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Updated: Nov 11, 2025

Author Spotlight: Advancements in 3D Optical Imaging for Comprehensive Body Composition Assessment in Modern Research
Published on: June 7, 2024
Validity of a 3-compartment body composition model using body volume derived from a novel 2-dimensional image
Katherine Sullivan1, Bjoern Hornikel1, Clifton J Holmes1,2
1Exercise Physiology Laboratory, Department of Kinesiology, The University of Alabama, Tuscaloosa, AL, USA.
Background/Objectives:
The purpose of this study was: (1) to compare body volume (BV) estimated from a 2-dimensional (2D) image analysis program (BVIMAGE), and a dual-energy x-ray absorptiometry (DXA) equation (BVDXA-Smith-Ryan) to an underwater weighing (UWW) criterion (BVUWW); (2) to compare relative adiposity (%Fat) derived from a 3-compartment (3C) model using BVIMAGE (%Fat3C-IMAGE), and a 4-compartment (4C) model using BVDXA-Smith-Ryan (%Fat4C-DXA-Smith-Ryan) to a 4C criterion model using BVUWW (%Fat4C-UWW).
Subject/Methods:
Forty-eight participants were included (60% male, 22.9 ± 5.0 years, 24.2 ± 2.6 kg/m2). BVIMAGE was derived using a single digital image of each participant taken from the rear/posterior view. DXA-derived BV was calculated according to Smith-Ryan et al. Bioimpedance spectroscopy and DXA were used to measure total body water and bone mineral content, respectively, in the 3C and 4C models. 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.
Results:
Near-perfect correlation (r = 0.998, p < 0.001) and no mean differences (p = 0.267) were observed between BVIMAGE (69.6 ± 11.5 L) and BVUWW (69.5 ± 11.4 L). No mean differences were observed between %Fat4C-DXA-Smith-Ryan and the %Fat4C-UWW criterion (p = 0.988). Small mean differences were observed between %Fat3C-IMAGE and %Fat4C-UWW (ES = 0.2, p < 0.001). %Fat3C-IMAGE exhibited smaller SEE and TE, and tighter limits of agreement than %Fat4C-DXA-Smith-Ryan.
Conclusions:
The 2D image analysis program provided an accurate and non-invasive estimate of BV, and subsequently %Fat within a 3C model in generally healthy, young adults.
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