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Proceedings Paper

Personalized design and virtual evaluation of physician-modified stent grafts for juxta-renal abdominal aortic aneurysms
Author(s): Soroosh Sanatkhani; Sanjeev G. Shroff; Prahlad G. Menon
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Paper Abstract

Endovascular aneurysm repair (EVAR) of juxtarenal aortic aneurysms (JAA) is particularly challenging owing to the requirement of suprarenal EVAR graft fixation, which has been associated with significant declines in long term renal function. Therefore, the ability to design fenestrated EVAR grafts on a personalized basis in order to ensure visceral and renal perfusion, is highly desirable. The objectives of this study are: a) To demonstrate novel 3D geometric methods to virtually design and deploy EVAR grafts into a virtually designed JAA, by applying a custom surface mesh deformation tool to a patient-specific descending aortic model reconstructed from computed tomographic (CT) images; and b) To virtually evaluate patient-specific renal flow and wall stresses in these patient-specific virtually EVAR geometries, using computational fluid dynamics (CFD). The presented framework may provide the modern cardiovascular surgeon the ability to leverage non-invasive, pre-operative imaging equipment to personalize and guide EVAR therapeutic strategy. Our CFD studies revealed that virtual EVAR grafting of a patient-specific JAA, with optimal fenestration sites and renal stenting, led to a 179.67±15.95% and 1051.43±18.34% improvement in right and left renal flow rates, respectively, when compared with the baseline patient-specific aortic geometry with renal stenoses, whereas a right and left renal flow improved by 36.44±2.24% and 885.93±12.41%, respectively, relative to the equivalently modeled JAA with renal stenoses, considering averages across the three simulated inflow rate cases. The proposed framework have utility to iteratively optimize suprarenal EVAR fixation length and achieve normal renal wall shear stresses and streamlined juxtarenal hemodynamics.

Paper Details

Date Published: 24 February 2017
PDF: 9 pages
Proc. SPIE 10133, Medical Imaging 2017: Image Processing, 101332C (24 February 2017); doi: 10.1117/12.2254404
Show Author Affiliations
Soroosh Sanatkhani, Univ. of Pittsburgh (United States)
Sanjeev G. Shroff, Univ. of Pittsburgh (United States)
Prahlad G. Menon, Univ. of Pittsburgh (United States)
Duquesne Univ. (United States)


Published in SPIE Proceedings Vol. 10133:
Medical Imaging 2017: Image Processing
Martin A. Styner; Elsa D. Angelini, Editor(s)

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