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.

项目概要 该提案的总体目标是证明一种新方法的临床可行性 尽管脑组织中淀粉样斑块的沉积是最明显的病理学特征。 AD 的指标，只能在尸检或正电子发射断层扫描 (PET) 过程中检测到 成像，这可能非常昂贵。因此，最广泛使用的方法是 诊断 AD 仍然是对认知障碍的临床识别，这是一种主观的认知障碍 仅在消除痴呆症的其他原因后才能提供可能的诊断的评估。 由于视神经和视网膜是中枢神经系统的延伸，因此 寻求的研究试图将视网膜特征与疾病的发作联系起来。使用光学 相干断层扫描（OCT），观察到视网膜变薄之间存在相关性 神经纤维层与AD有关，但这一特征也可以预示其他疾病。相反，我们建议 开发基于测量视网膜各层结构特征的诊断方法， 专门用于确定 AD 的诊断指标，该指标可能与其他病理学不同。 为了实现这一目标，我们寻求开发角度分辨低相干干涉测量法 (a/LCI) 用于临床测量视网膜层的结构特征。 a/LCI 是一种光散射方法 它结合了光散射的亚细胞敏感性和 OCT 的深度分辨率。它 已被证明可以使用体内深度检测食道和子宫颈中的癌前细胞 核形态的解析测量。而不是对细胞结构进行成像 直接视网膜，我们建议使用 a/LCI 来测量微米级结构 视网膜层的特征。初步数据显示，a/LCI 测量值 这些结构的组织与小鼠模型中 AD 的存在相关。下列 提出的具体目标： 1. 实施集成的 a/LCI 和 OCT 系统，用于体内研究 人类视网膜。 2. 使用 a/LCI 和 OCT 表征 AD 患者的视网膜特征。这项研究 将确认动物模型的测量结果并为建立生物标志物提供数据 人类 AD 的发生。 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. 在 AD 患者中进行体内前瞻性研究以验证 作为疾病预测的结构变化的生物标志物。该项目完成后，我们将 已经证明了可行性，并为未来发展 a/LCI 和 用于 AD 临床筛查的 OCT 系统。