ArticleClinical and translational radiation oncology2021
Analysis of data to Advance Personalised Therapy with MR-Linac (ADAPT-MRL).
Article in Clinical and translational radiation oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 8 citations in OpenAlex.
- Post-prostatectomy magnetic resonance-guided adaptive salvage radiotherapy: early toxicity and biochemical outcomes from a prospective single center cohort.Clinical and translational radiation oncology · 2026Article
- Clinical outcomes and quality of life in glioblastoma patients treated with MR-guided adaptive radiotherapy using a 1.5 T MR-Linac in an Australian setting.Clinical and translational radiation oncology · 2026Article
- Case Report: MR-guided adaptive stereotactic body radiotherapy for splenic metastases: a case series of technical feasibility and early clinical outcomes.Frontiers in oncology · 2026Article
- Adapting to the Future: Introducing the Radiation Oncology Alliance Adaptive Radiotherapy Working Group.Journal of medical imaging and radiation oncology · 2025Article
- Does a peer review group consensus process for MR-Linac patients affect clinical care? Evaluation of impact and feasibility.Clinical and translational radiation oncology · 2024Article
- Super-resolution neural networks improve the spatiotemporal resolution of adaptive MRI-guided radiation therapy.Communications medicine · 2024Article
- Magnetic resonance guided adaptive post prostatectomy radiotherapy: Accumulated dose comparison of different workflows.Journal of applied clinical medical physics · 2024Article
- Optimising the MR-Linac as a standard treatment modality.Journal of medical radiation sciences · 2023Article
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Corrections and comments
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Authors and funding
18 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAnalysis of Data to Advance Personalised Therapy with MR-Linac (ADAPT-MRL) is a multi-site, multinational, observational cohort registry designed to collect data on the use of the magnetic resonance linear accelerator (MR-Linac) for radiation therapy and patient outcomes. The registry will provide a linked repository of technical and clinical data that will form a platform for prospective studies and technology assessment.
methodsDesign: This registry aims to include an estimated 10,000 eligible participants across Australia and other countries over a 7- to 10-year period. Participants will undergo treatment and assessments in accordance with standard practice. Toxicity and survival outcomes will be assessed at baseline, during treatment, and with 3 monthly follow-up until 24 months, patient reported outcome measures will also be collected. Participants with a variety of cancers will be included. DISCUSSION: Data obtained from the ADAPT-MRL registry is expected to provide evidence on the safety and efficacy of the MR-Linac, a new technical innovation in radiation oncology. We expect this registry will generate data that will be used to optimise treatment techniques, MR-Linac software algorithms, evaluate participants' outcomes and toxicities and to create a repository of adapted plans, anatomical and functional MR sequences linked to participants' outcomes.
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Registered trials
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.