Segmentation and Evaluation of Adipose Tissue from Whole Body MRI Scans

Accurate quantification of total body and the distribution of regional adipose tissue using manual segmentation is a challenging problem due to the high variation between manual delineations. Manual segmentation also requires highly trained experts with knowledge of anatomy. We present a hybrid segmentation method that provides robust delineation results for adipose tissue from whole body MRI scans. A formal evaluation of accuracy of the segmentation method is performed. This semi-automatic segmentation algorithm reduces significantly the time required for quantification of adipose tissue, and the accuracy measurements show that the results are close to the ground truth obtained from manual segmentations

Organ-tissue mass measurement allows modeling of REE and metabolically active tissue mass.

Investigators have expressed interest in the associations between resting energy expenditure (REE) and body mass for over a century. Traditionally, descriptive models using regression analysis are applied, linking REE with metabolically active compartments such as body cell mass (BCM) and fat-free body mass (FFM). Recently developed whole body magnetic resonance imaging (MRI) and echocardiography methods now allow estimation of all major organs and tissue volumes in vivo. Because measured values are available for REE, BCM, and FFM content of individual organs and tissues, it should now be possible to develop energy expenditure-body composition estimation models based on MRI-measured organ-tissue volumes. Specifically, the present investigation tested the hypothesis that in vivo estimation of whole body REE, BCM, and FFM is possible using MRI- and echocardiography-derived organ volumes combined with previously reported organ-tissue metabolic rates and chemical composition. Thirteen subjects (5 females, 8 males) had REE, BCM, and FFM measured by indirect calorimetry, whole body40K counting, and dual-energy X-ray absorptiometry, respectively. Models developed from estimated and measured variables were highly correlated, with no significant differences between those estimated and measured [e.g., calculated vs. measured REE: r = 0.92, P &lt; 0.001; (mean ± SD) 6,962 ± 1,455 and 7,045 ± 1,450 kJ/day, respectively ( P = not significant)]. Strong associations were observed between REE, individual or combined organ weights, BCM, and FFM that provide new insights into earlier observed metabolic phenomona. The present approach, the first to establish an energy expenditure-body composition link with a mechanistic model in vivo, has the potential to greatly expand our knowledge of energy expenditure-body size relationships in humans.</jats:p