Ultrasonography as a method of characterizing abdominal fat tissue

Authors

  • Ricardo Teresa Ribeiro Unidade de Ensino e Investigação em Fisiologia, Imagem Médica e Terapia, Escola Superior de Tecnologia da Saúde de Lisboa, Instituto Politécnico de Lisboa. Lisboa, Portugal. H&TRC – Centro de Investigação em Saúde e Tecnologia. ESTeSL – Escola Superior de Tecnologia da Saúde, Instituto Politécnico de Lisboa. Lisboa, Portugal.
  • Daniel Leitão Cuf Infante Santo Hospital. Lisboa, Portugal.
  • Luís Dinis Hospital do SAMS. Lisboa, Portugal.
  • Aida Ferreira Unidade de Ensino e Investigação em Fisiologia, Imagem Médica e Terapia, Escola Superior de Tecnologia da Saúde de Lisboa, Instituto Politécnico de Lisboa. Lisboa, Portugal. H&TRC – Centro de Investigação em Saúde e Tecnologia. ESTeSL – Escola Superior de Tecnologia da Saúde, Instituto Politécnico de Lisboa. Lisboa, Portugal. Universidade Lusófona de Humanidades e Tecnologias. Lisboa, Portugal.

DOI:

https://doi.org/10.25758/set.2213

Keywords:

Ultrasonography, Obesity, Body Mass Index, Subcutaneous adipose tissue

Abstract

Aim of the study – To compare the thickness of subcutaneous, preperitoneal, and visceral adipose tissue measured by ultrasonography (US) and relate them to the value of Body Mass Index (BMI). Methods – Weight, height, and the abdominal perimeter were determined in 218 volunteers (177 females and 41 males, aged between 18 and 33 years, with a body mass index between 20.03 and 37.27kg/m2), later submitted to abdominal ultrasonography. Further, four lifestyle questions were answered by the volunteers. Results – The US allowed to quantify and classify objectively and reproducibly subcutaneous adipose tissue, preperitoneal and visceral, for p<0.01. Pearson's correlation (p<0.01) did not show inter-observer variability in US measurements of subcutaneous adipose tissue (r=0.9871), preperitoneal (r=0.9003), and visceral (r=0.9407). A strong linear correlation between BMI with subcutaneous adipose tissue (r=0.64) and with preperitoneal (r=0.56) was identified. It was verified that the US could classify the genus based on the thickness of the intra-abdominal adipose tissue, abdominal perimeter, and BMI with a total accuracy of 86.69%. Conclusions – US shows an objective and capable method in the characterization and differentiation of intra-abdominal adipose tissue. The combined use of biometrics (except weight and height) and US data allows a correct estimation of BMI. Future studies are needed to understand the usefulness of the Deep Learning frameworks in automatically detecting different types of abdominal adipose tissue, thus guaranteeing the possibility of the US becoming a quick and preventive method for assessing obesity.

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Published

2022-07-28

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Section

Artigos

How to Cite

Ultrasonography as a method of characterizing abdominal fat tissue. (2022). Saúde & Tecnologia, 22, 13-21. https://doi.org/10.25758/set.2213