In Silico Fluid-Structure Interaction Reveals Wall Strain as a Potential Trigger for Aneurysm Initiation in a Rat Model
ORAL
Abstract
A rat aneurysm model was created via bilateral common carotid artery anastomosis, as previously reported by Shimizu et al., and serial magnetic resonance angiography was performed. Five cases in which aneurysms developed near the vascular bifurcations were selected. CFD analysis was conducted using images acquired immediately before aneurysm initiation. Measured blood flow velocity and blood pressure were applied as inlet and outlet boundary conditions, respectively. For the FSI analysis, a two-layer model representing the vascular wall and surrounding tissues was added outside the lumen; its thickness was estimated by ultrasound and excised-vessel measurements. Material properties such as Young’s modulus were calibrated to match in vivo deformation observed on ultrasound imaging. Principal strain at each prospective aneurysm site was calculated as an index of wall stretch. For one representative case, vascular tissues were harvested for histopathological analyses.
In all cases, FSI analysis revealed a high-pressure region on the vessel wall near the apex of the bifurcation, where branching flow produced elevated wall shear stress divergence. Principal strain was observed in the same region, with a mean value of 12.3% ± 2.99% at the aneurysm sites. Previous in vitro studies have reported that stretching fibroblasts can elicit inflammatory responses. The strain magnitude obtained in this study aligns with the threshold of wall stretch reported to induce such inflammation. Furthermore, histology of the representative case revealed cellular damage and macrophage infiltration at the aneurysm initiation site. Therefore, integrating principal strain quantified through FSI with conventional hemodynamic indices offers the possibility of prospectively identifying sites of aneurysm initiation.
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Presenters
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Kohei Hoshino
Graduate School of Engineering, Tokyo University of Science / Division of Innovation for Medical Information Technology, The Jikei University School of Medicine
Authors
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Kohei Hoshino
Graduate School of Engineering, Tokyo University of Science / Division of Innovation for Medical Information Technology, The Jikei University School of Medicine
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Hirokazu Koseki
Department of Neurosurgery, The Jikei University School of Medicine
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Soichiro Fujimura
Faculty of Engineering, Tokyo University of Science / Division of Innovation for Medical Information Technology, The Jikei University School of Medicine, Department of Mechanical Engineering, Tokyo University of Science / Division of Innovation for Medical Information Technology, The Jikei University School of Medicine
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Hiroyuki Takao
Division of Innovation for Medical Information Technology, The Jikei University School of Medicine / Department of Neurosurgery, The Jikei University School of Medicine
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Yuichi Murayama
Department of Neurosurgery, The Jikei University School of Medicine
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Makoto Yamamoto
Faculty of Engineering, Tokyo University of Science, Department of Mechanical Engineering, Tokyo University of Science