ReviewPhysics and imaging in radiation oncology2024
A review of the clinical introduction of 4D particle therapy research concepts.
Review in Physics and imaging in radiation oncology, 2024. 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.
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Who cites it
9 citing papers in PubMed.
- Interplay effect evaluation on lung and esophageal cancer patients treated with compact proton system in free breathing.Physics and imaging in radiation oncology · 2026Article
- Upright and supine particle therapy of lung cancer: A 4D dosimetric comparison.Medical physics · 2026Article
- Towards ultra-fast treatments: large energy acceptance beam delivery systems and opportunities for proton beam therapy.Frontiers in oncology · 2026Review
- Effects of breath-hold reproducibility on proton and photon lung cancer stereotactic body radiotherapy.Physics and imaging in radiation oncology · 2026Article
- Dose comparison of proton beam therapy with and without a multileaf collimator in the treatment of multiple hepatocellular carcinoma.Physics and imaging in radiation oncology · 2026Article
- Interplay-robust optimization for treating irregularly breathing lung patients with pencil beam scanning.Medical physics · 2025Article
- New guidelines and recommendations to advance treatment planning in proton therapy.Physics and imaging in radiation oncology · 2025Article
- Comparison of deep inspiration breath hold and free breathing intensity modulated proton therapy of locally advanced lung cancer.Physics and imaging in radiation oncology · 2024Article
- The role of 4D particle therapy in daily patient care and research.Physics and imaging in radiation oncology · 2024Article
Corrections and comments
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Authors and funding
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and purpose: Many 4D particle therapy research concepts have been recently translated into clinics, however, remaining substantial differences depend on the indication and institute-related aspects. This work aims to summarise current state-of-the-art 4D particle therapy technology and outline a roadmap for future research and developments. Material and methods: This review focused on the clinical implementation of 4D approaches for imaging, treatment planning, delivery and evaluation based on the 2021 and 2022 Results: Available technological capabilities for motion surveillance and compensation determined the course of each 4D particle treatment. 4D motion management, delivery techniques and strategies including imaging were diverse and depended on many factors. These included aspects of motion amplitude, tumour location, as well as accelerator technology driving the necessity of centre-specific dosimetric validation. Novel methodologies for X-ray based image processing and MRI for real-time tumour tracking and motion management were shown to have a large potential for online and offline adaptation schemes compensating for potential anatomical changes over the treatment course. The latest research developments were dominated by particle imaging, artificial intelligence methods and FLASH adding another level of complexity but also opportunities in the context of 4D treatments. Conclusion: This review showed that the rapid technological advances in radiation oncology together with the available intrafractional motion management and adaptive strategies paved the way towards clinical implementation.
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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.