SynthesisInternational journal of radiation oncology, biology, physics2020
A Systematic Review of Contouring Guidelines in Radiation Oncology: Analysis of Frequency, Methodology, and Delivery of Consensus Recommendations.
Synthesis in International journal of radiation oncology, biology, physics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 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
38 citing papers in PubMed.
- Critical Review of Cataractogenesis and Lens Contouring in Radiation Oncology.Advances in radiation oncology · 2026Review
- Uncertainty quantification of U-Net based segmentation tool using conformal prediction.Journal of applied clinical medical physics · 2026Article
- Redefining oropharyngeal cancer in the HPV era: integrating precision medicine and immunotherapeutic frontiers.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- Data annotation and its evaluation in artificial intelligence-based anatomy recognition for ultrasound-guided regional anesthesia: a clinical perspective.Frontiers in medicine · 2026Article
- Geometrically focused training and evaluation of organs-at-risk segmentation via deep learning.Medical physics · 2025Article
- Geometric and dosimetric evaluation of a commercial AI auto-contouring tool on multiple anatomical sites in CT scans.Journal of applied clinical medical physics · 2025Article
- Evaluation and failure analysis of four commercial deep learning-based autosegmentation software for abdominal organs at risk.Journal of applied clinical medical physics · 2025Article
- Guidance on selecting and evaluating AI auto-segmentation systems in clinical radiotherapy: insights from a six-vendor analysis.Physical and engineering sciences in medicine · 2025Article
- Precision in the Face of Noise - Lessons from Kahneman, Siboney, and Sunstein for Radiation Oncology.ArXiv · 2024Article
- Optimum delineation of skin structure for dose calculation with the linear Boltzmann transport equation algorithm in radiotherapy treatment planning.Radiological physics and technology · 2024Article
- Artificial intelligence uncertainty quantification in radiotherapy applications - A scoping review.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2024Article
- Review of Quality Audit in a Radiation Oncology Department in a Tertiary Care Hospital- 2 Year-Results.Asian Pacific journal of cancer prevention : APJCP · 2024Article
- Radiation Dose-Induced Carotid Artery Stenosis and Brain Necrosis in Head and Neck Cancer-A Real World Cohort Study.Cancers · 2024Article
- Evolving Horizons in Radiation Therapy Auto-Contouring: Distilling Insights, Embracing Data-Centric Frameworks, and Moving Beyond Geometric Quantification.Advances in radiation oncology · 2024Article
- Associations Between Radiation Oncologist Demographic Factors and Segmentation Similarity Benchmarks: Insights From a Crowd-Sourced Challenge Using Bayesian Estimation.JCO clinical cancer informatics · 2024Article
- Evaluation of multiple-vendor AI autocontouring solutions.Radiation oncology (London, England) · 2024Article
- Artificial Intelligence Uncertainty Quantification in Radiotherapy Applications - A Scoping Review.medRxiv : the preprint server for health sciences · 2024Article
- NRG Oncology Assessment of Artificial Intelligence Deep Learning-Based Auto-segmentation for Radiation Therapy: Current Developments, Clinical Considerations, and Future Directions.International journal of radiation oncology, biology, physics · 2024Article
- Multicenter Study of Pelvic Nodal Autosegmentation Algorithm of Siemens Healthineers: Comparison of Male Versus Female Pelvis.Advances in radiation oncology · 2024Article
- Revolutionizing radiation therapy: the role of AI in clinical practice.Journal of radiation research · 2024Review
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
purposeClinical trials have described variation in radiation therapy plan quality, of which contour delineation is a key component, and linked this to inferior patient outcomes. In response, consensus guidelines have been developed to standardize contour delineation. This investigation assesses trends in contouring guidelines and examines the methodologies used to generate and deliver recommendations. METHODS AND MATERIALS: We conducted a literature search for contouring guidelines published after 1995. Of 11,124 citations, 332 were identified for full-text review to determine inclusion. We abstracted articles for the intent of the consensus process, key elements of the methodology, and mode of information delivery. A Fisher exact test was used to identify elements that differed among the guidelines generated for clinical trials and routine care.
resultsOverall, 142 guidelines were included, of which 16 (11%) were developed for a clinical trial. There was an increase in guideline publication over time (0 from 1995-1999 vs 65 from 2015- 2019; P = .03), particularly among recommendations for stereotactic radiation and brachytherapy. The most common disease sites were head and neck (24%), gastrointestinal (12%), and gynecologic (12%). Methods used to develop recommendations included literature review (50%) and image-based methods (45%). Panels included a median of 10 physicians (interquartile range, 7-16); 70% of panels represented multidisciplinary expertise. Guidelines developed for a clinical trial were more likely to include an image-based approach, with quantitative analysis of contours submitted by the panel members and to publish a full set of image-based recommendations (P < .005).
conclusionsThis review highlights an increase in consensus contouring recommendations over time. Guidelines focus on disease sites, such as head and neck, with evidence supporting a correlation between treatment planning and patient outcomes, although variation exists in the approach to the consensus process. Elements that may improve guideline acceptance (ie, image-based consensus contour analysis) and usability (ie, inclusion of a full image set) are more common in guidelines developed for clinical trials.
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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.