Fully automatic volume segmentation using deep learning approaches to assess aneurysmal sac evolution after infrarenal endovascular aortic repair.

Journal: Journal of vascular surgery
PMID:

Abstract

OBJECTIVE: Endovascular aortic repair (EVAR) surveillance relies on serial measurements of the maximal diameter despite significant inter- and intraobserver variability. Volumetric measurements are more sensitive; however, their general use has been hampered by the time required for their implementation. An innovative, fully automated software (PRAEVAorta; Nurea, Bordeaux, France), using artificial intelligence, had previously demonstrated fast and robust detection of the characteristics of infrarenal abdominal aortic aneurysms on preoperative imaging studies. In the present study, we assessed the robustness of these data on post-EVAR computed tomography (CT) scans.

Authors

  • Caroline Caradu
    Vascular Surgery Department, Bordeaux University Hospital, Bordeaux, France.
  • Anna-Louise Pouncey
    Department of Vascular Surgery, Imperial College London, London, UK.
  • Emilie Lakhlifi
    Department of Vascular Surgery, Bordeaux University Hospital, Bordeaux, France.
  • Céline Brunet
    Department of Vascular Surgery, Bordeaux University Hospital, Bordeaux, France.
  • Xavier Bérard
    Vascular Surgery Department, Bordeaux University Hospital, Bordeaux, France.
  • Eric Ducasse
    Vascular Surgery Department, Bordeaux University Hospital, Bordeaux, France. Electronic address: eric.ducasse@chu-bordeaux.fr.