Work

Anatomical deformation prediction using artificial intelligence for fusion imaging during aortic endovascular procedures

Year: 2026

Type: article

Abstract: Placement of an aortic stent graft induces anatomical deformations, particularly at the iliac level, because of the introduction of rigid devices. Anticipating these changes may improve the accuracy of fusion guidance during endovascular procedures. In this prospective single-center study, a deep learning-based sizing software was used to generate a deformation-adjusted three-dimensional fusion mask, which was compared with a conventional, nondeformed mask using intraoperative angiography as the reference standard. In a cohort of 31 patients, the deformation-adjusted mask significantly improved the fusion accuracy for renal artery ostia positioning, iliac artery alignment, and guidewire localization, without any additional acquisition time. These findings suggest that deformation-aware fusion masks may enhance intraoperative navigation during aortic endovascular repair.

Source: Journal of Vascular Surgery Cases and Innovative Techniques

DOI: 10.1016/j.jvscit.2026.102297

Authors: Vannier Cindy, Lalys Florent, Hollier-Ben Turkia Jade, Lucas Antoine, Kaladji Adrien

Institutions: Centre Hospitalier Universitaire de Rennes, Inserm, Laboratoire Traitement du Signal et de l'Image, Université Rennes 1, Université de Rennes

Language: English

Topic: Aortic aneurysm repair treatments

Subfield: Surgery

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,250