ArticlePhysics and imaging in radiation oncology2021
Application of an automatic segmentation method for evaluating cardiac structure doses received by breast radiotherapy patients.
Article in Physics and imaging in radiation oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 15 citations in OpenAlex.
- Interpretable Machine Learning for Choosing Radiation Dose-volume Constraints on Cardio-pulmonary Substructures Associated with Overall Survival in NRG Oncology RTOG 0617.International journal of radiation oncology, biology, physics · 2023Trial
- Cardiac substructure delineation in radiation therapy - A state-of-the-art review.Journal of medical imaging and radiation oncology · 2024Review
- Automated contouring and statistical process control for plan quality in a breast clinical trial.Physics and imaging in radiation oncology · 2023Article
- A deep learning segmentation method to assess dose to organs at risk during breast radiotherapy.Physics and imaging in radiation oncology · 2023Article
- Advances in automatic delineation of target volume and cardiac substructure in breast cancer radiotherapy (Review).Oncology letters · 2023Review
- Association of cardiac calcium burden with overall survival after radiotherapy for non-small cell lung cancer.Physics and imaging in radiation oncology · 2023Article
- Synthetic contrast-enhanced computed tomography generation using a deep convolutional neural network for cardiac substructure delineation in breast cancer radiation therapy: a feasibility study.Radiation oncology (London, England) · 2022Article
- Narrative Review: Cardiotoxicities and Cardiac-Sparing Techniques in Radiotherapy.Technology in cancer research & treatmentReview
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Authors and funding
13 authors at 6 institutions in 1 country.
Funding
Abstract
background and purposeQuantifying radiation dose to cardiac substructures is important for research on the etiology and prevention of complications following radiotherapy; however, segmentation of substructures is challenging. In this study we demonstrate the application of our atlas-based automatic segmentation method to breast cancer radiotherapy plans for generating radiation doses in support of late effects research. MATERIAL AND
methodsWe applied our segmentation method to contour heart substructures on the computed tomography (CT) images of 70 breast cancer patients who received external photon radiotherapy. Two cardiologists provided manual segmentation of the whole heart (WH), left/right atria, left/right ventricles, and left anterior descending artery (LAD). The automatically contours were compared with manual delineations to evaluate similarity in terms of geometry and dose.
resultsThe mean Dice similarity coefficient between manual and automatic segmentations was 0.96 for the WH, 0.65 to 0.82 for the atria and ventricles, and 0.06 for the LAD. The mean average surface distance was 1.2 mm for the WH, 3.4 to 4.1 mm for the atria and ventricles, and 6.4 mm for the LAD. We found the dose to the cardiac substructures based on our automatic segmentation agrees with manual segmentation within expected observer variability. For left breast patients, the mean absolute difference in mean dose was 0.1 Gy for the WH, 0.2 to 0.7 Gy for the atria and ventricles, and 1.8 Gy for the LAD. For right breast patients, these values were 0.0 Gy, 0.1 to 0.4 Gy, and 0.4 Gy, respectively.
conclusionOur automatic segmentation method will facilitate the development of radiotherapy prescriptive criteria for mitigating cardiovascular complications.
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