Hyperspectral Retinal Imaging as a Non-Invasive Marker to Determine Brain Amyloid Status.

Background: As an extension of the central nervous system (CNS), the retina shares many similarities with the brain and can manifest signs of various neurological diseases, including Alzheimer's disease (AD).

Objective: To investigate the retinal spectral features and develop a classification model to differentiate individuals with different brain amyloid levels.

Methods: Sixty-six participants with varying brain amyloid-β protein levels were non-invasively imaged using a hyperspectral retinal camera in the wavelength range of 450-900 nm in 5 nm steps.

Ocular biomarkers: useful incidental findings by deep learning algorithms in fundus photographs.

Background/objectives: Artificial intelligence can assist with ocular image analysis for screening and diagnosis, but it is not yet capable of autonomous full-spectrum screening. Hypothetically, false-positive results may have unrealized screening potential arising from signals persisting despite training and/or ambiguous signals such as from biomarker overlap or high comorbidity. The study aimed to explore the potential to detect clinically useful incidental ocular biomarkers by screening fundus photographs of hypertensive adults using diabetic deep learning algorithms.

Innovative diagnostic tools for early detection of Alzheimer's disease.

Current state-of-the-art diagnostic measures of Alzheimer's disease (AD) are invasive (cerebrospinal fluid analysis), expensive (neuroimaging) and time-consuming (neuropsychological assessment) and thus have limited accessibility as frontline screening and diagnostic tools for AD. Thus, there is an increasing need for additional noninvasive and/or cost-effective tools, allowing identification of subjects in the preclinical or early clinical stages of AD who could be suitable for further cognitive evaluation and dementia diagnostics. Implementation of such tests may facilitate early and potentially more effective therapeutic and preventative strategies for AD.

Pupil response biomarkers distinguish amyloid precursor protein mutation carriers from non-carriers.

Context: Alzheimer's disease (AD) is usually only diagnosed many years after pathology begins. Earlier detection would allow emerging interventions to have a greater chance to preserve healthy brain function. A rare form of Alzheimer's disease, caused by autosomal-dominant mutations, affects carriers with 100% certainty and at a younger age specific to their mutation.