Machine Learning Based Prediction of Post-operative Infrarenal Endograft Apposition for Abdominal Aortic Aneurysms.

Journal: European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery
PMID: 38972630

Abstract

OBJECTIVE: Challenging infrarenal aortic neck characteristics have been associated with an increased risk of type Ia endoleak after endovascular aneurysm repair (EVAR). Short apposition (< 10 mm circumferential shortest apposition length [SAL]) on the first post-operative computed tomography angiography (CTA) has been associated with type Ia endoleak. Therefore, this study aimed to develop a model to predict post-operative SAL in patients with an abdominal aortic aneurysm based on the pre-operative shape.

Authors

  • Willemina A van Veldhuizen
    Department of Surgery, Division of Vascular Surgery, University Medical Centre Groningen, Groningen, The Netherlands. Electronic address: w.a.van.veldhuizen@umcg.nl.
  • Jean-Paul P M de Vries
    Department of Surgery, Division of Vascular Surgery, University Medical Centre Groningen, Groningen, The Netherlands.
  • Annemarij Tuinstra
    Department of Surgery, Division of Vascular Surgery, University Medical Centre Groningen, Groningen, The Netherlands.
  • Roy Zuidema
    Department of Surgery, Division of Vascular Surgery, University Medical Centre Groningen, Groningen, The Netherlands.
  • Frank F A Ijpma
    Department of Trauma Surgery, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
  • Jelmer M Wolterink
    Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, Netherlands.
  • Richte C L Schuurmann
    Department of Surgery, Division of Vascular Surgery, University Medical Centre Groningen, Groningen, The Netherlands; Multimodality Medical Imaging Group, Technical Medical Centre, University of Twente, Enschede, The Netherlands.

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