A photographic method for human body composition assessment

一种用于人体成分评估的摄影方法

基本信息

批准号：
8295495
负责人：
Helen Olivia Affuso
金额：
$ 50.47万
依托单位：
UNIVERSITY OF ALABAMA AT BIRMINGHAM
依托单位国家：
美国
项目类别：
财政年份：
2012
资助国家：
美国
起止时间：
2012-06-01 至 2017-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8295495
关键词：
Abbreviations Advisory Committees Age Aging Air Algorithms Alzheimer&apos s Disease Anthropometry Body Composition Body Size Body Weight Body fat Body mass index Cachexia Categories Child Clinical Clinical Research Computational algorithm Data Devices Disease Dual-Energy X-Ray Absorptiometry Eating Disorders Epidemiologic Studies Equipment Exercise Fatty acid glycerol esters Growth HIV Hand Health Height Home environment Human Human body Image Image Analysis Imagery Individual Laboratories Laboratory Study Lead Longevity Machine Learning Magnetic Resonance Imaging Malignant Neoplasms Measurement Measures Methods Multiple Sclerosis Muscular Dystrophies Obesity Painless Parkinson Disease Participant Persons Plethysmography Population Public Health Race Radiation Relative (related person)Research Sampling Skeletal Muscle Skin Strategic Planning System Techniques Technology Testing Time Training United States National Institutes of Health Validation Visual Weight Woman Work Writing X-Ray Computed Tomography cost digital digital imaging electric impedance experience field study frailty improved interest light weight men muscle form nervous system disorder novel portability primary outcome response sarcopenia sex waist circumference wasting

Abbreviations Advisory Committees Age Aging Air Algorithms Alzheimer&apos s Disease Anthropometry Body Composition Body Size Body Weight Body fat Body mass index Cachexia Categories Child Clinical Clinical Research Computational algorithm Data Devices Disease Dual-Energy X-Ray Absorptiometry Eating Disorders Epidemiologic Studies Equipment Exercise Fatty acid glycerol esters Growth HIV Hand Health Height Home environment Human Human body Image Image Analysis Imagery Individual Laboratories Laboratory Study Lead Longevity Machine Learning Magnetic Resonance Imaging Malignant Neoplasms Measurement Measures Methods Multiple Sclerosis Muscular Dystrophies Obesity Painless Parkinson Disease Participant Persons Plethysmography Population Public Health Race Radiation Relative (related person)Research Sampling Skeletal Muscle Skin Strategic Planning System Techniques Technology Testing Time Training United States National Institutes of Health Validation Visual Weight Woman Work Writing X-Ray Computed Tomography cost digital digital imaging electric impedance experience field study frailty improved interest light weight men muscle form nervous system disorder novel portability primary outcome response sarcopenia sex waist circumference wasting

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项目摘要

DESCRIPTION (provided by applicant): The assessment of body composition, particularly fat and fat free mass, is vital to understanding many health-related conditions including obesity and sarcopenia, whose very definitions depend on assessment of fat and fat free mass, but also cachexia induced by HIV, cancer, and other diseases; multiple sclerosis; wasting in neurological disorders such as Parkinson's, Alzheimer's, muscular dystrophy; eating disorders; proper growth in children; and yet others still. Nevertheless, challenges remain in measuring body composition. Existing methods beyond height, weight, and very simple anthropometry are still not the norm in large-scale epidemiologic studies and clinical studies. This is because of concerns, depending on method, about cost, portability, time, radiation exposure, and accuracy. Calculation of body mass index (BMI; kg/m2) is a commonly used alternative, but is limited in that it is an assessment of body weight relative to height and not of body fatness per se. A hand-held device that could be carried by any individual, accurately assess fat mass and skeletal muscle mass, and be utilized without any discomfort to the subject, inexpensively, and without radiation exposure would be highly desirable. Evidence suggests that highly experienced trained observers can accurately estimate percentage of body fat by visual examination of subjects, but concerns about accuracy and subjectivity predominate. We hypothesize that we can develop a computer algorithm which can perform as or more accurately when analyzing photographic imagery data, will require no repeated retraining, and eliminate subjectivity. Our first specific aim is to develop a computer image analysis algorithm to accurately estimate adiposity and skeletal muscle mass from standardized photographic images in a bi-ethnic sample of men, women, and children. Our second specific aim is to validate the algorithm in a large diverse sample of men, women, and children. PUBLIC HEALTH RELEVANCE: Obesity, loss of skeletal muscle with aging, and other body composition alterations are of profound public health importance. We propose a novel method for measuring the quantity of fat and skeletal muscle mass in humans quickly, painlessly, safely, accurately, and inexpensively that can subsequently be used in many large scale and remote studies.

描述（由申请人提供）：对身体成分的评估，尤其是无脂肪和脂肪的质量，对于了解许多与健康相关的疾病在内至关重要，包括肥胖和肌肉减少症，其定义取决于评估无脂肪和无脂肪的肿块，也取决于艾滋病毒，癌症和其他疾病引起的卡希克西氏症；多发性硬化症;浪费在帕金森氏症，阿尔茨海默氏症，肌肉营养不良的神经系统疾病中；饮食失调；儿童的适当成长；还有其他人。然而，在测量身体成分中仍然存在挑战。在大规模流行病学研究和临床研究中，现有的高度，体重和非常简单的人体测量法仍然不是规范。这是由于关注，具体取决于方法，成本，可移植性，时间，辐射暴露和准确性。体重指数的计算（BMI; kg/m2）是一种常用的替代方案，但受到限制，因为它是对体重的评估，而不是体重相对于体重，而不是体内脂肪本身。任何个人都可以携带的手持装置可以准确地评估脂肪质量和骨骼肌肉质量，并且在没有对受试者的任何不适感的情况下使用，并且没有辐射暴露，这是非常需要的。有证据表明，经验丰富的训练有素的观察者可以通过视觉检查受试者准确估计体内脂肪的百分比，但担心准确性和主观性占主导地位。我们假设我们可以开发一种计算机算法，该算法可以在分析摄影图像数据时可以或更准确地执行，不需要重复进行重复的再培训并消除主观性。我们的第一个具体目的是开发一种计算机图像分析算法，以准确地估算男性，女性和儿童样本中的标准化照相图像中的标准化照相图像和骨骼肌质量。我们的第二个具体目的是验证各种各样的男性，女人和儿童样本中的算法。公共卫生相关性：肥胖，衰老骨骼肌的丧失以及其他身体组成改变具有极高的公共健康重要性。我们提出了一种新的方法，用于快速，无痛，安全，准确和廉价地测量人类脂肪和骨骼肌质量的数量，随后可以在许多大型和远程研究中使用。