Abstract
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.
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Article Info
Publication History
Published online: December 22, 2021
Accepted:
December 4,
2021
Received in revised form:
November 24,
2021
Received:
October 9,
2021
Identification
Copyright
© 2021 Elsevier Inc. All rights reserved.
