Automated Quantification of Muscle and Fat in the Thigh from Water-, Fat- and Non-suppressed MR Images

Abstract

Purpose-To introduce and validate an unsupervised muscle and fat quantification algorithm based on joint analysis of water-suppressed (WS), fat-suppressed (FS) and water-and-fat (nonsuppressed) volumetric MR images of the mid-thigh region. Materials and Methods-We first segment the subcutaneous fat by use of a parametric deformable model, and then apply centroid clustering in the feature domain defined by the voxel intensities in water-and fat-suppressed images to identify the inter-muscular fat and muscle. In the final step we compute volumetric and area measures of fat and muscle. We applied this algorithm on datasets of water-, fat-and non-suppressed volumetric MR images acquired from 28 participants. Results-We validated our tissue composition analysis against fat and muscle area measurements obtained from semi-manual analysis of single-slice mid-thigh CT images of the same participants and found very good agreement between the two methods. Furthermore, we compared the proposed approach with a variant that uses non-suppressed images only and observed that joint analysis of water-and fat-suppressed images is more accurate than the nonsuppressed only variant. Conclusion-Our MRI algorithm produces accurate tissue quantification, is less labor intensive and more reproducible than the original CT-based workflow and can address inter-participant anatomic variability and intensity inhomogeneity effects.

Quantitative CT imaging for adipose tissue analysis in mouse model of obesity

“…These imaging modalities differ in term of cost, reproducibility, accuracy and acquisition time. Both MRI and CT, have been used in 2D [2][3][4][5][6] and in 3D [7][8][9][10][11][12] in human. Better assessment of adipose tissue distribution is provided using a 3D region of interest than using a single slice [6].…”