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A comparison of two different software packages for analysis of body composition using computed tomography images

OBJECTIVES: The analysis of body composition from computed tomography (CT) imaging has become widespread. However, the methodology used is far from established. Two main software packages are commonly used for body composition analysis, with results used interchangeably. However, the equivalence of...

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Autores principales: Rollins, Katie E, Awwad, Amir, Macdonald, Ian A., Lobo, Dileep N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6269124/
https://www.ncbi.nlm.nih.gov/pubmed/30153585
http://dx.doi.org/10.1016/j.nut.2018.06.003
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author Rollins, Katie E
Awwad, Amir
Macdonald, Ian A.
Lobo, Dileep N.
author_facet Rollins, Katie E
Awwad, Amir
Macdonald, Ian A.
Lobo, Dileep N.
author_sort Rollins, Katie E
collection PubMed
description OBJECTIVES: The analysis of body composition from computed tomography (CT) imaging has become widespread. However, the methodology used is far from established. Two main software packages are commonly used for body composition analysis, with results used interchangeably. However, the equivalence of these has not been well established. The aim of this study was to compare the results of body composition analysis performed using the two software packages to assess their equivalence. METHODS: Triphasic abdominal CT scans from 50 patients were analyzed for a range of body composition measures at the third lumbar vertebral level using OsiriX (v7.5.1, Pixmeo, Switzerland) and SliceOmatic (v5.0, TomoVision, Montreal, Canada) software packages. Measures analyzed were skeletal muscle index (SMI), fat mass (FM), fat-free mass (FFM), and mean skeletal muscle Hounsfield Units (SMHU). RESULTS: The overall mean SMI calculated using the two software packages was significantly different (SliceOmatic 51.33 versus OsiriX 53.77, P < 0.0001), and this difference remained significant for non-contrast and arterial scans. When FM and FFM were considered, again the results were significantly different (SliceOmatic 33.7 versus OsiriX 33.1 kg, P < 0.0001; SliceOmatic 52.1 versus OsiriX 54.2 kg, P < 0.0001, respectively), and this difference remained for all phases of CT. Finally, when analyzed, mean SMHU was also significantly different (SliceOmatic 32.7 versus OsiriX 33.1 HU, P = 0.046). CONCLUSIONS: All four body composition measures were statistically significantly different by the software package used for analysis; however, the clinical significance of these differences is doubtful. Nevertheless, the same software package should be used if serial measurements are being performed.
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spelling pubmed-62691242019-01-01 A comparison of two different software packages for analysis of body composition using computed tomography images Rollins, Katie E Awwad, Amir Macdonald, Ian A. Lobo, Dileep N. Nutrition Article OBJECTIVES: The analysis of body composition from computed tomography (CT) imaging has become widespread. However, the methodology used is far from established. Two main software packages are commonly used for body composition analysis, with results used interchangeably. However, the equivalence of these has not been well established. The aim of this study was to compare the results of body composition analysis performed using the two software packages to assess their equivalence. METHODS: Triphasic abdominal CT scans from 50 patients were analyzed for a range of body composition measures at the third lumbar vertebral level using OsiriX (v7.5.1, Pixmeo, Switzerland) and SliceOmatic (v5.0, TomoVision, Montreal, Canada) software packages. Measures analyzed were skeletal muscle index (SMI), fat mass (FM), fat-free mass (FFM), and mean skeletal muscle Hounsfield Units (SMHU). RESULTS: The overall mean SMI calculated using the two software packages was significantly different (SliceOmatic 51.33 versus OsiriX 53.77, P < 0.0001), and this difference remained significant for non-contrast and arterial scans. When FM and FFM were considered, again the results were significantly different (SliceOmatic 33.7 versus OsiriX 33.1 kg, P < 0.0001; SliceOmatic 52.1 versus OsiriX 54.2 kg, P < 0.0001, respectively), and this difference remained for all phases of CT. Finally, when analyzed, mean SMHU was also significantly different (SliceOmatic 32.7 versus OsiriX 33.1 HU, P = 0.046). CONCLUSIONS: All four body composition measures were statistically significantly different by the software package used for analysis; however, the clinical significance of these differences is doubtful. Nevertheless, the same software package should be used if serial measurements are being performed. Elsevier Science 2019-01 /pmc/articles/PMC6269124/ /pubmed/30153585 http://dx.doi.org/10.1016/j.nut.2018.06.003 Text en © 2019 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Rollins, Katie E
Awwad, Amir
Macdonald, Ian A.
Lobo, Dileep N.
A comparison of two different software packages for analysis of body composition using computed tomography images
title A comparison of two different software packages for analysis of body composition using computed tomography images
title_full A comparison of two different software packages for analysis of body composition using computed tomography images
title_fullStr A comparison of two different software packages for analysis of body composition using computed tomography images
title_full_unstemmed A comparison of two different software packages for analysis of body composition using computed tomography images
title_short A comparison of two different software packages for analysis of body composition using computed tomography images
title_sort comparison of two different software packages for analysis of body composition using computed tomography images
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6269124/
https://www.ncbi.nlm.nih.gov/pubmed/30153585
http://dx.doi.org/10.1016/j.nut.2018.06.003
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