ArticleRadiation oncology (London, England)2022
A novel knowledge-based prediction model for estimating an initial equivalent uniform dose in semi-auto-planning for cervical cancer.
Article in Radiation oncology (London, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- The improved features to dose correlation for dose volumes prediction in multidisease radiation therapy plans.Scientific reports · 2025Article
- An extension to the OVH concept for knowledge-based dose volume histogram prediction in lung tumor volumetric-modulated arc therapy.Journal of applied clinical medical physics · 2025Article
- Improving Radiotherapy Plan Quality for Nasopharyngeal Carcinoma With Enhanced UNet Dose Prediction.Cancer medicine · 2025Article
- Application of the Monaco-serial biological function for cardiac dose constraints in DIBH-IMRT treatment planning for left-sided breast cancer.Frontiers in oncology · 2025Article
- Development and validation of an automated Tomotherapy planning method for cervical cancer.Radiation oncology (London, England) · 2024Article
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6 authors.
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Abstract
backgroundWe developed a novel concept, equivalent uniform length (EUL), to describe the relationship between the generalized equivalent uniform dose (EUD) and the geometric anatomy around a tumor target. By correlating EUL with EUD, we established two EUD-EUL knowledge-based (EEKB) prediction models for the bladder and rectum that predict initial EUD values for generating quality treatment plans.
methodsEUL metrics for the rectum and bladder were extracted and collected from the intensity-modulated radiotherapy therapy (IMRT) plans of 60 patients with cervical cancer. The two EEKB prediction models were built using linear regression to establish the relationships between EUL
resultsLinear regression analyses showed a significant correlation between EUL and EUD (R
conclusionsOur EEKB prediction models predicted reasonable initial EUD values for the rectum and bladder based on patient-specific geometric EUL values, thereby improving optimization and planning efficiency.
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