OCTA Precursors of Vision-Threatening Complications of Diabetic Retinopathy

OCTA 糖尿病视网膜病变视力威胁并发症的前兆

• 批准号: 10718643
• 负责人: Thomas Hwang
• 金额: $ 57.91万
• 依托单位: OREGON HEALTH & SCIENCE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-30 至 2028-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10718643
• 关键词: Address; Algorithms; Angiography; Background Diabetic Retinopathy; Biological Markers; Blindness; Clinical; Complications of Diabetes Mellitus; Cross-Sectional Studies; Data; Detection; Development; Diabetic Retinopathy; Diagnosis; Eye; Fluorescein Angiography; Fundus; Image; Intuition; Lesion; Life; Membrane; Methods; Microaneurysm; Monitor; Morphologic artifacts; Motion; Optical Coherence Tomography; Participant; Patients; Photography; Prediction of Response to Therapy; Prospective Studies; Qualitative Evaluations; Resolution; Risk; Scanning; Signal Transduction; Speed; System; Techniques; Technology; Testing; Time; Vision; clinical examination; clinically significant; deep learning; deep learning algorithm; detection sensitivity; diabetic; falls; high risk; improved; macular edema; neovascular; neovascularization; prevent; proliferative diabetic retinopathy; prospective; risk stratification; sample fixation; screening; structural imaging; technological innovation; technology validation

PROJECT SUMMARY Diabetic retinopathy (DR) is a leading cause of vision loss. This vision loss is largely preventable through timely diagnosis and treatment. The current method for identifying eyes at risk relies on qualitative evaluation of key features on clinical examinations or fundus photographs. While this approach stratifies risk, it does so imprecisely, requiring referral of many patients in order to identify the few who need treatment. We propose an alternative approach that focuses on the direct precursors of vision-threatening complications using advanced optical coherence tomography angiography (OCTA). This approach has the potential to more precisely identify patients at high risk for these complications than photographic screening, reducing the burden on the system. Our preliminary data has identified OCTA precursors of the vision-threatening DR complications: proliferative diabetic retinopathy (PDR) and center-involved diabetic macular edema (CI-DME). To use these biomarkers in real clinical settings, OCTA must have a wide field of view with high resolution while also providing a high imaging yield. In addition, these biomarkers must be accessible to clinicians, requiring automated and reliable identification and segmentation. The currently available systems fall short of these requirements. We propose making fundamental technological improvements to address the present limitations and to test our hypothesis that the OCTA precursors of PDR and CI-DME can precisely identify eyes at risk: In Specific Aim 1, we will develop a high-speed (1-MHz), wide-field (120?), and high-resolution (10-µmtransverse resolution) system capable of reliable, high-yield OCTA from a single scan that does not require montaging or eccentric fixation. This field of view is comparable to currently available ultra-widefield fluorescein angiography. GPU-based real-time processing will reduce motion artifacts and improve scan acquisition reliability. In Specific Aim 2, we will develop deep-learning algorithms that identify these precursors. The precursors of neovascularization (pNV) are epiretinal hyperreflective material with flow signal above the internal limiting membrane that are invisible with conventional imaging. Active microaneurysms (aMA) are characterized by hyperreflective walls with flow signal within the lumen. We will use deep-learning techniques to accurately segment and quantify these features and present the biomarkers in intuitive and interpretable format in real time. In Specific Aim 3, we will evaluate the clinical significance of advanced-OCTA derived biomarkers. (1) In a 2- year prospective study, we will follow 100 patients with moderate to severe nonproliferative DR at baseline for development of PDR or CI-DME. (2) In a cross-sectional study, we will compare the sensitivity for detecting neovascular lesions in 50 eyes with severe NPDR and PDR using the advanced OCTA vs. ultra-widefield fluorescein angiography vs. fundus photographs. (3) In an exploratory study, we will follow 50 patients undergoing treatments for PDR or CI-DME with advanced OCTA for 6 months to see if the advanced-OCTA biomarkers can provide clinically meaningful information to monitor or predict treatment response.

项目摘要 糖尿病视网膜病变（DR）是导致视力丧失的主要原因。这种视力丧失在很大程度上是可以预防的， 诊断和治疗。目前用于识别处于危险中的眼睛的方法依赖于对眼睛的关键特征的定性评估。 临床检查或眼底照片上的特征。虽然这种方法对风险进行了分层， 不准确地说，需要转诊许多病人，以确定少数需要治疗的人。我们提出了一个 另一种方法，重点是使用先进的威胁视力的并发症的直接前兆 光学相干断层扫描血管造影术（OCTA）。这种方法有可能更精确地识别 这些并发症的高风险患者比摄影筛查，减轻了系统的负担。 我们的初步数据已经确定了威胁视力的DR并发症的OCTA前体：增殖性 糖尿病视网膜病变（PDR）和中心受累的糖尿病黄斑水肿（CI-DME）。使用这些生物标记物 在真实的临床环境中，OCTA必须具有宽视野和高分辨率，同时还提供高成像 产率此外，这些生物标志物必须可供临床医生使用，需要自动化和可靠的 识别和分割。目前可用的系统达不到这些要求。我们提出 进行根本性的技术改进，以解决目前的局限性，并验证我们的假设 PDR和CI-DME的OCTA前体可以精确识别有风险的眼睛： 在具体目标1中，我们将开发一种高速（1 MHz），宽场（120？），和高分辨率（10微米横向 分辨率）系统，能够从单次扫描中获得可靠、高产量的OCTA，不需要剪辑或 偏心注视该视野与目前可用的超宽视野荧光素血管造影术相当。 基于GPU的实时处理将减少运动伪影并提高扫描采集可靠性。 在具体目标2中，我们将开发识别这些前兆的深度学习算法。的前体 新生血管（pNV）是视网膜前高反射物质，其血流信号高于内界 这些膜在常规成像中是不可见的。活动性微动脉瘤（aMA）的特征是： 在管腔内具有流动信号的超反射壁。我们将使用深度学习技术， 分割和量化这些特征，并以直观和可解释的格式真实的实时呈现生物标志物。 在特定目标3中，我们将评价高级OCTA衍生生物标志物的临床意义。(1)在一个2- 一项为期一年的前瞻性研究，我们将随访100例基线时患有中度至重度非增殖性DR的患者， PDR或CI-DME的开发。(2)在一项横断面研究中，我们将比较检测 使用高级OCTA与超宽视野对比，在50只患有重度NPDR和PDR的眼睛中观察新生血管病变 荧光素血管造影与眼底照片。(3)在一项探索性研究中，我们将跟踪50名患者， 接受PDR或CI-DME治疗6个月的晚期OCTA，以观察晚期OCTA是否 生物标志物可以提供临床上有意义的信息以监测或预测治疗反应。