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Quantification of human body fat tissue percentage by MRI
Author(s) -
Müller HansPeter,
Raudies Florian,
Unrath Alexander,
Neumann Heiko,
Ludolph Albert C.,
Kassubek Jan
Publication year - 2011
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.1549
Subject(s) - adipose tissue , subcutaneous adipose tissue , segmentation , computer science , volume rendering , lean tissue , merge (version control) , region of interest , body fat distribution , biomedical engineering , algorithm , artificial intelligence , medicine , rendering (computer graphics) , information retrieval , endocrinology
The MRI‐based evaluation of the quantity and regional distribution of adipose tissue is one objective measure in the investigation of obesity. The aim of this article was to report a comprehensive and automatic analytical method for the determination of the volumes of subcutaneous fat tissue (SFT) and visceral fat tissue (VFT) in either the whole human body or selected slices or regions of interest. Using an MRI protocol in an examination position that was convenient for volunteers and patients with severe diseases, 22 healthy subjects were examined. The software platform was able to merge MRI scans of several body regions acquired in separate acquisitions. Through a cascade of image processing steps, SFT and VFT volumes were calculated. Whole‐body SFT and VFT distributions, as well as fat distributions of defined body slices, were analysed in detail. Complete three‐dimensional datasets were analysed in a reproducible manner with as few operator‐dependent interventions as possible. In order to determine the SFT volume, the ARTIS (Adapted Rendering for Tissue Intensity Segmentation) algorithm was introduced. The advantage of the ARTIS algorithm was the delineation of SFT volumes in regions in which standard region grow techniques fail. Using the ARTIS algorithm, an automatic SFT volume detection was feasible. MRI data analysis was able to determine SFT and VFT volume percentages using new analytical strategies. With the techniques described, it was possible to detect changes in SFT and VFT percentages of the whole body and selected regions. The techniques presented in this study are likely to be of use in obesity‐related investigations, as well as in the examination of longitudinal changes in weight during various medical conditions. Copyright © 2010 John Wiley & Sons, Ltd.