Applying Artificial Intelligence to Quantify Body Composition on Abdominal CTs and Better Predict Kidney Transplantation Wait-List Mortality.

Journal: Journal of the American College of Radiology : JACR
PMID: 40044312

Abstract

BACKGROUND: Prekidney transplant evaluation routinely includes abdominal CT for presurgical vascular assessment. A wealth of body composition data are available from these CT examinations, but they remain an underused source of data, often missing from prognostication models, as these measurements require organ segmentation not routinely performed clinically by radiologists. We hypothesize that artificial intelligence facilitates accurate extraction of abdominal CT body composition data, allowing better prediction of outcomes.

Authors

  • Karim Yatim
    Department of Medicine, Division of Nephrology, Massachusetts General Hospital, Boston, Massachusetts.
  • Guilherme T Ribas
    Department of Surgery, Center for Transplantation Sciences, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.
  • Daniel C Elton
    Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bldg. 10 Room 1C224D MSC 1182, Bethesda, MD 20892-1182.
  • Marcio A B C Rockenbach
    MGH & BWH Center for Clinical Data Science, Boston, MA, USA.
  • Ayman Al Jurdi
    Department of Medicine, Division of Nephrology, Massachusetts General Hospital, Boston, Massachusetts; Department of Surgery, Center for Transplantation Sciences, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.
  • Perry J Pickhardt
    University of Wisconsin Medical School, Department of Radiology, Madison, Wisconsin, United States.
  • John W Garrett
    From the Departments of Medical Physics (R.Z., X.T., C.Z., D.G., J.W.G., K.L., S.B.R., G.H.C.) and Radiology (M.L.S., J.W.G., K.L., S.B.R., G.H.C.), University of Wisconsin-Madison School of Medicine and Public Health, 1111 Highland Ave, Madison, WI 53705; and Department of Radiology, Henry Ford Health System, Detroit, Mich (Z.Q., N.B.B., T.K.S., J.D.N,).
  • Keith J Dreyer
    Department of Radiology, Massachusetts General Hospital, Boston, MA, United States; Harvard Medical School, Boston, MA, United States; Mass General Brigham Data Science Office (DSO), Boston, MA, United States.
  • Bernardo C Bizzo
    Department of Radiology, Massachusetts General Hospital, Boston, MA, United States; Harvard Medical School, Boston, MA, United States; Mass General Brigham Data Science Office (DSO), Boston, MA, United States.
  • Leonardo V Riella
    Renal Division, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA.

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