Automated Eye Disease Screening System

描述(由申请者提供)：这个拟议的项目是基于这样一个事实，即在没有引入计算机辅助诊断视网膜图像的情况下，对年龄相关性黄斑变性(AMD)、青光眼和糖尿病视网膜病变(DR)等眼部疾病进行全面、广泛的筛查，在经济上是令人望而却步的。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2000万糖尿病患者有视网膜病变的风险，6000万人有青光眼的风险，1300万人被诊断为AMD。据估计，在这些糖尿病患者中，只有不到一半的人定期接受医生筛查，缺乏医疗保险，获得医疗保健提供者的机会给近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。为美国公民提供一项全面的筛查计划，利用眼科医生、验光师或其他训练有素的专家、读者对每个病例进行分级，费用将高得令人望而却步。解决方案是实施一种类似于其他医疗应用程序的计算机辅助技术，如乳房X光检查和巴氏涂片；这将为我们的高危人群提供全面、定期的筛查。我们的业务模型显示，通过将自动化集成到今天的手动筛选方法中，成本降低了400%。这项研究将通过在南得克萨斯州一个阅读中心的基础设施的实施而成为可能，据估计，那里居住着近20万糖尿病患者，超过50%的人没有接受年度检查。该中心将是一个演示场所，软件的有效性可以在这里被记录下来，提交给FDA进行上市前批准(PMA)。其目标是表明，通过使用混合(自动化-人工评分器)方法，中心每一时间段筛查的病例总数将增加五倍，其敏感度可与单纯基于人工的筛查相媲美或更好。这项拟议的研究的意义是双重的。首先，通过自动化提高阅读中心的生产力，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力和生活质量。其次，通过向FDA提供一个对晚期疾病高度有效和敏感的系统，基本上消除了安全问题。 与公共健康相关：今天，美国疾病控制与预防中心报告称，美国约有8000万人患有某种形式的眼病。糖尿病视网膜病变、老年性黄斑变性和青光眼是导致失明的主要原因。对于这些眼病中的每一种，如果及早发现，都有某种形式的干预措施可以导致有用的视力扩大。我们的自动化眼病筛查系统将使数百万有眼病风险的美国人可以进行检查，而不会对我们的医疗系统造成重大影响。这只能通过自动化作为眼科护理专家检查的辅助手段来实现。

DESCRIPTION (provided by applicant): This proposed project is motivated by the fact that comprehensive, broad-scale screening for eye diseases such as age-related macular degeneration (AMD), glaucoma, and diabetic retinopathy (DR), including advanced stages, is economically prohibitive without the introduction of computer-assisted diagnosis of retinal images. 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, 60 million at risk for glaucoma, and 13 million diagnosed with AMD. It is estimated that less than half 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. A comprehensive screening program for U.S. citizens utilizing ophthalmologists, optometrists, or other trained specialists, readers, to grade each case would be prohibitively expensive. The solution is to implement a computer-assisted technology similar to other medical applications, such as mammograms and Pap smears; that would provide comprehensive, periodic screening of our at-risk population. Our business models show a 400% decrease in costs with the integration of automation into today manual screening methods. The study will be made possible through the implementation of the infrastructure for a reading center in South Texas where it is estimated that nearly 200,000 diabetics reside and over 50% do not receive annual examinations. The center will be a demonstration site where the efficacy of the software can be documented for submission to the FDA for pre-market approval (PMA). The goal is to show that a center's through put number of cases screened per time period will increase fivefold through the use of a hybrid (automation-human graders) approach with sensitivity that is comparable or better than solely human-based screening. The significance of this proposed research is two-fold. First, by increasing the productivity of reading centers through automation, a much larger population of at-risk individuals will have access to this service, leading to improved productivity and quality of life through early detection and treatment. Second, by providing to the FDA, a system that is highly effective and sensitive to advanced disease, the issue of safety is essentially eliminated. PUBLIC HEALTH RELEVANCE: Today, the CDC reports that there are about 80 million people in the US who have some form of eye disease. Diabetic retinopathy, age-related macular degeneration, and glaucoma are the leading causes of blindness. There is some form of intervention for each of these eye diseases that can result in the extension of useful vision, if detected early. Our automated eye disease screening system will make examination available to millions of Americans at risk for eye disease available without major impact on our healthcare system. This is possible only through automation as an adjunct to examinations by eye care specialists.