Diagnostic Innovations in Glaucoma: Clinical Electrophysiology

描述（由申请人提供）：本申请旨在研究临床电生理测量（图形视网膜电图，PERG;和多焦视觉诱发电位，mfVEP）检测青光眼的诊断精度，该技术被2004年国家眼科研究所（NEI）国家计划确定为眼科研究中重要的青光眼相关最新进展。目标1：将对青光眼、可疑眼和健康眼的电生理反应进行表征，并将这些市售技术的诊断准确性与当前的参考标准进行比较（评价视盘的立体照片和标准自动视野检查）和最近开发的诊断技术，包括视盘和视网膜神经纤维层（RNFL）的光学成像（共焦扫描激光检眼镜检查、光学相干断层扫描和扫描激光偏振法）和视觉功能特异性视野检查（短波长自动视野检查和倍频技术视野检查）。目标二：机器学习分类器技术（例如，相关向量机、支持向量机、高斯混合技术、独立分量分析）的新用途将应用于电生理数据，以提高其诊断准确性，并且将组合来自不同诊断技术（如上所述）的数据，以提高整体诊断准确性。目标3：通过检查青光眼和青光眼疑似患者的电生理异常与视盘和RNFL损伤之间的关系，将电生理测量结果作为视神经损伤的功能指标进行验证。将招募210名患者（105名青光眼患者，105名青光眼疑似患者）和105名健康受试者并进行横断面研究。该提案的具体目的是解决当前NEI青光眼和视神经病变项目的目标，即开发改进的诊断措施以表征和检测视神经疾病发作，确定视神经损伤的功能相关性，并在结构和功能水平上表征视觉通路内的青光眼性神经变性。关于青光眼检测的电生理测量、光学成像技术和神经节细胞特异性视野检查的相对有用性的信息对于临床社区确定青光眼诊断和监测护理标准的未来循证变化非常重要。这些研究将证明与光学成像技术（共焦扫描检眼镜、光学相干断层扫描、扫描激光偏振法）和神经节细胞特异性视野检查（短波长和倍频视野检查）相比，电生理测量（图形视网膜电图，PERG;多焦视觉诱发电位，mfVEP）在青光眼检测中的相对有用性。该提案解决了当前NEI青光眼和视神经病变计划的目标，即开发改进的诊断措施，以表征和检测视神经疾病发作，确定视神经损伤的功能相关性，并在结构和功能水平上表征视觉通路内的青光眼性神经变性。这些发现对于临床社区确定未来青光眼诊断和监测护理标准的循证变化非常重要。

DESCRIPTION (provided by applicant): This application proposes to investigate the diagnostic precision for detecting glaucoma of clinical electrophysiological measurement (pattern electroretinogram, PERG; and multifocal visual evoked potentials, mfVEP), a technique identified as an important recent glaucoma- related development in eye research by the 2004 National Eye Institute (NEI) National Plan. Aim 1: Electrophysiological responses will be characterized in glaucoma, suspect and healthy eyes and the diagnostic accuracy of these commercially available techniques will be compared to current reference standards (evaluation of stereoscopic photographs of the optic disc and standard automated perimetry) and to recently developed diagnostic techniques including optical imaging of the optic disc and retinal nerve fiber layer (RNFL) (confocal scanning laser ophthalmoscopy, optical coherence tomography, and scanning laser polarimetry) and visual function-specific perimetry (short-wavelength automated perimetry and frequency doubling technology perimetry). Aim 2: Novel use of machine learning classifier techniques (e.g. relevance vector machines, support vector machines, mixture of Gaussian techniques, independent components analysis) will be applied to electrophysiological data to improve its diagnostic accuracy and data from different diagnostic techniques (named above) will be combined to improve overall diagnostic accuracy. Aim 3: Electrophysiological measurements will be validated as functional indicators of optic nerve damage by examining the relationship between electrophysiological abnormality and optic disc and RNFL damage in glaucoma and glaucoma suspect patients. 210 patients (105 glaucoma's, 105 glaucoma suspects) and 105 healthy participants will be enrolled and studied cross-sectionally. The specific aims of this proposal address the current NEI Glaucoma and Optic Neuropathies Program objectives of developing improved diagnostic measures to characterize and detect optic nerve disease onset, determining functional correlates of optic nerve damage, and characterizing glaucomatous neurodegeneration within the visual pathways at structural and functional levels. Information about the relative usefulness of electrophysiological measurement, optical imaging techniques, and ganglion cell-specific perimetry for glaucoma detection is important to the clinical community for determining future evidence-based changes in standard of care for glaucoma diagnosis and monitoring. These studies will demonstrate the relative usefulness of electrophysiological measurement (pattern electroretinogram, PERG; multi-focal visual evoked potential, mfVEP) compared to optical imaging techniques (confocal scanning ophthalmoscopy, optical coherence tomography, scanning laser polarimetry) and ganglion cell-specific perimetry (short wavelength and frequency doubling perimetry) for glaucoma detection. The proposal addresses the current NEI Glaucoma and Optic Neuropathies Program objectives of developing improved diagnostic measures to characterize and detect optic nerve disease onset, determining functional correlates of optic nerve damage, and characterizing glaucomatous neurodegeneration within the visual pathways at structural and functional levels. Findings will be important to the clinical community for determining future evidence-based changes in standard of care for glaucoma diagnosis and monitoring.