ArticlePhysics and imaging in radiation oncology2024
Predicting cervical cancer target motion using a multivariate regression model to enable patient selection for adaptive external beam radiotherapy.
Article in Physics and imaging in radiation oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 1 citations in OpenAlex.
- Risk of genitourinary late effects after radiotherapy for prostate cancer associated with early changes in bladder shape.Physics and imaging in radiation oncology · 2025Article
- Implementing Plan of the Day for Cervical Cancer: A Comparison of Target Volume Generation Methods.Advances in radiation oncology · 2024Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and purpose: Interfraction motion during cervical cancer radiotherapy is substantial in some patients, minimal in others. Non-adaptive plans may miss the target and/or unnecessarily irradiate normal tissue. Adaptive radiotherapy leads to superior dose-volume metrics but is resource-intensive. The aim of this study was to predict target motion, enabling patient selection and efficient resource allocation. Materials and methods: Forty cervical cancer patients had CT with full-bladder (CT-FB) and empty-bladder (CT-EB) at planning, and daily cone-beam CTs (CBCTs). The low-risk clinical target volume (CTV Results: The Two-CT model was based upon rectal volume, dice similarity coefficient between CT-FB and CT-EB CTV Conclusion: Uterocervix motion is complex and multifactorial. We present two multivariate models which predicted motion with reasonable accuracy using pre-treatment information, and outperformed the only published method.
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