HYPERSPECTRAL IMAGING FOR EARLY DETECTION OF ALZHEIMER'S DISEASE

Smart overview of the Invention

The application introduces a method utilizing visible near infrared (VNIR) hyperspectral imaging for the early detection of Alzheimer's Disease (AD). This non-invasive diagnostic tool aims to identify AD before the formation of β-amyloid plaques, which are typically detectable only after cognitive symptoms appear. By capturing hyperspectral images (HSI) of the retina, this method seeks to identify spectral differences indicative of AD, potentially allowing for earlier intervention and treatment.

Technical Specifications

The VNIR hyperspectral imaging system operates within wavelengths up to about 2500 nm, focusing primarily between 400 nm and 1000 nm. This system captures detailed spectral data from the retina, enabling comparison with previous images or reference standards. Significant spectral variations between these images may indicate the presence or predisposition to AD. The technology can be applied to a wide age range, particularly targeting individuals aged 30-80 years.

Applications in Treatment and Research

Beyond diagnosis, the hyperspectral imaging system is also applicable in evaluating therapeutic efficacy against AD. By monitoring changes in spectral differences over time, researchers can assess whether treatments reduce indicators of AD. Additionally, the system facilitates high throughput screening of compounds for their ability to affect β-amyloid aggregation, providing insights into potential therapeutic agents.

Research Findings

The patent includes detailed experimental results demonstrating the system's capabilities. Experiments on cells and tissue samples reveal that this imaging technique can detect spectral changes associated with β-amyloid peptide uptake and aggregation. These findings are supported by figures showing significant spectral differences in treated versus untreated samples, as well as in AD versus normal tissue.

Advanced Imaging Techniques

Hyperspectral imaging integrates conventional imaging with spectrophotometry, allowing for pixel-level spectral quantification. The use of a Cytoviva microscope assembly exemplifies this integration, providing enhanced signal-to-noise ratios and detailed spectral analysis. This approach extends beyond visible light analysis, offering deeper insights into cellular changes related to AD progression.