Evidence map›Paper›PMID 41323467›Full record

ArticleFrontiers in bioengineering and biotechnology2025

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

Mengqiang Hu, Ming Yang, Zhihao Ding, Shu Chen, Xiaoyu Qi, Chuanzhi Zhu, Yining Zhang, Chao Yang, Yuanming Luo

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Article in Frontiers in bioengineering and biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

9 authors.

Mengqiang Hu *State Key Laboratory of Transvascular Implantation Devices, Hangzhou, China.
Ming Yang *Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Zhihao DingState Key Laboratory of Transvascular Implantation Devices, Hangzhou, China.
Shu ChenDepartment of Cardiovascular Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Xiaoyu QiDepartment of Vascular Surgery, Union Hospital Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Chuanzhi ZhuState Key Laboratory of Transvascular Implantation Devices, Hangzhou, China.
Yining ZhangDepartment of Cardiovascular Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Chao YangDepartment of Vascular Surgery, Union Hospital Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yuanming LuoDepartment of Mechanical Engineering, The University of Iowa, Iowa, IA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

aortic diseasesboudary conditionCFDhemodynamicswindkessel model

Identifiers

PMID41323467
PMCPMC12657352

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.