Numerical Simulation and Clinical Implications of Stenosis in Coronary Blood Flow

dc.contributor.authorZhang, Jun-Mei
dc.contributor.authorZhong, Liang
dc.contributor.authorLuo, Tong
dc.contributor.authorHuo, Yunlong
dc.contributor.authorTan, Swee Yaw
dc.contributor.authorWong, Aaron Sung Lung
dc.contributor.authorSu, Boyang
dc.contributor.authorWan, Min
dc.contributor.authorZhao, Xiaodan
dc.contributor.authorKassab, Ghassan S.
dc.contributor.authorLee, Heow Pueh
dc.contributor.authorKhoo, Boo Cheong
dc.contributor.authorKang, Chang-Wei
dc.contributor.authorBa, Te
dc.contributor.authorTan, Ru San
dc.contributor.departmentBiomedical Engineering, Purdue School of Engineering and Technology
dc.date.accessioned2025-04-03T08:34:12Z
dc.date.available2025-04-03T08:34:12Z
dc.date.issued2014
dc.description.abstractFractional flow reserve (FFR) is the gold standard to guide coronary interventions. However it can only be obtained via invasive angiography. The objective of this study is to propose a noninvasive method to determine FFRCT by combining computed tomography angiographic (CTA) images and computational fluid dynamics (CFD) technique. Utilizing the method, this study explored the effects of diameter stenosis (DS), stenosis length, and location on FFRCT. The baseline left anterior descending (LAD) model was reconstructed from CTA of a healthy porcine heart. A series of models were created by adding an idealized stenosis (with DS from 45% to 75%, stenosis length from 4 mm to 16 mm, and at 4 locations separately). Through numerical simulations, it was found that FFRCT decreased (from 0.89 to 0.74), when DS increased (from 45% to 75%). Similarly, FFRCT decreased with the increase of stenosis length and the stenosis located at proximal position had lower FFRCT than that at distal position. These findings are consistent with clinical observations. Applying the same method on two patients' CTA images yielded FFRCT close to the FFR values obtained via invasive angiography. The proposed noninvasive computation of FFRCT is promising for clinical diagnosis of CAD.
dc.eprint.versionFinal published version
dc.identifier.citationZhang JM, Zhong L, Luo T, et al. Numerical simulation and clinical implications of stenosis in coronary blood flow. Biomed Res Int. 2014;2014:514729. doi:10.1155/2014/514729
dc.identifier.urihttps://hdl.handle.net/1805/46773
dc.language.isoen_US
dc.publisherHindawi
dc.relation.isversionof10.1155/2014/514729
dc.relation.journalBioMed Research International
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourcePMC
dc.subjectBlood flow velocity
dc.subjectCoronary circulation
dc.subjectCoronary stenosis
dc.subjectCoronary vessels
dc.subjectMyocardium
dc.titleNumerical Simulation and Clinical Implications of Stenosis in Coronary Blood Flow
dc.typeArticle
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