Computer-Generated R.E.N.A.L. Nephrometry Scores Yield Comparable Predictive Results to Those of Human-Expert Scores in Predicting Oncologic and Perioperative Outcomes.

Journal: The Journal of urology
Published Date: Dec 30, 2021

Abstract

PURPOSE: We sought to automate R.E.N.A.L. (for radius, exophytic/endophytic, nearness of tumor to collecting system, anterior/posterior, location relative to polar line) nephrometry scoring of preoperative computerized tomography scans and create an artificial intelligence-generated score (AI-score). Subsequently, we aimed to evaluate its ability to predict meaningful oncologic and perioperative outcomes as compared to expert human-generated nephrometry scores (H-scores).

Authors

  • N Heller
    Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota.
  • R Tejpaul
    Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota.
  • F Isensee
    German Cancer Research Center (DKFZ) Heidelberg, University of Heidelberg, Heidelberg, Germany.
  • T Benidir
    Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio.
  • M Hofmann
    Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio.
  • P Blake
    University of Minnesota School of Medicine, Minneapolis, Minnesota.
  • Z Rengal
    University of Minnesota School of Medicine, Minneapolis, Minnesota.
  • K Moore
    Carleton College, Northfield, Minnesota.
  • N Sathianathen
    Department of Urology, University of Melbourne, Melbourne, Australia.
  • A Kalapara
    Department of Urology, University of Melbourne, Melbourne, Australia.
  • J Rosenberg
    Department of Surgery, Herlev University Hospital, Copenhagen, Denmark.
  • S Peterson
    Brigham Young University, Provo, Utah.
  • E Walczak
    University of Minnesota School of Medicine, Minneapolis, Minnesota.
  • A Kutikov
    Urology, Fox Chase Cancer Center, Philadelphia, Pennsylvania.
  • R G Uzzo
    Urology, Fox Chase Cancer Center, Philadelphia, Pennsylvania.
  • D A Palacios
    Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio.
  • E M Remer
    Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio.
  • S C Campbell
    Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio.
  • N Papanikolopoulos
    Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota.
  • Christopher J Weight
    Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio.

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