A joint ESTRO and AAPM guideline for development, clinical validation and reporting of artificial intelligence models in radiation therapy.

Journal: Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Published Date:

Abstract

BACKGROUND AND PURPOSE: Artificial Intelligence (AI) models in radiation therapy are being developed with increasing pace. Despite this, the radiation therapy community has not widely adopted these models in clinical practice. A cohesive guideline on how to develop, report and clinically validate AI algorithms might help bridge this gap.

Authors

  • Coen Hurkmans
    Department of Radiation Oncology, Catharina Hospital, Eindhoven, The Netherlands. coen.hurkmans@catharinaziekenhuis.nl.
  • Jean-Emmanuel Bibault
    Radiation Oncology Department, Georges Pompidou European Hospital, Assistance Publique - Hôpitaux de Paris, Paris Descartes University, Paris Sorbonne Cité, Paris, France; INSERM UMR 1138 Team 22: Information Sciences to support Personalized Medicine, Paris Descartes University, Sorbonne Paris Cité, Paris, France. Electronic address: jean-emmanuel.bibault@aphp.fr.
  • Kristy K Brock
    Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas; Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Wouter van Elmpt
    Department of Radiation Oncology (Maastro), GROW School for Oncology, Maastricht University Medical Centre+, The Netherlands. Electronic address: wouter.vanelmpt@maastro.nl.
  • Mary Feng
    University of California San Francisco, San Francisco, CA, USA.
  • Clifton David Fuller
    Department of Radiation Oncology, The University of Texas MD Anderson Cancer, Houston, TX.
  • Barbara A Jereczek-Fossa
    Dept. of Oncology and Hemato-oncology, University of Milan, Milan, Italy; Dept. of Radiation Oncology, IEO European Institute of Oncology IRCCS, Milan, Italy.
  • Stine Korreman
    Danish Center for Particle Therapy & Department of Oncology, Aarhus University Hospital, Denmark.
  • Guillaume Landry
    Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München (LMU Munich), Garching bei München, 85748, Germany.
  • Frederic Madesta
  • Chuck Mayo
    Institute for Healthcare Policy and Innovation, University of Michigan, USA.
  • Alan McWilliam
    Division of Cancer Sciences, University of Manchester, Manchester, UK.
  • Filipe Moura
    CrossI&D Lisbon Research Center, Portuguese Red Cross Higher Health School Lisbon, Portugal.
  • Ludvig P Muren
    Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Danish Center for Particle Therapy, Aarhus University Hospital, Aarhus, Denmark.
  • Issam El Naqa
    Department of Machine Learning, Moffitt Cancer Center, Tampa, Florida.
  • Jan Seuntjens
    Medical Physics Unit, McGill University and Cedars Cancer Center, 1001 Décarie Blvd, Montréal, QC, H4A 3J1, Canada.
  • Vincenzo Valentini
    Agostino Gemelli University Polyclinic (IRCCS), Rome, Italy.
  • Michael Velec
    Radiation Medicine Program, Princess Margaret Cancer Centre and Department of Radiation Oncology, University of Toronto, Toronto, Canada.