Development and Validation of Quantitative Anterior Segment OCT-based Methods to Evaluate Patients with Primary Angle Closure Disease

基于定量眼前节 OCT 的方法的开发和验证，用于评估原发性房角闭合疾病患者

• 批准号: 10563187
• 负责人: Benjamin Y. Xu
• 金额: $ 22.88万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-02-01 至 2024-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10563187
• 关键词: Adoption; Affect; Age; Agreement; Anatomy; Anterior; Aqueous Humor; Area; Biostatistical Methods; Blindness; Caring; Cataract Extraction; Chinese American; Chronic Disease; Classification; Clinical; Clinical Data; Clinical Research; Data; Data Analyses; Development; Diagnosis; Diagnostic; Diagnostic Procedure; Diagnostic tests; Disease; Disease model; Epidemiology; Eye; Family; Foundations; Funding; Future; Gender; Glaucoma; Goals; Gonioscopy; Healthcare Systems; High Prevalence; Image; Impairment; Incidence; Individual; Lasers; Longitudinal Studies; Machine Learning; Measurement; Measures; Mentors; Methods; Modeling; Morbidity - disease rate; Optical Coherence Tomography; Patient Care; Patient Recruitments; Patients; Performance; Peripheral; Persons; Physiologic Intraocular Pressure; Primary Angle Closure Glaucoma; Pupil; Recording of previous events; Refractive Errors; Reproducibility; Research; Risk; Risk Factors; Scientist; Severities; Severity of illness; Specialist; Statistical Models; Structure; Study Subject; System; Trabecular meshwork structure; Training; Treatment Protocols; United States National Institutes of Health; Validation; Width; care providers; career development; clinical application; clinical care; clinical predictors; cost; diagnosis standard; disease classification; disorder risk; experience; high risk; imaging modality; improved; machine learning algorithm; novel; population based; programs; progression risk; prospective; quantitative imaging; research clinical testing; skills; standardized care; targeted treatment

PROJECT SUMMARY Primary angle closure glaucoma (PACG), the most severe form of primary angle closure disease (PACD), is a leading cause of permanent blindness worldwide. Gonioscopy, a qualitative and subjective angle assessment method, is the current clinical standard for diagnosing PACD despite its limited ability to quantify disease severity, especially in patients with early angle closure. Anterior segment optical coherence tomography (AS-OCT) is a quantitative and objective imaging-based method for assessing the angle. However, there are limited methods for clinicians to apply AS-OCT to the care of angle closure patients. The primary objectives of this K23 career development proposal are: 1) to demonstrate the benefit of a quantitative anterior segment OCT-based approach to evaluating patients with PACD and develop classification models for PACD based on AS-OCT measurements; and 2) to provide an academic glaucoma specialist with the training and mentored research experience necessary to conduct independent clinical research. Achieving these objectives will provide critical skills and experiences necessary to establish an independent research program focused on applying AS-OCT imaging to improve the clinical care of patients with PACD. The proposed K23 application will provide additional training in four vital areas: 1) epidemiology and mechanisms of chronic disease; 2) classification of disease and prediction of disease risk; 3) biostatistical methods for clinical research; 4) machine learning and automated data analysis. The proposed research will use population-based data collected as part of the NIH-funded Chinese American Eye Study (CHES) to compare AS-OCT and gonioscopic assessments of angle width and determine the strength of association between these assessments and known PACD risk factors. The relationship between the degree of angle closure, measured by AS-OCT, and intraocular pressure (IOP), a sequela of angle closure and strong risk factor for glaucoma, will be characterized with CHES data and validated with data obtained by using a novel pupil control system on PACD patients recruited from the USC Roski Eye Institute (USCREI). Classification models for PACD stage and severity based on AS-OCT data from CHES will be developed using machine learning algorithms and validated with prospective data from USCREI patients with PACD. The results of the proposed research will provide the foundation for a future longitudinal study examining the benefit of using anterior segment OCT-based assessments and classification models to evaluate PACD patients and deliver targeted treatment to patients with higher risk for PACG. The ultimate goal of my research is to develop quantitative imaging-based diagnostic and treatment protocols that guide the standardized care of PACD patients and decrease the incidence of PACG and its associated ocular morbidity.

项目概要 原发性闭角型青光眼 (PACG) 是原发性闭角病 (PACD) 的最严重形式，是一种 全球永久失明的主要原因。房角镜检查，定性和主观角度评估 方法，是目前诊断 PACD 的临床标准，尽管其量化疾病严重程度的能力有限， 特别是对于早期闭角的患者。眼前段光学相干断层扫描（AS-OCT）是一种 基于定量和客观成像的角度评估方法。但方法有限 供临床医生应用 AS-OCT 来护理闭角患者。 K23 职业生涯的主要目标 开发建议是： 1) 展示基于 OCT 的定量眼前段方法的益处 评估 PACD 患者并开发基于 AS-OCT 测量的 PACD 分类模型； 2) 为学术青光眼专家提供培训和指导研究经验 进行独立的临床研究所必需的。实现这些目标将提供关键技能和 建立一个专注于将 AS-OCT 成像应用于 改善 PACD 患者的临床护理。拟议的 K23 应用程序将提供额外的培训 四个重要领域：1）慢性病的流行病学和机制； 2）疾病分类及预测 疾病风险； 3）临床研究的生物统计方法； 4）机器学习和自动化数据分析。 拟议的研究将使用作为 NIH 资助的华裔美国人研究项目的一部分收集的基于人口的数据 眼科研究 (CHES)，用于比较 AS-OCT 和房角镜评估角宽度并确定强度 这些评估与已知的 PACD 风险因素之间的关联。学位之间的关系 通过 AS-OCT 测量的房角闭合度和眼压 (IOP)（房角闭合和强烈的后遗症） 青光眼的危险因素，将使用 CHES 数据进行表征，并使用通过使用新颖的方法获得的数据进行验证 PACD 患者的瞳孔控制系统由南加州大学罗斯基眼科研究所 (USCREI) 招募。分类 将使用机器开发基于 CHES AS-OCT 数据的 PACD 阶段和严重程度模型 学习算法并使用 USCREI 患有 PACD 患者的前瞻性数据进行验证。结果 拟议的研究将为未来的纵向研究奠定基础，研究使用 基于眼前节 OCT 的评估和分类模型，用于评估 PACD 患者并交付 针对 PACG 风险较高的患者进行针对性治疗。我研究的最终目标是开发 基于定量成像的诊断和治疗方案，指导 PACD 的标准化护理 患者并降低 PACG 的发生率及其相关的眼部发病率。

项目成果

Surgical Management of Primary Angle-Closure Disease-Why Less Is More.

原发性房角闭合性疾病的手术治疗-为什么少即是多。

• 发表时间: 2019-10-01
• 影响因子: 8.1
• 作者: Xu, Benjamin Y;Varma, Rohit
• 通讯作者: Varma, Rohit

Anterior Segment Optical Coherence Tomography: Applications for Clinical Care and Scientific Research.

眼前段光学相干断层扫描：临床护理和科学研究的应用。

• 发表时间: 2019
• 作者: Shan, Jing;DeBoer, Charles;Xu, Benjamin Y
• 通讯作者: Xu, Benjamin Y

Assessing accommodative presbyopic biometric changes of the entire anterior segment using single swept-source OCT image acquisitions.

使用单扫源 OCT 图像采集评估整个眼前节的调节性老花眼生物特征变化。

• 发表时间: 2022-01
• 作者: Xie, Xiaobin;Sultan, William;Corradetti, Giulia;Lee, Jong Yeon;Song, Abe;Pardeshi, Anmol;Yu, Fei;Chopra, Vikas;Sadda, Srinivas R;Xu, Benjamin Y;Huang, Alex S
• 通讯作者: Huang, Alex S

Rates and Patterns of Diagnostic Conversion from Anatomical Narrow Angle to Primary Angle-Closure Glaucoma in the United States.

美国从解剖性窄角型青光眼到原发性闭角型青光眼的诊断转换率和模式。

• 发表时间: 2023
• 作者: Yoo, Kristy;Apolo, Galo;Zhou, Sarah;Burkemper, Bruce;Lung, Khristina;Song, Brian;Wong, Brandon;Toy, Brian;Camp, Andrew;Xu, Benjamin
• 通讯作者: Xu, Benjamin

Anatomic Changes and Predictors of Angle Widening after Laser Peripheral Iridotomy: The Zhongshan Angle Closure Prevention Trial.

激光周边虹膜切开术后房角扩大的解剖学变化和预测因素：中山房角闭合预防试验。

• 发表时间: 2021
• 影响因子: 13.7
• 作者: Xu, Benjamin Y;Friedman, David S;Foster, Paul J;Jiang, Yu;Pardeshi, Anmol A;Jiang, Yuzhen;Munoz, Beatriz;Aung, Tin;He, Mingguang
• 通讯作者: He, Mingguang