Development, validation and assessment of an automated, topographic structure-function approach to the detection of glaucoma and its progression

项目概要/摘要 没有单一的（石蕊）测试来确认青光眼的存在或进展，这是一组视觉检查。 神经病因此，临床医生依赖于结构和功能测试的特征性变化来诊断 并监测疾病。越来越多的证据挑战了“结构先于 功能”。研究表明，诸如基线患者状况、测试范例和测试结果等因素 措施可以影响结构性和功能性昏迷性损害的程度。研究 报告说，通过视野（VF）测试评估的功能损伤和结构损失， 通过光学相干断层扫描（OCT）视网膜神经纤维层（RNFL）厚度的测量进行评价， 通常以线性方式重合。事实上，查米斯博士和他的导师最近的工作 一个研究小组（Hood教授和De Moraes博士）提供的证据表明，宽视野OCT扫描的地形方法 基于R算法的24 - 2和10 - 2VF可以识别异常结构-异常功能 与90%以上的早期青光眼损害一致。本提案的总体目标是 评估局部结构-功能评价在青光眼诊断和检测中的能力， 进展在K99阶段，将对工具算法进行改进，以提高其性能 早期青光眼的鉴别它还将扩展到包括其他类型的OCT扫描 协议（例如，圆扫描），以及来自其他制造商的扫描，以扩展该方法的实用性。 与此同时，Tsamis博士将接受数据科学和统计方面的广泛培训，以提高 他的技能，支持他的职业发展，并提供了一条通往研究独立的道路。他将利用 这些技能在R00阶段，以开发用于检测青光眼的地形图评估方法 早期和晚期青光眼的进展。将对新开发的技术进行评估 对照临床参考标准以及对照其他常规方法，这些方法可在 青光眼诊所这项研究在多个层面上具有转化潜力。第一，VF-OCT 地形评估应在评估的敏感性和准确性之间提供更好的平衡 比现有的方法更快的发展速度。这将减少患者就诊的频率 和试验.其次，开发的R算法有可能提供一个标准化的工具，以进一步 提高我们对肿瘤表型的理解和评估，以及它们与 结构状态在某种程度上受临床主观性的影响较小。最后，所提出的方法可以加速 设计和实施青光眼临床试验（例如神经保护）， 建立更好的结构-功能终点，提供疾病及其 进展这将导致研究人群规模和临床试验持续时间的减少， 他们的成本。

Project Summary / Abstract There is no single (litmus) test to confirm the presence or the progression of glaucoma, a group of optic neuropathies. Therefore, clinicians rely on characteristic changes on structural and functional tests to diagnose and monitor the disease. There is increasing evidence that challenge the old notion that “structure precedes function”. Research has shown that factors, such as baseline patient conditions, test paradigms, and test measures can affect the extent to which structural and functional glaucomatous damage agree. Studies have reported that functional damage, assessed by means of visual field (VF) testing, and structural loss, as evaluated by measures of optical coherence tomography (OCT) retinal nerve fiber layer (RNFL) thickness, typically coincide, often in a linear manner. As a matter of fact, recent work by Dr. Tsamis and his mentoring team (Prof Hood and Dr. De Moraes) provided evidence that a topographic approach of widefield OCT scans and 24-2 and 10-2 VFs, based on an R algorithm, can identify abnormal structure – abnormal function agreement in over 90% of eyes with early glaucomatous damage. The overarching goal of this proposal is to assess the capability of a topographic structure-function evaluation in glaucoma diagnosis and detection of progression. During the K99 phase, the tool-algorithm will be refined with the aim of improving its performance in the identification of early glaucomatous eyes. It will also be expanded to include other types of OCT scan protocols (e.g., circle scans), as well as scans from other manufacturers to extend the utility of this approach. At the same time, Dr. Tsamis will undergo extensive training in data science and statistics in order to enhance his skills, support his career development and provide a pathway towards research independency. He will use these skills during the R00 phase to develop a method of topographic assessment for detection of glaucoma progression in eyes with early and advanced glaucoma. The newly developed technique will be evaluated against a clinical reference standard as well as against other conventional methods, which are available in the glaucoma clinic. The proposed research has translational potential at multiple levels. First, the VF-OCT topographic assessment should provide a better balance between sensitivity and accuracy for the assessment of rates of progression than currently available methods. This should lead to reduced frequency of patient visits and testing. Second, the developed R algorithm has the potential to provide a standardized tool to further improve our understanding and assessment of glaucomatous phenotypes and their association with the structural status in a way less influenced by clinical subjectivity. Last, the proposed method could accelerate the design and conduction of clinical trials in glaucoma (e.g. neuroprotection) by demonstrating and establishing better structure-function endpoints, providing surrogate measures of the disease and its progression. This should lead to a reduction in study population size and duration of clinical trials, and thus their costs.