Patient-specific analysis of post-operative aortic hemodynamics: a focus on thoracic endovascular repair (TEVAR)
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The purpose of this study is to quantitatively evaluate the impact of endovascular repair on aortic hemodynamics. The study addresses the assessment of post-operative hemodynamic conditions of a real clinical case through patient-specific analysis, combining accurate medical image analysis and advanced computational fluid-dynamics (CFD). Although the main clinical concern was firstly directed to the endoluminal protrusion of the prosthesis, the CFD simulations have demonstrated that there are two other important areas where the local hemodynamics is impaired and a disturbed blood flow is present: the first one is the ostium of the subclavian artery, which is partially closed by the graft; the second one is the stenosis of the distal thoracic aorta. Besides the clinical relevance of these specific findings, this study highlights how CFD analyses allow to observe important flow effects resulting from the specific features of patient vessel geometries. Consequently, our results demonstrate the potential impact of computational biomechanics not only on the basic knowledge of physiopathology, but also on the clinical practice, thanks to a quantitative extraction of knowledge made possible by merging medical data and mathematical models.
KeywordsComputational fluid dynamics (CFD) Biomechanics Aorta Endograft Patient-specific
This work is partially funded by: the Cariplo Foundation through the Project no. 2009.2822; ERC Starting Grant through the Project ISOBIO: Isogeometric Methods for Biomechanics (No. 259229); Ministero dell’Istruzione, dell’Università e della Ricerca through the Project no. 2010BFXRHS. The authors would like to acknowledge: Dr. T. Passerini for the support regarding the computational analysis; MD Matteo Pegorer, MD Jip Tolenaar, and MD G. H. W. van Bogerijen for the support regarding the data collection and clinical considerations; S. Marconi and Dr. M. Piccinelli for the support regarding the medical image elaboration. Moreover, Regione Lombardia and CINECA Consortium through a LISA Initiative (Laboratory for Interdisciplinary Advanced Simulation) 2013 grant are gratefully acknowledged.
Conflict of interest
The authors have no commercial, proprietary, or financial interest in any products or companies described in this paper.
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