A Systematic Review on Retinal Biomarkers to Diagnose Dementia from OCT/OCTA Images.
J Alzheimers Dis Rep
; 7(1): 1201-1235, 2023.
Article
en En
| MEDLINE
| ID: mdl-38025800
Background: Traditional methods for diagnosing dementia are costly, time-consuming, and somewhat invasive. Since the retina shares significant anatomical similarities with the brain, retinal abnormalities detected via optical coherence tomography (OCT) and OCT angiography (OCTA) have been studied as a potential non-invasive diagnostic tool for neurodegenerative disorders; however, the most effective retinal changes remain a mystery to be unraveled in this review. Objective: This study aims to explore the relationship between retinal abnormalities in OCT/OCTA images and cognitive decline as well as evaluating biomarkers' effectiveness in detecting neurodegenerative diseases. Methods: A systematic search was conducted on PubMed, Web of Science, and Scopus until December 2022, resulted in 64 papers using agreed search keywords, and inclusion/exclusion criteria. Results: The superior peripapillary retinal nerve fiber layer (pRNFL) is a trustworthy biomarker to identify most Alzheimer's disease (AD) cases; however, it is inefficient when dealing with mild AD and mild cognitive impairment (MCI). The global pRNFL (pRNFL-G) is another reliable biomarker to discriminate frontotemporal dementia from mild AD and healthy controls (HCs), moderate AD and MCI from HCs, as well as identifing pathological Aß42/tau in cognitively healthy individuals. Conversely, pRNFL-G fails to realize mild AD and the progression of AD. The average pRNFL thickness variation is considered a viable biomarker to monitor the progression of AD. Finally, the superior and average pRNFL thicknesses are considered consistent for advanced AD but not for early/mild AD. Conclusions: Retinal changes may indicate dementia, but further research is needed to confirm the most effective biomarkers for early and mild AD.
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Base de datos:
MEDLINE
Tipo de estudio:
Systematic_reviews
Idioma:
En
Revista:
J Alzheimers Dis Rep
Año:
2023
Tipo del documento:
Article