Computer Based Screening for Diabetic Retinopathy

基于计算机的糖尿病视网膜病变筛查

• 批准号: 8312281
• 负责人: Peter N Soliz
• 金额: $ 74.81万
• 依托单位: VISIONQUEST BIOMEDICAL, LLC
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-02-01 至 2014-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8312281
• 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; Screening procedure; 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; software systems; tv watching

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. PUBLIC HEALTH RELEVANCE: According to the CDC, there are over 25 million diabetics in the United States, of which less than 50% get their recommended yearly eye exams. This has resulted in an increase of the incidence of diabetic retinopathy, making it the second leading cause of blindness. Our proposed DR screening system, EyeStar(tm), would allow for an increase in examinations available to millions of Americans at risk, without major impact on our healthcare system. The proposed project will perform the necessary clinical validation of the system for FDA approval..

描述(由申请者提供)：此第二阶段竞争更新项目的目标是实施一项临床研究，以收集数据来验证EyeStar(Tm)软件系统 作为糖尿病视网膜病变(DR)所有阶段的全面电子筛查的基础。根据美国疾病控制与预防中心的数据，美国约有8000万人患有某种形式的眼病，其中包括2000万有视网膜病变风险的糖尿病患者。据估计，只有不到一半的糖尿病患者定期接受医生筛查，缺乏医疗保险，医疗保健提供者的提供给近1000万糖尿病患者带来了重大障碍。为这些糖尿病患者提供负担得起和可获得的解决方案，对医疗保健社区来说是一个巨大的挑战。最初的第二阶段拨款的目的是演示一种“自上而下”的筛选算法，用于对可疑视网膜进行分类，即使用调幅-调频(AM-FM)新技术来分析多场数字视网膜图像。作为第二阶段拨款的结果，开发了用于糖尿病视网膜病变筛查的EyeStar(Tm)软件。在这个项目中，我们将进行临床验证，使我们能够申请食品和药物管理局(FDA)的510(K)批准。为了实现这一目标，我们将这项提议分为三个目标。在目标1中，我们将建立一个临床网络，并满足进行临床研究所需的病例数量要求，以获得FDA对我们集成的自动筛查系统的批准。在AIM#2中，我们将执行独立验证，以便向FDA提交510(K)批准申请。在Aim#3中，我们将在近乎“实时”的环境中运行EyeStar(Tm)的所有组件。 这个项目之所以意义重大，主要有两个原因：提高生产率和安全测试。首先，通过自动化提高DR筛查中心的生产率，更多的高危人群将能够获得这项服务，从而通过早期发现和治疗提高生产率和生活质量。其次，通过向FDA提供一个高效和敏感的系统，我们将确保满足糖尿病视网膜病变半自动筛查的安全要求。 FDA批准的软件将整合到我们在德克萨斯州和新墨西哥州现有的视网膜筛查网站网络中，作为商业化的第一步。 与公共健康相关：根据美国疾病控制与预防中心的数据，美国有超过2500万糖尿病患者，其中不到50%的人接受了推荐的年度眼科检查。这导致糖尿病视网膜病变的发病率增加，使其成为第二大致盲原因。我们建议的DR筛查系统EyeStar(Tm)将允许数百万处于危险中的美国人增加可用检查，而不会对我们的医疗系统产生重大影响。拟议的项目将对该系统进行必要的临床验证，以获得FDA的批准。