Malarial Retinopathy Screening System for Improved Diagnosis of Cerebral Malaria

疟疾视网膜病变筛查系统可改善脑型疟疾的诊断

• 批准号: 8714453
• 负责人: Vinayak S Joshi
• 金额: $ 29.99万
• 依托单位: VISIONQUEST BIOMEDICAL, LLC
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-06-01 至 2016-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8714453
• 关键词: Address; Affect; Africa; African; Algorithms; Cause of Death; Cephalic; Cerebral Malaria; Cessation of life; Characteristics; Child; Clinical; Computer software; Data; Detection; Development; Diabetic Retinopathy; Diagnosis; Diagnostic; Disease; Equipment; Guidelines; Hemorrhage; Image; Image Analysis; Imaging Device; Incidence; Infection; Laboratories; Lesion; Life; Measurement; Methods; Mydriatics; National Institute of Allergy and Infectious Disease; Ophthalmologist; Ophthalmology; Outcome; Papilledema; Pathology; Patients; Performance; Phase; Physicians; Population; Positioning Attribute; Process; Reporting; Research; Retinal; Retinal Diseases; Scientist; Specificity; Spottings; Symptoms; Syndrome; System; Testing; Width; clinical Diagnosis; cost; experience; image processing; improved; innovation; mortality; performance tests; portability; pressure; prevent; prospective; public health relevance; screening; software systems; tool

DESCRIPTION (provided by applicant): VisionQuest Biomedical and its collaborators have assembled a team of inter-disciplinary scientists with considerable experience in automated retinal image analysis, clinical ophthalmology with specialized research in malarial retinopathy (MR), and cerebral malaria diagnosis (CM). This team will develop and test an automated MR screening software system integrated with a low-cost and portable retinal camera, iRxCam, developed by VisionQuest; to assist and improve the accuracy of CM diagnosis. CM is the most lethal clinical syndrome associated with malarial disease. It affects more than 200 million people annually and claims about 800,000 deaths worldwide which include 700,000 mortalities from African children. As a consequence of high incidence of CM, it is often misdiagnosed for other pathologies with similar symptoms, leading to an incorrect treatment. Once clinically suspected, an accurate means to confirm the presence of CM or to investigate for a non-malarial illness is critically needed to improve outcomes. Since MR is greater than 90% sensitive and specific to the presence of CM once clinically diagnosed, retinal screening for MR represents an effective means to assist and improve the specificity of CM diagnosis. Our proposed system will not replace the current CM diagnostic standard, but instead will be added to it to increase the accuracy of CM diagnosis leading to a smaller number of false positive outcomes. We propose a fully automated MR screening system that eliminates the need of clinical expertise and equipment, as well as its low-cost and portability make this system more accessible and affordable to affected population in Africa. There are three specific aims to be achieved in phase I of this project. First, we will develop new methods and adapt previously developed methods for automated detection of retinal signs of MR and test them using a retrospective image data. The second aim will focus on interfacing the automated software system with the low-cost and portable retinal camera developed by VisionQuest. Third, we will test our software system on a retrospective image data obtained from diabetic retinopathy patients imaged with our camera to demonstrate the applicability of the software system on images obtained from our camera.

描述（由申请人提供）：VisionQuest Biomedical及其合作者已经组建了一支跨学科的科学家团队，他们在自动视网膜图像分析、临床眼科以及疟疾视网膜病变（MR）的专业研究和脑疟疾诊断（CM）方面拥有丰富的经验。该团队将开发和测试一种自动化的MR筛选软件系统，该系统集成了VisionQuest公司开发的低成本便携式视网膜相机iRxCam；协助和提高CM诊断的准确性。CM是与疟疾相关的最致命的临床综合征。它每年影响2亿多人，在全世界造成约80万人死亡，其中包括70万非洲儿童死亡。由于CM的高发病率，它经常被误诊为具有类似症状的其他病理，导致错误的治疗。一旦临床怀疑，就迫切需要一种准确的手段来确认CM的存在或调查非疟疾疾病，以改善结果。由于MR在临床诊断后对CM的敏感性和特异性大于90%，因此视网膜MR筛查是辅助和提高CM诊断特异性的有效手段。我们提出的系统不会取代目前的CM诊断标准，而是将其添加到其中以提高CM诊断的准确性，从而减少假阳性结果的数量。我们提出一种完全自动化的核磁共振筛查系统，它消除了对临床专业知识和设备的需求，而且它的低成本和便携性使该系统对非洲受影响的人群更容易获得和负担得起。该项目的第一阶段有三个具体目标要实现。首先，我们将开发新的方法，并适应以前开发的方法，用于自动检测视网膜磁共振征象，并使用回顾性图像数据进行测试。第二个目标是将自动化软件系统与VisionQuest公司开发的低成本便携式视网膜相机连接起来。第三，我们将对我们的软件系统进行测试，使用我们的相机成像的糖尿病视网膜病变患者的回顾性图像数据，以证明软件系统对我们的相机获得的图像的适用性。