A deep-learning method using computed tomography scout images for estimating patient body weight

Abstract Body weight is an indispensable parameter for determination of contrast medium dose, appropriate drug dosing, or management of radiation dose. However, we cannot always determine the accurate patient body weight at the time of computed tomography (CT) scanning, especially in emergency care....

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Autores principales:	Shota Ichikawa, Misaki Hamada, Hiroyuki Sugimori
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/5494661527bf4f8593b4bd0b539078cd
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spelling	oai:doaj.org-article:5494661527bf4f8593b4bd0b539078cd2021-12-02T14:53:43ZA deep-learning method using computed tomography scout images for estimating patient body weight10.1038/s41598-021-95170-92045-2322https://doaj.org/article/5494661527bf4f8593b4bd0b539078cd2021-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-95170-9https://doaj.org/toc/2045-2322Abstract Body weight is an indispensable parameter for determination of contrast medium dose, appropriate drug dosing, or management of radiation dose. However, we cannot always determine the accurate patient body weight at the time of computed tomography (CT) scanning, especially in emergency care. Time-efficient methods to estimate body weight with high accuracy before diagnostic CT scans currently do not exist. In this study, on the basis of 1831 chest and 519 abdominal CT scout images with the corresponding body weights, we developed and evaluated deep-learning models capable of automatically predicting body weight from CT scout images. In the model performance assessment, there were strong correlations between the actual and predicted body weights in both chest (ρ = 0.947, p < 0.001) and abdominal datasets (ρ = 0.869, p < 0.001). The mean absolute errors were 2.75 kg and 4.77 kg for the chest and abdominal datasets, respectively. Our proposed method with deep learning is useful for estimating body weights from CT scout images with clinically acceptable accuracy and potentially could be useful for determining the contrast medium dose and CT dose management in adult patients with unknown body weight.Shota IchikawaMisaki HamadaHiroyuki SugimoriNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Shota Ichikawa Misaki Hamada Hiroyuki Sugimori A deep-learning method using computed tomography scout images for estimating patient body weight
description	Abstract Body weight is an indispensable parameter for determination of contrast medium dose, appropriate drug dosing, or management of radiation dose. However, we cannot always determine the accurate patient body weight at the time of computed tomography (CT) scanning, especially in emergency care. Time-efficient methods to estimate body weight with high accuracy before diagnostic CT scans currently do not exist. In this study, on the basis of 1831 chest and 519 abdominal CT scout images with the corresponding body weights, we developed and evaluated deep-learning models capable of automatically predicting body weight from CT scout images. In the model performance assessment, there were strong correlations between the actual and predicted body weights in both chest (ρ = 0.947, p < 0.001) and abdominal datasets (ρ = 0.869, p < 0.001). The mean absolute errors were 2.75 kg and 4.77 kg for the chest and abdominal datasets, respectively. Our proposed method with deep learning is useful for estimating body weights from CT scout images with clinically acceptable accuracy and potentially could be useful for determining the contrast medium dose and CT dose management in adult patients with unknown body weight.
format	article
author	Shota Ichikawa Misaki Hamada Hiroyuki Sugimori
author_facet	Shota Ichikawa Misaki Hamada Hiroyuki Sugimori
author_sort	Shota Ichikawa
title	A deep-learning method using computed tomography scout images for estimating patient body weight
title_short	A deep-learning method using computed tomography scout images for estimating patient body weight
title_full	A deep-learning method using computed tomography scout images for estimating patient body weight
title_fullStr	A deep-learning method using computed tomography scout images for estimating patient body weight
title_full_unstemmed	A deep-learning method using computed tomography scout images for estimating patient body weight
title_sort	deep-learning method using computed tomography scout images for estimating patient body weight
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/5494661527bf4f8593b4bd0b539078cd
work_keys_str_mv	AT shotaichikawa adeeplearningmethodusingcomputedtomographyscoutimagesforestimatingpatientbodyweight AT misakihamada adeeplearningmethodusingcomputedtomographyscoutimagesforestimatingpatientbodyweight AT hiroyukisugimori adeeplearningmethodusingcomputedtomographyscoutimagesforestimatingpatientbodyweight AT shotaichikawa deeplearningmethodusingcomputedtomographyscoutimagesforestimatingpatientbodyweight AT misakihamada deeplearningmethodusingcomputedtomographyscoutimagesforestimatingpatientbodyweight AT hiroyukisugimori deeplearningmethodusingcomputedtomographyscoutimagesforestimatingpatientbodyweight
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A deep-learning method using computed tomography scout images for estimating patient body weight

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