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Metabolism. 2013 Nov;62(11):1686-95. doi: 10.1016/j.metabol.2013.06.009. Epub 2013 Jul 25.

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

Author information

1
Advanced Magnetic Resonance Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104.

Abstract

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.

KEYWORDS:

AT; Adipose tissue; Adiposity; Body fat distribution analysis; DXA; Diet-induced obesity; Dual-energy X-ray absorptiometry; Fat-weighted MRI; MRI; Magnetic resonance imaging; ROI; Region of interest; T; Tesla

PMID:
23890668
PMCID:
PMC3809152
DOI:
10.1016/j.metabol.2013.06.009
[Indexed for MEDLINE]
Free PMC Article

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