ReviewJCO global oncology2023
Addressing the Global Expertise Gap in Radiation Oncology: The Radiation Planning Assistant.
Review in JCO global oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed.
- Can physics review catch prescription and PTV margin errors in fully automated radiotherapy plans? A hazard study.Journal of applied clinical medical physics · 2026Article
- Artificial Intelligence and the Global Radiotherapy Gap.JCO global oncology · 2026Article
- Global spotlight editorial: Advancing treatment planning to promote equity through AI and automation in clinical medical physics.Journal of applied clinical medical physics · 2026Article
- Review
- Leveraging large language models for heuristic usability assessment of medical software: Insights with the Radiation Planning Assistant.Journal of applied clinical medical physics · 2026Article
- Dosimetric evaluation of Ethos 2.0 high-fidelity mode for single-isocenter SRS.Journal of applied clinical medical physics · 2025Article
- Article
- NRG Oncology Assessment of Artificial Intelligence for Automatic Treatment Planning in Radiation Therapy Clinical Trials: Present and Future.International journal of radiation oncology, biology, physics · 2025Article
- First Decade of the National Cancer Institute's Affordable Cancer Technologies Program: Accelerating Translational Technology Research and Development for Cancer Globally.JCO global oncology · 2025Review
- External validation of an algorithm to detect vertebral level mislabeling and autocontouring errors.Physics and imaging in radiation oncology · 2025Article
- When are Diffusion Priors Helpful in Sparse Reconstruction? A Study with Sparse-view CT.ArXiv · 2025Article
- Ultra-fast, one-click radiotherapy treatment planning outside a treatment planning system.Physics and imaging in radiation oncology · 2025Article
- Analyzing the Relationship between Dose and Geometric Agreement Metrics for Auto-Contouring in Head and Neck Normal Tissues.Diagnostics (Basel, Switzerland) · 2024Article
- Autocontouring of primary lung lesions and nodal disease for radiotherapy based only on computed tomography images.Physics and imaging in radiation oncology · 2024Article
- Addressing challenges in low-income and middle-income countries through novel radiotherapy research opportunities.The Lancet. Oncology · 2024Review
- Artificial Intelligence-Based Radiotherapy Contouring and Planning to Improve Global Access to Cancer Care.JCO global oncology · 2024Article
- Clinical acceptability of automatically generated lymph node levels and structures of deglutition and mastication for head and neck radiation therapy.Physics and imaging in radiation oncology · 2024Article
- Validation of an automated contouring and treatment planning tool for pediatric craniospinal radiation therapy.Frontiers in oncology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
26 authors.
Funding
Abstract
purposeAutomation, including the use of artificial intelligence, has been identified as a possible opportunity to help reduce the gap in access and quality for radiotherapy and other aspects of cancer care. The Radiation Planning Assistant (RPA) project was conceived in 2015 (and funded in 2016) to use automated contouring and treatment planning algorithms to support the efforts of oncologists in low- and middle-income countries, allowing them to scale their efforts and treat more patients safely and efficiently (to increase access).
designIn this review, we discuss the development of the RPA, with a particular focus on clinical acceptability and safety/risk across jurisdictions as these are important indicators for the successful future deployment of the RPA to increase radiotherapy availability and ameliorate global disparities in access to radiation oncology.
resultsRPA tools will be offered through a webpage, where users can upload computed tomography data sets and download automatically generated contours and treatment plans. All interfaces have been designed to maximize ease of use and minimize risk. The current version of the RPA includes automated contouring and planning for head and neck cancer, cervical cancer, breast cancer, and metastases to the brain.
conclusionThe RPA has been designed to bring high-quality treatment planning to more patients across the world, and it may encourage greater investment in treatment devices and other aspects of 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.