Key result
A novel fluid-structure computational framework successfully modeled a patient-specific abdominal aortic aneurysm, demonstrating its effectiveness for assessing clinical quantities and risk indexes.
A novel fluid-structure interaction computational framework effectively models vascular physiopathology and can assess clinical risk indexes in patient-specific aortic aneurysms.
Introduces histologically grounded vascular modeling framework; leaves open clinical translation pending validation.
A novel fluid-structure computational framework for vascular applications is herein presented. It is developed by combining the double multi-scale nature of vascular physiopathology in terms of both tissue properties and blood flow. Addressing arterial tissues, they are modelled via a nonlinear multiscale constitutive rationale, based only on parameters having a clear histological and biochemical meaning. Moreover, blood flow is described by coupling a three-dimensional fluid domain (undergoing physiological inflow conditions) with a zero-dimensional model, which allows to reproduce the influence of the downstream vasculature, furnishing a realistic description of the outflow proximal pressure. The fluid-structure interaction is managed through an explicit time-marching approach, able to accurately describe tissue nonlinearities within each computational step for the fluid problem. A case study associated to a patient-specific aortic abdominal aneurysmatic geometry is numerically investigated, highlighting advantages gained from the proposed multiscale strategy, as well as showing soundness and effectiveness of the established framework for assessing useful clinical quantities and risk indexes.
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Bianchi et al. (2017) studied Abdominal aortic aneurysm (n=1). Fluid-structure computational framework was evaluated on Assessment of clinical quantities and risk indexes. A novel fluid-structure computational framework successfully modeled a patient-specific abdominal aortic aneurysm, demonstrating its effectiveness for assessing clinical quantities and risk indexes.
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