Clinical Relevance Retinal imaging provides a non-invasive method for the early diagnosis of Alzheimer’s disease. Early identification of RNFL thinning, impaired vasculature, and electrophysiological alterations through routine examinations can be helpful in referrals, risk stratification, and follow-up for early intervention. This allows optometrists to have an important impact on neurodegenerative diseases. Background Convergence of Research Evidence Related to Retinal Biomarkers in Early Alzheimer’s Disease (AD): The aim of this work is to provide an overview of the most recent research evidence regarding retinal biomarkers for identifying very early changes associated with AD. Additionally, the purpose of this work is to provide a comprehensive view of the emerging diagnostic value for multimodal retinal imaging technologies. Methods A review of peer-reviewed studies investigating the effects of structural retinal changes, vascular changes and electrical functional changes of the retina on the neurophysiology of patients with AD has been conducted. The evidence from Optical Coherence Tomography (OCT); OCT-angiography (OCT-A), hyperspectral imaging, adaptive optics, electroretinography (ERG), visual evoked potentials (VEP), pupillometry and deep learning-based Photoretinal Analysis have been collected and reviewed to create a framework for the early detection of Alzheimer’s Disease based on retinal characteristics. Results Study results identified that AD has been associated with patterns of retinal thinning cross modally across the RNFL, Ganglion Cell Layer, Ganglion Cell Complex and varying degrees of micro vascular degeneration based upon findings observed in OCT-A. Study results also identified the presence of amyloid-β and tau proteins expressed physiologically within retinal tissue based on Molecular Imaging and an increase in response latency and reduction in amplitude of pERG and spVEP responses when compared to normal healthy controls suggestive of increased neurodegeneration of the posterior retina experienced by AD subjects. AI diagnostic models demonstrated a significant improvement in early detection of AD by identifying latent structural or spectral characteristics that were undetectable by human observer methods. Conclusions The findings regarding retinal neuroimaging indicate that the retina offers a unique vantage point for the detection of pathological retinal changes that mimic the changes that occur with neurodegeneration as seen in AD. The development of next generation retinal imaging technology will enable retinal biomarkers to evolve from an experimental tool to a standard method for the noninvasive identification of greater than preclinical amounts of retinal change associated with Alzheimer’s Disease. As such, optometrists due to their access to a broad range of patients and their frequency of patient contact will be pivotal in the adoption and integration of retinal neuro diagnostics into future dementia-related treatment pathways.