Comparison of Sarcopenia Assessment in Liver Transplant Recipients by Computed Tomography Freehand Region-of-Interest versus an Automated Deep Learning System.

Journal: Clinical transplantation
Published Date: Jun 1, 2025

Abstract

INTRODUCTION: Sarcopenia, or the loss of muscle quality and quantity, has been associated with poor clinical outcomes in liver transplantation such as infection, increased length of stay, and increased patient mortality. Abdominal computed tomography (CT) scans are utilized to measure patient core musculature as a measurement of sarcopenia. Methods to extract information on core body musculature can be through either freehand region-of-interest (ROI) or machine learning algorithms to quantitate total body muscle within a given area. This study directly compares these two collection methods leveraging length of stay (LOS) outcomes previously found to be associated with freehand ROI measurements.

Authors

  • William Miller
    Division of Solid Organ Transplantation, Department of Surgery, University of Minnesota, Minneapolis, Minnesota, USA.
  • Kassandra Fate
    Division of Solid Organ Transplantation, Department of Surgery, University of Minnesota, Minneapolis, Minnesota, USA.
  • Jessica Fisher
    Division of Solid Organ Transplantation, Department of Surgery, University of Minnesota, Minneapolis, Minnesota, USA.
  • Jessica Thul
    University of Minnesota Medical Center, MHealth Fairview, Minneapolis, Minnesota, USA.
  • Yousun Ko
    Biomedical Research Center, Asan Institute for Life Sciences, Asan Medical Center, Seoul, Republic of Korea.
  • Kyung Won Kim
    Department of Pediatrics, Severance Children's Hospital, Institute of Allergy, Institute for Immunology and Immunological Diseases, Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea. kwkim@yuhs.ac.
  • Timothy Pruett
    Department of Surgery, University of Minnesota, Minneapolis, Minnesota, US.
  • Levi Teigen
    Department of Food Science and Nutrition, University of Minnesota, St Paul, Minnesota, USA.

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