ReviewPhysics in medicine and biology2022
Reflections on beam configuration optimization for intensity-modulated proton therapy.
Review in Physics in medicine and biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Knowledge-based radiation therapy treatment planning decision support system for head and neck cancer utilizing multi-organ constellation matching.International journal of computer assisted radiology and surgery · 2026Article
- Validation of automated script-based proton therapy optimisation for comparative head and neck planning.Physics and imaging in radiation oncology · 2026Article
- Deep learning-based dose prediction in proton beam therapy for hepatocellular carcinoma: comparison of network architectures and loss functions.Journal of radiation research · 2026Article
- A hybrid cluster-then-predict machine learning radiotherapy knowledge-based planning framework for similarity matching using holistic target-OAR constellation geometry.Radiation oncology (London, England) · 2026Article
- Cervical Cancer Tissue Analysis Using Photothermal Midinfrared Spectroscopic Imaging.Chemical & biomedical imaging · 2024Article
- A unified path seeking algorithm for IMRT and IMPT beam orientation optimization.Physics in medicine and biology · 2023Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Presumably, intensity-modulated proton radiotherapy (IMPT) is the most powerful form of proton radiotherapy. In the current state of the art, IMPT beam configurations (i.e. the number of beams and their directions) are, in general, chosen subjectively based on prior experience and practicality. Beam configuration optimization (BCO) for IMPT could, in theory, significantly enhance IMPT's therapeutic potential. However, BCO is complex and highly computer resource-intensive. Some algorithms for BCO have been developed for intensity-modulated photon therapy (IMRT). They are rarely used clinically mainly because the large number of beams typically employed in IMRT renders BCO essentially unnecessary. Moreover, in the newer form of IMRT, volumetric modulated arc therapy, there are no individual static beams. BCO is of greater importance for IMPT because it typically employs a very small number of beams (2-4) and, when the number of beams is small, BCO is critical for improving plan quality. However, the unique properties and requirements of protons, particularly in IMPT, make BCO challenging. Protons are more sensitive than photons to anatomic changes, exhibit variable relative biological effectiveness along their paths, and, as recently discovered, may spare the immune system. Such factors must be considered in IMPT BCO, though doing so would make BCO more resource intensive and make it more challenging to extend BCO algorithms developed for IMRT to IMPT. A limited amount of research in IMPT BCO has been conducted; however, considerable additional work is needed for its further development to make it truly effective and computationally practical. This article aims to provide a review of existing BCO algorithms, most of which were developed for IMRT, and addresses important requirements specific to BCO for IMPT optimization that necessitate the modification of existing approaches or the development of new effective and efficient ones.
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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.