ArticleTechnical innovations & patient support in radiation oncology2020
Analysis of dose using CBCT and synthetic CT during head and neck radiotherapy: A single centre feasibility study.
Article in Technical innovations & patient support in radiation oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.
- Deep learning methods for enhancing cone-beam CT image quality toward adaptive radiation therapy: A systematic review.Medical physics · 2022Pooled it
- Dose monitoring-guided replanning timing in adaptive radiotherapy for laryngeal cancer.Physical and engineering sciences in medicine · 2026Article
- Fast, automated optimization of virtual monoenergetic images with the dual-energy image synthesizer for cone-beam CT.Journal of applied clinical medical physics · 2025Article
- Article
- Technical note: TIGRE-DE for the creation of virtual monoenergetic images from dual-energy cone-beam CT.Medical physics · 2024Article
- Evaluating the Hounsfield unit assignment and dose differences between CT-based standard and deep learning-based synthetic CT images for MRI-only radiation therapy of the head and neck.Journal of applied clinical medical physics · 2024Article
- Evaluating synthetic computed tomography images for adaptive radiotherapy decision making in head and neck cancer.Physics and imaging in radiation oncology · 2023Article
- CBCT-to-CT Translation Using Registration-Based Generative Adversarial Networks in Patients with Head and Neck Cancer.Cancers · 2023Article
- The geometric and dosimetric accuracy of kilovoltage cone beam computed tomography images for adaptive treatment: a systematic review.BJR open · 2023Article
- Assessment of CBCT-based synthetic CT generation accuracy for adaptive radiotherapy planning.Journal of applied clinical medical physics · 2022Article
- Adaptive replanning using cone beam CT for deformation of original CT simulation.Journal of medical radiation sciences · 2022Article
- Diversity in radiation therapist/therapeutic radiographer (RTT) advanced practice (AP) roles delivering on the four domains.Technical innovations & patient support in radiation oncology · 2021Article
Corrections and comments
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Authors and funding
12 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThe study aimed to assess the suitability of deformable image registration (DIR) software to generate synthetic CT (sCT) scans for dose verification during radiotherapy to the head and neck. Planning and synthetic CT dose volume histograms were compared to evaluate dosimetric changes during the treatment course.
methodsEligible patients had locally advanced (stage III, IVa and IVb) oropharyngeal cancer treated with primary radiotherapy. Weekly CBCT images were acquired post treatment at fractions 1, 6, 11, 16, 21 and 26 over a 30 fraction treatment course. Each CBCT was deformed with the planning CT to generate a sCT which was used to calculate the dose at that point in the treatment. A repeat planning CT2 was acquired at fraction 16 and deformed with the fraction 16 CBCT to compare differences between the calculations mid-treatment.
results20 patients were evaluated generating 138 synthetic CT sets. The single fraction mean dose to PTV_HR between the synthetic and planning CT did not vary, although dose to 95% of PTV_HR was smaller at week 6 compared to planning (difference 2.0%, 95% CI (0.8 to 3.1), p = 0.0). There was no statistically significant difference in PRV_brainstem or PRV_spinal cord maximum dose, although greater variation using the sCT calculations was reported. The mean dose to structures based on the fraction 16 sCT and CT2 scans were similar.
conclusionsSynthetic CT provides comparable dose calculations to those of a repeat planning CT; however the limitations of DIR must be understood before it is applied within the clinical setting.
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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.