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Blood flow velocity prediction in aorto-iliac stent grafts using computational fluid dynamics and Taguchi method.

Authors :
Chong AY
Doyle BJ
Jansen S
Ponosh S
Cisonni J
Sun Z
Source :
Computers in biology and medicine [Comput Biol Med] 2017 May 01; Vol. 84, pp. 235-246. Date of Electronic Publication: 2017 Mar 20.
Publication Year :
2017

Abstract

Covered Endovascular Reconstruction of Aortic Bifurcation (CERAB) is a new technique to treat extensive aortoiliac occlusive disease with covered expandable stent grafts to rebuild the aortoiliac bifurcation. Post stenting Doppler ultrasound (DUS) measurement of maximum peak systolic velocity (PSV <subscript>max</subscript> ) in the stented segment is widely used to determine patency and for follow up surveillance due to the portability, affordability and ease of use. Anecdotally, changes in hemodynamics created by CERAB can lead to falsely high PSV <subscript>max</subscript> requiring CT angiography (CTA) for further assessment. Therefore, the importance of DUS would be enhanced with a proposed PSV <subscript>max</subscript> prediction tool to ascertain whether PSV <subscript>max</subscript> falls within the acceptable range of prediction. We have developed a prediction tool based on idealized models of aortoiliac bifurcations with various infra-renal PSV (PSV <subscript>in</subscript> ), iliac to aortic area ratios (R) and aortoiliac bifurcation angles (α). Taguchi method with orthogonal arrays (OA) was utilized to minimize the number of Computational Fluid Dynamics (CFD) simulations performed under physiologically realistic conditions. Analysis of Variance (ANOVA) and Multiple Linear Regression (MLR) analyses were performed to assess Goodness of fit and to predict PSV <subscript>max.</subscript> PSV <subscript>in</subscript> and R were found to contribute 94.06% and 3.36% respectively to PSV <subscript>max</subscript> . The Goodness of fit based on adjusted R <superscript>2</superscript> improved from 99.1% to 99.9% based on linear and exponential functions. The PSV <subscript>max</subscript> predictor based on the exponential model was evaluated with sixteen patient specific cases with a mean prediction error of 9.9% and standard deviation of 6.4%. Eleven out of sixteen cases (69%) in our current retrospective studies would have avoided CTA if the proposed predictor was used to screen out DUS measured PSV <subscript>max</subscript> with prediction error greater than 15%. The predictor therefore has the potential to be used as a clinical tool to detect PSV <subscript>max</subscript> more accurately post aortoiliac stenting and might reduce diagnostic errors and avoid unnecessary expense and risk from CTA follow-up imaging.<br /> (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Details

Language :
English
ISSN :
1879-0534
Volume :
84
Database :
MEDLINE
Journal :
Computers in biology and medicine
Publication Type :
Academic Journal
Accession number :
28457427
Full Text :
https://doi.org/10.1016/j.compbiomed.2017.03.015