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PMID: 28457427 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't

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

Computers in biology and medicine ·Vol. 84 ·2017-00-01 ·页码 235-246

Chong AY, Doyle BJ, Jansen S, Ponosh S, Cisonni J, Sun Z

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 (PSVmax) 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 PSVmax requiring CT angiography (CTA) for further assessment. Therefore, the importance of DUS would be enhanced with a proposed PSVmax prediction tool to ascertain whether PSVmax 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 (PSVin), 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 PSVmax. PSVin and R were found to contribute 94.06% and 3.36% respectively to PSVmax. The Goodness of fit based on adjusted R2 improved from 99.1% to 99.9% based on linear and exponential functions. The PSVmax 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 PSVmax with prediction error greater than 15%. The predictor therefore has the potential to be used as a clinical tool to detect PSVmax more accurately post aortoiliac stenting and might reduce diagnostic errors and avoid unnecessary expense and risk from CTA follow-up imaging.

Keywords
Analysis of variance Aortoiliac stenting Computational fluid dynamics Multiple linear regressions Orthogonal array Peak Systolic Velocity Taguchi method
MeSH 主题词
Aorta, Abdominal/diagnostic imaging,physiology,surgery Blood Flow Velocity/physiology Blood Vessel Prosthesis Implantation Humans Iliac Artery/diagnostic imaging,physiology,surgery Image Processing, Computer-Assisted/methods Models, Statistical Stents Systole/physiology Ultrasonography, Doppler
作者与单位
共 6 位作者,点击展开单位 / ORCID
Chong Albert Y
Department of Medical Radiation Sciences, Curtin University, Perth, Australia.
Doyle Barry J
Vascular Engineering Laboratory, Harry Perkins Institute of Medical Research, Perth, Australia; School of Mechanical and Chemical Engineering, The University of Western Australia, Perth, Australia; Centre for Cardiovascular Science, The University of Edinburgh, Edinburgh, UK.
Jansen Shirley
Department of Vascular and Endovascular Surgery, Sir Charles Gairdner Hospital, Perth, WA, Australia; Centre for Population Health Research, Curtin University, Western Australia, Australia; Faculty of Health and Medical Sciences, University of Western Australia, Australia; Heart Research Institute, Harry Perkins Institute of Medical Research, Perth, WA, Australia.
Ponosh Stefan
Hollywood Private Hospital, Perth, Western Australia, Australia.
Cisonni Julien
Department of Mechanical Engineering, Curtin University, Perth, Australia.
Sun Zhonghua
Department of Medical Radiation Sciences, Curtin University, Perth, Australia. Electronic address: [email protected].
Article Info
Journal
Computers in biology and medicine
Abbr.
Comput Biol Med
ISSN
1879-0534
Corresponding email
Published
2017-00-01
电子出版
2017-00-20
页码
235-246
Language
English
Country/Region
United States
NLM ID
1250250
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