Quantification of functional hemodynamics in aortic valve disease using cardiac computed tomography angiography

被引：1
作者：
Liu X. [1 ]
Guo G. [2 ]
Wang A. [1 ]
Wang Y. [3 ,4 ,5 ,6 ]
Chen S. [3 ,4 ,5 ,6 ]
Zhao P. [3 ,4 ,5 ,6 ]
Yin Z. [3 ,4 ,5 ,6 ]
Liu S. [3 ,4 ,5 ,6 ]
Gao Z. [1 ]
Zhang H. [1 ]
Zu L. [3 ,4 ,5 ,6 ]
机构：
[1] School of Biomedical Engineering, Sun Yat-sen University, Shenzhen
[2] Department of Radiology, Peking University Third Hospital, Beijing
[3] Department of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital, Beijing
[4] State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing
[5] NHC Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Peking University, Beijing
[6] Beijing Key Laboratory of Cardiovascular Receptors Research, Beijing
来源：
Computers in Biology and Medicine | 2024年 / 177卷
基金：
中国国家自然科学基金;
关键词：
Aortic valve disease; Computed tomography angiography; Hemodynamic assessment; Image-based modeling; Transvalvular pressure gradient;
D O I：
10.1016/j.compbiomed.2024.108608
中图分类号：
学科分类号：
摘要：
Background and Objective: Cardiac computed tomography angiography (CTA) is the preferred modality for preoperative planning in aortic valve stenosis. However, it cannot provide essential functional hemodynamic data, specifically the mean transvalvular pressure gradient (MPG). This study aims to introduce a computational fluid dynamics (CFD) approach for MPG quantification using cardiac CTA, enhancing its diagnostic value. Methods: Twenty patients underwent echocardiography, cardiac CTA, and invasive catheterization for pressure measurements. Cardiac CTA employed retrospective electrocardiographic gating to capture multi-phase data throughout the cardiac cycle. We segmented the region of interest based on mid-systolic phase cardiac CTA images. Then, we computed the average flow velocity into the aorta as the inlet boundary condition, using variations in end-diastolic and end-systolic left ventricular volume. Finally, we conducted CFD simulations using a steady-state model to obtain pressure distribution within the computational domain, allowing for the derivation of MPG. Results: The mean value of MPG, measured via invasive catheterization (MPGInv), echocardiography (MPGEcho), and cardiac CTA (MPGCT), were 51.3 ± 28.4 mmHg, 44.8 ± 19.5 mmHg, and 55.8 ± 25.6 mmHg, respectively. In comparison to MPGInv, MPGCT exhibited a higher correlation of 0.91, surpassing that of MPGEcho, which was 0.82. Moreover, the limits of agreement for MPGCT ranged from −27.7 to 18.7, outperforming MPGEcho, which ranged from −40.1 to 18.0. Conclusions: The proposed method based on cardiac CTA enables the evaluation of MPG for aortic valve stenosis patients. In future clinical practice, a single cardiac CTA examination can comprehensively assess both the anatomical and functional hemodynamic aspects of aortic valve disease. © 2024 Elsevier Ltd
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