Evaluation of a knowledge-based planning solution for head and neck cancer.

Journal: International journal of radiation oncology, biology, physics
Published Date:

Abstract

PURPOSE: Automated and knowledge-based planning techniques aim to reduce variations in plan quality. RapidPlan uses a library consisting of different patient plans to make a model that can predict achievable dose-volume histograms (DVHs) for new patients and uses those models for setting optimization objectives. We benchmarked RapidPlan versus clinical plans for 2 patient groups, using 3 different libraries.

Authors

  • Jim P Tol
    Department of Radiotherapy, VU University Medical Center, Amsterdam, The Netherlands. Electronic address: j.tol@vumc.nl.
  • Alexander R Delaney
    Department of Radiotherapy, VU University Medical Center, Amsterdam, The Netherlands.
  • Max Dahele
    Department of Radiotherapy, VU University Medical Center, Amsterdam, The Netherlands.
  • Ben J Slotman
    Department of Radiotherapy, VU University Medical Center, Amsterdam, The Netherlands.
  • Wilko F A R Verbakel
    Department of Radiotherapy, VU University Medical Center, Amsterdam, The Netherlands.