Towards the improved quantification of in vivo abnormal wall shear stresses in BAV-affected patients from 4D-flow imaging: Benchmarking and application to real data |
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| Institution: | 1. Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milano, Italy;2. Department of Chemical Engineering, Imperial College, London, United Kingdom;3. Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom;4. Institute of Hydromechanics, National Academy of Sciences of Ukraine, Kyiv, Ukraine;5. Department of cardiothoracic and Respiratory Sciences, Second University of Naples, Naples, Italy;1. Department of Biomedical Engineering, Tel Aviv University and Stony Brook University;2. Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA;3. Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA;1. University of Maryland Baltimore School of Medicine, Department of Neurology, 110 S. Paca St, Baltimore, MD 21202, USA;2. IRCCS Fondazione Don Carlo Gnocchi ONLUS, Biomedical Technology Department, via Capecelatro 66, 20148 Milano, Italy;3. Politecnico di Milano, Department of Electronics, Information and Bioengineering, via Golgi 39, 20133 Milano, Italy;1. Biomedical Engineering, University of Strathclyde, UK;2. Institute for Applied Health Research, Glasgow Caledonian University, UK;3. School of Health Sciences, University of Salford, UK;4. Stroke MCN, NHS Lanarkshire, UK;1. INRIA Paris, 2 Rue Simone Iff, 75012 Paris, France;2. Sorbonne Universités, UPMC Univ. Paris 6, Laboratoire Jacques-Louis Lions, 75252 Paris, France;3. Medical R&D, WBL Healthcare, Air Liquide Santé International, 1 Chemin de la Porte des Loges, 78350 Les Loges-en-Josas, France;4. Department of Mechanical Engineering, Lafayette College, Easton, PA 18042, USA |
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| Abstract: | Bicuspid aortic valve (BAV), i.e. the fusion of two aortic valve cusps, is the most frequent congenital cardiac malformation. Its progression is often characterized by accelerated leaflet calcification and aortic wall dilation. These processes are likely enhanced by altered biomechanical stimuli, including fluid-dynamic wall shear stresses (WSS) acting on both the aortic wall and the aortic valve. Several studies have proposed the exploitation of 4D-flow magnetic resonance imaging sequences to characterize abnormal in vivo WSS in BAV-affected patients, to support prognosis and timing of intervention. However, current methods fail to quantify WSS peak values.On this basis, we developed two new methods for the improved quantification of in vivo WSS acting on the aortic wall based on 4D-flow data.We tested both methods separately and in combination on synthetic datasets obtained by two computational fluid-dynamics (CFD) models of the aorta with healthy and bicuspid aortic valve. Tests highlighted the need for data spatial resolution at least comparable to current clinical guidelines, the low sensitivity of the methods to data noise, and their capability, when used jointly, to compute more realistic peak WSS values as compared to state-of-the-art methods.The integrated application of the two methods on the real 4D-flow data from a preliminary cohort of three healthy volunteers and three BAV-affected patients confirmed these indications. In particular, quantified WSS peak values were one order of magnitude higher than those reported in previous 4D-flow studies, and much closer to those computed by highly time- and space-resolved CFD simulations. |
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| Keywords: | Aorta Bicuspid aortic valve Cardiac magnetic resonance Fluid dynamics |
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