ArticleRadiation oncology (London, England)2021
Biologically consistent dose accumulation using daily patient imaging.
Article in Radiation oncology (London, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- First dosimetric evaluation of deformable dose accumulation in human individuals.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2026Article
- Magnetic resonance-guided online adaptive stereotactic body radiotherapy for advanced inoperable pancreatic cancer: a prospective study.Radiation oncology (London, England) · 2025Article
- Review and recommendations on deformable image registration uncertainties for radiotherapy applications.Physics in medicine and biology · 2023Review
- Applicability and usage of dose mapping/accumulation in radiotherapy.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2023Review
- Article
- Radiomic and Dosiomic Features for the Prediction of Radiation Pneumonitis Across Esophageal Cancer and Lung Cancer.Frontiers in oncology · 2022Article
- Biological dosiomic features for the prediction of radiation pneumonitis in esophageal cancer patients.Radiation oncology (London, England) · 2021Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis work addresses a basic inconsistency in the way dose is accumulated in radiotherapy when predicting the biological effect based on the linear quadratic model (LQM). To overcome this inconsistency, we introduce and evaluate the concept of the total biological dose, bEQD
methodsDaily computed tomography imaging of nine patients treated for prostate carcinoma with intensity-modulated radiotherapy was used to compute the delivered deformed dose on the basis of deformable image registration (DIR). We compared conventional dose accumulation (DA) with the newly introduced bEQD
resultsbEQD
conclusionUsing bEQD
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