心血管系统的电网络建模及动脉硬化与狭窄诊断研究
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摘要
心血管系统是维持人体正常运作的重要系统，也是疾病高发区。心血管疾病己成为威胁人类生命的最危险因素之一，全球约三分之一的人死于心血管疾病。心血管疾病的早期诊断对降低心血管疾病导致的死亡率和经济负担具有重要意义。为研究心血管疾病中动脉硬化和狭窄的早期诊断，本文主要围绕心血管系统的电网络建模与仿真、动脉硬化和狭窄诊断模型的建立、心血管动力学参数检测仪器研发和临床实验四个方面展开研究。
通过比较动脉系统与电网络系统之间的对应关系，提炼和总结了集总参数电网络模型的特点，建立了上肢动脉的电网络模型，采用数值计算方法和Matlab中Simulink/Simpowersystem模块进行模型求解和仿真，结果与实际数据符合较好。但该模型不能有效模拟脉搏波的传播和反射等现象。
在55段人体动脉树分布式电网络模型的基础上，提出了新的基于数据链表和递归算法的模型求解方法，实现模型的自动求解计算。利用模型和算法对正常人的脉搏波传播进行了仿真，得到动脉树中各点血压和血流波形，并将结果以3D形式呈现，能直观分析脉搏波的传播和反射特性。分析了身高、心率、每搏输出量、动脉内径和壁厚等不同生理参数对血压和血流波形的影响，同时分析了动脉顺应性、外周阻力、动脉长度、动脉内径和壁厚对动脉树输入阻抗的影响。结果表明：不同因素对血压波形、血流波形和输入阻抗的影响有较大不同，呈现各自独有特征，是人体动脉树生理病理诊断的重要辅助参考。
利用分布式电网络模型对动脉硬化和动脉狭窄进行了模拟仿真，结果表明：该模型能准确模拟PWV随动脉硬化程度的改变而改变；能有效模拟脉搏波反射对收缩压增强指数的影响；能有效模拟动脉硬化参数改变对全身动脉系统中的血压和血流波形的影响；能准确模拟动脉狭窄的位置、大小和程度对ABI、血压和血流波形的影响；传递函数能有效反映动脉狭窄的位置、大小和程度等信息。
以输入阻抗为动脉狭窄的特征参数，结合支持向量机建立了动脉狭窄预测模型，预测结果表明：不同狭窄度的总准确率均在82%以上，且准确率随着狭窄程度的增加而增加，当动脉狭窄程度超过60%时，准确率大于90%；离心距离越近准确率越高，主动脉弓狭窄的准确率为95%左右，但对于离心距离较远(股动脉以下)的中度动脉狭窄（50%）的预测有一定的局限，准确率约为50%。但当动脉狭窄为90%及以上时，SVM对离心距离较远动脉狭窄的预测准确率上升为91.6%。
以传递函数为动脉狭窄的特征参数，结合支持向量机建立了动脉狭窄预测模型，结果表明：动脉狭窄阈值取90%时，SVM十次交叉验证的平均准确率为97.8%；对于中度和重度（50%和90%）动脉狭窄，利用传递函数预测传递函数两点之间的动脉狭窄较为理想，准确率分别在87%和99%以上，而对传递函数两点之外的分支动脉段狭窄有一定的局限性，预测颈动脉狭窄的总准确率Q分别为62.1%和91.4%，灵敏度QP分别在25.8%和18%左右。
提出了利用传递函数和支持向量机对动脉狭窄分段定位的新方法，结果表明：动脉狭窄50%、60%、70%、80%和90%时预测总准确率Q分别为82.0%、80.0%、81.4%、83.7%和91.5%，说明对动脉狭窄度为90%及以上的情况能较好地定位，但颈动脉和锁骨下动脉狭窄的定位准确率分别为85.7%和44.4%，说明在传递函数两点之外狭窄的分段定位有一定局限性。
利用LabVIEW开发平台，开发和研制出心血管系统动脉硬化和动脉狭窄检测仪YF/XGYD-2000B，该仪器能检测PWV、ABI、ASI、C1和C2等多项参数和指标。通过YF/XGYD-2000B与无创血压模拟仪的对比测试，证实该仪器测量血压的准确性和可重复性；通过与欧姆龙动脉硬化检测仪的临床对比研究，证实了该仪器动脉硬化和狭窄检测的有效性；通过仪器自身多参数的比较，证实了参数间的良好相关性，并分析了与动脉硬化和狭窄相关的其他常规参数的关系；通过脑梗塞病人的PWV与年龄、SBP和ABI进行了分析，得到了较好的临床效果，体现了其应用价值。
The cardiovascular system is an important system which maintains the normalfunctioning of human body, and is also a high-incidence area of disease. Cardiovasculardisease has become one of the most dangerous threats to human life. About a third ofpeople around the world die of cardiovascular disease. Early diagnosis of cardiovasculardisease is very important to reduce the mortality and economic burden caused bycardiovascular disease. This paper mainly focused on four aspects: electric networkmodeling and simulation of cardiovascular system, diagnosis modeling ofarteriosclerosis and stenosis for early detecting cardiovascular disease, equipment R&Dof cardiovascular dynamics parameters and clinical trials.
By comparing arterial system with electrical network system, one refined andsummarized the characteristics of lumped electrical network model. An electric networkmodel of upper limb arteries was established. And numerical method and MatlabSimulink/Simpowersystem module model were used to solve the model. The results ofsimulation are in good agreement with actual data. However, the model couldn’teffectively simulate pulse wave propagation and reflection.
Based on the distributed electric network model of55human arterial tree, a novelcalculation method of the model was proposed with data lists and recursive algorithm,which can automatically complete the computation of model. The model and algorithmwere applied in the simulation of pulse wave propagation, blood pressure and flowwaveform of normal arterial tree, and the results rendered in3D figure which directlydisplay the properties of pulse wave propagation and reflection. The effects of differentphysiological parameters: height, heart rate, stroke output, arterial diameter and wallthickness on blood pressure and flow waveform were analyzed and discussed. We alsodiscussed the effects of different physiological parameters: arterial compliance,peripheral resistance, arterial length, arterial diameter and wall thickness of the arterialtree on input impedance. The results showed that different factors affect the bloodpressure and flow waveforms and input impedance in quite different way showing theirunique characteristics. The model provided us with an important auxiliary reference forphysiological and pathological diagnosis of human arterial tree.
The distributed electric network model was applied to simulate atherosclerosis andarterial stenosis. The results showed that the model can accurately simulate: PWV changes with the degree of atherosclerosis; augmentation index of systolic bloodpressure changes with pulse wave reflection; blood pressure and flow waveforms wereaffected by arteriosclerosis parameters; ABI, blood pressure and flow waveforms wereaffected by the location, size and degree of artery stenosis; transfer function caneffectively reflect the location, size and degree of artery stenosis.
A prediction model of artery stenosis was established by support vector machineusing input impedance as the characteristic parameters of arterial stenosis. Predictionresults showed that overall accuracies were more than82%under different stenosisdegrees. And, the accuracy increases with the degree of stenosis increasing. When thedegree of stenosis reaches to60%, the accuracy rises to more than90%. Additionally,the nearer the artery stenosis was to heart, the higher the accuracy was. The accuracy ofaortic arch stenosis approached to95%under the degree of stenosis60%. But, theaccuracy of femoral artery stenosis dropped down to about50%. It means the methodhas some limitations for the prediction of moderate stenosis far from heart. When thedegree of arterial stenosis increased to90%and above, the limitation disappeared forfemoral artery stenosis whose prediction accuracy increased to91.6%.
A prediction model of artery stenosis was built using support vector machine withtransfer function as the characteristic parameters of arterial stenosis. Prediction resultsshowed that: the10cross-validation average accuracy of SVM reached to97.8%for thedegree of stenosis90%. For moderate and severe (50%and90%) artery stenosis,transfer function can predict accurately the artery stenosis situating between two pointsof transfer function, whose accuracy were more than87%and99%, respectively. But,the prediction total accuracy Q of carotid stenosis were62.1%and91.4%, sensitivity QPwere25.8%and18%, respectively. It means the stenosis was hard to predict for thestenosis outside transfer function.
A new method of the positioning of arterial stenosis was proposed using transferfunction and the multi-classification theory of support vector machine. The positioningresults showed that: total accuracy Q was82.0%,80%,81.4%,83.7%and91.5%forartery stenosis50%,60%,70%,80%and90%, respectively. It means the artery stenosisabove90%can be positioned easily. But the positioning accuracies of carotid andsubclavian artery stenosis were85.7%and44.4%, which indicated the proposed methodhas some limitations for the artery stenosis outside two points of transfer function.
An arteriosclerosis and arterial stenosis detection apparatus YF/XGYD-2000B wasdeveloped on LabVIEW development platform. It can detect a series of parameters and indicators of PWV, ABI, ASI, C1and C2. The comparison between YF/XGYD-2000Band noninvasive blood pressure simulator verified that YF/XGYD-2000B can measureblood pressure accuracy, and have good repeatability. Clinical comparative studydemonstrated that the results of YF/XGYD-2000B were in good agreement with thoseresults of Omron atherosclerosis apparatus. Comparison of itself parameters ofYF/XGYD-2000B indicated a good correlation between the parameters. Clinical trial ofcerebral infarction patients was implemented, and results showed PWV had a goodcorrelation with age, SBP, and ABI, which demonstrated the application value ofYF/XGYD-2000B.
通过比较动脉系统与电网络系统之间的对应关系，提炼和总结了集总参数电网络模型的特点，建立了上肢动脉的电网络模型，采用数值计算方法和Matlab中Simulink/Simpowersystem模块进行模型求解和仿真，结果与实际数据符合较好。但该模型不能有效模拟脉搏波的传播和反射等现象。
在55段人体动脉树分布式电网络模型的基础上，提出了新的基于数据链表和递归算法的模型求解方法，实现模型的自动求解计算。利用模型和算法对正常人的脉搏波传播进行了仿真，得到动脉树中各点血压和血流波形，并将结果以3D形式呈现，能直观分析脉搏波的传播和反射特性。分析了身高、心率、每搏输出量、动脉内径和壁厚等不同生理参数对血压和血流波形的影响，同时分析了动脉顺应性、外周阻力、动脉长度、动脉内径和壁厚对动脉树输入阻抗的影响。结果表明：不同因素对血压波形、血流波形和输入阻抗的影响有较大不同，呈现各自独有特征，是人体动脉树生理病理诊断的重要辅助参考。
利用分布式电网络模型对动脉硬化和动脉狭窄进行了模拟仿真，结果表明：该模型能准确模拟PWV随动脉硬化程度的改变而改变；能有效模拟脉搏波反射对收缩压增强指数的影响；能有效模拟动脉硬化参数改变对全身动脉系统中的血压和血流波形的影响；能准确模拟动脉狭窄的位置、大小和程度对ABI、血压和血流波形的影响；传递函数能有效反映动脉狭窄的位置、大小和程度等信息。
以输入阻抗为动脉狭窄的特征参数，结合支持向量机建立了动脉狭窄预测模型，预测结果表明：不同狭窄度的总准确率均在82%以上，且准确率随着狭窄程度的增加而增加，当动脉狭窄程度超过60%时，准确率大于90%；离心距离越近准确率越高，主动脉弓狭窄的准确率为95%左右，但对于离心距离较远(股动脉以下)的中度动脉狭窄（50%）的预测有一定的局限，准确率约为50%。但当动脉狭窄为90%及以上时，SVM对离心距离较远动脉狭窄的预测准确率上升为91.6%。
以传递函数为动脉狭窄的特征参数，结合支持向量机建立了动脉狭窄预测模型，结果表明：动脉狭窄阈值取90%时，SVM十次交叉验证的平均准确率为97.8%；对于中度和重度（50%和90%）动脉狭窄，利用传递函数预测传递函数两点之间的动脉狭窄较为理想，准确率分别在87%和99%以上，而对传递函数两点之外的分支动脉段狭窄有一定的局限性，预测颈动脉狭窄的总准确率Q分别为62.1%和91.4%，灵敏度QP分别在25.8%和18%左右。
提出了利用传递函数和支持向量机对动脉狭窄分段定位的新方法，结果表明：动脉狭窄50%、60%、70%、80%和90%时预测总准确率Q分别为82.0%、80.0%、81.4%、83.7%和91.5%，说明对动脉狭窄度为90%及以上的情况能较好地定位，但颈动脉和锁骨下动脉狭窄的定位准确率分别为85.7%和44.4%，说明在传递函数两点之外狭窄的分段定位有一定局限性。
利用LabVIEW开发平台，开发和研制出心血管系统动脉硬化和动脉狭窄检测仪YF/XGYD-2000B，该仪器能检测PWV、ABI、ASI、C1和C2等多项参数和指标。通过YF/XGYD-2000B与无创血压模拟仪的对比测试，证实该仪器测量血压的准确性和可重复性；通过与欧姆龙动脉硬化检测仪的临床对比研究，证实了该仪器动脉硬化和狭窄检测的有效性；通过仪器自身多参数的比较，证实了参数间的良好相关性，并分析了与动脉硬化和狭窄相关的其他常规参数的关系；通过脑梗塞病人的PWV与年龄、SBP和ABI进行了分析，得到了较好的临床效果，体现了其应用价值。
The cardiovascular system is an important system which maintains the normalfunctioning of human body, and is also a high-incidence area of disease. Cardiovasculardisease has become one of the most dangerous threats to human life. About a third ofpeople around the world die of cardiovascular disease. Early diagnosis of cardiovasculardisease is very important to reduce the mortality and economic burden caused bycardiovascular disease. This paper mainly focused on four aspects: electric networkmodeling and simulation of cardiovascular system, diagnosis modeling ofarteriosclerosis and stenosis for early detecting cardiovascular disease, equipment R&Dof cardiovascular dynamics parameters and clinical trials.
By comparing arterial system with electrical network system, one refined andsummarized the characteristics of lumped electrical network model. An electric networkmodel of upper limb arteries was established. And numerical method and MatlabSimulink/Simpowersystem module model were used to solve the model. The results ofsimulation are in good agreement with actual data. However, the model couldn’teffectively simulate pulse wave propagation and reflection.
Based on the distributed electric network model of55human arterial tree, a novelcalculation method of the model was proposed with data lists and recursive algorithm,which can automatically complete the computation of model. The model and algorithmwere applied in the simulation of pulse wave propagation, blood pressure and flowwaveform of normal arterial tree, and the results rendered in3D figure which directlydisplay the properties of pulse wave propagation and reflection. The effects of differentphysiological parameters: height, heart rate, stroke output, arterial diameter and wallthickness on blood pressure and flow waveform were analyzed and discussed. We alsodiscussed the effects of different physiological parameters: arterial compliance,peripheral resistance, arterial length, arterial diameter and wall thickness of the arterialtree on input impedance. The results showed that different factors affect the bloodpressure and flow waveforms and input impedance in quite different way showing theirunique characteristics. The model provided us with an important auxiliary reference forphysiological and pathological diagnosis of human arterial tree.
The distributed electric network model was applied to simulate atherosclerosis andarterial stenosis. The results showed that the model can accurately simulate: PWV changes with the degree of atherosclerosis; augmentation index of systolic bloodpressure changes with pulse wave reflection; blood pressure and flow waveforms wereaffected by arteriosclerosis parameters; ABI, blood pressure and flow waveforms wereaffected by the location, size and degree of artery stenosis; transfer function caneffectively reflect the location, size and degree of artery stenosis.
A prediction model of artery stenosis was established by support vector machineusing input impedance as the characteristic parameters of arterial stenosis. Predictionresults showed that overall accuracies were more than82%under different stenosisdegrees. And, the accuracy increases with the degree of stenosis increasing. When thedegree of stenosis reaches to60%, the accuracy rises to more than90%. Additionally,the nearer the artery stenosis was to heart, the higher the accuracy was. The accuracy ofaortic arch stenosis approached to95%under the degree of stenosis60%. But, theaccuracy of femoral artery stenosis dropped down to about50%. It means the methodhas some limitations for the prediction of moderate stenosis far from heart. When thedegree of arterial stenosis increased to90%and above, the limitation disappeared forfemoral artery stenosis whose prediction accuracy increased to91.6%.
A prediction model of artery stenosis was built using support vector machine withtransfer function as the characteristic parameters of arterial stenosis. Prediction resultsshowed that: the10cross-validation average accuracy of SVM reached to97.8%for thedegree of stenosis90%. For moderate and severe (50%and90%) artery stenosis,transfer function can predict accurately the artery stenosis situating between two pointsof transfer function, whose accuracy were more than87%and99%, respectively. But,the prediction total accuracy Q of carotid stenosis were62.1%and91.4%, sensitivity QPwere25.8%and18%, respectively. It means the stenosis was hard to predict for thestenosis outside transfer function.
A new method of the positioning of arterial stenosis was proposed using transferfunction and the multi-classification theory of support vector machine. The positioningresults showed that: total accuracy Q was82.0%,80%,81.4%,83.7%and91.5%forartery stenosis50%,60%,70%,80%and90%, respectively. It means the artery stenosisabove90%can be positioned easily. But the positioning accuracies of carotid andsubclavian artery stenosis were85.7%and44.4%, which indicated the proposed methodhas some limitations for the artery stenosis outside two points of transfer function.
An arteriosclerosis and arterial stenosis detection apparatus YF/XGYD-2000B wasdeveloped on LabVIEW development platform. It can detect a series of parameters and indicators of PWV, ABI, ASI, C1and C2. The comparison between YF/XGYD-2000Band noninvasive blood pressure simulator verified that YF/XGYD-2000B can measureblood pressure accuracy, and have good repeatability. Clinical comparative studydemonstrated that the results of YF/XGYD-2000B were in good agreement with thoseresults of Omron atherosclerosis apparatus. Comparison of itself parameters ofYF/XGYD-2000B indicated a good correlation between the parameters. Clinical trial ofcerebral infarction patients was implemented, and results showed PWV had a goodcorrelation with age, SBP, and ABI, which demonstrated the application value ofYF/XGYD-2000B.
引文
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