ReviewFrontiers in oncology2025
Recent technical advancements and clinical applications of MR-guided radiotherapy in lung cancer treatment.
Review in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
6 citing papers in PubMed.
- MR-Guided Adaptive Radiotherapy in Lung Cancer: Current Landscape and Future Directions.Cancers · 2026Review
- Artificial Intelligence for Prognostic Modelling and Adaptive Treatment Monitoring in Radiation Oncology.Cureus · 2026Review
- The role of the gut microbiota in radiation enteritis: from mechanistic insights to therapeutic applications.Communications biology · 2026Review
- Artificial Intelligence in Lung Cancer: A Narrative Review of Recent Advances in Diagnosis, Biomarker Discovery, and Drug Development.Pharmaceutics · 2026Review
- Multitask learning for early treatment response and survival prediction in lung cancer radiotherapy using sequential CBCT imaging.Frontiers in oncology · 2026Article
- A bias field correction workflow based on generative adversarial network for abdominal cancers treated with 0.35T MR-LINAC.Journal of applied clinical medical physics · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Magnetic resonance-guided radiotherapy (MRgRT) represents a significant advancement in lung cancer treatment, integrating non-ionizing high-resolution magnetic resonance imaging (MRI) with linear accelerators to enable real-time tumor visualization and adaptive treatment planning. This review highlights recent advancements in MRgRT technology and explores its clinical applications, particularly in managing lung cancer patients. MRgRT has proven particularly advantageous in stereotactic body radiotherapy (SBRT) treatment for lung cancer, where motion management is critical due to respiratory-induced tumor motion. Real-time tumor monitoring and online adaptive plan modifications ensure target accuracy, reduce margins, and mitigate radiation-induced toxicity. Additionally, MRgRT could potentially allow multileaf collimator (MLC) tracking to further improve the treatment efficiency. Recent technological innovations, including AI-powered auto-contouring algorithms, deep-learning (DL) based prediction models, and adaptive treatment strategies, further optimize MRgRT by improving workflow efficiency and reducing treatment time. Despite these benefits, the widespread adoption of MRgRT is challenged by high infrastructure costs, prolonged treatment time, and the need for specialized expertise. Ongoing research is addressing these challenges through workflow optimization, remote treatment models, and AI-driven decision support systems. As MRgRT technology continues to evolve, its integration with functional imaging, radiomics, and adaptive protocols is expected to expand its applications beyond lung cancer treatment. MRgRT represents a paradigm shift in precision oncology, delivering personalized care. Future research and prospective clinical trials should be warranted to generate high-quality clinical evidence supporting MRgRT's clinical adoption for lung cancer patient management. As these advancements progress, MRgRT is poised to transform the future of lung cancer treatment.
Indexed as
Identifiers
What OpenQuestion holds
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.