title: Automated separation of visceral and subcutaneous adiposity in in vivo microcomputed tomographies of mice.
abstract: Reflecting its high resolution and contrast capabilities, microcomputed tomography (microCT) 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 microCT 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.
authors.affiliation: Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794-2580, USA.
authors.forename: Svetlana
authors.initials: S
authors.lastname: Lublinsky
authors.forename: Yen K
authors.initials: YK
authors.lastname: Luu
authors.forename: Clinton T
authors.initials: CT
authors.lastname: Rubin
authors.forename: Stefan
authors.initials: S
authors.lastname: Judex