Retinal Light Scattering Measurements as a Clinical Biomarker of Alzheimer's Disease

视网膜光散射测量作为阿尔茨海默病的临床生物标志物

• 批准号: 10368529
• 负责人: Adam Wax
• 金额: $ 49.32万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-15 至 2027-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10368529
• 关键词: Age; Aging; Alzheimer disease screening; Alzheimer' s Disease; Alzheimer' s disease diagnosis; Alzheimer' s disease diagnostic; Alzheimer' s disease patient; Alzheimer’s disease biomarker; Amyloid deposition; Anatomy; Animal Model; Animals; Autopsy; Barrett Epithelium; Barrett Esophagus; Biological Markers; Cellular Structures; Cerebrospinal Fluid; Cervical; Cervix Uteri; Characteristics; Clinical; Clinical Research; Cone; Crystalline Lens; Data; Data Analyses; Dementia; Descriptor; Detection; Development; Devices; Diagnosis; Diagnostic; Discrimination; Disease; Epithelial; Esophagus; Evaluation; Exclusion Criteria; Future; Ganglion Cell Layer; Glaucoma; Goals; Health; Human; Image; Impaired cognition; Individual; Interferometry; Investigation; Label; Link; Machine Learning; Measurement; Measures; Meta-Analysis; Methods; Morphology; Neuraxis; Neurodegenerative Disorders; Neurology; Nuclear; Onset of illness; Ophthalmology; Optic Nerve; Optical Coherence Tomography; Pathologic; Pathology; Patients; Photophobia; Photoreceptors; Population; Positron-Emission Tomography; Premalignant Cell; Prospective Studies; Recording of previous events; Research; Resolution; Retina; Rod; Scanning; Senile Plaques; Spinal Puncture; Structure; System; Techniques; Technology; Testing; Thick; Thinness; Tissues; Translating; Work; adaptive optics; base; biomarker development; brain tissue; cellular imaging; clinical biomarkers; clinical diagnostics; cost; diagnostic platform; diagnostic tool; early onset; functional disability; in vivo; light scattering; machine learning algorithm; mouse model; nephelometry; new technology; novel; organizational structure; prevent; retinal imaging; retinal nerve fiber layer

Project Summary The overall objective of this proposal is to demonstrate the clinical feasibility of a novel method Although deposition of amyloid plaques in brain tissue is the clearest pathological indicator of AD, it can only be detected during autopsy or positron emission tomography (PET) imaging, which can be prohibitively expensive. As a result, the most widely used approach for diagnosing AD continues to be the clinical recognition of cognitive impairment, a subjective evaluation which only provides probable diagnosis when other causes of dementia are eliminated. Because the optic nerve and retina are extensions of the central nervous system, several investigations to seek have sought to link retinal features with onset of the disease. Using optical coherence tomography (OCT), a correlation has been observed between thinning of the retinal nerve fiber layer and AD but this feature can also indicate other diseases. Instead, we propose to develop a diagnostic based on measuring structural features in the various layers of the retina, specifically to identify a diagnostic metric of AD that is potentially distinct from other pathologies. To meet this objective, we seek to develop angle-resolved low coherence interferometry (a/LCI) for clinical measurement of structural features of retinal layers. a/LCI is a light scattering method that combines the sub-cellular sensitivity of light scattering with the depth resolution of OCT. It has been shown to detect precancerous cells in esophagus and cervix using in vivo depth resolved measurements of nuclear morphology. Rather than imaging the cellular structure of the retina directly, we instead propose to use a/LCI to measure the micron-scale structural characteristics of retinal layers. Preliminary data shows that a/LCI measurements of the organization of these structures correlates with presence of AD in a murine model. The following Specific Aims are proposed: 1. Implement integrated a/LCI & OCT system for in vivo studies of the human retina. 2. Characterize retinal features in AD patients with a/LCI & OCT. This study will confirm measurements from the animal model and provide data for establishing biomarkers of AD in humans. 3. Conduct data analysis for biomarker development using morphological descriptors and machine learning. 4. Perform in vivo prospective studies in AD patients to validate biomarkers of structural changes as predictive of disease. Upon completion of this project, we will have shown feasibility and provided justification for future development of a combined a/LCI & OCT system for clinical screening for AD.

项目摘要 该提案的总体目的是证明一种新方法的临床可行性 虽然淀粉样蛋白斑块在脑组织中的沉积是最清晰的病理 AD指标，只能在尸检或正电子发射断层扫描（PET）中检测到它 成像，可能非常昂贵。结果，最广泛使用的方法 诊断AD继续是对认知障碍的临床认可，这是一种主观 仅当消除其他痴呆症原因时才能提供可能诊断的评估。 因为视神经和视网膜是中枢神经系统的扩展 寻求的调查试图将视网膜特征与疾病发作联系起来。使用光学 相干断层扫描（OCT），在视网膜变薄之间观察到相关性 神经纤维层和AD，但此功能也可以指示其他疾病。相反，我们建议 为了根据视网膜各个层中的结构特征进行测量的诊断， 专门用于识别可能与其他病理学不同的AD诊断指标。 为了满足这一目标，我们试图开发垂直分辨的低相干干涉法（A/LCI） 用于视网膜层结构特征的临床测量。 A/LCI是一种轻散射方法 这将光散射的亚细胞灵敏度与OCT的深度分辨率结合在一起。它 已显示出使用体内深度检测食道和子宫颈的癌前细胞 解决核形态的测量。而不是成像 直接的视网膜，我们建议使用A/LCI测量微米级结构 视网膜层的特征。初步数据表明，A/LCI的测量值 这些结构的组织与鼠模型中的AD存在相关。下列 提出了具体目的：1。实施集成的A/LCI和OCT系统，用于体内研究 人类视网膜。 2。表征A/LCI和OCT的AD患者的视网膜特征。这项研究 将确认动物模型的测量，并提供建立生物标志物的数据 人类的广告。 3。使用形态学进行生物标志物开发的数据分析 描述符和机器学习。 4。对AD患者进行体内前瞻性研究以验证 结构变化的生物标志物作为疾病的预测。该项目完成后，我们将 已经显示出可行性，并为将来的A/LCI合并提供了理由 AD临床筛查的OCT系统。