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Pediatric body composition based on automatic segmentation of computed tomography scans: a pilot study
BACKGROUND: Body composition during childhood may predispose to negative health outcomes later in life. Automatic segmentation may assist in quantifying pediatric body composition in children. OBJECTIVE: To evaluate automatic segmentation for body composition on pediatric computed tomography (CT) sc...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10635977/ https://www.ncbi.nlm.nih.gov/pubmed/37640800 http://dx.doi.org/10.1007/s00247-023-05739-x |
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author | Samim, Atia Spijkers, Suzanne Moeskops, Pim Littooij, Annemieke S. de Jong, Pim A. Veldhuis, Wouter B. de Vos, Bob D. van Santen, Hanneke M. Nievelstein, Rutger A. J. |
author_facet | Samim, Atia Spijkers, Suzanne Moeskops, Pim Littooij, Annemieke S. de Jong, Pim A. Veldhuis, Wouter B. de Vos, Bob D. van Santen, Hanneke M. Nievelstein, Rutger A. J. |
author_sort | Samim, Atia |
collection | PubMed |
description | BACKGROUND: Body composition during childhood may predispose to negative health outcomes later in life. Automatic segmentation may assist in quantifying pediatric body composition in children. OBJECTIVE: To evaluate automatic segmentation for body composition on pediatric computed tomography (CT) scans and to provide normative data on muscle and fat areas throughout childhood using automatic segmentation. MATERIALS AND METHODS: In this pilot study, 537 children (ages 1–17 years) who underwent abdominal CT after high-energy trauma at a Dutch tertiary center (2002–2019) were retrospectively identified. Of these, the CT images of 493 children (66% boys) were used to establish normative data. Muscle (psoas, paraspinal and abdominal wall) and fat (subcutaneous and visceral) areas were measured at the third lumbar vertebral (L3) level by automatic segmentation. A representative subset of 52 scans was also manually segmented to evaluate the performance of automatic segmentation. RESULTS: For manually-segmented versus automatically-segmented areas (52 scans), mean Dice coefficients were high for muscle (0.87–0.90) and subcutaneous fat (0.88), but lower for visceral fat (0.60). In the control group, muscle area was comparable for both sexes until the age of 13 years, whereafter, boys developed relatively more muscle. From a young age, boys were more prone to visceral fat storage than girls. Overall, boys had significantly higher visceral-to-subcutaneous fat ratios (median 1.1 vs. 0.6, P<0.01) and girls higher fat-to-muscle ratios (median 1.0 vs. 0.7, P<0.01). CONCLUSION: Automatic segmentation of L3-level muscle and fat areas allows for accurate quantification of pediatric body composition. Using automatic segmentation, the development in muscle and fat distribution during childhood (in otherwise healthy) Dutch children was demonstrated. SUPPLEMENTARY INFORMATION: Supplementary material is available at 10.1007/s00247-023-05739-x. |
format | Online Article Text |
id | pubmed-10635977 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-106359772023-11-14 Pediatric body composition based on automatic segmentation of computed tomography scans: a pilot study Samim, Atia Spijkers, Suzanne Moeskops, Pim Littooij, Annemieke S. de Jong, Pim A. Veldhuis, Wouter B. de Vos, Bob D. van Santen, Hanneke M. Nievelstein, Rutger A. J. Pediatr Radiol Original Article BACKGROUND: Body composition during childhood may predispose to negative health outcomes later in life. Automatic segmentation may assist in quantifying pediatric body composition in children. OBJECTIVE: To evaluate automatic segmentation for body composition on pediatric computed tomography (CT) scans and to provide normative data on muscle and fat areas throughout childhood using automatic segmentation. MATERIALS AND METHODS: In this pilot study, 537 children (ages 1–17 years) who underwent abdominal CT after high-energy trauma at a Dutch tertiary center (2002–2019) were retrospectively identified. Of these, the CT images of 493 children (66% boys) were used to establish normative data. Muscle (psoas, paraspinal and abdominal wall) and fat (subcutaneous and visceral) areas were measured at the third lumbar vertebral (L3) level by automatic segmentation. A representative subset of 52 scans was also manually segmented to evaluate the performance of automatic segmentation. RESULTS: For manually-segmented versus automatically-segmented areas (52 scans), mean Dice coefficients were high for muscle (0.87–0.90) and subcutaneous fat (0.88), but lower for visceral fat (0.60). In the control group, muscle area was comparable for both sexes until the age of 13 years, whereafter, boys developed relatively more muscle. From a young age, boys were more prone to visceral fat storage than girls. Overall, boys had significantly higher visceral-to-subcutaneous fat ratios (median 1.1 vs. 0.6, P<0.01) and girls higher fat-to-muscle ratios (median 1.0 vs. 0.7, P<0.01). CONCLUSION: Automatic segmentation of L3-level muscle and fat areas allows for accurate quantification of pediatric body composition. Using automatic segmentation, the development in muscle and fat distribution during childhood (in otherwise healthy) Dutch children was demonstrated. SUPPLEMENTARY INFORMATION: Supplementary material is available at 10.1007/s00247-023-05739-x. Springer Berlin Heidelberg 2023-08-29 2023 /pmc/articles/PMC10635977/ /pubmed/37640800 http://dx.doi.org/10.1007/s00247-023-05739-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Samim, Atia Spijkers, Suzanne Moeskops, Pim Littooij, Annemieke S. de Jong, Pim A. Veldhuis, Wouter B. de Vos, Bob D. van Santen, Hanneke M. Nievelstein, Rutger A. J. Pediatric body composition based on automatic segmentation of computed tomography scans: a pilot study |
title | Pediatric body composition based on automatic segmentation of computed tomography scans: a pilot study |
title_full | Pediatric body composition based on automatic segmentation of computed tomography scans: a pilot study |
title_fullStr | Pediatric body composition based on automatic segmentation of computed tomography scans: a pilot study |
title_full_unstemmed | Pediatric body composition based on automatic segmentation of computed tomography scans: a pilot study |
title_short | Pediatric body composition based on automatic segmentation of computed tomography scans: a pilot study |
title_sort | pediatric body composition based on automatic segmentation of computed tomography scans: a pilot study |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10635977/ https://www.ncbi.nlm.nih.gov/pubmed/37640800 http://dx.doi.org/10.1007/s00247-023-05739-x |
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