In:
Emergency and Critical Care Medicine, Ovid Technologies (Wolters Kluwer Health), Vol. 2, No. 4 ( 2022-12), p. 181-190
Abstract:
Hemodynamic parameters derived from computed tomography angiography–based computational fluid dynamics (CFD) analysis have been widely used for clinical decision-making and researches to assess the vulnerability of atherosclerotic plaques and explain the initialization and development of atherosclerosis. Subbranches in the CFD model might affect the accuracy of hemodynamic parameters, but the effectiveness has been least quantified. Methods A coronary artery baseline model was generated with focal stenosis at the proximal left anterior descending artery. Nineteen comparing models were created by systematically removing various subbranches to examine the changes in hemodynamic parameters, including time-averaged pressure (TAP), time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), and particle relative residence time (RRT). Changes in these parameters were assessed quantitatively around the stenosis and near the region where subbranches were removed. Results The removal of subbranches caused a significant change in outflow rate, and there was generally a decrease in all CFD parameters in the regions of interest with a decrease in outflow rate. The subbranch removal had a significant impact on the calculation of TAWSS, OSI, and RRT, whereas TAP was insensitive to the removal with approximately 0.25% variation in all 19 models. The local effect from removing branch segments generally became negligible after 5 diameters away from the cutting-off position, but the decrease could be affected by other factors, such as a large curvature. Conclusion The outflow rate is a dominant factor for the calculation of TAP, TAWSS, OSI, and RRT. Removal of subbranches has a minor effect on the TAP calculation, but its effect is considerable on the TAWSS, OSI, and RRT. The effect of subbranch removal is limited in a region with 5 local diameters.
Type of Medium:
Online Resource
ISSN:
2097-0617
DOI:
10.1097/EC9.0000000000000062
Language:
English
Publisher:
Ovid Technologies (Wolters Kluwer Health)
Publication Date:
2022
detail.hit.zdb_id:
3123831-2
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