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Article Dans Une Revue Biomechanics and Modeling in Mechanobiology Année : 2016

Adaptive outflow boundary conditions improve post-operative predictions after repair of peripheral pulmonary artery stenosis

Résumé

Peripheral pulmonary artery stenosis (PPS) is a congenital abnormality resulting in pulmonary blood flow disparity and right ventricular hypertension. Despite recent advance in catheter-based interventions, surgical reconstruction is still preferred to treat complex PPS. However optimal surgical strategies remain unclear. It would be of great benefit to be able to predict post-operative hemodynamics to assist with surgical planning toward optimizing outcomes. While image-based computational fluid dynamics has been used in cardiovascular surgical planning, most studies have focused on the impact of local geometric changes on hemodynamic performance. Previous experimental studies suggest morphological changes in the pulmonary arteries not only alter local hemodynamics but also lead to distal pulmonary adaptation. In this proof of concept study, a constant shear stress hypothesis and structured pulmonary trees are used to derive adaptive outflow boundary conditions for postoperative simulations. Patient-specific simulations showed the adaptive outflow boundary conditions by the constant shear stress model to provide better predictions of pulmonary flow distribution than the conventional strategy of maintaining outflow boundary conditions. On average, the relative difference, when compared to the gold standard clinical test, in blood flow distribution to the right lung is reduced from 20 to 4%. This suggests adaptive outflow boundary conditions should be incorporated into post-operative modeling in patients with complex PPS.
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Dates et versions

hal-01414295 , version 1 (12-12-2016)

Identifiants

Citer

Weiguang Yang, Jeffrey A. Feinstein, Irene E. Vignon-Clementel. Adaptive outflow boundary conditions improve post-operative predictions after repair of peripheral pulmonary artery stenosis. Biomechanics and Modeling in Mechanobiology, 2016, 15 (5), pp.1345-1353. ⟨10.1007/s10237-016-0766-5⟩. ⟨hal-01414295⟩
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