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Agreement between software programmes of body composition analyses on abdominal computed tomography scans of obese adults

Overview of attention for article published in Archives of Endocrinology and Metabolism, September 2019
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Title
Agreement between software programmes of body composition analyses on abdominal computed tomography scans of obese adults
Published in
Archives of Endocrinology and Metabolism, September 2019
DOI 10.20945/2359-3997000000174
Pubmed ID
Authors

Erica Roberta Barbalho, Ilanna Marques Gomes da Rocha, Galtieri Otávio Cunha de Medeiros, Rogerio Friedman, Ana Paula Trussardi Fayh

Abstract

A large number of studies have used abdominal computed tomography (CT) to quantify body composition, and different software programmes have been used to perform these analyses. Thus, this comparison is important to enable researchers to know the performance of more accessible software. Fifty-four abdominal CT scans of obese (BMI 30 to 39.9 kg/m2), sedentary adults (24-41 years) patients from a Brazilian single center were selected. Two software programs were compared: Slice-O-Matic (Tomovision, Canada) version 5.0 and OsiriX version 5.8.5. The body composition analysis were segmented using standard Hounsfield unit (HU) (adipose tissue: -190 to +30 and skeletal muscle: -29 to +150) and measured at the mid third lumbar vertebra (L3) level on a slice showing both transversal processes. Bland-Altman limits of agreement analyses were used to assess the level of agreement between Slice-O-Matic and OsiriX. A total of fifty-four participants were evaluated, with majority women (69%), mean of age 31.3 (SD 6.5) years and obesity grade I most prevalent (74.1%). The agreement, in Bland-Altman analysis, between Slice-O-Matic and OsiriX analisys for the muscle mass tissue, visceral adipose tissue and subcutaneous adipose tissue were excellent (≥ 0.954) with P-values < 0.001. These findings show that Slice-O-Matic and OsiriX softwares agreement in measurements of skeletal muscle and adipose tissue and sarcopenia diagnosis in obese patients, suggesting good applicability in studies with body composition in this population and clinical practice.

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Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 12%
Student > Master 6 12%
Student > Bachelor 4 8%
Other 4 8%
Student > Doctoral Student 2 4%
Other 7 14%
Unknown 21 42%
Readers by discipline Count As %
Medicine and Dentistry 9 18%
Nursing and Health Professions 4 8%
Agricultural and Biological Sciences 3 6%
Social Sciences 3 6%
Sports and Recreations 2 4%
Other 4 8%
Unknown 25 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 October 2019.
All research outputs
#22,771,990
of 25,385,509 outputs
Outputs from Archives of Endocrinology and Metabolism
#649
of 801 outputs
Outputs of similar age
#310,663
of 361,310 outputs
Outputs of similar age from Archives of Endocrinology and Metabolism
#5
of 8 outputs
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