Validation of a fast method for quantification of intra‐abdominal and subcutaneous adipose tissue for large‐scale human studies. (2nd November 2015)

• Record Type: Journal Article
• Authors: Borga, Magnus; Thomas, E Louise; Romu, Thobias; Rosander, Johannes; Fitzpatrick, Julie; Dahlqvist Leinhard, Olof; Bell, Jimmy D.
• Is Part Of: NMR in biomedicine. Volume 28:Number 12(2015:Dec.)
• Page Start: 1747
• Page End: 1753
• Publication Date: 2015-11-02
• Subjects: adipose tissue -- fat quantitation -- obesity -- MRI -- Dixon -- abdominal fat; Nuclear magnetic resonance -- Periodicals; Magnetic Resonance Spectroscopy -- Periodicals; 574
• DOI: 10.1002/nbm.3432
• Languages: English
• ISSNs: 0952-3480

Abstract

Abstract : 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. Abstract : In this study we tested the value of using the semi‐automated fat–muscle quantitation system AMRA TM Profiler in the analysis of MR images for population studies. The results show extremely high agreement with the current 'gold‐standard' method across a range of BMI, with the AMRA TM Profiler technique taking up to 10 times less time than its counterpart. The speed and robustness of this method makes it an ideal tool for small‐ and large‐scale human phenotypic studies.