TY - JOUR
T1 - Voxel-based analysis
T2 - Roadmap for clinical translation
AU - McWilliam, Alan
AU - Palma, Giuseppe
AU - Abravan, Azadeh
AU - Acosta, Oscar
AU - Appelt, Ane
AU - Aznar, Marianne
AU - Monti, Serena
AU - Onjukka, Eva
AU - Panettieri, Vanessa
AU - Placidi, Lorenzo
AU - Rancati, Tiziana
AU - Vasquez Osorio, Eliana
AU - Witte, Marnix
AU - Cella, Laura
N1 - Funding Information:
Dr Alan McWilliam and Dr Marianne Aznar are supported by NIHR Manchester Biomedical Research Centre and by Cancer Research UK via funding to the Cancer Research Manchester Centre [ C147/A25254 ]. Dr Alan McWilliam, Dr Marianne Aznar, Dr Eliana Vasquez Osorio and Dr Azadeh Abravan are also supported by the Cancer Research UK RadNet Manchester [ C1994/A28701 ]. Dr Marianne Aznar also acknowledges the support of the Engineering and Physical Research Council (Grant number EP/T028017/1 ). Dr Ane Appelt is supported by Cancer Research UK RadNet [ C19942/A28832 ] and Yorkshire Cancer Research [ L389AA ]. Dr Serena Monti is supported by PROGETTO CIR01_00023 -IMPARA -IMAGING DALLE MOLECOLE ALLA PRECLINICA -RAFFORZAMENTO DEL CAPITALE UMANO. Dr Eva Onjukka is supported by a fellowship from the Swedish Cancer Society [ 22 0531 ]. Dr Oscar Acosta acknowledge fundings from the French National Research Agency (ANR) in the framework of the ‘‘Investing for the Future” program, CominLabs Excellence Laboratory ( ANR-10-LABX-07-01 ), via the European Frame ERA Permed ( PerPlanRT ERAPERMED2020-110 ) and Fondation Rennes 1 via the program Semesters for innovation. Dr Marnix Witte is supported by Research institutional grants awarded to the Netherlands Cancer Institute from the Dutch Cancer Society and of the Dutch Ministry of Health, Welfare and Sport.
Funding Information:
Dr Alan McWilliam, Dr Giuseppe Palma and Dr Laura Cella would like to thank ESTRO for the opportunity to chair the physics workshop theme “Mining the radiotherapy dose, exploring dose response patterns in radiation therapy”. This paper is a direct output from the discussions during this workshop. Dr Alan McWilliam and Dr Marianne Aznar are supported by NIHR Manchester Biomedical Research Centre and by Cancer Research UK via funding to the Cancer Research Manchester Centre [C147/A25254]. Dr Alan McWilliam, Dr Marianne Aznar, Dr Eliana Vasquez Osorio and Dr Azadeh Abravan are also supported by the Cancer Research UK RadNet Manchester [C1994/A28701]. Dr Marianne Aznar also acknowledges the support of the Engineering and Physical Research Council (Grant number EP/T028017/1). Dr Ane Appelt is supported by Cancer Research UK RadNet [C19942/A28832] and Yorkshire Cancer Research [L389AA]. Dr Serena Monti is supported by PROGETTO CIR01_00023 -IMPARA -IMAGING DALLE MOLECOLE ALLA PRECLINICA -RAFFORZAMENTO DEL CAPITALE UMANO. Dr Eva Onjukka is supported by a fellowship from the Swedish Cancer Society [22 0531]. Dr Oscar Acosta acknowledge fundings from the French National Research Agency (ANR) in the framework of the ‘‘Investing for the Future” program, CominLabs Excellence Laboratory (ANR-10-LABX-07-01), via the European Frame ERA Permed (PerPlanRT ERAPERMED2020-110) and Fondation Rennes 1 via the program Semesters for innovation. Dr Marnix Witte is supported by Research institutional grants awarded to the Netherlands Cancer Institute from the Dutch Cancer Society and of the Dutch Ministry of Health, Welfare and Sport.
Publisher Copyright:
© 2023 The Author(s)
PY - 2023/11
Y1 - 2023/11
N2 - Voxel-based analysis (VBA) allows the full, 3-dimensional, dose distribution to be considered in radiotherapy outcome analysis. This provides new insights into anatomical variability of pathophysiology and radiosensitivity by removing the need for a priori definition of organs assumed to drive the dose response associated with patient outcomes. This approach may offer powerful biological insights demonstrating the heterogeneity of the radiobiology across tissues and potential associations of the radiotherapy dose with further factors. As this methodological approach becomes established, consideration needs to be given to translating VBA results to clinical implementation for patient benefit. Here, we present a comprehensive roadmap for VBA clinical translation. Technical validation needs to demonstrate robustness to methodology, where clinical validation must show generalisability to external datasets and link to a plausible pathophysiological hypothesis. Finally, clinical utility requires demonstration of potential benefit for patients in order for successful translation to be feasible. For each step on the roadmap, key considerations are discussed and recommendations provided for best practice.
AB - Voxel-based analysis (VBA) allows the full, 3-dimensional, dose distribution to be considered in radiotherapy outcome analysis. This provides new insights into anatomical variability of pathophysiology and radiosensitivity by removing the need for a priori definition of organs assumed to drive the dose response associated with patient outcomes. This approach may offer powerful biological insights demonstrating the heterogeneity of the radiobiology across tissues and potential associations of the radiotherapy dose with further factors. As this methodological approach becomes established, consideration needs to be given to translating VBA results to clinical implementation for patient benefit. Here, we present a comprehensive roadmap for VBA clinical translation. Technical validation needs to demonstrate robustness to methodology, where clinical validation must show generalisability to external datasets and link to a plausible pathophysiological hypothesis. Finally, clinical utility requires demonstration of potential benefit for patients in order for successful translation to be feasible. For each step on the roadmap, key considerations are discussed and recommendations provided for best practice.
KW - Clinical translation
KW - Outcome modelling
KW - Radiotherapy
KW - Validation
KW - Voxel-based analysis
UR - http://www.scopus.com/inward/record.url?scp=85171776342&partnerID=8YFLogxK
U2 - 10.1016/j.radonc.2023.109868
DO - 10.1016/j.radonc.2023.109868
M3 - Review Article
C2 - 37683811
AN - SCOPUS:85171776342
SN - 0167-8140
VL - 188
JO - Radiotherapy and Oncology
JF - Radiotherapy and Oncology
M1 - 109868
ER -