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Cancers (Basel). 2018 Feb 18;10(2). pii: E55. doi: 10.3390/cancers10020055.

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.

Author information

1
Department of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre, Doctor Tanslaan 12, Maastricht 6229 ET, The Netherlands. walshsharp@gmail.com.
2
The D-Lab: Decision Support for Precision Medicine, GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre, Universiteitssingel 40, Maastricht 6229 ER, The Netherlands. walshsharp@gmail.com.
3
Gray Laboratory, CRUK/MRC Oxford Oncology Institute, University of Oxford, ORCRB-Roosevelt Drive, Oxford OX3 7DQ, UK. walshsharp@gmail.com.
4
Department of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre, Doctor Tanslaan 12, Maastricht 6229 ET, The Netherlands. erik.roelofs@maastrichtuniversity.nl.
5
Department of Radiation Oncology and Christian Doppler Laboratory for Medical Radiation Research for Radiation Oncology, Medical University of Vienna, 1090 Vienna, Austria. peter.kuess@meduniwien.ac.at.
6
The D-Lab: Decision Support for Precision Medicine, GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre, Universiteitssingel 40, Maastricht 6229 ER, The Netherlands. y.vanwijk@maastrichtuniversity.nl.
7
Department of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre, Doctor Tanslaan 12, Maastricht 6229 ET, The Netherlands. ben.vanneste@maastro.nl.
8
Department of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre, Doctor Tanslaan 12, Maastricht 6229 ET, The Netherlands. andre.dekker@maastro.nl.
9
The D-Lab: Decision Support for Precision Medicine, GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre, Universiteitssingel 40, Maastricht 6229 ER, The Netherlands. philippe.lambin@maastrichtuniversity.nl.
10
Gray Laboratory, CRUK/MRC Oxford Oncology Institute, The University of Oxford, ORCRB-Roosevelt Drive, Oxford OX3 7DQ, UK. bleddyn.jones@oncology.ox.ac.uk.
11
Department of Radiation Oncology and Christian Doppler Laboratory for Medical Radiation Research for Radiation Oncology, Medical University of Vienna, 1090 Vienna, Austria. dietmar.georg@akhwien.at.
12
Department of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre, Doctor Tanslaan 12, Maastricht 6229 ET, The Netherlands. frank.verhaegen@maastro.nl.

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.

KEYWORDS:

clinical decision support systems; in silico trial; prostate cancer; proton therapy; radiobiological modelling; radiotherapy

Conflict of interest statement

The funding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results. Andre Dekker, leader of the Knowledge Engineering division at MAASTRO Clinic, and Seán Walsh declare that in a separate research project they received financial support from Varian Medical Systems, a company developing a rapid learning health-care system. Erik Roelofs and Yvonka van Wijk consult for ptTheragnostic B.V., a company developing biomarkers and software to individualize radiotherapy treatment. Philippe Lambin is co‑inventor of several radiomics patents.

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