ArticlePhysics and imaging in radiation oncology2022
The impact of a metal artefact reduction algorithm on treatment planning for patients undergoing radiotherapy of the pelvis.
Article in Physics and imaging in radiation oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 8 citations in OpenAlex.
- Deep learning-based metal artifact reduction in CT for head and neck radiotherapy.Physics and imaging in radiation oncology · 2026Review
- Practical considerations for handling implants in proton therapy.Journal of applied clinical medical physics · 2025Article
- A PEEK into carbon fiber: A practical guide for high performance composite polymeric implants for orthopaedic oncology.Journal of orthopaedics · 2023Article
- Benefits and considerations in using a novel computed tomography system optimized for radiotherapy planning.Physics and imaging in radiation oncology · 2023Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and purpose: Metallic implants cause artefacts in computed tomography (CT) images and can introduce significant errors to structure visualisation and dosimetric calculation within the radiotherapy planning process. This study evaluated an orthopaedic metal artefact reduction algorithm and its effect on the CT number, image noise, structure delineation, and treatment dose. Methods: Raw CT data were reconstructed using standard filtered back projection and an artefact reduction algorithm to create 'standard' and 'corrected' images. A phantom containing tissue-mimicking inserts and two titanium plugs was imaged. The average CT number was compared to baseline data acquired without metal inserts. Data from 11 pelvic external beam radiotherapy (EBRT) patients with bi- or uni-lateral hip implants were retrospectively analysed. The clinically used treatment plans were re-computed on the corrected images. A prostate-mimicking phantom containing metal 'implants' was imaged, and 11 observers contoured both reconstructions. Results: The artefact reduction algorithm improved the CT number in those areas most affected by metal artefacts and decreased noise by 19 % (P =.04) Changes in dose distributions on corrected images compared to those calculated using the current clinical protocol were clinically insignificant. Volumes contoured on the corrected phantom images had larger Dice coefficients than those contoured on the standard images (P =.001), as well as a 36 % lower standard deviation in volumes. Conclusion: This study demonstrates that the metal artefact reduction software reduces the error in CT numbers, can improve delineation accuracy, and can reduce inter-observer variability. It has the potential to streamline the planning pathway and improve treatment planning accuracy.
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