Towards rapid and efficient simulation-free radiotherapy: MR guided adaptive prostate radiotherapy on the MR-Linac using diagnostic MRI reference planning
- PMID: 40692080
- DOI: 10.1016/j.radonc.2025.111053
Towards rapid and efficient simulation-free radiotherapy: MR guided adaptive prostate radiotherapy on the MR-Linac using diagnostic MRI reference planning
Abstract
Background and purpose: Simulation-free radiotherapy offers improved efficiency for adaptive treatments. This planning study presents a simulation-free pre-treatment workflow for prostate cancer online adaptive radiotherapy on a MR-Linac. Previously acquired diagnostic MR images are used to create a reference treatment plan without clinician input, and adapted plans are then simulated, and compared with those from the traditional workflow.
Materials and methods: All patients treated with 36.25 Gy in 5-fractions within the HERMES trial were retrospectively assessed for eligibility of simulation-free reference planning. If eligible, reference images were created from existing diagnostic MRI (T1w and T2w) to enable MR-only reference treatment planning. Target and OAR reference structures were autosegmented without clinician input. Online plan adaptation was simulated using existing clinical treatment images and structure sets. Adapted plans were compared with existing clinical plans, and synthetic CT accuracy assessed.
Results: 87.5 % of patients had suitable diagnostic scans. Reference images and treatment plans were successfully created. Online treatment plans were simulated and were clinically acceptable for target dose and conformality, meeting all mandatory clinical goals with no detriment to OAR dose or plan deliverability. Accuracy of the synthetic CT approach was high with gamma results at 2mm/2% all above 98.9 %.
Conclusion: This study has shown that non radiotherapy-dedicated diagnostic MRI can be used for reference prostate planning on the MR-Linac, generating clinically equivalent adapted plans when compared to those originating from radiotherapy-simulation reference plans. This potentially saves multiple weeks in the pathway, improving radiotherapy efficiency and patient experience.
Copyright © 2025 The Authors. Published by Elsevier B.V. All rights reserved.
Conflict of interest statement
Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust are part of the Elekta MR-Linac Research Consortium. Sian Cooper: The Royal Marsden NHS Foundation Trust with the funding of the research fellow program receiving funds from Elekta. Sophie Alexander:Cancer Research UK Programme Grant C33589/A28284. Norina Predescu: Funded by MVision AI. Szabolcs-Botond Lőrincz-Molnár: Funded by MVision AI. Uwe Oelfke:CRUK Programme Grant, Adaptive Data-Driven Radiation Oncology, C33589/A28284. Alison Tree: Institution research funding from Elekta, Accuray & Varian. Alex Dunlop: NIHR Senior Clinical and Practitioner Research Award (SCPRA) holder. All remaining authors have declared no conflicts of interest.
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