Towards a Clinical Decision Support System for External Beam Radiation Oncology Prostate Cancer Patients: Proton vs. Photon Radiotherapy? A Radiobiological Study of Robustness and Stability

Sean Walsh, Erik Roelofs, Peter Kuess, Yvonka van Wijk, Ben Vanneste, Andre Dekker, Philippe Lambin, Bleddyn Jones, Dietmar Georg, Frank Verhaegen*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Web of Science)

Abstract

We present a methodology which can be utilized to select proton or photon radiotherapy in prostate cancer patients. Four state-of-the-art competing treatment modalities were compared (by way of an in silico trial) for a cohort of 25 prostate cancer patients, with and without correction strategies for prostate displacements. Metrics measured from clinical image guidance systems were used. Three correction strategies were investigated; no-correction, extended-no-action-limit, and online-correction. Clinical efficacy was estimated via radiobiological models incorporating robustness (how probable a given treatment plan was delivered) and stability (the consistency between the probable best and worst delivered treatments at the 95% confidence limit). The results obtained at the cohort level enabled the determination of a threshold for likely clinical benefit at the individual level. Depending on the imaging system and correction strategy; 24%, 32% and 44% of patients were identified as suitable candidates for proton therapy. For the constraints of this study: Intensity-modulated proton therapy with online-correction was on average the most effective modality. Irrespective of the imaging system, each treatment modality is similar in terms of robustness, with and without the correction strategies. Conversely, there is substantial variation in stability between the treatment modalities, which is greatly reduced by correction strategies. This study provides a 'proof-of-concept' methodology to enable the prospective identification of individual patients that will most likely (above a certain threshold) benefit from proton therapy.
Original languageEnglish
Article number55
Number of pages16
JournalCancers
Volume10
Issue number2
DOIs
Publication statusPublished - 1 Feb 2018

Keywords

  • prostate cancer
  • radiotherapy
  • proton therapy
  • clinical decision support systems
  • in silico trial
  • radiobiological modelling
  • CELL-LUNG-CANCER
  • ULTRASOUND IMAGE GUIDANCE
  • RANGE UNCERTAINTIES
  • COMPUTED-TOMOGRAPHY
  • PRECISION MEDICINE
  • COST-EFFECTIVENESS
  • THERAPY
  • TRIAL
  • MOTION
  • LOCALIZATION

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