ArticleTechnical innovations & patient support in radiation oncology2022
Online adaptive MR-guided radiotherapy: Conformity of contour adaptation for prostate cancer, rectal cancer and lymph node oligometastases among radiation therapists and radiation oncologists.
Article in Technical innovations & patient support in radiation oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed, 24 citations in OpenAlex.
- Online adaptive radiotherapy: International strategies for AI-enabled workflow efficiency and radiation therapist-led delivery for sustainable practice.Technical innovations & patient support in radiation oncology · 2026Article
- Transition from Oncologist- to Therapist-Led MRI-Guided Ultra-Hypofractionated Adaptive Prostate Radiation Therapy: Evaluation of Early Clinical Outcomes.Current oncology (Toronto, Ont.) · 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
- Feasibility of reusing online-generated treatment plans for adaptive radiotherapy in prostate cancer.Physics and imaging in radiation oncology · 2026Article
- Feasibility of Therapist-Driven MR-Guided Adaptive Radiotherapy for Oligometastatic Disease: Geometric Accuracy and Dosimetric Impact.Journal of medical imaging and radiation oncology · 2025Article
- Towards clinical implementation of T2-weighted cine imaging for intrafraction drift correction workflows on the 1.5 Tesla magnetic resonance-linear accelerator.Physics and imaging in radiation oncology · 2025Article
- Training for tomorrow: Establishing a worldwide curriculum in online adaptive radiation therapy.Technical innovations & patient support in radiation oncology · 2025Article
- Treatment time and learning curve analysis of 1.5 T MR-Linac workflows led by radiation oncologists or therapists.Clinical and translational radiation oncology · 2025Article
- Geometric and dosimetric evaluation of CTV contour adaptations by radiation therapists for adaptive prostate radiotherapy on a 0.35 T MR-Linac.Technical innovations & patient support in radiation oncology · 2025Article
- Pan-Canadian assessment of image guided adaptive radiation therapy and the role of the radiation therapist.Technical innovations & patient support in radiation oncology · 2025Article
- Evaluating CBCT-Guided Adaptive Radiotherapy for Pancreatic Cancer Using Synthetic CBCT Data.Current oncology (Toronto, Ont.) · 2025Article
- Clinical implementation of RTT-only CBCT-guided online adaptive focal radiotherapy for bladder cancer.Clinical and translational radiation oncology · 2025Article
- Article
- The impact of an Advanced Practice Radiation Therapist contouring for a CBCT-based adaptive radiotherapy program.Technical innovations & patient support in radiation oncology · 2024Article
- The Radiation Therapist profession through the lens of new technology: A practice development paper based on the ESTRO Radiation Therapist Workshops.Technical innovations & patient support in radiation oncology · 2024Article
- Evaluation of clinical parallel workflow in online adaptive MR-guided Radiotherapy: A detailed assessment of treatment session times.Technical innovations & patient support in radiation oncology · 2024Article
- Beginning of clinical treatment using the 1.5 Tesla MR-Linac system in Japan: a narrative review.Translational cancer research · 2024Review
- Practice-based training strategy for therapist-driven prostate MR-Linac adaptive radiotherapy.Technical innovations & patient support in radiation oncology · 2023Article
- Large scale crowdsourced radiotherapy segmentations across a variety of cancer anatomic sites.Scientific data · 2023Article
- Optimal planning target margin for prostate radiotherapy based on interfractional and intrafractional variability assessment during 1.5T MRI-guided radiotherapy.Frontiers in oncology · 2023Article
Corrections and comments
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Authors and funding
17 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and purpose: Online adaptive MR-guided treatment planning workflows facilitate daily contour adaptation to the actual anatomy. Allocating contour adaptation to radiation therapists (RTTs) instead of radiation oncologists (ROs) might allow for increasing workflow efficiency. This study investigates conformity of adapted target contours provided by dedicated RTTs and ROs. Materials and methods: In a simulated online procedure, 6 RTTs and 6 ROs recontoured targets and organs at risk (OAR) in prostate cancer (n = 2), rectal cancer (n = 2) and lymph node-oligometastases (n = 2) cases. RTTs gained contouring competence beforehand by following a specific in-house training program. For all target contours and the reference delineations volumetric differences were determined and Dice similarity coefficient (DSC), conformity index (CI) and generalized CI were calculated. Delineation time and -confidence were registered for targets and OAR. Impact of contour adaptation on treatment plan quality was investigated. Results: Delineation conformity was generally high with DSC, CI and generalized CI values in the range of 0.81-0.94, 0.87-0.95 and 0.63-0.85 for prostate cancer, rectal cancer and LN-oligometastasis, respectively. Target volumes were comparable for both, RTTs and ROs. Time needed and confidence in contour adaptation was comparable as well. Treatment plans derived with adapted contours did not violate dose volume constrains as used in clinical routine. Conclusion: After tumor site specific training, daily contour adaptations as needed in adaptive online radiotherapy workflows can be accurately performed by RTTs. Conformity of the derived contours is high and comparable to contours as provided by ROs.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.