The BCI (Brain Computer Interface) Glaucoma Study: Objective Home-Based Detection of Progressive Visual Function Loss in Glaucoma

项目总结 青光眼是世界上导致不可逆性失明和视力障碍的主要原因。作为一种疾病 通常直到晚期仍无症状，早期发现功能损害是至关重要的，因此 可以启动或提前治疗，以避免进展为残疾。功能丧失的检测是 传统上使用标准自动视野检查(SAP)。然而，SAP测试受到以下主观性的限制 患者的反应和很大的变异性，需要进行大量的测试来检测随时间的变化。这些 测试在以诊所为基础的环境中进行，由于患者可用时间和卫生保健资源有限， 随着时间的推移，通常会获得不充分的测试，导致对进展的延迟检测。这一要求 对于训练有素的技术人员来说，SAP的成本、复杂性和缺乏可移植性也使其无法用于筛查 在缺乏服务的人群中视野丧失的风险。解决当前评估视觉效果的方法的缺点 功能，我们开发了一种创新的脑机接口(BCI)，使便携和客观 多焦稳态视觉诱发电位(MfSSVEP)评价视功能损害。BCI 由采用头戴式显示器(HMD)的可穿戴设备组成，集成了无线 脑电(EEG)。在横断面调查中，我们证明了BCI mfSSVEP 参数能够成功地检测青光眼损害，具有极好的重测重复性。基座 根据初步研究的令人鼓舞的结果，我们现在提议对这一能力进行多中心调查 纵向BCI mfSSVEP参数在检测青光眼进展中的作用在具体目标1中，我们将收集 青光眼患者和健康受试者临床就诊期间的纵向BCI mfSSVEP数据。我们 假设BCI mfSSVEP数据将能够成功地检测进程并测量变化速率， 与SAP的功能评估和光学相干断层扫描的结构评估相比较。在……里面 目标2，收集基于家庭的纵向mfSSVEP数据，并考察其检测性能 青光眼的进展和变化率的测量。我们假设测试频率的增加 与临床相比，基于家庭的脑机接口测试将导致更早地检测和预测病情进展 基于数据和常规测试。在目标3中，我们将研究BCI mfSSVEP数据在预测中的能力 青光眼患者报告的生活质量。总而言之，这项提议采用了一种高度创新的脑机接口设备来 获取纵向mfSSVEP数据，主要目的是改进青光眼的检测和预测 进步。该方法有可能解决目前标准测试的主要局限性，显著 影响疾病的管理。客观的基于家庭的视觉功能测试可以代表一种 诊断和监测进展的变革性方法。

PROJECT SUMMARY Glaucoma is the leading cause of irreversible blindness and visual impairment in the world. As the disease generally remains asymptomatic until late stages, early detection of functional damage is paramount, so that treatment can be initiated or advanced in order to avoid progression to disability. Detection of functional loss is traditionally made with standard automated perimetry (SAP). However, SAP testing is limited by subjectivity of patient responses and large variability, requiring a large number of tests for detection of change over time. These tests are conducted in clinic-based settings and, due to limited patient availability and health care resources, insufficient tests are usually acquired over time, resulting in delayed detection of progression. The requirement for highly trained technicians, cost, complexity, and lack of portability of SAP also preclude its use for screening of visual field loss in underserved populations. To address shortcomings of current methods to assess visual function, we have developed an innovative brain-computer interface (BCI) that allows portable and objective assessment of visual function loss through multifocal steady-state visual-evoked potentials (mfSSVEP). The BCI consists of a wearable device employing a head-mounted display (HMD) integrated with wireless electroencephalography (EEG). In cross-sectional investigations, we demonstrated that the BCI mfSSVEP parameters were able to successfully detect glaucomatous damage with excellent test-retest repeatability. Based on the encouraging results of the preliminary studies, we now propose a multicenter investigation of the ability of longitudinal BCI mfSSVEP parameters in detecting glaucoma progression. In Specific Aim 1, we will collect longitudinal BCI mfSSVEP data during clinic-based visits in glaucoma patients and healthy subjects. We hypothesize that BCI mfSSVEP data will be able to successfully detect progression and measure rates of change, as compared to functional assessment by SAP and structural assessment by optical coherence tomography. In Aim 2, we will collect home-based longitudinal mfSSVEP data and investigate their performance for detecting glaucoma progression and measuring rates of change. We hypothesize that the increased frequency of testing from home-based BCI testing will result in earlier detection and prediction of progression compared to clinic- based data and conventional testing. In Aim 3, we will investigate the ability of BCI mfSSVEP data in predicting patient-reported quality of life in glaucoma. In summary, this proposal employs a highly innovative BCI device to acquire longitudinal mfSSVEP data with the central aim of improving detection and prediction of glaucoma progression. The approach has the potential to address major current limitations of standard testing, significantly impacting management of the disease. Objective home-based testing of visual function could represent a transformative way of diagnosing and monitoring progression.