In vivo quantification of subcutaneous and visceral adiposity by micro-computed tomography in a small animal model

Abstract

Accurate and precise techniques that identify the quantity and distribution of adipose tissue in vivo are critical for investigations of adipose development, obesity, or diabetes. Here, we tested whether in vivo micro-computed tomography (microCT) can be used to provide information on the distribution of total, subcutaneous and visceral fat volume in the mouse. Ninety C57BL/6J mice (weight range: 15.7-46.5 g) were microCT scanned in vivo at 5 months of age and subsequently sacrificed. Whole body fat volume (base of skull to distal tibia) derived from in vivo microCT was significantly (p<0.001) correlated with the ex vivo tissue weight of discrete perigonadal (R(2)=0.94), and subcutaneous (R(2)=0.91) fat pads. Restricting the analysis of tissue composition to the abdominal mid-section between L1 and L5 lumbar vertebrae did not alter the correlations between total adiposity and explanted fat pad weight. Segmentation allowed for the precise discrimination between visceral and subcutaneous fat as well as the quantification of adipose tissue within specific anatomical regions. Both the correlations between visceral fat pad weight and microCT determined visceral fat volume (R(2)=0.95, p<0.001) as well as subcutaneous fat pad weight and microCT determined subcutaneous fat volume (R(2)=0.91, p<0.001) were excellent. Data from these studies establish in vivo microCT as a non-invasive, quantitative tool that can provide an in vivo surrogate measure of total, visceral, and subcutaneous adiposity during longitudinal studies. Compared to current imaging techniques with similar capabilities, such as microMRI or the combination of DEXA with NMR, it may also be more cost-effective and offer higher spatial resolutions.

Figure 1

MicroCT scout view of a mouse (top). The abdominal region of interest between the proximal end of L1 and the distal end of the L5 vertebrae is highlighted. Cross-sectional view though the proximal and distal landmarks that were used to identify the abdominal region of interest (bottom). Red arrows indicate the muscle layer that separates visceral from subcutaneous fat.

Figure 2

Selection of threshold values for each tissue type to separate fat and bone from other tissues. (a). Representative regions of interest (ROI) of known composition were selected. Histograms of the gray-level intensities (x-axis) within these representative ROIs were generated. The top histogram presents a histogram for a ROI in which only one tissue type (fat) was present. The relatively homogenous fat tissue is represented by a narrow distribution of gray level intensities (densities), allowing the selection of an upper and lower thresholds (Th1 and Th2) specific for fat. For the histogram below, an ROI was selected in which two tissue types - fat and lean tissue (muscles and/or internal viscera) – were present, causing a bimodal intensity distribution. The bottom histogram shows a trimodal distribution of density values from a ROI with two tissue types and background. (b). A reconstructed image from the mid-torso areas was utilized in the selection of the ROI with known tissue types (top). The enlarged image (bottom) provides an example for a ROI which yields a bimodal distribution.

Figure 3

(a) Reconstructed microCT scan of a mouse in which the skeleton can be readily identified to define the region of interest. (b). The majority of the adipose tissue in the mouse is localized in the abdominal region, as the thoracic cavity and legs show lower prevalence of low density (fat) tissue. (c). To quantify fat volume in these different body compartments, tissues of different density were segregated and categorized as either fat (yellow) lean mass (red) or bone (white). (d). Representative images from three different animals with either low, intermediate, or high adiposity. Subcutaneous fat is shown in gray, visceral fat in red.

Figure 4

(a) Total fat volume (from the base of the skull to the distal tibia) determined by in vivo microCT was highly correlated with both the visceral and subcutaneous tissue weight of the fat pads harvested at sacrifice (n=90). (b). A scan of the abdominal region reduced the scan time by two-thirds. Despite the much smaller region, fat volume of the abdomen (spanning between L1 and L5 vertebrae) was highly correlated with total fat volume of the entire mouse body (n=45).

Figure 5

Evaluation of abdominal adiposity separating visceral adipose tissue (VAT) from subcutaneous adipose tissue (SAT). For these analyses, data from 45 animals were randomly selected from the entire population. (a). Visceral adipose tissue volume was highly correlated with the weight of the visceral (perigonadal) fat pad (p<0.001). (b). Subcutaneous adipose tissue volume was highly correlated with the weight of the subcutaneous (from the lower back) fat pad (p<0.001). (c). As the microCT calculated volumes for both fat deposits correlated well with the weights of the respective fat pads, VAT and SAT area were also correlated to each other (p<0.001).