Aortic dissection is a life-threatening condition that remains an unpredictable complication of aortic aneurysm, a mostly silent and progressive disease. The only aortic morphological measurement established as predictor of dissection in existing guidelines is the maximal aortic diameter and its growth rate [1]. However, in more than 50% of patients who ultimately experienced aortic dissection, the aortic diameter was found below the recommended surgical threshold [2].

Recent studies based on computed tomography (CT) have shown that in addition to significant aortic luminal dilation, patients with ascending thoracic aortic aneurysm (ATAA) also present with significant elongation of the aorta [3,4]. These studies indicated that length and diameters were predictors of dissection independently of conventional risk factors [3,4], which suggests the need for multifactorial risk scores encompassing the most significant aortic morphological changes. Furthermore, both cohort [5], [6], [7] and computational fluid simulation [8] studies highlighted increased risk of aortic dissection with an increase in angle between the aortic root and brachiocephalic artery planes, induced by aortic tortuosity. Also, volume growth can occur in abdominal aortic aneurysm even though the maximal diameter remains stable [9] or in the ascending aorta of patients with descending aortic dissection and normal maximal diameters [10]. Thus, authors reported a higher reproducibility of aortic volume and its superiority for detecting aneurysm growth as compared with maximal diameters measured on selected slices [9,11].

Because repeat imaging is often needed for standard follow-up of patients with aortic disease, magnetic resonance imaging (MRI) of the aorta has emerged as an effective radiation-free modality for the three-dimensional (3D) evaluation of aortic morphology [12].

Accordingly, the purpose of this study was to investigate the added value of aortic volumes compared to diameters or cross-sectional areas in discriminating between patients with dilated aorta and matched controls using a semi-automated segmentation of 3D MRI images [13].