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

推进3D光学体表扫描技术评估高度肥胖人群的生理和心理影响

• 批准号: 10280172
• 负责人: JAMES K HAHN
• 金额: $ 59.3万
• 依托单位: GEORGE WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10280172
• 关键词: 3-Dimensional; Adipose tissue; Biological Markers; Biopsy; Blood; Body Image; Body Surface; Body Weight decreased; Body mass index; Cartoons; Cellular Phone; Computer software; Data; Databases; Devices; Diagnosis; Diet; Dual-Energy X-Ray Absorptiometry; Evaluation; Explosion; Face; Fatty Liver; Fibrosis; Geometry; Gold; Health; Histologic; Image; Intention; Liver Fibrosis; Longitudinal Studies; Longitudinal observational study; Machine Learning; Measurement; Measures; Metabolic Marker; Metabolic syndrome; Methodology; Mining; Morbid Obesity; Morbidity - disease rate; Obesity; Operative Surgical Procedures; Optics; Patient Self-Report; Patients; Perception; Physical activity; Physiological; Postoperative Period; Psychological Factors; Research; Research Personnel; Risk; Scanning; Sensitivity and Specificity; Serum; Shapes; Surface; Tablets; Techniques; Technology; Testing; Training; Translating; Validation; Visceral; Waist-Hip Ratio; Weight; Work; bariatric surgery; base; cost; cost effective; data mining; elastography; high body mass index; high risk; innovation; insight; liver biopsy; machine learning algorithm; non-alcoholic fatty liver disease; nonalcoholic steatohepatitis; obese person; population based; prediction algorithm; predictive marker; psychologic; recruit; sensor; success; tool

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

项目摘要 目前用于测量肥胖症的生理或心理影响的技术， 外科手术要么缺乏敏感性，要么是侵入性的，要么需要昂贵的专门设备。用于测量 生理效应，BMI通常用于 诊断肥胖尽管已知的缺点作为一个标志 代谢综合征的治疗方法生物标志物如人体测量（例如，腰臀比）和内脏 脂肪组织（VAT）在预测与肥胖相关的健康风险方面已经显示出优于BMI的上级， 但是这些测量缺乏灵敏度、特异性或者昂贵。与肥胖相关的另一个关键发病率 非酒精性脂肪性肝病（NAFLD）和非酒精性脂肪性肝炎（NASH）。金本位制 这些疾病的诊断和评估是肝活组织检查的组织学评价。Fibroscan瞬变 弹性成像是一种非侵入性检查，也可以评估纤维化，但高BMI和严重脂肪变性可以 降低其准确性。这些方法要么是侵入性的、昂贵的，要么相对不准确。措施 自我身体知觉通常用于评估肥胖的心理方面，因为身体意象是一种 饮食、体育活动和减肥意图的重要动力。身体形象感知通常是 使用自我报告和卡通式的线条画进行评估，这些线条画不针对特定主题，也不敏感。 基于我们的初步工作（R21HL124443），开发了光学身体扫描技术来捕获3D 身体形状使用廉价的硬件，我们建议使用该技术来研究生理和 对严重肥胖受试者的心理影响： ·开发用于肝脂肪变性、纤维化、肥胖和血液生物标志物的预测算法， 扫描。光学扫描和活检数据将用作训练和验证集，以开发 机器学习算法，以廉价和非侵入性地预测来自3D身体表面的生物标志物 数据 ·开发光学扫描的使用，以测量肥胖的生理影响。我们将进行 横截面和纵向研究，以进一步评估使用光学表面扫描，以确定 与肥胖相关的健康指标（使用来自表面扫描，DXA和血清生物标志物的数据）， 手术后一年。我们将沿着建立一个数据库，并配备数据挖掘软件 数据库 ·开发光学扫描的使用，以测量肥胖的心理影响。我们将收集3D 使用光学扫描每个对象的表面几何形状， 更大或更小的身体形状的图像。我们将用这些图像来研究与肥胖相关的感知 特别是经历术后身体变化的患者