Deep learning dose prediction to approach Erasmus-iCycle dosimetric plan quality within seconds for instantaneous treatment planning.

Journal: Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Published Date: Dec 6, 2024

Abstract

BACKGROUND AND PURPOSE: Fast, high-quality deep learning (DL) prediction of patient-specific 3D dose distributions can enable instantaneous treatment planning (IP), in which the treating physician can evaluate the dose and approve the plan immediately after contouring, rather than days later. This would greatly benefit clinical workload, patient waiting times and treatment quality. IP requires that predicted dose distributions closely match the ground truth. This study examines how training dataset size and model size affect dose prediction accuracy for Erasmus-iCycle GT plans to enable IP.

Authors

  • Joep van Genderingen
    Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center, Rotterdam, The Netherlands.
  • Dan Nguyen
    University of Massachusetts Chan Medical School, Worcester, Massachusetts.
  • Franziska Knuth
    Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center, Rotterdam, The Netherlands.
  • Hazem A A Nomer
    Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center, Rotterdam, The Netherlands.
  • Luca Incrocci
    Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
  • Abdul Wahab M Sharfo
    Erasmus MC Cancer Institute, University Medical Center Rotterdam, Department of Radiotherapy, Rotterdam, the Netherlands.
  • András Zolnay
    Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center, Rotterdam, The Netherlands.
  • Uwe Oelfke
    The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK.
  • Steve Jiang
  • Linda Rossi
    Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center, Rotterdam, The Netherlands.
  • Ben J M Heijmen
    Department of Radiation Oncology, Erasmus MC Cancer Institute, Groene Hilledijk 301, Rotterdam, 3075 EA, The Netherlands.
  • Sebastiaan Breedveld
    Department of Radiation Oncology, Erasmus University Medical Center - Cancer Institute, Rotterdam, The Netherlands.

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