Advancing 3D optical body surface scan technology to assess physiological and psychological effects in highly obese population

Project Summary Current techniques for measuring the physiological or psychological effects of obesity, and in particular bariatric surgery, either lack sensitivity, are invasive, or require expensive specialized devices. For measuring the physiological effects, BMI is commonly used to diagnose obesity despite the known shortcomings as a marker

for metabolic syndrome. Biomarkers such as anthropometric measurements (e.g., waist-to-hip ratio) and visceral adipose tissue (VAT) have been shown to be superior to BMI in predicting health risks associated with obesity, but these measures lack sensitivity, specificity, or are expensive. Another key morbidity associated with obesity

is non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH). The gold standard to the diagnosis and assessment of these conditions is histologic evaluation of liver biopsies. Fibroscan transient elastography is a noninvasive test which can also assess fibrosis, but high BMI and severe steatosis can

decrease its accuracy. These approaches are either invasive, expensive, or relatively inaccurate. Measures of self-body perception are commonly used to assess psychological aspects of obesity, as body image is an important motivator for diet, physical activity, and weight loss intention. Body image perception is commonly

assessed using self-reports and cartoon-like line drawings which are non-subject specific and insensitive. Based on our preliminary work (R21HL124443) that developed optical body scanning technology to capture 3D body shapes using inexpensive hardware, we propose to use the technology to study the physiological and

psychological effects on subjects with severe obesity: · Develop prediction algorithm for hepatic steatosis, fibrosis, adiposity, and blood biomarkers using optical scans. The optical scan and biopsy data will be used as the training and validation set to develop a machine learning algorithm to cheaply and non-invasively predict the biomarkers from 3D body surface

data. · Develop the use of optical scans for measuring the physiological effects of obesity. We will conduct a cross sectional and longitudinal study to further assess the use of optical surface scans to determine health indicators associated with obesity (using data from surface scan, DXA and serum biomarkers) for

one year following surgery. We will establish a database of such data along with software for data mining the database. · Develop the use of optical scans for measuring the psychological effects of obesity. We will collect 3D surface geometry of each subject using optical scans and morph these to produce subject-specific

images of larger or smaller body shape. We will use these images to study perception related to obesity and in particular patients undergoing post-operative body changes