Comparison of Gross Body Fat-Water Magnetic Resonance Imaging at 3 Tesla to Dual-Energy X-Ray Absorptiometry in Obese Women

Calibration of a semi-automated segmenting method for quantification of adipose tissue compartments from magnetic resonance images of mice

OBJECTIVE

To use an automated water-suppressed magnetic resonance imaging (MRI) method to objectively assess adipose tissue (AT) volumes in whole body and specific regional body components (subcutaneous, thoracic and peritoneal) of obese and lean mice.

MATERIALS/METHODS

Water-suppressed MR images were obtained on a 7T, horizontal-bore MRI system in whole bodies (excluding head) of 26 week old male C57BL6J mice fed a control (10% kcal fat) or high-fat diet (60% kcal fat) for 20 weeks. Manual (outlined regions) versus automated (Gaussian fitting applied to threshold-weighted images) segmentation procedures were compared for whole body AT and regional AT volumes (i.e., subcutaneous, thoracic, and peritoneal). The AT automated segmentation method was compared to dual-energy X-ray (DXA) analysis.

RESULTS

The average AT volumes for whole body and individual compartments correlated well between the manual outlining and the automated methods (R2>0.77, p<0.05). Subcutaneous, peritoneal, and total body AT volumes were increased 2-3 fold and thoracic AT volume increased more than 5-fold in diet-induced obese mice versus controls (p<0.05). MRI and DXA-based method comparisons were highly correlative (R2=0.94, p<0.0001).

CONCLUSIONS

Automated AT segmentation of water-suppressed MRI data using a global Gaussian filtering algorithm resulted in a fairly accurate assessment of total and regional AT volumes in a pre-clinical mouse model of obesity.

Whole body fat: content and distribution

Obesity and its co-morbidities, including type II diabetes, insulin resistance and cardiovascular diseases, have become one of the biggest health issues of present times. The impact of obesity goes well beyond the individual and is so far-reaching that, if it continues unabated, it will cause havoc with the economies of most countries. In order to be able to fully understand the relationship between increased adiposity (obesity) and its co-morbidity, it has been necessary to develop proper methodology to accurately and reproducibly determine both body fat content and distribution, including ectopic fat depots. Magnetic Resonance Imaging (MRI) and Spectroscopy (MRS) have recently emerged as the gold-standard for accomplishing this task. Here, we will review the use of different MRI techniques currently being used to determine body fat content and distribution. We also discuss the pros and cons of MRS to determine ectopic fat depots in liver, muscle, pancreas and heart and compare these to emerging MRI techniques currently being put forward to create ectopic fat maps. Finally, we will discuss how MRI/MRS techniques are helping in changing the perception of what is healthy and what is normal and desirable body-fat content and distribution.

Canine body composition quantification using 3 tesla fat-water MRI

PURPOSE

To test the hypothesis that a whole-body fat-water MRI (FWMRI) protocol acquired at 3 Tesla combined with semi-automated image analysis techniques enables precise volume and mass quantification of adipose, lean, and bone tissue depots that agree with static scale mass and scale mass changes in the context of a longitudinal study of large-breed dogs placed on an obesogenic high-fat, high-fructose diet.

MATERIALS AND METHODS

Six healthy adult male dogs were scanned twice, at weeks 0 (baseline) and 4, of the dietary regiment. FWMRI-derived volumes of adipose tissue (total, visceral, and subcutaneous), lean tissue, and cortical bone were quantified using a semi-automated approach. Volumes were converted to masses using published tissue densities.

RESULTS

FWMRI-derived total mass corresponds with scale mass with a concordance correlation coefficient of 0.931 (95% confidence interval = [0.813, 0.975]), and slope and intercept values of 1.12 and -2.23 kg, respectively. Visceral, subcutaneous and total adipose tissue masses increased significantly from weeks 0 to 4, while neither cortical bone nor lean tissue masses changed significantly. This is evidenced by a mean percent change of 70.2% for visceral, 67.0% for subcutaneous, and 67.1% for total adipose tissue.

CONCLUSION

FWMRI can precisely quantify and map body composition with respect to adipose, lean, and bone tissue depots. The described approach provides a valuable tool to examine the role of distinct tissue depots in an established animal model of human metabolic disease.