A personalized 0D-1D model of cardiovascular system for the hemodynamic simulation of enhanced external counterpulsation

血流动力学 计算机科学 医学 心脏病学 生物医学工程
作者
Qi Zhang,Yahui Zhang,Liling Hao,Yujia Zhong,Kunlin Wu,Zhuo Wang,Shuai Tian,Lin Qi,Guifu Wu
出处
期刊:Computer Methods and Programs in Biomedicine [Elsevier BV]
卷期号:227: 107224-107224 被引量:9
标识
DOI:10.1016/j.cmpb.2022.107224
摘要

Enhanced external counterpulsation (EECP) is a non-invasive treatment modality capable of treating a variety of ischemic diseases. Currently, no effective methods of predicting the patient-specific hemodynamic effects of EECP are available. In this study, a personalized 0D-1D model of the cardiovascular system was developed for hemodynamic simulation to simulate the changes in blood flow in the EECP state and develop the best treatment protocol for each individual.A 0D-1D closed-loop model of the cardiovascular system was developed for hemodynamic simulation, consisting of a 1D wave propagation model for arteries, a 0D model for veins and capillaries, and a one-fiber model for the heart. Additionally, a simulation model coupling EECP with a 1D model was established. Physiological data, including the blood flow in different arteries, were clinically collected from 22 volunteers at rest and in the EECP state. Sensitivity analysis and a simulated annealing algorithm were used to build personalized 0D-1D models using the clinical data in the rest state as optimization objectives. Then, the clinical data on EECP were used to verify the applicability and accuracy of the personalized models.The simulation results and clinical data were found to be in agreement for all 22 subjects, with waveform similarity coefficients (r) exceeding 90% for most arteries at rest and 80% for most arteries during EECP.The 0D-1D closed-loop model and the optimized method can facilitate personalized modeling of the cardiovascular system using the data in the rest state and effectively predict the hemodynamic changes in the EECP state, which is significant for the numerical simulation of personalized hemodynamics. The model can also potentially be used to make decisions regarding patient-specific treatment.
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