Introduction: The treatment of abdominal aortic aneurysm relies on surgical repair and the indication mainly depends on its size evaluated by the maximal diameter (Dmax). The aim of this study was to evaluate a new automatic method based on artificial intelligence to measure the Dmax on computed tomography angiography.
Methods: A fully automatic segmentation of the vascular system was performed using a hybrid method combining expert system with supervised deep learning. The aorta centreline was extracted from the segmented aorta and the aortic diameters were automatically calculated. Results were compared to manual segmentation performed by two human operators.
Results: The median absolute error between the two human operators was 1.2 mm (IQR 0.5-1.9). The automatic method using the deep learning algorithm demonstrated correlation with the human segmentation, with a median absolute error of 0.8 (0.5-4.2) mm and a coefficient correlation of 0.91 (P < 0.001).
Conclusions: Although validation in larger cohorts is required, this method brings perspectives to develop new tools to standardize and automate the measurement of abdominal aortic aneurysm Dmax in order to help clinicians in the decision-making process.
Copyright © 2021. Published by Elsevier Inc.