FD-OCT Retinal Map Analysis for Glaucoma Detection
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Solution Overview
Problem
Current methods for diagnosing glaucoma are inadequate for early detection due to difficulty in detecting retinal ganglion cell loss and anatomical changes, relying heavily on visual field deficits and optic nerve cupping, which can precede detectable function loss by up to 5 years, and existing optical coherence tomography techniques lack reliable methods for computing diagnostic parameters from imaging data.
Innovation Solution
A method involving novel scanning patterns and image processing techniques using Fourier-domain optical coherence tomography (FD-OCT) to acquire and analyze macular maps, constructing three-dimensional thickness maps, and computing diagnostic parameters such as focal loss volume and global loss volume to detect and diagnose optic neuropathies, including glaucoma, by identifying abnormal retinal thickness and ganglion cell complex loss.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional diagnostic methods (visual field tests and optic nerve cupping assessment) are used, then clinical diagnosis can be made, but early detection capability is poor because structural changes precede functional loss by up to 5 years
Solution Approach 1:
The patent applies preliminary action by detecting structural changes in the retinal ganglion cell layer and nerve fiber layer before functional vision loss occurs. The method measures thickness changes and pattern deviations in the inner retinal layers that precede detectable visual field defects, enabling early intervention 5 years before conventional methods would detect the disease.
Solution Approach 2:
The patent replaces conventional mechanical/clinical examination methods (slit-lamp ophthalmoscopy, visual field testing) with optical coherence tomography imaging and automated pattern analysis. This substitution enables objective, quantitative measurement of retinal layer thickness and structural changes that are not detectable by traditional clinical examination.
2Measurement precision
If optical coherence tomography is used to measure retinal layer thickness, then diagnostic information can be obtained, but reliable methods for computing diagnostic parameters from imaging data are insufficient
Solution Approach 1:
The patent applies segmentation by dividing the retinal structure into distinct inner layers (nerve fiber layer, ganglion cell layer, inner plexiform layer) and analyzing each layer's thickness and pattern separately. This segmentation enables precise measurement of specific structural changes in different retinal regions, providing diagnostic specificity that improves glaucoma detection accuracy.
Solution Approach 2:
The patent introduces pattern deviation maps as an intermediary computational step that transforms raw OCT thickness measurements into diagnostic parameters. The pattern deviation map compares measured thickness values against age-matched normative data and highlights statistically significant deviations, providing a bridge between raw imaging data and clinical diagnosis.
3Measurement precision
If overall retinal thickness measurements are taken, then general diagnostic information is obtained, but diagnostic specificity is reduced because the NFL is thickest near the optic nerve head where glaucomatous changes occur
Solution Approach 1:
The patent applies local quality by focusing measurements on specific high-diagnostic-value regions: the peripapillary area near the optic nerve head where the nerve fiber layer is thickest and most susceptible to glaucomatous damage, and the macular region containing the ganglion cell layer. The method weights and analyzes thickness measurements differently across these distinct regions to maximize diagnostic specificity for glaucoma detection.
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
Enables early detection and quantification of retinal ganglion cell population changes, improving diagnostic specificity and sensitivity for glaucoma and other optic neuropathies, facilitating earlier intervention and more accurate diagnosis.
Implementation Method 1
acquire FD-OCT images of a subject's macular region
Data Source
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AI summary
Methods for analyzing retinal tomography maps to detect patterns of optic nerve diseases such as glaucoma, optic neuritis, anterior ischemic optic neuropathy are disclosed in this invention. The areas of mapping include the macula centered on the fovea, and the region centered on the optic nerve head. The retinal layers that are analyzed include the nerve fiber, ganglion cell, inner plexiform and inner nuclear layers and their combinations. The overall retinal thickness can also be analyzed. Pattern analysis are applied to the maps to create single parameter for diagnosis and progression analysis of glaucoma and optic neuropathy.