Thursday, April 25, 2024
4/25/2024
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.
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