Retinal Vascular Stress Testing With OCT-A Deformation Maps
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Solution Overview
Problem
Existing ophthalmological techniques fail to consider the interrelationship between intraocular pressure (IOP) changes, mechanical deformation of the eye, and nerve fiber function and blood perfusion in the retina, leading to inadequate early detection and monitoring of retinal diseases like glaucoma, age-related macular degeneration, and diabetic retinopathy.
Innovation Solution
A method and system that combines structural, functional, and biomechanical data to visualize and quantify the relationship between IOP changes, nerve fiber function, and blood perfusion by using optical coherence tomography angiography (OCT-A) scans, visual field analyzers, and mechanical pressure stress tests to generate connectivity models, deformation maps, and thickness maps, allowing for colocalization and prediction of retinal disease progression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing ophthalmological techniques are used to diagnose ocular conditions, then diagnosis can be performed, but early detection capability is insufficient and monitoring of disease progression is inadequate
Solution Approach 1:
The patent combines multiple imaging modalities (OCT, OCT-A, visual field testing) and biomechanical data into a unified retinal stress test system. This integration allows simultaneous assessment of structural integrity, blood perfusion, and mechanical deformation, enabling both early detection and reliable monitoring of disease progression through comprehensive multi-parameter analysis
Solution Approach 2:
The patent introduces biomechanical deformation data as a new dimension of analysis alongside traditional structural and functional imaging. By measuring changes in retinal topology and vascular configuration under controlled pressure, the system adds a mechanical dimension that enhances both early detection sensitivity and monitoring accuracy for glaucoma and other retinal diseases
2Measurement precision
If comprehensive multi-modal imaging is used to capture structural, functional, and biomechanical data, then detection accuracy improves, but system complexity increases
Solution Approach 1:
The patent divides the comprehensive retinal assessment into distinct modular components: structural imaging (OCT), functional imaging (OCT-A), biomechanical testing (pressure-induced deformation), and visual field analysis. Each module can be independently optimized and performed sequentially, reducing overall system complexity while maintaining high detection accuracy through integrated data analysis
3Measurement precision
If multiple imaging data sets are captured at different intraocular pressures, then biomechanical deformation can be measured, but testing time increases
Solution Approach 1:
The patent employs periodic pressure application cycles where intraocular pressure is systematically varied between baseline and elevated levels, allowing capture of retinal responses at different pressure states. This periodic stress testing enables measurement of biomechanical deformation and vascular response without requiring continuous prolonged pressure maintenance, thus reducing total testing time while obtaining comprehensive deformation data
Data Source
AI summary
Relationships between morphological changes to an eye due to intraocular pressure changes and blood perfusion and nerve function changes in the retina are determined by colocalizing retinal perfusion data, optic nerve head (ONH) mechanical deformation data, visual field data and nerve fiber data. Perfusion and nerve function changes from intraocular pressure (IOP) changes are determined by colocalizing retinal perfusion data with ONH mechanical deformation data, visual field data and nerve fiber data. Optical coherence tomography-angiography (OCT-A) can be used to generate retinal perfusion data, mechanical deformation data for an imaged volume, and nerve fiber data. A three-dimensional model (e.g., connectivity map or connectivity model) of the vasculature and nerve fibers can be generated from the OCT-A imaging data and used to predict changes in blood perfusion and nerve function in various areas of the retina due to IOP-induced mechanical deformations.