Literature DB >> 24703481

Abdominal adipose tissue distribution on MRI and diabetes.

Michalis Mantatzis1, Thanos Milousis2, Simoni Katergari2, Andreas Delistamatis3, Dimitrios N Papachristou4, Panos Prassopoulos3.   

Abstract

RATIONALE AND
OBJECTIVES: To introduce a simple magnetic resonance imaging (MRI) protocol for quantitative assessment of intraperitoneal, retroperitoneal, and subcutaneous adipose tissue (AT) and to compare AT distribution between diabetic and nondiabetic individuals.
MATERIALS AND METHODS: Thirty-eight consecutive male diabetic patients (group A) and 38 males (who matched for body mass index [BMI]) without metabolic syndrome (group B) underwent abdominal MRI with a three-dimensional spoiled gradient echo T1-weighted sequence. The amounts of intraperitoneal, retroperitoneal, and subcutaneous AT were calculated on a workstation, after manual anatomic segmentation and were correlated with 10 anthropometric measurements. Pearson product-moment correlation coefficients were used for correlation of AT volumes with anthropometric measurements, Wilcoxon test to compare AT measurements between automatic and manual technique used, and unpaired t test to compare volumes of AT compartments between group A and B.
RESULTS: Diabetic patients exhibited larger amount of intraperitoneal and retroperitoneal AT than normal individuals at all levels (t = 2.02,P < .05). Among anthropometric measurements, the waist circumference, BMI, and body fat percentage exhibited the best correlations with intraperitoneal and retroperitoneal AT (group A (r) = 0.88/0.78/0.0.69 and group B (r) = 0.91/0.87/0.81). The L2-L5 set of images was found to be the most representative of the amount of AT volumes.
CONCLUSIONS: Amount and distribution of AT can be accurately and easily assessed on MRI. Quantification of intraabdominal AT may promote the role of imaging in the study of metabolic syndrome.
Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Adipose tissue; MRI; diabetes; metobolic syndrome; segmentation, body fat measurements

Mesh:

Year:  2014        PMID: 24703481     DOI: 10.1016/j.acra.2014.01.009

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


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