ArticlePhysics in medicine and biology2024
Deep learning-based synthetic dose-weighted LET map generation for intensity modulated proton therapy.
Article in Physics in medicine and biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Recent advances in applying machine learning to proton radiotherapy.Biomedical physics & engineering express · 2025Pooled it
- Deep learning for dose-averaged linear energy transfer estimation in pencil-beam scanning and double scattering proton radiotherapy plans with uncertainty-aware external validation.Physics and imaging in radiation oncology · 2026Article
- Generalizability of deep learning-based dose conversion model in proton beam therapy.Journal of applied clinical medical physics · 2026Article
- A deep learning model for predicting the modified micro-dosimetric kinetic model-based dose and the dose-averaged linear energy transfer for prostate cancer in carbon ion therapy.Physics and imaging in radiation oncology · 2024Article
- CT-based synthetic iodine map generation using conditional denoising diffusion probabilistic model.Medical physics · 2024Article
- CT-based synthetic contrast-enhanced dual-energy CT generation using conditional denoising diffusion probabilistic model.Physics in medicine and biology · 2024Article
- MRI-only based material mass density and relative stopping power estimation via deep learning for proton therapy: a preliminary study.Scientific reports · 2024Article
- Artificial Intelligence in Proton Therapy: What Works, What Does Not, and What Is Next.Cancer journal (Sudbury, Mass.)Review
- Radiobiological Modeling with Monte Carlo Tools - Simulating Cellular Responses to Ionizing Radiation.Technology in cancer research & treatmentReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
The advantage of proton therapy as compared to photon therapy stems from the Bragg peak effect, which allows protons to deposit most of their energy directly at the tumor while sparing healthy tissue. However, even with such benefits, proton therapy does present certain challenges. The biological effectiveness differences between protons and photons are not fully incorporated into clinical treatment planning processes. In current clinical practice, the relative biological effectiveness (RBE) between protons and photons is set as constant 1.1. Numerous studies have suggested that the RBE of protons can exhibit significant variability. Given these findings, there is a substantial interest in refining proton therapy treatment planning to better account for the variable RBE. Dose-average linear energy transfer (LET
Indexed as
Identifiers
What Socratic 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 Socratic graph.