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Updated: Aug 6, 2026
Segmentation and Measurement of Fat Volumes in Murine Obesity Models Using X-ray Computed Tomography
Published on: April 4, 2012
Agreement Between A 2-Dimensional Digital Image-Based 3-Compartment Body Composition Model and Dual Energy X-Ray
Katherine Sullivan1, Casey J Metoyer1, Bjoern Hornikel1
1Department of Kinesiology, The University of Alabama, Tuscaloosa, Alabama, USA.
Abstract:
The purpose of this study was to compare relative adiposity (%Fat) derived from a 2-dimensional image-based 3-component (3C) model (%Fat3C-IMAGE) and dual-energy X-ray absorptiometry (DXA) (%FatDXA) against a 5-component (5C) laboratory criterion (%Fat5C). 57 participants were included (63.2% male, 84.2% White/Caucasian, 22.5±4.7 yrs., 23.9±2.8 kg/m2). For each participant, body mass and standing height were measured to the nearest 0.1 kg and 0.1 cm, respectively. A digital image of each participant was taken using a 9.7 inch, 16g iPad Air 2 and analyzed using a commercially available application (version 1.1.2, made Health and Fitness, USA) for the estimation of body volume (BV) and inclusion in %Fat3C-IMAGE . %Fat3C-IMAGE and %Fat5C included measures of total body water derived from bioimpedance spectroscopy. The criterion %Fat5C included BV estimates derived from underwater weighing and bone mineral content measures via DXA. %FatDXA estimates were calculated from a whole-body DXA scan. A standardized mean effect size (ES) assessed the magnitude of differences between models with values of 0.2, 0.5, and 0.8 for small, moderate, and large differences, respectively. Data are presented as mean ± standard deviation. A strong correlation (r = 0.94, p <.001) and small mean difference (ES = 0.24, p <.001) was observed between %Fat3C-IMAGE (19.20±5.80) and %Fat5C (17.69±6.20) whereas a strong correlation (r = 0.87, p <.001) and moderate-large mean difference (ES = 0.70, p <.001) was observed between %FatDXA (22.01±6.81) and %Fat5C. Furthermore, %Fat3C-IMAGE (SEE = 2.20 %Fat, TE= 2.6) exhibited smaller SEE and TE than %FatDXA (SEE = 3.14 %Fat, TE = 5.5). The 3C image-based model performed slightly better in our sample of young adults than the DXA 3C model. Thus, the 2D image analysis program provides an accurate and non-invasive estimate of %Fat within a 3C model in young adults. Compared to DXA, the 3C image-based model allows for a more cost-effective and portable method of body composition assessment, potentially increasing accessibility to multi-component methods.
