Highly Resilient 3D Aortic Hemodynamics derived directly from Aortic Geometry using AI

Aortic hemodynamic quantifications are vital for patient management. While 4D Flow MRI provides comprehensive aortic hemodynamics, it is hampered by long-acquisition times and cumbersome pre-processing. In this study, we developed an AI for the prediction of systolic 3D blood flow velocity vector fields with 3D aortic geometry as the only input. We performed testing on 248 BAV and 104 TAV datasets, using the systolic velocity vector fields from the 4D flow MRI as the ground-truth. Generally, we saw very strong agreement between the AI and the 4D flow and resilience to geometric changes (volume, dimension) in the input segmentation.