586 - 3-D optical imaging captures changes in body composition during hospital refeeding in youth with eating disorders

Publication Number: 586.3661

Amanda E. Downey, University of California, San Francisco, School of Medicine, San Francisco, CA, United States; Sasha Gorrell, PhD, University of California, San Francisco, School of Medicine, San Francisco, CA, United States; Siena Vendlinski, University of South Florida, Tampa, FL, United States; Arjun S.. Mehta, UCSF Benioff Children's Hospital San Francisco, Berkeley, CA, United States; Nadia Bourdoud, MPH, University of California, San Francisco, San Francisco, CA, United States; Sara M. Buckelew, UCSF Benioff Children's Hospital San Francisco, Oakland, CA, United States; Sophia E. Ramirez, Pennington Biomedical Research Center, Baton, LA, United States; Jonathan P. Bennett, University of Hawaii Cancer Center, Honolulu, HI, United States; Steven B.. Heymsfield, Pennington Biomedical, Baton Rouge, LA, United States; John A. Shepherd, University of Hawaii, Honolulu, HI, United States; Andrea K. Garber, University of California, San Francisco, School of Medicine, San Francisco, CA, United States

Background: To assess malnutrition at every body size, new recommendations include body composition analysis. While dual energy X-ray absorptiometry is the preferred method, its use in hospital settings is limited by accessibility challenges and radiation exposure. We previously showed three-dimensional whole-body optical (3DO) surface scans accurately detect malnutrition without radiation.

Objective: In this pilot study, we examine changes in 3DO body composition in association with physiologic, functional, and metabolic biomarkers during short-term refeeding in anorexia nervosa (AN) and atypical AN.

Design/Methods: Hospitalized female patients with AN or atypical AN, age 12-24 years, underwent 3DO imaging with Styku X2 scanner (body composition), hand grip (strength) and resting energy expenditure (REE) testing on admission and discharge; weight and heart rate (HR) nadir were measured daily. Fat free mass index (FFMI) was calculated as FFM/height (kg/m2). Paired t-tests (Wilcoxon signed rank tests) assessed changes in fat mass (FM), FFMI, weight, HR, strength, and REE between admission and discharge; linear regression examined cross-sectional relations between admission FFMI and admission HR, as well as the relation between change in FFMI and change in HR over hospitalization, both adjusted for % of admission median BMI (mBMI). Change in HR from admission to discharge was log transformed to normalize the distribution for regression analysis.

Results: In 17 participants, mean (SD) age=16.5(2.5) yrs, weight=44.2(8.8) kg [81.3(11) %mBMI], HR=42.6(8.1) bpm, FM=10.7(4.4) kg, FFMI=12.8(1.1) kg/m2), FFMI z-score= -1.4(1), REE=1262(244) kcal, handgrip strength=50.4(10.9) kg. Increases from day 2.5(0.9) to 8.0(2.3) were: 2.5(.93) kg weight (p <.001), 1.6(0.8) kg fat mass (p <.001), 0.34(.3) FFMI (p=.002), 387(226) kcal REE (p <.001). Handgrip strength did not show improvements over short-term refeeding (p=.22). Lower admission HR approached association with lower admit FFMI [B=3.81 (-.24, 7.86), p=.06]; Greater change in FFMI predicted greater improvements in HR over hospitalization [B=-1.19 (.07, 2.3), p=.04].

Conclusion(s): 3DO captured low lean mass criteria for malnutrition at admission and detected significant changes in body composition over the course of short-term refeeding. Notably, FFMI emerged as a predictor of medical instability. FFMI is now recommended for diagnosing malnutrition; these findings suggest that it could inform medical restoration during hospital refeeding. Larger sample sizes are needed to validate these results.