Novel dosimetric validation of a commercial CT scanner based deep learning automated contour solution for prostate radiotherapy.

Journal: Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PMID: 38718703

Abstract

PURPOSE: OAR delineation accuracy influences: (i) a patient's optimised dose distribution (PD), (ii) the reported doses (RD) presented at approval, which represent plan quality. This study utilised a novel dosimetric validation methodology, comprehensively evaluating a new CT-scanner-based AI contouring solution in terms of PD and RD within an automated planning workflow.

Authors

  • Salvatore Berenato
    Velindre Cancer Centre, Radiotherapy Physics Department, Cardiff, Wales, United Kingdom.
  • Matthew Williams
    Velindre Cancer Centre, Radiotherapy Physics Department, Cardiff, Wales, United Kingdom.
  • Owain Woodley
    Velindre Cancer Centre, Radiotherapy Physics Department, Cardiff, Wales, United Kingdom.
  • Christian Möhler
    Cancer Therapy, Siemens Healthineers, Forchheim, Germany.
  • Elin Evans
    Velindre Cancer Centre, Medical Directorate, Cardiff, Wales, United Kingdom.
  • Anthony E Millin
    Velindre Cancer Centre, Radiotherapy Physics Department, Cardiff, Wales, United Kingdom.
  • Philip A Wheeler
    Velindre Cancer Centre, Radiotherapy Physics Department, Cardiff, Wales, United Kingdom. Electronic address: philip.wheeler@wales.nhs.uk.

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