ArticleJournal of applied clinical medical physics2023
Deep learning-based body weight from scout images can be an alternative to actual body weight in CT radiation dose management.
Article in Journal of applied clinical medical physics, 2023. 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.
- Machine learning-based estimation of patient body weight from radiation dose metrics in computed tomography.Journal of applied clinical medical physics · 2024Article
- Deep learning-based body weight from scout images can be an alternative to actual body weight in CT radiation dose management.Journal of applied clinical medical physics · 2023Article
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Authors and funding
3 authors.
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Abstract
purposeAccurate body weight measurement is essential to promote computed tomography (CT) dose optimization; however, body weight cannot always be measured prior to CT examination, especially in the emergency setting. The aim of this study was to investigate whether deep learning-based body weight from chest CT scout images can be an alternative to actual body weight in CT radiation dose management.
methodsChest CT scout images and diagnostic images acquired for medical checkups were collected from 3601 patients. A deep learning model was developed to predict body weight from scout images. The correlation between actual and predicted body weight was analyzed. To validate the use of predicted body weight in radiation dose management, the volume CT dose index (CTDI
resultsThe median actual and predicted body weight were 64.1 (interquartile range: 56.5-72.4) and 64.0 (56.3-72.2) kg, respectively. There was a strong correlation between actual and predicted body weight (ρ = 0.892, p < 0.001). The CTDI
conclusionPredicted body weight can be an alternative to actual body weight in managing dose metrics and simplifying SSDE calculation. Our proposed method can be useful for CT radiation dose management in adult patients with unknown body weight.
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