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.

项目摘要 初级角度闭合青光眼（PACG），最严重的原发角闭合疾病（PACD）是一个 全世界永久失明的主要原因。 Gonii镜镜检查，定性和主观角度评估 方法，是当前用于诊断PACD的临床标准，尽管其量化疾病严重程度的能力有限， 特别是在早期闭合的患者中。前段光学相干断层扫描（AS-OCT）是一个 基于定量和客观成像的方法评估角度。但是，方法有限 临床医生将AS-OCT应用于角度闭合患者的护理。这个K23职业的主要目标 开发建议是：1）证明基于OCT的定量前段的好处 评估PACD患者并根据AS-OCT测量开发PACD的分类模型； 2）为学术青光眼专家提供培训和指导的研究经验 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 建立独立研究计划所需的经验，旨在将AS-OCT成像应用于 改善PACD患者的临床护理。拟议的K23申请将提供额外的培训 四个重要领域：1）慢性病的流行病学和机制； 2）疾病和预测分类 疾病风险； 3）用于临床研究的生物统计学方法； 4）机器学习和自动数据分析。 拟议的研究将使用收集的基于人群的数据作为NIH资助的中国美国人 眼研究（CHE）比较角度宽度的AS-OCT和Goniososcic评估，并确定强度 这些评估与已知PACD风险因素之间的关联。学位之间的关系 角度闭合，通过AS-OCT和眼内压（IOP）测量，角度闭合和强烈的续集 青光眼的危险因素将以CHES数据为特征，并通过使用新颖的数据验证 从USC Roski Eye Institute（USCREI）招募的PACD患者的学生控制系统。分类 基于CHE的AS-OCT数据，将使用机器开发基于CHE的AS-OCT数据的PACD阶段和严重性的模型 学习算法，并通过USCREI 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，以研究使用的好处 基于OCT的前部评估和分类模型，以评估PACD患者并提供 针对PACG风险较高的患者的目标治疗。我研究的最终目标是发展 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

Age-Related Changes in Dynamic Iris Behavior Assessed Using a Programmable Closed-Loop Iris Control System.

• DOI: 10.1167/tvst.11.11.9
• 发表时间: 2022-11-01
• 期刊: TRANSLATIONAL VISION SCIENCE & TECHNOLOGY
• 影响因子: 3
• 作者: Apolo, Galo;Lazkani, Naim;Zhou, Sarah;Song, Abe E.;Pardeshi, Anmol A.;Torossian, Lernik;Nguyen, Kent;Weinreb, Robert N.;Xu, Benjamin Y.
• 通讯作者: Xu, Benjamin Y.

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。

• DOI: 10.1001/jamaophthalmol.2019.2503
• 发表时间: 2019
• 期刊: JAMA ophthalmology
• 影响因子: 8.1
• 作者: Xu,BenjaminY;Varma,Rohit
• 通讯作者: Varma,Rohit

Age- and refraction-related changes in anterior segment anatomical structures measured by swept-source anterior segment OCT.

• DOI: 10.1371/journal.pone.0240110
• 发表时间: 2020
• 期刊: PloS one
• 影响因子: 3.7
• 作者: Xie X;Corradetti G;Song A;Pardeshi A;Sultan W;Lee JY;Yu F;Zhang L;Chen S;Chopra V;Sadda SR;Xu B;Huang AS
• 通讯作者: Huang AS

Automated expert-level scleral spur detection and quantitative biometric analysis on the ANTERION anterior segment OCT system.

在 ANTERION 眼前段 OCT 系统上进行自动化专家级巩膜刺检测和定量生物特征分析。

• DOI: 10.1136/bjo-2022-322328
• 发表时间: 2023
• 期刊: The British journal of ophthalmology
• 作者: Bolo,Kyle;ApoloAroca,Galo;Pardeshi,AnmolA;Chiang,Michael;Burkemper,Bruce;Xie,Xiaobin;Huang,AlexS;Simonovsky,Martin;Xu,BenjaminY
• 通讯作者: Xu,BenjaminY

Racial and Sociodemographic Disparities in the Detection of Narrow Angles before Detection of Primary Angle-Closure Glaucoma in the United States.

• DOI: 10.1016/j.ogla.2022.01.001
• 发表时间: 2022-07
• 期刊: OPHTHALMOLOGY GLAUCOMA
• 影响因子: 2.9
• 作者: Apolo, Galo;Bohner, Austin;Pardeshi, Anmol;Lung, Khristina;Toy, Brian;Wong, Brandon;Song, Brian;Camp, Andrew;Xu, Benjamin
• 通讯作者: Xu, Benjamin