Longitudinal Evaluation of Mobile 3D Body Scanning for Body Composition Assessment During Pharmaceutical Weight Loss Therapy - 26.29
Title:
Longitudinal Evaluation of Mobile 3D Body Scanning for Body Composition Assessment During Pharmaceutical Weight Loss Therapy
Authors:
Matthew S. GILMER 1, Sofia RAMIREZ 2, Steven HEYMSFIELD 2, Steven C. HAUSER 1, David BRUNER 1
1 Size Stream, Cary NC, USA;
2 Pennington Biomedical Research Center, Louisiana State Univ., Baton Rouge LA, USA
Keywords:
mobile body scanning, GLP-1, longitudinal body composition, DXA validation, sarcopenia risk
Abstract:
Longitudinal assessment of body composition is of growing importance in the setting of GLP-1-mediated weight loss, where changes in total body weight may not adequately reflect the balance of fat and lean mass change. Dual-energy X-ray absorptiometry (DXA) is a well-established reference method, but its cost and limited accessibility constrain routine longitudinal use. Mobile 3D body scanning based on standardized front and side images may provide a practical and scalable alternative for repeated body composition monitoring. This study is an ongoing evaluation of the Size Stream body composition models against Hologic Horizon A DXA in a longitudinal study of 20 adult female subjects (all self- identified Black or African American) undergoing a 5-month course of Tirzepatide (weekly dose escalated by 2.5 mg each month, from 2.5 mg per week in month 1 to 12.5 mg per week in month 5) at the Pennington Biomedical Research Center. Each subject was scanned with DXA during at least two of three visits (S1, V3, V6), spaced approximately 75 days between apart. For each DXA scan, 1-2 corresponding scans were acquired in a booth with a mounted iPad running the Size Stream application MS1. Five body-composition metrics were evaluated (body-fat percentage (BFP), visceral adipose tissue (VAT), bone mineral content (BMC), and lean mass of the arms (LMA) and legs (LML)). Baseline cross-sectional agreement and longitudinal change agreement were quantified by bias, mean absolute error (MAE), root mean square error (RMSE), and sign-agreement rate.
Full paper:
Note:
This paper is currently under review for publication in the 3DBDOY.TECH Journal - Vol. 3, Dec. 2026.
It will be updated also in this page once the review process is concluded.
Presentation:
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How to Cite (MLA):
Gilmer, Matthew S. et al., "Longitudinal Evaluation of Mobile 3D Body Scanning for Body Composition Assessment During Pharmaceutical Weight Loss Therapy", Proceedings of 3DBODY.TECH 2026 - 17th International Conference and Expo on 3D/4D Body Technologies, Lugano, Switzerland, 20-21 Oct. 2026, #29, https://doi.org/10.15221/26.29
Details:
Proceedings: 3DBODY.TECH 2026, 20-21 Oct. 2026, Lugano, Switzerland
Paper/Presentation: #29
DOI: https://doi.org/10.15221/26.29
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