Fluid-structure simulations outperform computational fluid dynamics in the differentiation of progressive dilation in Marfan syndrome patients
Cite this dataset
Pons, Ramon et al. (2020). Fluid-structure simulations outperform computational fluid dynamics in the differentiation of progressive dilation in Marfan syndrome patients [Dataset]. Dryad. https://doi.org/10.5061/dryad.zcrjdfn6j
Introduction: Abnormal fluid dynamics at the ascending aorta may be at the origin of aortic aneurysms. This study was aimed at comparing the performance of computational fluid dynamics (CFD) and fluid-structure interaction (FSI) simulations against 4D-flow MRI data; and to assess the capacity of advanced fluid dynamics markers to stratify aneurysm progression risk.
Methods: Eight Marfan syndrome patients, four with stable and four with dilating aneurysms of the proximal aorta, and four healthy controls were studied. FSI and CFD simulations were performed with MRI-derived geometry, inlet velocity field and Young’s modulus. Flow displacement, jet angle and maximum velocity evaluated from FSI and CFD simulations were compared to 4D-flow MRI data. A dimensionless parameter, the shear stress ratio, was evaluated from FSI and CFD simulations and assessed as potential correlate of aneurysm progression.
Results: FSI simulations successfully matched MRI data regarding descending to ascending aorta flow rates (R2=0.92) and pulse wave velocity (R2=0.99). Compared to CFD, FSI simulations showed significantly lower percentage errors in ascending and descending aorta in flow displacement (-46% ascending, -41% descending), jet angle (-28% ascending, -50% descending) and maximum velocity (-37% ascending, -34% descending) with respect to 4D-flow MRI. FSI- but not CFD-derived shear stress ratio differentiated between stable and dilating Marfan patients.
Conclusions: Fluid dynamic simulations of the thoracic aorta require fluid-solid interaction to properly reproduce complex hemodynamics. FSI- but not CFD-derived shear stress ratio could help stratifying Marfan patients.