ArticleClinical and translational radiation oncology2025
Treatment time and learning curve analysis of 1.5 T MR-Linac workflows led by radiation oncologists or therapists.
Article in Clinical and translational radiation oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04075305 (The Multiple Outcome Evaluation of Radiation Therapy Using the MR-Linac Study), which is not on this map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
The Multiple Outcome Evaluation of Radiation Therapy Using the MR-Linac Study
Who cites it
7 citing papers in PubMed.
- MR-guided ultra-hypofractionated radiotherapy for early-stage glottic cancer: A phase I feasibility study.Clinical and translational radiation oncology · 2027Article
- Automated planning architectures for online adaptive radiotherapy: A narrative review of the ethos and unity/Monaco platforms.Journal of applied clinical medical physics · 2026Review
- Automated workflow for target volume propagation in online adaptive magnetic resonance guided radiotherapy for lung lesions using foundation models.Physics and imaging in radiation oncology · 2026Article
- Development of an artificial intelligence driven dose prediction pipeline for online adaptive magnetic resonance-guided radiotherapy.Physics and imaging in radiation oncology · 2026Article
- Practice development perspective of RTT contouring in online adaptive radiotherapy for prostate cancer: A single-centre cost-consequence analysis.Technical innovations & patient support in radiation oncology · 2026Article
- Recent advancements in radiotherapy for hepatocellular carcinoma.ESMO gastrointestinal oncology · 2026Review
- Automated target misalignment correction for cone beam computed tomography-based online adaptive radiotherapy of locally advanced lung cancer patients.Physics and imaging in radiation oncology · 2025Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and purpose: This study assessed the treatment time of online adaptive (i.e. Adapt-to-Shape, ATS) and virtual couch shift (i.e. Adapt-to-Position, ATP) magnetic resonance guided radiotherapy (MRgRT) on a 1.5 Tesla MR-Linac. Additionally, the transition from a radiation oncologists (RO)-led to a radiation therapist (RTT)-led workflow, and the presence of a learning curve were assessed. Materials and methods: This study was conducted utilizing the prospective Multi-OutcoMe EvaluatioN of radiation Therapy Using the MR-Linac study (MOMENTUM, NCT04075305). Mean (±standard deviation) online adaptation time and total treatment time were collected from MR-Linac log files. Learning and proficiency phases were defined using a cumulative sum (CUSUM) analysis. Independent T-tests were performed. A p-value < 0.01 was considered statistically significant. Results: In total, 4942 fractions of 645 patients were included. Mean total treatment time was 39 (±7), 15 (±2), 34 (±8), 41 (±11), and 40 (±7) minutes for ATS-treated prostate cancer, ATP-treated prostate cancer, ATS-treated pelvic lymph node metstasis (LNM), ATS-treated abdominal LNM and ATS-treated rectal cancer, respectively. Mean online adaptation time of RO-led and RTT-led treatment was 28 (±6) and 25 (±6) minutes (p < 0.001) for ATS-treated prostate cancer. No significant differences in the remaining subgroups were found. In subgroups with a learning curve, mean online adaptation time of learning and proficiency phase were 30 (±6) and 26 (±5) minutes (p < 0.001) for ATS-treated prostate cancer, 27 (±8) and 19 (±7) minutes for pelvic LNM (p < 0.001), and 29 (±7) and 25 (±7) minutes (p < 0.001) for rectal cancer, respectively. Conclusion: The transition from RO-led to RTT-led workflows did not significantly increase total treatment time. The online adaptation time reduced after a learning curve for ATS-treated prostate cancer, pelvic LNM and rectal cancer.
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Registered trials
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