Deep learning-based classification of kidney transplant pathology: a retrospective, multicentre, proof-of-concept study.

Journal: The Lancet. Digital health
PMID:

Abstract

BACKGROUND: Histopathological assessment of transplant biopsies is currently the standard method to diagnose allograft rejection and can help guide patient management, but it is one of the most challenging areas of pathology, requiring considerable expertise, time, and effort. We aimed to analyse the utility of deep learning to preclassify histology of kidney allograft biopsies into three main broad categories (ie, normal, rejection, and other diseases) as a potential biopsy triage system focusing on transplant rejection.

Authors

  • Jesper Kers
    Department of Pathology, Amsterdam Infection & Immunity, Amsterdam Cardiovascular Sciences, Amsterdam UMC, and.
  • Roman D Bülow
    Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany.
  • Barbara M Klinkhammer
  • Gerben E Breimer
    Department of Pathology, University Medical Center Utrecht, Utrecht, Netherlands.
  • Francesco Fontana
    Division of Nephrology, Dialysis and Renal Transplantation, Azienda Ospedaliera Universitaria Policlinico di Modena, Modena, Italy.
  • Adeyemi Adefidipe Abiola
    Department of Pathology, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands; Department of Morbid Anatomy and Forensic Medicine, Obafemi Awolowo University Teaching Hospitals Complex, Ile-Ife, Nigeria.
  • Rianne Hofstraat
    Department of Pathology, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands; Van 't Hoff Institute for Molecular Sciences, University of Amsterdam, Amsterdam, Netherlands.
  • Garry L Corthals
    Department of Pathology, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands; Van 't Hoff Institute for Molecular Sciences, University of Amsterdam, Amsterdam, Netherlands.
  • Hessel Peters-Sengers
    Center for Experimental and Molecular Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.
  • Sonja Djudjaj
    Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany.
  • Saskia von Stillfried
    Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany.
  • David L Hölscher
    Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany.
  • Tobias T Pieters
    Department of Nephrology and Hypertension, University Medical Center Utrecht, Utrecht, Netherlands.
  • Arjan D van Zuilen
    Department of Nephrology and Hypertension, University Medical Center Utrecht, Utrecht, Netherlands.
  • Frederike J Bemelman
    Renal Transplant Unit, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.
  • Azam S Nurmohamed
    Renal Transplant Unit, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.
  • Maarten Naesens
    Department of Microbiology, Immunology and Transplantation, KU Leuven, Leuven, Belgium.
  • Joris J T H Roelofs
    Department of Pathology, Amsterdam Infection & Immunity, Amsterdam Cardiovascular Sciences, Amsterdam UMC, and.
  • Sandrine Florquin
    Department of Pathology, Amsterdam Infection & Immunity, Amsterdam Cardiovascular Sciences, Amsterdam UMC, and.
  • Jürgen Floege
    Department of Nephrology and Immunology, RWTH Aachen University Hospital, Aachen, Germany.
  • Tri Q Nguyen
    Pathology, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Jakob N Kather
    Department of Gastroenterology, University Hospital RWTH Aachen, Aachen, Germany. jakob.kather@gmail.com.
  • Peter Boor
    Institute of Pathology, University Hospital Aachen, RWTH Aachen University, Aachen, Germany.