameters and blood flow simulation, the system can dynamically analyze the impact of blood flow friction on blood vessels at different locations and identify high-risk injury areas in advance. Attached Figure Description

[0015] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 This is a schematic diagram of the overall process structure of the method in this application; Figure 2 This is a schematic diagram of the process for analyzing vascular tolerance at various locations in the method of this application; Figure 3 This is a schematic diagram of the process for analyzing the effects of extracorporeal circulation on blood vessels in the method of this application; Figure 4 This is a schematic diagram of the system structure of this application. Detailed Implementation

[0016] The technical solution of this application will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments and specific features in the embodiments are detailed descriptions of the technical solution of this application, rather than limitations thereof. In the absence of conflict, the embodiments and technical features in the embodiments can be combined with each other.

[0017] Please see Figures 1 to 3 , Figure 1 This is a schematic diagram of the overall process of the extracorporeal circulation clinical intervention analysis method based on three-dimensional simulation provided in the embodiments of this application, which specifically includes the following steps: Step 1: Obtain the operating status of the extracorporeal circulation device, and simultaneously obtain the blood vessel distribution, image information, and distance relative to the circulation location at each corresponding location; In this embodiment, the operation status of the extracorporeal circulation device is acquired, and the distribution and condition of blood vessels at each corresponding location, as well as their distances relative to the circulation location, are acquired. This includes the following specific details: S11. Obtain high-resolution CT or MRI images of the patient before surgery (covering the heart, aortic arch, brachiocephalic artery, descending aorta, superior and inferior vena cava, etc.); the images must include enhanced angiography sequences to clearly show the vascular morphology, and at the same time measure morphological parameters such as initial elasticity, diameter, curvature, and wall thickness of the blood vessels using sensors. Among them, the initial elasticity is the average elastic modulus of the blood vessels at the corresponding location for the corresponding age, medical history, and gender, which is obtained through historical records; used to analyze the vulnerability of blood vessels at each location; S12. Obtain the model of the cardiopulmonary bypass machine, pump head type (centrifugal pump / roller pump), cannula model and size, as well as the target pump flow rate, speed, and negative pressure suction pressure operating parameters; used to analyze abnormal operation of the cardiopulmonary bypass machine and its impact on blood vessels; S13. Use medical image processing software (such as Mimics, 3DSlicer) to perform semi-automatic / automatic segmentation of the target vascular region, generate a patient-specific three-dimensional vascular model (including the aorta, cannulation location, and major branch arteries), virtually place the extracorporeal circulation cannula in the three-dimensional model, and determine its location according to the surgical plan; at the same time, store the acquired data of various types in the corresponding storage modules.

[0018] Step 2: Analyze the tolerance of blood vessels at each location based on the distribution of blood vessels and the image data at each location; In this embodiment, the tolerance of blood vessels at various locations is analyzed, including the following specific steps: S21. Obtain vascular images and assess vascular elasticity abnormalities based on the calcification distribution, plaque characteristics, and initial elasticity of the vascular wall in the vascular images. Among them, plaques are lesions such as hemorrhages identified by MRI. Specifically, the following steps are included: S211. Obtain images of each blood vessel and use image processing software to obtain the volume, density, and distribution of calcification in the blood vessel wall. The image processing software compares the image features on the blood vessel wall with previously identified calcification features using a similarity comparison method to obtain the region and characteristics of calcifications. It also obtains the average calcification volume, average density, and the proportion of the contact surface with the blood vessel interior to the area of ​​the blood vessel wall per unit distance. The calcification volume abnormality is obtained by dividing the average calcification volume by the safe calcification volume, the calcification density abnormality is obtained by dividing the average calcification density by the safe density, and the calcification influence abnormality is obtained by multiplying the calcification volume abnormality by the calcification density abnormality and then by the proportion of the contact surface with the blood vessel interior to the area of ​​the blood vessel wall. S212. Obtain the pixel features of each pixel in the image of the patch, and obtain the patch impact anomaly by the average of the standard deviations of the pixel values ​​of each point from the safe pixel values; S213. The internal influence abnormality coefficient is obtained by weighted summation of calcification influence abnormality and plaque influence abnormality. The initial elasticity abnormality is obtained by dividing the safe elasticity value by the initial elasticity of the corresponding blood vessel. The elasticity abnormality assessment result is obtained by multiplying the internal influence abnormality coefficient by the initial elasticity abnormality. In the above steps, by quantitatively assessing the calcification and plaque characteristics of the vascular wall, the traditional image interpretation relying on subjective experience is transformed into objective and repeatable numerical indicators. This allows for early identification of structural weaknesses in the vascular wall. By calculating the results of elasticity anomaly assessments, the system can comprehensively reflect the interaction between calcification load, plaque instability, and basic vascular elasticity. This predicts the relative risk of vascular wall rupture, dissection, or plaque detachment under blood flow impact, providing crucial structural vulnerability evidence for subsequent risk hotspot fusion and localization. The assessment is based on a clear pathophysiological mechanism. The volume and density of vascular wall calcification are directly related to its stiffness, representing a late stage of atherosclerosis and significantly reducing vascular compliance. Damaged plaques such as those identified by MRI, including hemorrhage, are characteristic of vulnerable plaques. Their internal components (such as lipids and hemorrhage) exhibit high pixel heterogeneity and large standard deviation, marking instability and rupture susceptibility. Initial elasticity reflects the inherent mechanical properties of the blood vessel wall. The multiplicative model combining these three factors (abnormal calcification effect × abnormal plaque effect × abnormal initial elasticity) is based on the principle that multiple defects lead to a non-linear increase in risk. That is, when calcification is severe, plaque is unstable, and basic elasticity is poor, the overall risk of functional failure increases dramatically. It should also be noted that safe calcification volume / density, safe pixel value, and safe elasticity value are not fixed constants. Their setting should be based on large-scale clinical cohort studies, typically using the corresponding parameter distributions of healthy individuals or stable patient groups (e.g., the mean or a specific percentile, such as the upper limit of the 95% confidence interval). A better approach is to establish a stratified reference database related to age, gender, and underlying diseases (e.g., hypertension, diabetes) to achieve individualized safety baseline settings. The weighted summation weights in S213, specifically the weighting of abnormal calcification effect and abnormal plaque effect, should be determined through retrospective clinical data fitting. For example, data on existing patient imaging features and subsequent vascular complications (such as intraoperative embolism and postoperative stroke) can be collected, and machine learning models such as logistic regression can be used to determine the predictive contribution of these two types of features to adverse outcomes (i.e., regression coefficients), and these coefficients can be normalized into weights; this ensures that the evaluation model is correlated with real clinical outcomes.

[0019] S22. Analyze the abnormal vascular friction index based on the diameter, curvature, and wall thickness characteristics of the corresponding blood vessels; including the following specific steps: S221. Obtain the average diameter and wall thickness of the corresponding blood vessel. Divide the safe value of the average diameter and wall thickness of the corresponding blood vessel by the corresponding parameter to obtain the abnormality of the corresponding parameter. Divide the average curvature of the corresponding blood vessel by the safe value of curvature to obtain the curvature abnormality. S222. The abnormal diameter, abnormal wall thickness, and abnormal curvature are weighted and summed to obtain the vascular friction abnormality index; where the safety values ​​of the corresponding parameters are all set by medical personnel; and the weights of the weighted summation are obtained by fitting historical data. In the steps described above, the potential impact of vascular geometry on blood flow resistance and the local hemodynamic environment is assessed. By quantifying the degree of abnormality in diameter, wall thickness, and curvature, it reveals the inherent tendency of vessels to generate turbulence, blood stasis, or high wall shear forces due to anatomical variations. The calculated vascular friction anomaly index is a comprehensive morphological risk indicator that helps identify vessel segments that, even without severe plaque, may become injury hotspots under high-flow-rate cardiopulmonary bypass due to congenital or remodeled poor geometry. Abnormal vessel diameter (usually stenosis or dilation) alters flow velocity and pressure gradient; abnormal wall thickness (such as uneven thickening) may be accompanied by luminal irregularities; abnormal curvature (excessive tortuosity) is a major cause of secondary flow and flow separation. These geometric factors collectively determine local blood flow resistance (i.e., the physical analogue of friction) and flow stability. The weighted summation model reflects the synergistic or dominant effects of these factors on blood flow disturbance; diameter / wall thickness / curvature safety values: similar to the safety values ​​in elasticity assessment, these parameters should be set based on anatomically normal reference ranges. For example, vessels in different anatomical locations (such as the ascending aorta, brachiocephalic artery, and common carotid artery) have typical diameter and wall thickness ranges, the mean and standard deviation of which can be obtained from authoritative anatomy textbooks or large normal population image databases. The safe curvature value can be defined as the radius of curvature threshold that does not cause significant blood flow separation within the physiological range; the weights in S222 are key optimization parameters for the model and should be obtained through a data-driven approach; the best approach is to use historical patient vascular geometry data and intraoperative / postoperative hemodynamic measurements (such as turbulence intensity and pressure gradient measured by ultrasound) or related complications for correlation analysis; methods such as multiple regression or feature importance ranking (such as based on random forest models) should be used to determine the relative importance of the three features—diameter, wall thickness, and curvature—to adverse hemodynamic outcomes and quantify them as weights; S23. The abnormal vascular tolerance is obtained by weighted summation of the results of the vascular elasticity abnormality assessment and the vascular friction abnormality index. Combining the elasticity abnormality assessment results, which reflect the risk of vascular wall material properties, with the friction abnormality index, which reflects the risk of vascular geometric properties, generates a more comprehensive vascular tolerance abnormality score. This score represents a leap from a single risk dimension to multi-dimensional risk integration, and can more accurately characterize the overall vulnerability of a segment of blood vessel to external impact. Since the ultimate failure of a blood vessel (such as rupture or endothelial damage) is the result of local mechanical load (applied by blood flow influenced by geometry) exceeding the structural strength of the vascular wall (determined by material properties), a comprehensive tolerance assessment must simultaneously consider the capacity to withstand force (elasticity-related) and the magnitude and manner of the force (geometric / friction-related). Weighted summation of these two factors is a concise and effective linear fusion model. Its rationale lies in allowing adjustment of the contribution ratio of each factor to the overall risk based on clinical evidence. The weighting parameter for the weighted summation is the most crucial weighting parameter in the entire tolerance assessment model. The determination of these values ​​requires collecting a large dataset containing detailed patient imaging features (for calculating elasticity and friction abnormalities), detailed surgical parameters, and clearly defined postoperative vascular complications (such as arterial dissection, embolic events, and anastomotic bleeding). Advanced statistical models (such as the Cox proportional hazards model and machine learning classifiers) are used for analysis to determine the independent contribution (hazard ratio or feature importance) of the two combined indicators—elasticity abnormality assessment and vascular friction abnormality index—to predicting the clinical hard endpoint, thereby deriving the optimal fusion weights. This process is essentially model training and validation.

[0020] Step 3: Analyze the impact of extracorporeal circulation on blood vessels based on the operation of the extracorporeal circulation device, blood flow, and the distance of blood vessels relative to the circulatory location; In this embodiment, the effects of extracorporeal circulation on blood vessels include the following specific aspects: S31. Obtain the operating parameters and fluctuations of the extracorporeal circulation device, and analyze the impact of abnormal operation of the circulation device by comparing the operating parameters with the safe range and the abnormal fluctuations. The impact of abnormal operation of the circulation equipment includes the following specific steps: The system acquires the set operating flow rate, speed, and negative pressure suction pressure of the circulating equipment; it also acquires the fluctuation value of the actual operation of the equipment in the previous stage relative to the set value, and obtains the fluctuation anomaly of the corresponding parameter by dividing the average of the absolute values ​​of the fluctuation values ​​of the corresponding parameter by the corresponding set value. The standard deviation of the operating parameters of the extracorporeal circulation device and the corresponding safe range of the parameters is obtained to obtain the comparative anomalies of the corresponding parameters. The fluctuation anomalies of the corresponding parameters are summed with the comparative anomalies of the corresponding parameters to obtain the operating anomalies of the corresponding parameters. The weighted sum of the operating anomalies of all parameters is multiplied by the device influence coefficient to obtain the impact of the operating anomalies of the circulation device. The device influence coefficient is obtained by linear fitting of historical data; the weights are obtained by analyzing the average importance of each anomaly in historical data and then fitting the data. The benefit of this step lies in quantitatively assessing the potential impact of the stability and safety of the extracorporeal circulation device's operation on the vascular system. By simultaneously monitoring the setting deviations (contrast anomalies) and operational fluctuations (fluctuation anomalies) of key device parameters, this method can identify subclinical performance declines or abnormal operating states of the device at an early stage. The calculated impact of abnormal circulatory device operation is a comprehensive indicator that unifies anomalies in discrete technical parameters such as pump flow rate, speed, and negative pressure into a risk score reflecting the abnormal mechanical load the device may exert on the circulatory system (especially blood vessels). This helps to provide more sensitive and proactive device status warnings beyond traditional device alarms (based on single-point thresholds). The operating parameters of the extracorporeal circulation device directly determine the state of perfusion blood flow. Abnormalities in flow rate and speed directly affect the pulsatility and average flow of output blood flow, which may lead to non-physiological shear stress on the vessel wall. Abnormalities in negative pressure suction pressure may directly damage the vascular endothelium at the suction site or lead to gas embolism. Parameter deviations from the safe range (contrast anomalies) represent absolute risk, while operational fluctuations (fluctuation anomalies) represent relative instability. Combining the two allows for a more comprehensive assessment of device risk. The weighted summation model reflects the relative importance of different parameters on vascular effects, while the equipment influence coefficient is used to calibrate the impact of inherent characteristics such as equipment model and age on risk amplification. Safety range: The safety range for each operating parameter (flow rate, rotation speed, negative pressure) is typically set by the equipment manufacturer based on physiological requirements and equipment engineering characteristics, and is written into the equipment operating specifications. Equipment influence coefficient: This coefficient needs to be obtained through retrospective data analysis. Detailed operating logs, model information, and related vascular complication data of the equipment from historical cases are collected. The quantitative relationship between the comprehensive score of equipment malfunction and the actual incidence of adverse events is analyzed using models such as linear regression. The fitted slope or proportionality coefficient can be used as the equipment influence coefficient to correct for the risk transmission efficiency of different equipment. The weight of each parameter's malfunction should be determined based on a multifactorial analysis of historical adverse events. For example, analyzing the correlation strength between abnormal flow rate, abnormal rotation speed, and abnormal negative pressure, whether occurring individually or in combination, and vascular injury events (such as intimal tearing and increased hemolysis) in historical data. The feature importance of each parameter (such as regression coefficient and information gain) is calculated by using logistic regression or decision tree models, and then normalized and used as weights to ensure that the model focuses more on parameters that have a greater impact on clinical outcomes. S32. Analyze the abnormal effects of blood flow by examining blood flow patterns and the distance of blood vessels relative to circulatory locations; The analysis of abnormal blood flow includes the following specific steps: The flow rate of the corresponding blood vessel and its distance from the circulatory location are obtained. The distance effect is obtained by dividing the safe distance by the distance of the blood vessel relative to the circulatory location. The distance effect is multiplied by the distance attenuation coefficient to obtain the distance effect anomaly. The flow rate anomaly is obtained by dividing the blood vessel's flow rate by the corresponding safe flow rate. The blood flow effect anomaly is obtained by multiplying the flow rate anomaly by the distance effect anomaly. Here, the safe flow rate of the corresponding blood vessel is the average flow rate of the corresponding blood vessels of healthy individuals of the corresponding age and gender. The distance attenuation coefficient is obtained by fitting the average value of historical experimental data. The core hemodynamic variable of flow rate is combined with the spatial attenuation factor of distance. By calculating the blood flow effect anomaly, it is possible to identify which blood vessel segments will be subjected to excessive, non-physiological blood flow shocks due to their proximity to the extracorporeal circulation pump, and which blood vessel segments may face the risk of relatively insufficient flow due to their distance. This provides a quantitative tool for understanding the uneven stress on blood vessels throughout the body during extracorporeal circulation and helps predict high-risk areas of local vascular endothelial damage or over-dilation. In the extracorporeal circulation tubing, the energy generated by the blood pump (manifested as flow rate and pressure) is gradually dissipated due to resistance (vascular friction, branching) as blood flows in the vascular network. Therefore, the closer a blood vessel is to the pump outlet, the closer its actual flow rate and pressure may be to or even exceed the pump's set output; while the farther the vessel is, the lower the actual perfusion flow rate will be. Multiplying the flow abnormality (the deviation between local flow rate and physiological needs) and the distance effect (the flow / pressure amplification effect caused by spatial location) aligns with clinical observations and physical intuition that proximal vessels bear a higher risk. The distance attenuation coefficient is used to quantify the specific rate of this spatial attenuation. In this embodiment, the safe flow rate for the corresponding blood vessel is determined as follows: This is an individualized physiological reference value, which should be based on a large-scale healthy population's imaging hemodynamic database, stratified by age, sex, height, weight (or body surface area), to obtain the average blood flow range of blood vessels in different anatomical locations (such as the ascending aorta, common carotid artery, renal artery, etc.) at rest (e.g., measured by ultrasound or phase-contrast MRI). For patients, it can be fine-tuned by combining their preoperative echocardiogram or CMR flow measurement values. The distance attenuation coefficient is determined as follows: The attenuation curves of flow rate and pressure relative to the pump outlet value of blood vessels at different locations can be accurately measured in in vitro simulated circulation experiments or computational fluid dynamics (CFD) simulations. By fitting this decay curve (which typically follows an exponential or power-law decay), an average or piecewise distance decay coefficient can be obtained, which can be used to quantify the influence of distance on blood flow impact in the model.

[0021] S33. The sum of the effects of abnormal circulatory equipment operation and value 1, multiplied by the abnormal blood flow effect, yields the abnormal impact of extracorporeal circulation on blood vessels. The source risk of equipment instability (result in S31) is combined with the transmissible risk of non-physiological blood flow distribution within the blood vessels (result in S32) to generate the final abnormal impact score of extracorporeal circulation on blood vessels. This score comprehensively reflects the overall level of abnormal mechanical load borne by the vascular system during extracorporeal circulation support. It serves as a crucial bridge connecting the equipment's operational status with the risk of terminal vascular damage, providing an external load input for subsequent risk superposition with the blood vessel's own tolerance. The impact of extracorporeal circulation on blood vessels is essentially the application of an external load. The total load consists of two parts: 1) the source intensity of the load, i.e. the degree of equipment malfunction (S31), which determines the total abnormal output energy; 2) the spatial distribution of the load, i.e. the abnormal impact of blood flow (S32), which determines how this total abnormality is distributed across different vascular segments. The multiplicative model ((equipment impact + 1) * blood flow impact) has a clear physical meaning: when the equipment is operating normally (equipment impact is 0), the total impact is determined only by the basic blood flow distribution (1 * blood flow impact); when the equipment malfunctions, it acts as an amplifier, proportionally aggravating the abnormal blood flow impact experienced by all vascular segments. This better reflects the multiplicative effect of source risk on the overall situation than simple addition.

[0022] Step 4: Analyze the damage to blood vessels caused by extracorporeal circulation based on the effects of extracorporeal circulation on blood vessels and the tolerance of blood vessels at different locations. In this embodiment, the analysis of vascular damage caused by extracorporeal circulation includes the following specific details: The first step involves obtaining information on the abnormal effects of cardiopulmonary bypass (CPB) on blood vessels and abnormal vascular tolerance. These two factors are then weighted and summed to obtain the damage analysis results for the corresponding blood vessels caused by CPB. The externally applied abnormal load (abnormal effects of CPB) and the inherent internal resistance (abnormal vascular tolerance) are placed within the same risk balance framework. Through weighted summation, the model simulates the mechanism of damage: when the external load exceeds the tolerance limit of the blood vessel, the risk of damage increases significantly. The calculated damage analysis result is a final risk score for each specific blood vessel segment, integrating all risk factors from both the load and tolerance ends. This upgrades clinical decision-making from a general assessment of whether equipment or blood flow is abnormal to a precise early warning of the likelihood of damage to a specific segment of blood vessel under current circulatory support. This provides a direct basis for targeted monitoring or intervention (such as adjusting cannulation position and optimizing perfusion strategies). Vascular injury (such as endothelial dysfunction, tearing, and atherosclerotic plaque detachment) is essentially caused by the mechanical stress (including shear stress, circumferential stress, etc., reflected by abnormalities in extracorporeal circulation) on the vessel wall exceeding the mechanical strength or physiological tolerance limit of its local tissues (reflected by abnormalities in vascular tolerance). The weighted summation model conforms to the basic logic that the risk of injury increases with increasing load and decreases with increasing tolerance. The setting of weights is crucial for model calibration and must be based on retrospective studies or prospective observational data from multicenter clinical cohorts. It requires collecting data on abnormal cardiopulmonary bypass effects (calculated according to S33), abnormal vascular tolerance (calculated according to S23), and clear vascular injury outcomes (such as new intimal injury detected by intraoperative ultrasound, dissection or embolism confirmed by postoperative imaging, and elevation of ischemic markers in related organs) for each segment of the vessel in a large number of cases. A logistic regression model is used, with whether injury occurs as the dependent variable and abnormal effects and tolerance as independent variables for fitting. The standardized regression coefficients of the two independent variables obtained by fitting are normalized (i.e., the sum is 1) and can be used as the weights for this step. The second step involves obtaining the damage analysis results for each blood vessel and comparing them with the corresponding damage analysis thresholds. Vessels with damage values ​​greater than or equal to the thresholds are designated as damaged vessels and marked on the 3D model, while vessels with damage values ​​less than the thresholds are designated as safe vessels. By setting a unified damage analysis threshold, the model provides a clear binary decision boundary, dividing the continuous risk spectrum into damaged and safe vessels. The visual markings on the 3D model pinpoint the abstract risk to specific and intuitive anatomical structures, greatly improving the understandability and operability of the information. This helps the surgical team and perfusionist quickly focus on high-risk areas for focused inspection and real-time intervention, potentially preventing the occurrence or worsening of damage. Setting the threshold is based on the statistically optimal distinguishing point, typically chosen to maximize sensitivity and specificity (e.g., the Youden index point determined by ROC curve analysis) or based on a clinically acceptable risk level (e.g., defining a damage prediction probability >20% as high risk). Marking high-risk vessels on the 3D model is a classic application of human factors engineering and clinical decision support systems, conforming to the cognitive patterns of spatial location memory and visual highlighting. Effectively reducing information overload and guiding attention has been proven to improve decision-making speed and accuracy in complex situations. Parameter value selection method: The damage analysis threshold must be carried out in conjunction with the weight determination process in the first step. Based on the same clinical dataset, after obtaining the correspondence between the damage analysis results (i.e., the predicted probability value of damage occurrence) and the actual damage outcome through the logistic regression model, the receiver operating characteristic curve is plotted. Each point on the curve corresponds to a different threshold. For example, in scenarios that emphasize safety, high sensitivity (e.g., >95%) can be prioritized, even at the cost of slightly lower specificity, to ensure that high-risk blood vessels are not missed.

[0023] Step 5: Analyze the vascular damage results using extracorporeal circulation at each location and conduct health intervention and early warning for each location. In this embodiment, the health intervention and early warning for each location based on the analysis results of vascular damage through extracorporeal circulation at each location includes the following specific steps: The location of damaged blood vessels during extracorporeal circulation is obtained and sent to medical staff, who then issue warnings for the corresponding locations. Based on the location of the damaged blood vessels, medical staff can choose to replan the circulation route and add anti-inflammatory drugs or endothelial protectants to the corresponding blood vessel locations.

[0024] The advantages of this embodiment are as follows: By integrating patient images, physiological data, and extracorporeal circulation parameters, an individualized hemodynamic model is constructed to accurately predict the risk of vascular wall damage, providing quantitative support for clinical decision-making. At the same time, by integrating imaging, physiological, and equipment data, the system constructs an individualized vascular tolerance model to achieve quantitative assessment of vulnerable factors such as vascular calcification and plaque, providing a basis for accurate early warning. Based on real-time extracorporeal circulation parameters and blood flow simulation, the system can dynamically analyze the impact of blood flow friction on blood vessels at different locations and identify high-risk damage areas in advance.

[0025] Please see Figure 4 , Figure 4 This is a schematic diagram of the structure of the extracorporeal circulation clinical intervention analysis system based on three-dimensional simulation provided in this application embodiment, which includes the following specific modules: The system includes a data acquisition module, a tolerance analysis module, an extracorporeal circulation effect module, a damage analysis module, and an intervention and early warning module. The acquisition module is used to acquire the operating status of the extracorporeal circulation device, as well as the distribution of blood vessels, images, and distances relative to the circulation location at each corresponding position. The tolerance analysis module analyzes the tolerance of blood vessels at each location based on the distribution of blood vessels and the image conditions at each location. The extracorporeal circulation impact module analyzes the impact of extracorporeal circulation on blood vessels based on the operation of the extracorporeal circulation equipment, blood flow, and the distance of blood vessels relative to the circulatory location. The damage analysis module analyzes the damage to blood vessels caused by extracorporeal circulation based on the impact of extracorporeal circulation on blood vessels and the tolerance of blood vessels at various locations. The intervention and early warning module analyzes vascular damage results through extracorporeal circulation at various locations and provides early warnings for health interventions at each location.

[0026] The parameters and steps for implementing the corresponding functions of each unit module in the three-dimensional simulation-based extracorporeal circulation clinical intervention analysis system of this application can be referred to the parameters and steps in the embodiments of the three-dimensional simulation-based extracorporeal circulation clinical intervention analysis method, and will not be repeated here.

[0027] Embodiments of this application also provide an electronic device, including a memory, a processor, and a communication bus; the memory and the processor are connected via the communication bus. The memory stores a method for analyzing extracorporeal circulation based on three-dimensional simulation, which can be loaded and executed by the processor, as provided in the above embodiments.

[0028] The memory can be used to store instructions, programs, code, code sets, or instruction sets. The memory may include a program storage area and a data storage area. The program storage area may store instructions for implementing an operating system, instructions for at least one function, and instructions for implementing the three-dimensional simulation-based extracorporeal circulation clinical intervention analysis method provided in the above embodiments, etc. The data storage area may store data involved in the three-dimensional simulation-based extracorporeal circulation clinical intervention analysis method provided in the above embodiments, etc.

[0029] A processor may include one or more processing cores. The processor executes instructions, programs, code sets, or instruction sets stored in memory, and calls data stored in memory to perform various functions and process data as described in this application. The processor may be at least one of a specific application-specific integrated circuit, a digital signal processor, a digital signal processing device, a programmable logic device, a field-programmable gate array, a central processing unit, a controller, a microcontroller, and a microprocessor. It is understood that, for different devices, the electronic devices used to implement the above-described processor functions may also be other types, and the embodiments of this application do not specifically limit this.

[0030] A communication bus may include a pathway for transmitting information between the aforementioned components. The communication bus can be a PCI bus or an EISA bus, etc. Communication buses can be categorized into address buses, data buses, control buses, etc.

[0031] This application provides a computer-readable storage medium storing a computer program that can be loaded by a processor and executed as described in the above embodiments, which is a three-dimensional simulation-based extracorporeal circulation clinical intervention analysis method.

[0032] In this embodiment, a computer-readable storage medium can be a tangible device that holds and stores instructions used by an instruction execution device. The computer-readable storage medium can be, but is not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any combination thereof. Specifically, the computer-readable storage medium can be a portable computer disk, a hard disk, a USB flash drive, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), staging random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory stick, floppy disk, optical disk, magnetic disk, mechanical encoding device, or any combination thereof.

[0033] The term includes, or any other variation thereof, is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0034] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the foregoing application concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions claimed in this application.

Claims

1. A clinical intervention analysis system for extracorporeal circulation based on three-dimensional simulation, characterized in that, Includes the following specific modules: The system includes a data acquisition module, a tolerance analysis module, an extracorporeal circulation effect module, a damage analysis module, and an intervention and early warning module. The acquisition module is used to acquire the operating status of the extracorporeal circulation device, and at the same time acquire the blood vessel distribution, image status, and distance relative to the circulation position at each corresponding location. The tolerance analysis module analyzes the tolerance of blood vessels at each location based on the blood vessel distribution and image conditions at each location. The extracorporeal circulation impact module analyzes the impact of extracorporeal circulation on blood vessels based on the operation of the extracorporeal circulation equipment, blood flow, and the distance of blood vessels relative to the circulation location. The damage analysis module performs damage analysis on blood vessels based on the effects of extracorporeal circulation on blood vessels and the tolerance of blood vessels at various locations. The intervention and early warning module provides health intervention and early warning for each location based on the analysis results of vascular damage through extracorporeal circulation at each location.

2. The extracorporeal circulation clinical intervention analysis system based on three-dimensional simulation according to claim 1, characterized in that, The acquisition of the operational status of the extracorporeal circulation device, and the acquisition of the blood vessel distribution and conditions at each corresponding location, as well as the corresponding distances relative to the circulation location, includes the following specific information: S11. Obtain high-resolution CT or MRI images of the patient before surgery; the images must include enhanced angiography sequences to clearly show the vascular morphology; S12. Obtain the model of the cardiopulmonary bypass machine, pump head type, cannula type and size, as well as the target pump flow rate, speed, and negative pressure suction pressure operating parameters; used to analyze abnormal operation of the cardiopulmonary bypass machine and its impact on blood vessels; S13. Use medical image processing software to perform semi-automatic / automatic segmentation of the target vascular region, generate a patient-specific three-dimensional vascular model, virtually place the extracorporeal circulation cannula in the three-dimensional model, and determine its position according to the surgical plan.

3. The extracorporeal circulation clinical intervention analysis system based on three-dimensional simulation according to claim 1, characterized in that, The analysis of vascular tolerance at various locations includes the following specific steps: S21. Obtain vascular images and assess vascular elasticity abnormalities based on the calcification distribution, plaque characteristics, and initial elasticity of the vascular wall in the vascular images. S22. Analyze the abnormal vascular friction index based on the diameter, curvature, and wall thickness characteristics of the corresponding blood vessels. S23. The abnormal vascular tolerance is obtained by weighting and summing the results of the abnormal vascular elasticity assessment with the abnormal vascular friction index.

4. The extracorporeal circulation clinical intervention analysis system based on three-dimensional simulation according to claim 3, characterized in that, The elasticity anomaly assessment includes the following specific aspects: S211. Obtain images of each blood vessel, use image processing software to obtain the volume, density and distribution of calcification in the blood vessel wall, obtain the region and characteristics of calcification, obtain the average calcification volume, average density and the proportion of the contact surface with the inside of the blood vessel to the area of ​​the blood vessel wall per unit distance, obtain the calcification volume abnormality by dividing the average calcification volume by the safe calcification volume, obtain the calcification density abnormality by dividing the average calcification density by the safe density, obtain the calcification influence abnormality by multiplying the calcification volume abnormality by the calcification density abnormality and then by multiplying the contact surface with the inside of the blood vessel to the proportion of the area of ​​the blood vessel wall to the area of ​​the blood vessel wall. S212. Obtain the pixel features of each pixel in the image of the patch, and obtain the patch impact anomaly by the average of the standard deviations of the pixel values ​​of each point from the safe pixel values; S213. The internal influence abnormality coefficient is obtained by weighted summation of calcification influence abnormality and plaque influence abnormality. The initial elasticity abnormality is obtained by dividing the safe elasticity value by the initial elasticity of the corresponding blood vessel. The elasticity abnormality assessment result is obtained by multiplying the internal influence abnormality coefficient by the initial elasticity abnormality.

5. The extracorporeal circulation clinical intervention analysis system based on three-dimensional simulation according to claim 3, characterized in that, The analysis of the abnormal vascular friction index includes the following specific steps: S221. Obtain the average diameter and wall thickness of the corresponding blood vessel. Divide the safe value of the average diameter and wall thickness of the corresponding blood vessel by the corresponding parameter to obtain the abnormality of the corresponding parameter. Divide the average curvature of the corresponding blood vessel by the safe value of curvature to obtain the curvature abnormality. S222. The abnormal blood vessel friction index is obtained by weighted summation of abnormal diameter, abnormal wall thickness, and abnormal curvature.

6. The extracorporeal circulation clinical intervention analysis system based on three-dimensional simulation according to claim 1, characterized in that, The effects of extracorporeal circulation on blood vessels include the following specific aspects: S31. Obtain the operating parameters and fluctuations of the extracorporeal circulation device, and analyze the impact of abnormal operation of the circulation device by comparing the operating parameters with the safe range and the abnormal fluctuations. S32. Analyze the abnormal effects of blood flow by examining blood flow patterns and the distance of blood vessels relative to circulatory locations; S33. The abnormal impact of the circulatory equipment operation is summed with the value 1 and then multiplied by the abnormal impact of blood flow to obtain the abnormal impact of extracorporeal circulation on blood vessels.

7. The extracorporeal circulation clinical intervention analysis system based on three-dimensional simulation according to claim 6, characterized in that, The abnormal operation of the circulation equipment has the following specific effects: The system acquires the set operating flow rate, speed, and negative pressure suction pressure of the circulating equipment; it also acquires the fluctuation value of the actual operation of the equipment in the previous stage relative to the set value, and obtains the fluctuation anomaly of the corresponding parameter by dividing the average of the absolute values ​​of the fluctuation values ​​of the corresponding parameter by the corresponding set value. Obtain the standard deviation of the operating parameters of the extracorporeal circulation device from the safety range of the corresponding parameters, obtain the comparative anomalies of the corresponding parameters, sum the fluctuation anomalies of the corresponding parameters with the comparative anomalies of the corresponding parameters to obtain the operating anomalies of the corresponding parameters, and then multiply the weighted sum of the operating anomalies of all parameters by the device influence coefficient to obtain the impact of the operating anomalies of the circulation device.

8. The extracorporeal circulation clinical intervention analysis system based on three-dimensional simulation according to claim 6, characterized in that, The analysis of abnormal blood flow effects includes the following specific steps: The flow rate of the corresponding blood vessel and the distance of the blood vessel relative to the circulatory position are obtained. The distance influence is obtained by dividing the safe distance by the distance of the blood vessel relative to the circulatory position. The distance influence abnormality is obtained by multiplying the distance influence by the distance attenuation coefficient. The flow rate abnormality is obtained by dividing the flow rate of the blood vessel by the safe flow rate of the corresponding blood vessel. The blood flow influence abnormality is obtained by multiplying the flow rate abnormality by the distance influence abnormality.

9. The extracorporeal circulation clinical intervention analysis system based on three-dimensional simulation according to claim 1, characterized in that, The analysis of vascular damage caused by extracorporeal circulation includes the following specific details: The first step is to obtain information on the abnormal effects of cardiopulmonary bypass on blood vessels and the abnormal vascular tolerance; the two are then weighted and summed to obtain the damage analysis results of cardiopulmonary bypass on the corresponding blood vessels. The second step is to obtain the damage analysis results of each blood vessel, compare them with the corresponding damage analysis threshold, mark the blood vessels with damage values ​​greater than or equal to the damage analysis threshold on the 3D model, and mark the blood vessels with damage values ​​less than the damage analysis threshold as safe blood vessels.

10. The extracorporeal circulation clinical intervention analysis system based on three-dimensional simulation according to claim 1, characterized in that, The method of using extracorporeal circulation at various locations to analyze vascular damage results and provide early warning for health intervention at each location includes the following specific steps: The location of damaged blood vessels during extracorporeal circulation is obtained and sent to medical staff, who then issue warnings for the corresponding locations. Based on the location of the damaged blood vessels, medical staff can choose to replan the circulation route and add anti-inflammatory drugs or endothelial protectants to the corresponding blood vessel locations.

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