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Proceedings Paper

Association between hemodynamic modifications and clinical outcome of intracranial aneurysms treated using flow diverters
Author(s): Nikhil Paliwal; Robert J. Damiano; Jason M. Davies; Adnan H. Siddiqui; Hui Meng
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Paper Abstract

Treatment of intracranial aneurysms (IAs) has been revolutionized by the advent of endovascular Flow Diverters (FDs), which disrupt blood flow within the aneurysm to induce pro-thrombotic conditions, and serves as a scaffold for endothelial ingrowth and arterial remodeling. Despite good clinical success of FDs, complications like incomplete occlusion and post-treatment rupture leading to subarachnoid hemorrhage have been reported. In silico computational fluid dynamic analysis of the pre- and post-treated geometries of IA patients can shed light on the contrasting blood hemodynamics associated with different clinical outcomes. In this study, we analyzed hemodynamic modifications in 15 IA patients treated using a single FD; 10 IAs were completely occluded (successful) and 5 were partially occluded (unsuccessful) at 12-month follow-up. An in-house virtual stenting workflow was used to recapitulate the clinical intervention on these cases, followed by CFD to obtain pre- and post-treatment hemodynamics. Bulk hemodynamic parameters showed comparable reductions in both groups with average inflow rate and aneurysmal velocity reduction of 40.3% and 52.4% in successful cases, and 34.4% and 49.2% in unsuccessful cases. There was a substantial reduction in localized parameter like vortex coreline length and Energy Loss for successful cases, 38.2% and 42.9% compared to 10.1% and 10.5% for unsuccessful cases. This suggest that for successfully treated IAs, the localized complex blood flow is disrupted more prominently by the FD as compared to unsuccessful cases. These localized hemodynamic parameters can be potentially used in prediction of treatment outcome, thus aiding the clinicians in a priori assessment of different treatment strategies.

Paper Details

Date Published: 3 March 2017
PDF: 7 pages
Proc. SPIE 10135, Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling, 101352F (3 March 2017); doi: 10.1117/12.2254584
Show Author Affiliations
Nikhil Paliwal, Univ. at Buffalo (United States)
Robert J. Damiano, Univ. at Buffalo (United States)
Jason M. Davies, Univ. at Buffalo (United States)
Adnan H. Siddiqui, Univ. at Buffalo (United States)
Hui Meng, Univ. at Buffalo (United States)


Published in SPIE Proceedings Vol. 10135:
Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling
Robert J. Webster; Baowei Fei, Editor(s)

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