Retinal Polarized Imaging for Amyloid Classification and Early Diagnosis
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Solution Overview
Problem
Current methods for diagnosing neurodegenerative diseases like Alzheimer's disease are invasive, expensive, or not widely available, lacking a sensitive and specific means for early and accurate diagnosis, and there is a need for a non-invasive, cost-effective method to detect and quantify protein deposits in the retina for differential diagnosis and severity assessment.
Innovation Solution
An optical imaging method using polarized light and multiple wavelengths to classify protein deposits in the retina, employing machine learning algorithms to differentiate between amyloid and other proteins, determine their type, position, and severity, and infer brain conditions based on retinal findings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If invasive methods (CSF analysis, genetic markers) are used to detect neurodegenerative diseases, then diagnostic accuracy is improved, but patient comfort and accessibility deteriorate
Solution Approach 1:
The patent uses the retina as an intermediary tissue to detect brain pathology. Instead of directly sampling brain tissue or CSF, the system images protein deposits in the retinal tissue, which serve as a window to brain conditions. This intermediary approach maintains diagnostic accuracy while eliminating invasiveness.
Solution Approach 2:
The patent creates an optical copy of the retinal tissue's light scattering properties through Mueller matrix imaging. This non-invasive optical copying technique captures the structural information of protein deposits without physical contact or intervention, replacing invasive sampling methods.
2Measurement precision
If brain scans (MRI, PET) are used to detect neurodegenerative diseases, then diagnostic capability is improved, but cost and availability deteriorate
Solution Approach 1:
The patent employs standard ophthalmic imaging equipment and widely available optical components rather than expensive specialized scanners. By using accessible technology platforms already present in clinical settings, the system dramatically reduces cost while maintaining detection capability.
Solution Approach 2:
The patent makes the imaging system multi-functional by using a single optical platform to perform both standard retinal imaging and specialized Mueller matrix polarimetry for protein deposit detection. This universal approach eliminates the need for separate expensive specialized equipment.
3Device complexity
If single-wavelength optical imaging is used to image retinal tissue, then simplicity is improved, but classification accuracy of protein deposits deteriorates
Solution Approach 1:
The patent adds spectral dimensionality by implementing multi-wavelength imaging across the visible spectrum. Instead of relying solely on spatial information from single-wavelength images, the system incorporates wavelength-dependent light scattering properties as an additional dimension for differentiating protein types.
Solution Approach 2:
The patent systematically varies the wavelength parameter of illuminating light to probe different scattering mechanisms. By changing this physical parameter across multiple wavelengths, the system extracts enhanced spectral signatures that improve protein classification accuracy.
4Measurement precision
If polarized light imaging is used to differentiate protein deposits, then classification ability is improved, but system complexity deteriorates
Solution Approach 1:
The patent merges polarized light imaging with multi-wavelength spectroscopy into a unified Mueller matrix measurement system. This combination integrates polarization state analysis with spectral information, achieving enhanced classification ability while managing system complexity through integrated optical design.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Provides a non-invasive, cost-effective, and accurate method for diagnosing neurodegenerative diseases by classifying protein deposits in the retina, enabling early detection and assessing disease severity, with potential applications in both human and animal models.
Implementation Method 1
a system for imaging that uses more than one colour for said imaging. Said system is combined with the previously patented use of polarized light
Implementation Method 2
Optical imaging of the brain has been proposed but this is most suitable for imaging through the thinner skull of rodent models of the disease, rather than through the human skull. The presence of Aβ in neural tissue is recognized as indicative of Alzheimer's disease.
Data Source
AI summary
The present disclosure provides methods and an apparatus for imaging and analysing images of presumed protein deposits in the retina, retinal tissue or retinal structures and discloses methods differentiating or classifying these deposits and other optical signals from retinal structures into 1) whether they contain or do not contain classes, of proteins or protein deposits called amyloids or other proteins and/or protein deposits related to neurodegenerative eye and brain disease(s); 2) which type(s) of amyloid or other proteins or protein deposits they contain, as well as 3) whether the form and/or properties of the deposit are associated with a class of diseases or with one or another specific condition(s) (or disease(s)); whether or not this is a disease or class of disease associated with the retina or more generally with the nervous system, including the brain or 4) classified as associated with one or another level of severity of condition(s), or disease(s).