Artificial intelligence measured 3D body composition to predict pathological response in rectal cancer patients.

Journal: ANZ journal of surgery
PMID: 38456517

Abstract

BACKGROUND: The treatment of locally advanced rectal cancer (LARC) is moving towards total neoadjuvant therapy and potential organ preservation. Of particular interest are predictors of pathological complete response (pCR) that can guide personalized treatment. There are currently no clinical biomarkers which can accurately predict neoadjuvant therapy (NAT) response but body composition (BC) measures present as an emerging contender. The primary aim of the study was to determine if artificial intelligence (AI) derived body composition variables can predict pCR in patients with LARC.

Authors

  • Matthew Y Wei
    Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Victoria, Australia.
  • Ke Cao
    The Third Xiangya Hospital, Central South University, Changsha, China.
  • Wei Hong
    Department of Geriatrics and Gerontology, Huadong Hospital, Affiliated with Fudan University, Shanghai, China.
  • Josephine Yeung
    Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Victoria, Australia.
  • Margaret Lee
    Department of Medical Oncology, Western Health, Melbourne, Victoria, Australia.
  • Peter Gibbs
    Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Ian G Faragher
    Department of Colorectal Surgery, Western Health, Melbourne, Victoria, Australia.
  • Paul N Baird
    Department of Surgery, Ophthalmology, University of Melbourne, Parkville, Victoria, Australia.
  • Justin M Yeung
    Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Victoria, Australia.

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