Calibration of patient-specific boundary conditions for coupled CFD models of the aorta derived from 4D Flow-MRI.
Calibration of patient-specific boundary conditions for coupled CFD models of the aorta derived from 4D Flow-MRI.
复制标题
DOI:
10.3389/fbioe.2023.1178483
复制
发表时间:
2023
影响因子:
5.7
通讯作者:
Kazakidi, Asimina
中科院分区:
文献类型:
--
作者:
Black, Scott MacDonald;Maclean, Craig;Hall Barrientos, Pauline;Ritos, Konstantinos;McQueen, Alistair;Kazakidi, Asimina
Introduction: Patient-specific computational fluid dynamics (CFD) models permit analysis of complex intra-aortic hemodynamics in patients with aortic dissection (AD), where vessel morphology and disease severity are highly individualized. The simulated blood flow regime within these models is sensitive to the prescribed boundary conditions (BCs), so accurate BC selection is fundamental to achieve clinically relevant results. Methods: This study presents a novel reduced-order computational framework for the iterative flow-based calibration of 3-Element Windkessel Model (3EWM) parameters to generate patient-specific BCs. These parameters were calibrated using time-resolved flow information derived from retrospective four-dimensional flow magnetic resonance imaging (4D Flow-MRI). For a healthy and dissected case, blood flow was then investigated numerically in a fully coupled zero dimensional-three dimensional (0D-3D) numerical framework, where the vessel geometries were reconstructed from medical images. Calibration of the 3EWM parameters was automated and required ~3.5 min per branch. Results: With prescription of the calibrated BCs, the computed near-wall hemodynamics (time-averaged wall shear stress, oscillatory shear index) and perfusion distribution were consistent with clinical measurements and previous literature, yielding physiologically relevant results. BC calibration was particularly important in the AD case, where the complex flow regime was captured only after BC calibration. Discussion: This calibration methodology can therefore be applied in clinical cases where branch flow rates are known, for example, via 4D Flow-MRI or ultrasound, to generate patient-specific BCs for CFD models. It is then possible to elucidate, on a case-by-case basis, the highly individualized hemodynamics which occur due to geometric variations in aortic pathology high spatiotemporal resolution through CFD.
登录
查看更多内容
影响因子:
4.6
作者:
Cherry, Molly;Khatir, Zinedine;Khan, Amirul;Bissell, Malenka
通讯作者:
Bissell, Malenka
影响因子:
3.9
作者:
Chen D;Müller-Eschner M;von Tengg-Kobligk H;Barber D;Böckler D;Hose R;Ventikos Y
通讯作者:
Ventikos Y
影响因子:
--
作者:
Celi S;Vignali E;Capellini K;Gasparotti E
通讯作者:
Gasparotti E
影响因子:
2.2
作者:
Bonfanti, Mirko;Franzetti, Gaia;Diaz-Zuccarini, Vanessa
通讯作者:
Diaz-Zuccarini, Vanessa
影响因子:
3.7
作者:
Amaya R;Cancel LM;Tarbell JM
通讯作者:
Tarbell JM