Agreement between software programmes of body composition analyses on abdominal computed tomography scans of obese adults
Arch. endocrinol. metab. (Online)
;
64(1): 24-29, Jan.-Feb. 2020. tab, graf
Artículo
en Inglés
| LILACS
| ID: biblio-1088778
ABSTRACT
ABSTRACT Objective 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. Subjects and methods 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. Results 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. Conclusion 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.
Texto completo:
Disponible
Índice:
LILACS (Américas)
Asunto principal:
Composición Corporal
/
Grasa Intraabdominal
/
Grasa Subcutánea
/
Obesidad
Límite:
Adulto
/
Femenino
/
Humanos
/
Masculino
Idioma:
Inglés
Revista:
Arch. endocrinol. metab. (Online)
Asunto de la revista:
Endocrinologia
/
Metabolismo
Año:
2020
Tipo del documento:
Artículo
País de afiliación:
Brasil
Institución/País de afiliación:
Universidade Federal do Rio Grande do Norte/BR
/
Universidade Federal do Rio Grande do Sul/BR
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