3-Dimensional Optical Scanning to Assess and Monitor Malnutrition in Eating Disorders (3D-ED) Study

Overview

People with anorexia nervosa often become medically unstable because of severe malnutrition and require hospitalization for nutritional rehabilitation. Clinicians currently rely heavily on body weight to assess malnutrition, but body weight does not always reflect the severity of illness. This study will use infrared scanning to assess body composition in adolescents and young adults hospitalized with anorexia nervosa. Researchers will then examine how organ and tissue stores relate to the degree of malnutrition, predict nutritional needs and medical restoration in hospital, and recovery outcomes over the following year. The goal is to develop more individualized approaches to nutritional rehabilitation and improve recovery for individuals with malnutrition due to eating disorders.

Background: The proposed project is aligned with NIH's Strategic Plan for Nutrition Research (SPNR) Objectives 4-2 and 4-3, to reduce the burden of malnutrition in clinical settings. Up to 40% of patients with anorexia nervosa (AN) become medically unstable due to malnutrition and require hospitalization for refeeding; 25% progress to severe and enduring illness. Long, intensive hospitalizations with frequent readmissions drive high healthcare costs in AN. Historically, clinicians have relied on body weight to assess malnutrition and response to intervention. However, body weight lost diagnostic power due to rising BMIs. About one third of patients today are diagnosed with atypical AN (AAN), with medical instability at "normal" weight. The upward shift in BMI is reflected globally, leading new recommendations to include body composition to diagnose malnutrition. Emphasis is on low fat free mass (FFM) as a predictor of poor hospital outcomes. However, this has not been examined in hospitalized patients with AN, who are often too medically unstable to transport for research scans. This gap can now be filled with whole-body, infrared, 3-dimensional optical imaging (3DO) at the bedside. Prior work by the investigators showed excellent concordance between 3DO and dual X-ray absorptiometry (DXA) for detecting malnutrition at low BMI and captured changes in FFM with bedside 3DO during refeeding. Proposed project: The investigators will employ a functional approach to body composition, integrating compartment mass with physiologic function, to assess malnutrition and predict short-term and long-term refeeding outcomes across the malnutrition continuum. Prior research on FFM has focused on the skeletal muscle and bone components and long-term risks in AN. In contrast, organ residual mass (ORM), which comprises 43% of FFM, has received little attention despite its central role in refeeding. Profound ORM depletion in AN (loss of 43% cardiac, 22% renal, and 39% hepatic mass) contributes to organ dysfunction, hypometabolism, and refeeding complications. The investigators will generate ORM reference values from large, representative datasets, calculate ORM index z-scores (ORMIz), and examine their correlation with malnutrition at baseline, in response to short-term refeeding intensity, and as a predictor of long-term outcomes in patients across the continuum of malnutrition due to AN. Purpose, hypotheses and design: This multicenter, prospective, observational study will include N=90 hospitalized 15 to 26 year olds with medical instability and malnutrition due to AAN, AN, or extreme AN. Aim 1) Assess clinical utility of ORMIz at admission. Lower baseline ORMIz will: H1) correlate with malnutrition markers, H2) correlate with pre-admission energy imbalance, and H3-Primary) predict refeeding intensity. Aim 2) Monitor response to refeeding in hospital. Change in ORM will correlate with: H1) medical stability, H2) metabolic stability, and H3) lower baseline FM. Aim 3) Predict long-term outcomes. Lower discharge ORMIz will predict poor outcomes at 3, 6, 9, and 12 months. Findings will be rapidly translated into individualized refeeding approaches.