Automated Separation of Visceral and Subcutaneous Adiposity in In Vivo Microcomputed Tomographies of Mice

Abstract

Reflecting its high resolution and contrast capabilities, microcomputed tomography (μCT) can provide an in vivo assessment of adiposity with excellent spatial specificity in the mouse. Herein, an automated algorithm that separates the total abdominal adiposity into visceral and subcutaneous compartments is detailed. This algorithm relies on Canny edge detection and mathematical morphological operations to automate the manual contouring process that is otherwise required to spatially delineate the different adipose deposits. The algorithm was tested and verified with μCT scans from 74 C57BL/ 6J mice that had a broad range of body weights and adiposity. Despite the heterogeneity within this sample of mice, the algorithm demonstrated a high degree of stability and robustness that did not necessitate changing of any of the initially set input variables. Comparisons of data between the automated and manual methods were in complete agreement (R 2 =0.99). Compared to manual contouring, the increase in precision and accuracy, while decreasing processing time by at least an order of magnitude, suggests that this algorithm can be used effectively to separately assess the development of total, visceral, and subcutaneous adiposity. As an application of this method, preliminary data from adult mice suggest that a relative increase in either subcutaneous, visceral, or total fat negatively influences skeletal quantity and that fat infiltration in the liver is greatly increased by a high-fat diet.

Restriction on an Energy-Dense Diet Improves Markers of Metabolic Health and Cellular Aging in Mice Through Decreasing Hepatic mTOR Activity

“…Three mice per group were anesthetized with ketamine/xylazine, and the abdominal region between the first and the fifth lumbar vertebra was scanned using a conebeam in vivo micro-CT system (vivaCT 40 Scanner, Scanco Inc., Bruettisellen, Switzerland). The scan was performed using the following parameters: Energy settings of the X-ray source 45 24 which uses canny edge detection and mathematical morphological operations (http://bme.sunysb.edu/ labs/sjudex/miscellaneous.html). Adaptations included an additional dilation sequence of 3 voxels prior to component labeling to remove the background of the body image and the increase of the close distance in generating the mask for the visceral fat from 26 to 30.…”

A Correlative Method for Imaging Identical Regions of Samples by Micro-CT, Light Microscopy, and Electron Microscopy

“…been made (Lublinsky et al 2009). These algorithms are based on edge detection and mathematical operations that identify the body surface, perform a preliminary separation between visceral adipose tissue and subcutaneous adipose tissue, and then, after automatic correction, achieve an accurate separation between adipose deposits, eliminating the need for manually drawing contour lines (Hildebrandt et al 2002;Judex et al 2010;Marchadiera et al 2011).…”

Adipose Measurement Using Micro MRI

“…Recently imaging technologies have emerged as powerful tools for refined adipose assessment (Zhao et al, 2006;Luu et al, 2009). Imaging can provide not only the size of an adipose depot, but also its location.…”

“…It has the merits of high resolution and low cost. It has been developed in both humans (Zhao et al, 2006;Ohshima et al, 2008) and animals (Luu et al, 2009;Lublinsky et al, 2009). Compared to CT, Magnetic Resonance Imaging (MRI) (Gray, 1991;Gronemeyer, 2000) has advantageous in adipose research.…”

“…For this purpose, mice were placed prone in a semi cylindrical holder. In previous research (Luu et al, 2009), the abdominal region has been defined from L1 to L5 of the spine in the CT images. Because in the MRI, bone hypointense is not as easily differentiated as it is in the CT, we define the abdominal region in micro MRI using the kidneys as a reference.…”