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Computed tomographic abdominal fat volume estimation – a handy tool to predict the risk of metabolic syndrome

PURPOSE: Abdominal obesity plays a significant role in the development of metabolic syndrome, with individual metabolic risk profiles for visceral and subcutaneous adipose tissues. This study aimed to calculate and correlate the subcutaneous, visceral, and total fat compartment volume in metabolic a...

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Autores principales: Navaneeth, G.C., Hiremath, Rudresh, Poojary, Shweta Raviraj, Kini, Divya Vishwanatha, Chittaragi, Kavitha B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Termedia Publishing House 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10493863/
https://www.ncbi.nlm.nih.gov/pubmed/37701173
http://dx.doi.org/10.5114/pjr.2023.131010
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author Navaneeth, G.C.
Hiremath, Rudresh
Poojary, Shweta Raviraj
Kini, Divya Vishwanatha
Chittaragi, Kavitha B.
author_facet Navaneeth, G.C.
Hiremath, Rudresh
Poojary, Shweta Raviraj
Kini, Divya Vishwanatha
Chittaragi, Kavitha B.
author_sort Navaneeth, G.C.
collection PubMed
description PURPOSE: Abdominal obesity plays a significant role in the development of metabolic syndrome, with individual metabolic risk profiles for visceral and subcutaneous adipose tissues. This study aimed to calculate and correlate the subcutaneous, visceral, and total fat compartment volume in metabolic and non-metabolic syndrome patients. MATERIAL AND METHODS: This was a cross-sectional study conducted on 112 patients categorized into Group A (with metabolic syndrome) and Group B (without metabolic syndrome). They were subjected to computed tomography (CT) study of the abdomen using a 128-slice MDCT scanner. Body mass index (BMI), visceral fat volume (VFV), subcutaneous fat volume (SFV), and total fat volume (TFV) were calculated and correlated with biochemical evidence of metabolic syndrome. RESULTS: The mean age of patients in Group A was 60.91 ± 12.23 years as compared to Group B, which was 50.12 ± 16.30 years. Overall, a male predominance was observed, i.e. 69 cases (61.6%). BMI was proven to be an inaccurate risk predictor. However, mean VFV, SFV, and TFV was statistically higher in patients with metabolic syndrome (p = 0.001), with visceral fat volume predicting a higher risk in females (p = 0.026). CONCLUSIONS: Abdominal CT is a commonly performed yet unexplored tool for the risk assessment of metabolic syndrome. Through the results obtained in this study, we have proven the need for calculating SFV, VFV, and TFV as predictors of metabolic syndrome in comparison to the conventional practice of BMI assessment. The radiologist can thus work with the clinician to effectively detect and treat this health condition.
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spelling pubmed-104938632023-09-12 Computed tomographic abdominal fat volume estimation – a handy tool to predict the risk of metabolic syndrome Navaneeth, G.C. Hiremath, Rudresh Poojary, Shweta Raviraj Kini, Divya Vishwanatha Chittaragi, Kavitha B. Pol J Radiol Original Paper PURPOSE: Abdominal obesity plays a significant role in the development of metabolic syndrome, with individual metabolic risk profiles for visceral and subcutaneous adipose tissues. This study aimed to calculate and correlate the subcutaneous, visceral, and total fat compartment volume in metabolic and non-metabolic syndrome patients. MATERIAL AND METHODS: This was a cross-sectional study conducted on 112 patients categorized into Group A (with metabolic syndrome) and Group B (without metabolic syndrome). They were subjected to computed tomography (CT) study of the abdomen using a 128-slice MDCT scanner. Body mass index (BMI), visceral fat volume (VFV), subcutaneous fat volume (SFV), and total fat volume (TFV) were calculated and correlated with biochemical evidence of metabolic syndrome. RESULTS: The mean age of patients in Group A was 60.91 ± 12.23 years as compared to Group B, which was 50.12 ± 16.30 years. Overall, a male predominance was observed, i.e. 69 cases (61.6%). BMI was proven to be an inaccurate risk predictor. However, mean VFV, SFV, and TFV was statistically higher in patients with metabolic syndrome (p = 0.001), with visceral fat volume predicting a higher risk in females (p = 0.026). CONCLUSIONS: Abdominal CT is a commonly performed yet unexplored tool for the risk assessment of metabolic syndrome. Through the results obtained in this study, we have proven the need for calculating SFV, VFV, and TFV as predictors of metabolic syndrome in comparison to the conventional practice of BMI assessment. The radiologist can thus work with the clinician to effectively detect and treat this health condition. Termedia Publishing House 2023-08-21 /pmc/articles/PMC10493863/ /pubmed/37701173 http://dx.doi.org/10.5114/pjr.2023.131010 Text en © Pol J Radiol 2023 https://creativecommons.org/licenses/by-nc-nd/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0). License (https://creativecommons.org/licenses/by-nc-nd/4.0/)
spellingShingle Original Paper
Navaneeth, G.C.
Hiremath, Rudresh
Poojary, Shweta Raviraj
Kini, Divya Vishwanatha
Chittaragi, Kavitha B.
Computed tomographic abdominal fat volume estimation – a handy tool to predict the risk of metabolic syndrome
title Computed tomographic abdominal fat volume estimation – a handy tool to predict the risk of metabolic syndrome
title_full Computed tomographic abdominal fat volume estimation – a handy tool to predict the risk of metabolic syndrome
title_fullStr Computed tomographic abdominal fat volume estimation – a handy tool to predict the risk of metabolic syndrome
title_full_unstemmed Computed tomographic abdominal fat volume estimation – a handy tool to predict the risk of metabolic syndrome
title_short Computed tomographic abdominal fat volume estimation – a handy tool to predict the risk of metabolic syndrome
title_sort computed tomographic abdominal fat volume estimation – a handy tool to predict the risk of metabolic syndrome
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10493863/
https://www.ncbi.nlm.nih.gov/pubmed/37701173
http://dx.doi.org/10.5114/pjr.2023.131010
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