Trial reportPhysics in medicine and biology2015
Atlas-guided prostate intensity modulated radiation therapy (IMRT) planning.
Trial report in Physics in medicine and biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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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.
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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
17 citing papers in PubMed.
- Desargues cloud TPS: a cloud-based automatic radiation treatment planning system for IMRT.Biomedical engineering online · 2026Article
- Artificial general intelligence for radiation oncology.Meta-radiology · 2023Article
- Artificial intelligence guided physician directive improves head and neck planning quality and practice Uniformity: A prospective study.Clinical and translational radiation oncology · 2023Article
- Automatic treatment planning for cervical cancer radiation therapy using direct three-dimensional patient anatomy match.Journal of applied clinical medical physics · 2022Article
- Artificial Intelligence in Radiation Therapy.IEEE transactions on radiation and plasma medical sciences · 2022Article
- Assessing the robustness of artificial intelligence powered planning tools in radiotherapy clinical settings-a phantom simulation approach.Quantitative imaging in medicine and surgery · 2021Article
- Knowledge-based radiation treatment planning: A data-driven method survey.Journal of applied clinical medical physics · 2021Review
- Prospective study of artificial intelligence-based decision support to improve head and neck radiotherapy plan quality.Clinical and translational radiation oncology · 2021Article
- A method of using deep learning to predict three-dimensional dose distributions for intensity-modulated radiotherapy of rectal cancer.Journal of applied clinical medical physics · 2020Article
- Knowledge Models as Teaching Aid for Training Intensity Modulated Radiation Therapy Planning: A Lung Cancer Case Study.Frontiers in artificial intelligence · 2020Article
- Fluence Map Prediction Using Deep Learning Models - Direct Plan Generation for Pancreas Stereotactic Body Radiation Therapy.Frontiers in artificial intelligence · 2020Article
- Knowledge-based planning for intensity-modulated radiation therapy: A review of data-driven approaches.Medical physics · 2019Review
- Incorporating Case-Based Reasoning for Radiation Therapy Knowledge Modeling: A Pelvic Case Study.Technology in cancer research & treatment · 2019Article
- Automation in intensity modulated radiotherapy treatment planning-a review of recent innovations.The British journal of radiology · 2018Review
- Outlier identification in radiation therapy knowledge-based planning: A study of pelvic cases.Medical physics · 2017Article
- Knowledge mapping visualization analysis of the military health and medicine papers published in the web of science over the past 10 years.Military Medical Research · 2017Article
- Automated Intensity Modulated Radiation Therapy Treatment Planning for Cervical Cancer Based on Convolution Neural Network.Technology in cancer research & treatmentArticle
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
An atlas-based IMRT planning technique for prostate cancer was developed and evaluated. A multi-dose atlas was built based on the anatomy patterns of the patients, more specifically, the percent distance to the prostate and the concaveness angle formed by the seminal vesicles relative to the anterior-posterior axis. A 70-case dataset was classified using a k-medoids clustering analysis to recognize anatomy pattern variations in the dataset. The best classification, defined by the number of classes or medoids, was determined by the largest value of the average silhouette width. Reference plans from each class formed a multi-dose atlas. The atlas-guided planning (AGP) technique started with matching the new case anatomy pattern to one of the reference cases in the atlas; then a deformable registration between the atlas and new case anatomies transferred the dose from the atlas to the new case to guide inverse planning with full automation. 20 additional clinical cases were re-planned to evaluate the AGP technique. Dosimetric properties between AGP and clinical plans were evaluated. The classification analysis determined that the 5-case atlas would best represent anatomy patterns for the patient cohort. AGP took approximately 1 min on average (corresponding to 70 iterations of optimization) for all cases. When dosimetric parameters were compared, the differences between AGP and clinical plans were less than 3.5%, albeit some statistical significances observed: homogeneity index (p > 0.05), conformity index (p < 0.01), bladder gEUD (p < 0.01), and rectum gEUD (p = 0.02). Atlas-guided treatment planning is feasible and efficient. Atlas predicted dose can effectively guide the optimizer to achieve plan quality comparable to that of clinical plans.
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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.