A high-fidelity geometric multiscale hemodynamic model for predicting myocardial ischemia

IF 4.8 2区 医学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Jincheng Liu , Bao Li , Yanping Zhang , Liyuan Zhang , Suqin Huang , Hao Sun , Jian Liu , Xi Zhao , Mingzi Zhang , Wenxin Wang , Youjun Liu
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引用次数: 2

Abstract

Background and Objectives

Coronary computed tomography angiography (CCTA) derived fractional flow reserve (CT-FFR) requires a maximal hyperemic state to be modeled by assuming the total coronary resistance decreased to a constant 0.24 of that under the resting state. However, this assumption neglects the vasodilator capacity of individual patients. Herein, we proposed a high-fidelity geometric multiscale model (HFMM) to characterize coronary pressure and flow under the resting state, seeking to better predict myocardial ischemia by using CCTA-derived instantaneous wave-free ratio (CT-iFR).

Methods

Fifty-seven patients (62 lesions) who had undergone CCTA and were then referred to invasive FFR were prospectively enrolled. The coronary microcirculation resistance hemodynamic model (RHM) under the resting condition was established on a patient-specific basis. Coupled with a closed-loop geometric multiscale model (CGM) of their individual coronary circulations, the HFMM model was established to non-invasively derive the CT-iFR from CCTA images.

Results

With the invasive FFR being the reference standard, accuracy of the obtained CT-iFR in identifying myocardial ischemia was greater than those of the CCTA and non-invasively derived CT-FFR (90.32% vs. 79.03% vs. 84.3%). The overall computational time of CT-iFR was 61 ± 6 min, faster than that of the CT-FFR (8 h). The sensitivity, specificity, positive predictive value, and negative predictive value of the CT-iFR in discriminating an invasive FFR > 0.8 were 78% (95% CI: 40–97%), 92% (95% CI: 82–98%), 64% (95% CI: 39–83%), and 96% (95% CI:88–99%), respectively.

Conclusions

A high-fidelity geometric multiscale hemodynamic model was developed for rapid and accurate estimation of CT-iFR. Compared with CT-FFR, CT-iFR is of less computational cost and enables assessment of tandem lesions.

预测心肌缺血的高保真几何多尺度血流动力学模型
背景和目的冠状动脉计算机断层摄影血管造影术(CCTA)衍生的血流储备分数(CT-FFR)需要通过假设总冠状动脉阻力降低到静息状态下的0.24来模拟最大充血状态。然而,这一假设忽略了个别患者的血管舒张能力。在此,我们提出了一个高保真几何多尺度模型(HFMM)来表征静息状态下的冠状动脉压力和流量,试图通过CCTA衍生的瞬时无波比(CT-iFR)更好地预测心肌缺血。建立静息状态下冠状动脉微循环阻力血流动力学模型。结合各自冠状动脉循环的闭环几何多尺度模型(CGM),建立了HFMM模型,以从CCTA图像中无创地导出CT iFR。结果以有创性血流储备分数为参考标准,所获得的CT iFR在识别心肌缺血方面的准确率高于CCTA和非侵入性推导的CT-FFR(90.32%对79.03%对84.3%)。CT iFR的总计算时间为61±6min,比CT-FFR快8h。CT iFR在鉴别有创性FFR>;0.8分别为78%(95%CI:40-97%)、92%(95%CI:82-98%)、64%(95%CI:39-83%)和96%(95%CI:88-99%)。结论建立了一个高保真几何多尺度血流动力学模型,可快速准确地估计CT iFR。与CT-FFR相比,CT-iFR的计算成本更低,并且能够评估串联病变。
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来源期刊
Computer methods and programs in biomedicine
Computer methods and programs in biomedicine 工程技术-工程:生物医学
CiteScore
12.30
自引率
6.60%
发文量
601
审稿时长
135 days
期刊介绍: To encourage the development of formal computing methods, and their application in biomedical research and medical practice, by illustration of fundamental principles in biomedical informatics research; to stimulate basic research into application software design; to report the state of research of biomedical information processing projects; to report new computer methodologies applied in biomedical areas; the eventual distribution of demonstrable software to avoid duplication of effort; to provide a forum for discussion and improvement of existing software; to optimize contact between national organizations and regional user groups by promoting an international exchange of information on formal methods, standards and software in biomedicine. Computer Methods and Programs in Biomedicine covers computing methodology and software systems derived from computing science for implementation in all aspects of biomedical research and medical practice. It is designed to serve: biochemists; biologists; geneticists; immunologists; neuroscientists; pharmacologists; toxicologists; clinicians; epidemiologists; psychiatrists; psychologists; cardiologists; chemists; (radio)physicists; computer scientists; programmers and systems analysts; biomedical, clinical, electrical and other engineers; teachers of medical informatics and users of educational software.
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