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PMID: 29107636 Published · ppublish English Journal Article

Impact of Side Branches on the Computation of Fractional Flow in Intracranial Arterial Stenosis Using the Computational Fluid Dynamics Method.

Liu H, Lan L, Leng X, Ip HL, Leung TWH, Wang D, Wong KS

Abstract

Computational fluid dynamics (CFD) allows noninvasive fractional flow (FF) computation in intracranial arterial stenosis. Removal of small artery branches is necessary in CFD simulation. The consequent effects on FF value needs to be judged. An idealized vascular model was built with 70% focal luminal stenosis. A branch with one third or one half of the radius of the parent vessel was added at a distance of 5, 10, 15 and 20 mm to the lesion. With pressure and flow rate applied as inlet and outlet boundary conditions, CFD simulations were performed. Flow distribution at bifurcations followed Murray's law. By including or removing side branches, five patient-specific intracranial artery models were simulated. Transient simulation was performed on a patient-specific model, with a larger branch for validation. Branching effect was considered trivial if the FF difference between paired models (branches included or removed) was within 5%. Compared with the control model without a branch, in all idealized models the relative differences of FF was within 2%. In five pairs of cerebral arteries (branches included/removed), FFs were 0.876 and 0.877, 0.853 and 0.858, 0.874 and 0.869, 0.865 and 0.858, 0.952 and 0.948. The relative difference in each pair was less than 1%. In transient model, the relative difference of FF was 3.5%. The impact of removing side branches with radius less than 50% of the parent vessel on FF measurement accuracy is negligible in static CFD simulations, and minor in transient CFD simulation.

Keywords
Side branches computational fluid dynamics fractional flow intracranial arterial stenosis
MeSH 主题词
Blood Flow Velocity Cerebral Angiography/methods Cerebral Arteries/diagnostic imaging,physiopathology Cerebrovascular Circulation Computed Tomography Angiography Constriction, Pathologic Humans Hydrodynamics Intracranial Arterial Diseases/diagnostic imaging,physiopathology Models, Cardiovascular Patient-Specific Modeling Radiographic Image Interpretation, Computer-Assisted Regional Blood Flow
作者与单位
共 7 位作者,点击展开单位 / ORCID
Liu Haipeng
Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China; Research Center for Medical Image Computing, Department of Diagnostic and Interventional Radiology, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China.
Lan Linfang
Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China.
Leng Xinyi
Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China.
Ip Hing Lung
Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China.
Leung Thomas W H
Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China.
Wang Defeng
Research Center for Medical Image Computing, Department of Diagnostic and Interventional Radiology, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China. Electronic address: [email protected].
Wong Ka Sing
Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China. Electronic address: [email protected].
Article Info
Journal
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Abbr.
J Stroke Cerebrovasc Dis
ISSN
1532-8511
Published
2018-01-00
电子出版
2017-00-27
页码
44-52
Language
English
Country/Region
United States
NLM ID
9111633
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