Artificial Intelligence-Based Assessment of Preoperative Body Composition Is Associated With Early Complications After Radical Cystectomy.

Journal: The Journal of urology
PMID: 39392812

Abstract

PURPOSE: We aimed to use a validated artificial intelligence (AI) algorithm to extract muscle and adipose areas from CT images before radical cystectomy (RCx) and then correlate these measures with 90-day post-RCx complications.

Authors

  • Vidit Sharma
    Mayo Clinic, Rochester, MN 55905, USA.
  • Anthony Fadel
    Department of Urology, Mayo Clinic, Rochester, Minnesota.
  • Matthew K Tollefson
    Department of Surgery, Mayo Clinic, Rochester, MN, USA.
  • Sarah P Psutka
    Department of Urology, University of Washington, Seattle, WA, USA. Electronic address: spsutka@uw.edu.
  • Daniel J Blezek
    Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
  • Igor Frank
    Department of Urology, Mayo Clinic, Rochester, Minnesota.
  • Prabin Thapa
    Department of Health Services Research, Mayo Clinic, Rochester, Minnesota.
  • Robert Tarrell
    Department of Health Services Research, Mayo Clinic, Rochester, Minnesota.
  • Lyndsay D Viers
    Department of Radiology, Mayo Clinic, Rochester, Minnesota.
  • Aaron M Potretzke
    Washington University School of Medicine, Division of Urology, St. Louis, MO, USA.
  • Robert P Hartman
    Department of Radiology, Mayo Clinic, Rochester, Minnesota.
  • Stephen A Boorjian
    Department of Urology, Mayo Clinic, Rochester, Minnesota, MN, USA.
  • Boyd R Viers
    Department of Urology, Mayo Clinic, Rochester, MN. Electronic address: viers.boyd@mayo.edu.

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