Determinants of ascending aortic morphology: Cross-sectional deep learning-based analysis on 25,073 non-contrast-enhanced NAKO MRI studies.

Aims: Understanding determinants of thoracic aortic morphology is crucial for precise diagnostics and therapeutic approaches. This study aimed to automatically characterize ascending aortic morphology based on 3D non-contrast-enhanced magnetic resonance angiography (NC-MRA) data from the epidemiological cross-sectional German National Cohort (NAKO) and to investigate possible determinants of mid-ascending aortic diameter (mid-AAoD).

Methods And Results: Deep learning (DL) automatically segmented the thoracic aorta and ascending aortic length, volume, and diameter was extracted from 25,073 NC-MRAs.