Computer Based Screening for Diabetic Retinopathy

基于计算机的糖尿病视网膜病变筛查

基本信息

批准号：
8502503
负责人：
Peter N Soliz
金额：
$ 54.23万
依托单位：
VISIONQUEST BIOMEDICAL, LLC
依托单位国家：
美国
项目类别：
财政年份：
2008
资助国家：
美国
起止时间：
2008-02-01 至 2015-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8502503
关键词：
Address Algorithms American Applications Grants Automation Biometry Blindness Centers for Disease Control and Prevention (U.S.)Clinic Clinical Clinical Data Clinical Research Clinical Study Element Collection Communication Community Healthcare Computer software Computers Credentialing Data Data Collection Databases Devices Diabetes Mellitus Diabetic Retinopathy Disease Early Diagnosis Early treatment Effectiveness Ensure Environment Exercise Eye diseases Frequencies Goals Gold Grant Health Insurance Portability and Accountability Act Health Personnel Health Sciences Health Services Accessibility Healthcare Systems Image Incidence Individual Institutes Letters Manuals Masks Medical Medical Device Monitor New Mexico Ophthalmic examination and evaluation Optic Disk Phase Populations at Risk Process Productivity Quality of life Reader Reading Retina Retinal Retinal Diseases Risk Safety Screening Result Services Site Software Validation Solutions South Texas Specificity Staging System Techniques Technology Testing Texas Time Training Triage United States United States Food and Drug Administration Universities Validation adjudication base commercialization diabetic digital improved meetings safety testing screening software systems tv watching

项目摘要

DESCRIPTION (provided by applicant): The objective of this Phase II competitive renewal project is to implement a clinical study to collect data to validate EyeStar(tm), a software system as the basis for comprehensive telescreening for all stages of diabetic retinopathy (DR). According to the CDC, approximately 80 million people in the U.S. have some form of eye disease, including 20 million diabetics at risk for retinopathy. It is estimated that less than hal of those individuals with diabetes are screened periodically for DR. Lack of medical coverage and access to healthcare providers imposes major obstacles for nearly 10 million diabetics. Creating an affordable and accessible solution to providing screening services to these diabetics presents a significant challenge to the healthcare community. The objective of the original Phase II grant was to demonstrate a "top-down" screening algorithm for triaging normal, i.e. no disease, from suspect retinas using a new technique, amplitude modulation-frequency modulation (AM-FM), to analyze multi-field digital retinal images. As a result of the Phase II grant, the EyeStar(tm) software for diabetic retinopathy screening was developed. In this project, we will perform a clinical validation that will allow us to apply for 510(k) clearance by the Food and Drug Administration (FDA). To meet this goal, we have divided this proposal in three aims. In Aim #1, we will establish a clinical network and meet the requirements for the number of cases needed to perform a clinical study in order to obtain FDA clearance for our integrated, automatic screening system. In Aim #2, we will perform an independent validation for purposes of submitting to the FDA a 510(k) clearance application. In Aim #3, we will operate all the EyeStar(tm) components in a near "real-time" environment. This project is significant for two main reasons: increase of productivity and safety testing. Firs, by increasing the productivity of DR screening centers through automation, a much larger population of at-risk individuals will have access to this service, leading to improved productivit and quality of life through early detection and treatment. Second, by providing to the FDA a system that is highly effective and sensitive, we will insure that the safety requirements of semi-automatic screening for diabetic retinopathy are met. The FDA-cleared software will be integrated into our existing network of retinal screening sites in Texas and New Mexico as the first step toward commercialization.

描述（由申请人提供）：II阶段竞争性更新项目的目的是实施临床研究以收集数据以验证Eyestar（TM），这是软件系统作为糖尿病性视网膜病（DR）所有阶段的全面伸缩屏幕的基础。据疾病预防控制中心（CDC）称，美国约有8000万人患有某种形式的眼科疾病，其中包括有2000万糖尿病患者患视网膜病风险。据估计，针对DR的那些糖尿病患者的HAL小于HAL。缺乏医疗保险和获得医疗保健提供者的机会，对近1000万个糖尿病患者施加了主要障碍。为这些糖尿病患者提供筛查服务的负担得起且易于使用的解决方案给医疗保健社区带来了重大挑战。原始II期赠款的目的是证明使用新技术使用新技术，幅度调制频率调制（AM-FM）来证明一种用于分类正常的“自上而下”的筛选算法，即没有疾病，以分析多场数字视网膜图像。由于II期赠款，开发了Eyestar（TM）软件用于糖尿病性视网膜病变筛查。在该项目中，我们将进行临床验证，该临床验证将使我们能够申请食品药品监督管理局（FDA）的510（k）批准。为了实现这一目标，我们将该提议分为三个目标。在AIM＃1中，我们将建立一个临床网络，并满足执行临床研究所需病例数的要求，以便为我们集成的自动筛查系统获得FDA清除率。在AIM＃2中，我们将进行独立验证，以提交FDA A 510（k）清算申请。在AIM＃3中，我们将在几乎“实时”环境中操作所有Eyestar（TM）组件。该项目重要的是有两个主要原因：提高生产率和安全性测试。通过通过自动化提高DR筛查中心的生产率，FIRS将有能力获得这项服务，从而通过早期发现和治疗改善了生产力和生活质量。其次，通过向FDA提供非常有效和敏感的系统，我们将确保满足半自动筛查的安全要求。 FDA被清除的软件将集成到我们现有的德克萨斯州和新墨西哥州的视网膜筛查网站网络中，作为商业化的第一步。