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Validation of a fast method for quantification of intra‐abdominal and subcutaneous adipose tissue for large‐scale human studies
Author(s) -
Borga Magnus,
Thomas E Louise,
Romu Thobias,
Rosander Johannes,
Fitzpatrick Julie,
Dahlqvist Leinhard Olof,
Bell Jimmy D.
Publication year - 2015
Publication title -
nmr in biomedicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.278
H-Index - 114
eISSN - 1099-1492
pISSN - 0952-3480
DOI - 10.1002/nbm.3432
Subject(s) - adipose tissue , abdominal fat , coefficient of variation , correlation coefficient , nuclear medicine , medicine , subcutaneous adipose tissue , abdomen , urology , biomedical engineering , chemistry , radiology , body weight , mathematics , chromatography , statistics
Central obesity is the hallmark of a number of non‐inheritable disorders. The advent of imaging techniques such as MRI has allowed for a fast and accurate assessment of body fat content and distribution. However, image analysis continues to be one of the major obstacles to the use of MRI in large‐scale studies. In this study we assess the validity of the recently proposed fat–muscle quantitation system (AMRA TM Profiler) for the quantification of intra‐abdominal adipose tissue (IAAT) and abdominal subcutaneous adipose tissue (ASAT) from abdominal MR images. Abdominal MR images were acquired from 23 volunteers with a broad range of BMIs and analysed using sliceOmatic, the current gold‐standard, and the AMRA TM Profiler based on a non‐rigid image registration of a library of segmented atlases. The results show that there was a highly significant correlation between the fat volumes generated by the two analysis methods, (Pearson correlation r = 0.97, p < 0.001), with the AMRA TM Profiler analysis being significantly faster (~3 min) than the conventional sliceOmatic approach (~40 min). There was also excellent agreement between the methods for the quantification of IAAT (AMRA 4.73 ± 1.99 versus sliceOmatic 4.73 ± 1.75 l, p = 0.97). For the AMRA TM Profiler analysis, the intra‐observer coefficient of variation was 1.6% for IAAT and 1.1% for ASAT, the inter‐observer coefficient of variation was 1.4% for IAAT and 1.2% for ASAT, the intra‐observer correlation was 0.998 for IAAT and 0.999 for ASAT, and the inter‐observer correlation was 0.999 for both IAAT and ASAT. These results indicate that precise and accurate measures of body fat content and distribution can be obtained in a fast and reliable form by the AMRA TM Profiler, opening up the possibility of large‐scale human phenotypic studies. Copyright © 2015 John Wiley & Sons, Ltd.