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Accurate segmentation of subcutaneous and intermuscular adipose tissue from MR images of the thigh
Authors:Vincenzo Positano MSc  Tore Christiansen MSc  Maria Filomena Santarelli PhD  Steffen Ringgaard MD  Luigi Landini PhD  Amalia Gastaldelli PhD
Affiliation:1. MRI Laboratory, “G. Monasterio” Foundation and Institute of Clinical Physiology, Pisa, Italy;2. Department of Medicine and Endocrinology C, Aarhus University Hospital, Aarhus, Denmark;3. MR Research Center, Aarhus University Hospital, Aarhus, Denmark;4. Department of Information Engineering, University of Pisa, Pisa, Italy
Abstract:

Purpose

To describe and evaluate a computer‐assisted method for assessing the quantity and distribution of adipose tissue in thigh by magnetic resonance imaging (MRI).

Materials and Methods

Twenty obese subjects were imaged on a Philips Achieva 1.5T scanner by a fast spin‐echo (FSE) sequence. A total of 636 images were acquired and analyzed by custom‐made software. Thigh subcutaneous adipose tissue (SAT) and bone were identified by fuzzy clustering segmentation and an active contour algorithm. Muscle and intermuscular adipose tissue (IMAT) were assessed by identifying the two peaks of the signal histogram with an expectation maximization algorithm. The whole analysis was performed in an unsupervised manner without the need of any user interaction.

Results

The coefficient of variation (CV) was evaluated between the unsupervised algorithm and manual analysis performed by an expert operator. The CV was low for all measurements (SAT <2%, muscle <1%, IMAT <5%). Limited manual correction of unsupervised segmentation results (less than 10% of contours modified) allowed us to further reduce the CV (SAT <0.5%, muscle <0.5%, IMAT <2%).

Conclusion

The proposed approach allowed effective computer‐assisted analysis of thigh MR images, dramatically reducing the user work compared to manual analysis. It allowed routine assessment of IMAT, a fat‐depot linked with metabolic abnormalities, important in monitoring the effect of nutrition and exercise. J. Magn. Reson. Imaging 2009;29:677–684. © 2009 Wiley‐Liss, Inc.
Keywords:IMAT  SAT  fuzzy clustering  adipose tissue  fat  MRI
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