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PMID: 41323467 Published · epublish English Journal Article

Estimating flow division in aortic branches of diseased aorta: a method for boundary condition specification in CFD analysis.

Frontiers in bioengineering and biotechnology ·Vol. 13 ·2025-00-00 ·页码 1640687

Hu M, Yang M, Ding Z, Chen S, Qi X, Zhu C, Zhang Y, Yang C, Luo Y

Abstract

Hemodynamic predictions using computational fluid dynamics (CFD) simulations can provide valuable guidance assessing aortic disease risks. However, their reliability is hindered by the lack of patient-specific boundary conditions, particularly measured flow rates. This study addresses this knowledge gap by introducing a method for estimating flow division in aortic branches. The geometry of the lesional aorta was first repaired to obtain a near-healthy reference geometry. An iterative CFD simulation was then employed to estimate the flow division in the branches of the diseased aorta. Specifically, empirical boundary conditions from healthy individuals were used to predict the outlet pressures of reference geometry, which were subsequently converted into resistance models. These resistance models were then assigned to the outlets of the diseased aorta to predict the inlet pressure. The discrepancy between the predicted and target inlet pressures was iteratively minimized by adjusting the inlet pressure of the reference model until convergence was achieved. The final flow division in the branches of the diseased aorta was then obtained. The performance of the proposed method was investigated in three patients with aortic dissection or aneurysm. The proposed method predicted lower flow rates in branches with severe stenosis, which was more consistent with physiological expectations. Furthermore, the predicted blood pressure differed significantly from that obtained using the traditional method and was closer to the target values. The proposed method provides a practical solution for specifying boundary conditions in hemodynamic studies when clinically measured flow rates are unavailable.

Keywords
CFD aortic diseases boudary condition hemodynamics windkessel model
作者与单位
共 9 位作者,点击展开单位 / ORCID
Hu Mengqiang
State Key Laboratory of Transvascular Implantation Devices, Hangzhou, China. | Department of Technology, Boea Wisdom (Hangzhou) Network Technology Co., Ltd., Hangzhou, China. | Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yang Ming
Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. | Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China.
Ding Zhihao
State Key Laboratory of Transvascular Implantation Devices, Hangzhou, China. | Department of Technology, Boea Wisdom (Hangzhou) Network Technology Co., Ltd., Hangzhou, China.
Chen Shu
Department of Cardiovascular Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Qi Xiaoyu
Department of Vascular Surgery, Union Hospital Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Zhu Chuanzhi
State Key Laboratory of Transvascular Implantation Devices, Hangzhou, China. | Department of Technology, Boea Wisdom (Hangzhou) Network Technology Co., Ltd., Hangzhou, China.
Zhang Yining
Department of Cardiovascular Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yang Chao
Department of Vascular Surgery, Union Hospital Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Luo Yuanming
Department of Mechanical Engineering, The University of Iowa, Iowa, IA, United States.
Article Info
Journal
Frontiers in bioengineering and biotechnology
Abbr.
Front Bioeng Biotechnol
ISSN
2296-4185
Published
2025-00-00
电子出版
2025-00-13
页码
1640687
Language
English
Country/Region
Switzerland
NLM ID
101632513
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