Clinical evaluation of two AI models for automated breast cancer plan generation.

Journal: Radiation oncology (London, England)
PMID: 35123517

Abstract

BACKGROUND: Artificial intelligence (AI) shows great potential to streamline the treatment planning process. However, its clinical adoption is slow due to the limited number of clinical evaluation studies and because often, the translation of the predicted dose distribution to a deliverable plan is lacking. This study evaluates two different, deliverable AI plans in terms of their clinical acceptability based on quantitative parameters and qualitative evaluation by four radiation oncologists.

Authors

  • Esther Kneepkens
    Department of Radiation Oncology, Catharina Hospital, Eindhoven, The Netherlands.
  • Nienke Bakx
    Department of Radiation Oncology, Catharina Hospital, Eindhoven, The Netherlands.
  • Maurice van der Sangen
    Department of Radiation Oncology, Catharina Hospital, Eindhoven, The Netherlands.
  • Jacqueline Theuws
    Department of Radiation Oncology, Catharina Hospital, Eindhoven, The Netherlands.
  • Peter-Paul van der Toorn
    Department of Radiation Oncology, Catharina Hospital, Eindhoven, The Netherlands.
  • Dorien Rijkaart
    Department of Radiation Oncology, Catharina Hospital, Eindhoven, The Netherlands.
  • Jorien van der Leer
    Department of Radiation Oncology, Catharina Hospital, Eindhoven, The Netherlands.
  • Thérèse van Nunen
    Department of Radiation Oncology, Catharina Hospital, Eindhoven, The Netherlands.
  • Els Hagelaar
    Department of Radiation Oncology, Catharina Hospital, Eindhoven, The Netherlands.
  • Hanneke Bluemink
    Department of Radiation Oncology, Catharina Hospital, Eindhoven, The Netherlands.
  • Coen Hurkmans
    Department of Radiation Oncology, Catharina Hospital, Eindhoven, The Netherlands. coen.hurkmans@catharinaziekenhuis.nl.

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