Imaging analysis using Artificial Intelligence to predict outcomes after endovascular aortic aneurysm repair: protocol for a retrospective cohort study.

Journal: BMJ open
Published Date: Jul 16, 2025

Abstract

INTRODUCTION: Endovascular aortic aneurysm repair (EVAR) requires long-term surveillance to detect and treat postoperative complications. However, prediction models to optimise follow-up strategies are still lacking. The primary objective of this study is to develop predictive models of post-operative outcomes following elective EVAR using Artificial Intelligence (AI)-driven analysis. The secondary objective is to investigate morphological aortic changes following EVAR.

Authors

  • Fabien Lareyre
    Université Côte d'Azur, CHU, Inserm U1065, C3M, Nice, France; Department of Vascular Surgery, University Hospital of Nice, Nice, France.
  • Juliette Raffort
    Clinical Chemistry Laboratory, University Hospital of Nice, Nice, France; Université Côte d'Azur, CHU, Inserm U1065, C3M, Nice, France. Electronic address: juliette.raffort@hotmail.fr.
  • Stavros K Kakkos
    Department of Vascular Surgery, University Hospital of Patras, Patras, Greece.
  • Mario D'Oria
    Division of Vascular and Endovascular Surgery, Cardio-Thoracic-Vascular Department, University Hospital of Trieste, Trieste, Italy.
  • Bahaa Nasr
    LaTIM, INSERM UMR1101, Brest, France.
  • Athanasios Saratzis
    Department of Cardiovascular Sciences, National Institute for Health and Care Research Leicester Biomedical Research Center (NIHR BRC), Glenfield Hospital, University of Leicester, Leicester, UK.
  • George A Antoniou
    Liverpool Vascular and Endovascular Service, Royal Liverpool University Hospital, Liverpool, United Kingdom.
  • Robert J Hinchliffe
    North Bristol NHS Trust and University of Bristol, Bristol, UK.

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