ArticleClinical and translational radiation oncology2022
Clinical implementation and feasibility of long-course fractionated MR-guided chemoradiotherapy for patients with esophageal cancer: An R-IDEAL stage 1b/2a evaluation of technical innovation.
Article in Clinical and translational radiation oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 10 citations in OpenAlex.
- Do AI-based contouring algorithms influence physicians in the online adaptive radiotherapy of patients with bladder cancer?Technical innovations & patient support in radiation oncology · 2026Article
- Benefits of daily online plan adaptation with reduced margins in neoadjuvant chemoradiotherapy for esophageal cancer.Physics and imaging in radiation oncology · 2026Article
- MR-Guided Radiotherapy in Oesophageal Cancer: From Principles to Practice-A Narrative Review.Current oncology (Toronto, Ont.) · 2026Review
- Online Radiotherapy: The Paradigm Shift to Real-Time Adaptive Radiotherapy.Deutsches Arzteblatt international · 2025Review
- Potential of automated online adaptive proton therapy to reduce margins for oesophageal cancer.Physics and imaging in radiation oncology · 2025Article
- A simplified online adaptive workflow for long-course magnetic resonance-guided radiotherapy in esophageal cancer.Physics and imaging in radiation oncology · 2025Article
- Autodelineation methods in a simulated fully automated proton therapy workflow for esophageal cancer.Physics and imaging in radiation oncology · 2024Article
- MR-linac based radiation therapy in gastrointestinal cancers: a narrative review.Journal of gastrointestinal oncology · 2024Review
- Intrafraction motion analysis in online adaptive radiotherapy for esophageal cancer.Physics and imaging in radiation oncology · 2023Article
- Feasibility study of adaptive radiotherapy for esophageal cancer using artificial intelligence autosegmentation based on MR-Linac.Frontiers in oncology · 2023Article
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Authors and funding
10 authors at 4 institutions in 2 countries.
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No grant is acknowledged in the PubMed record.
Abstract
Purpose: This R-Ideal stage 1b/2a study describes the workflow and feasibility of long-course fractionated online adaptive MR-guided chemoradiotherapy with reduced CTV-to-PTV margins on the 1.5T MR-Linac for patients with esophageal cancer. Methods: Patients with esophageal cancer scheduled to undergo chemoradiation were treated on a 1.5T MR-Linac. Daily MR-images were acquired for online contour adaptation and replanning. Contours were manually adapted to match the daily anatomy and an isotropic CTV-to-PTV margin of 6 mm was applied. Time was recorded for all individual steps in the workflow. Feasibility and patient tolerability were defined as on-table time of ≤60 min and completion of >95% of the fractions on the MR-Linac, respectively. Positioning verification and post-treatment MRIs were retrospectively analyzed and dosimetric parameters were compared to standard non-adaptive conventional treatment plans. Results: Nine patients with esophageal cancer were treated with chemoradiation; eight patients received 41.4 Gy in 23 fractions and one received 50.4 Gy in 28 fractions. Four patients received all planned fractions on the MR-Linac, whereas for two patients >5% of fractions were rescheduled to a conventional linac for reasons of discomfort. A total of 183 (86%) of 212 scheduled fractions were successfully delivered on the MR-Linac. Three fractions ended prematurely due to technical issues and 26 fractions were rescheduled on a conventional linac due to MR-Linac downtime (n = 10), logistical reasons (n = 3) or discomfort (n = 13).The median time per fraction was 53 min (IQR = 3 min). Daily adapted MR-Linac plans had similar target coverage, whereas dose to the organs-at-risk was significantly reduced compared to conventional treatment (26% and 12% reduction in mean lung and heart dose, respectively). Conclusion: Daily online adaptive fractionated chemoradiotherapy with reduced PTV margins is moderately feasible for esophageal cancer and results in better sparing of heart and lungs. Future studies should focus on further optimization and acceleration of the current workflow.
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