Automated assessment of glaucoma loss from optical coherence tomography
Inventors
Abramoff, Michael • Sonka, Milan
Assignees
University of Iowa Research Foundation UIRF • US Department of Veterans Affairs
Publication Number
US-11972568-B2
Publication Date
2024-04-30
Expiration Date
2033-03-15
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Abstract
Systems and methods for assessing glaucoma loss using optical coherence topography. One method according to an aspect comprises receiving optical coherence image data and assessing functional glaucoma damage from retinal optical coherence image data. In an aspect, the systems and methods can map regions and layers of the eye to determine structural characteristics to compare to functional characteristics.
Core Innovation
The invention provides systems and methods for assessing glaucoma loss using optical coherence tomography (OCT). The methods include receiving optical coherence image data and assessing functional glaucoma damage from retinal OCT image data. The systems and methods can map regions and layers of the eye to determine structural characteristics and compare them to functional characteristics such as visual field sensitivity.
The issue being addressed is the limitation in reliable detection and monitoring of glaucoma damage through current clinical standards. Automated perimetry and clinical assessment of optic nerve cup, while standard, have limitations especially once moderate visual field loss occurs, due to high retest variability and limited dynamic range in structural measurements. Existing OCT measurements such as peripapillary retinal nerve fiber layer (PP-NFL) and ganglion cell layer (GCL) thickness reach a floor in advanced glaucoma, limiting their clinical utility in assessing functional deficits that extend beyond certain thresholds.
The disclosed approach introduces more sophisticated structural indices based on retinal ganglion cell (RGC) anatomy, rather than single layer thicknesses, to increase dynamic range matching that of the visual field (VF). The methods include automated segmentation of retinal layers using graph search and voxel classification algorithms applied to spectral-domain OCT (SD-OCT) images. Mapping of the retinal ganglion cell-axonal complex (RGC-AC) connectivity between macular ganglion cells, nerve fiber bundles (NFB), and optic nerve head (ONH) regions is performed using correlation analysis of thickness measurements across these regions. The systems establish and utilize baseline predictive models correlating structural OCT data to functional VF data, improving glaucoma damage assessment and potentially reducing test burden.
Claims Coverage
The patent includes multiple independent claims covering methods and systems for analyzing OCT images to assess cell layer thickness, mapping connectivity, and determining correlations for glaucoma damage evaluation. Key inventive features describe image processing, grid-based regional analysis, correlation-based mapping, and determination of retinal connectivity paths.
Image-based assessment of cell layer thickness correlations
A method or system receives an image and determines thickness of a cell layer within regions of interest. It calculates correlations between the cell layer thickness and multiple nerve regions and selects nerve regions indicative of macular damage based on highest correlations.
Grid generation for regions of interest
Generating regions of interest based on image grids including nerve fiber bundle (NFB) grids, macular grids that are subsets of NFB grids, and optic nerve head (ONH) grids. Grid regions are sized based on scaling factors defined by anatomical landmarks such as the distance from fovea to neural canal opening.
Connectivity path determination within retinal structures
Determining connectivity paths of the cell layer to nerve fiber bundle segments and selecting paths with highest cumulative correlations among possible retinal segment paths, mapping connectivity between macular ganglion cell layers, NFB, and ONH neural rim regions.
Automated multi-layer retinal image segmentation and analysis
Utilizing multi-dimensional graph search segmentation on spectral-domain OCT volumes to segment intraretinal layers including NFL, GCL, and combined outer segment and retinal pigment epithelium layers, facilitating structural index computation.
The claims cover techniques for detailed image-based structural analysis of retinal layers, grid-based regional correlation and mapping of retinal connectivity, and use of these determinations for assessing glaucoma damage, embodied in methods, systems, and computer-readable media.
Stated Advantages
Improved ability to stage glaucoma disease over the entire spectrum by correlating objective structural measurements with functional loss.
Enhanced capacity to detect and confirm functional changes through corresponding structural changes, aiding glaucoma progression detection.
Reduced patient testing burden and variability by enabling more frequent and objective structural testing with OCT compared to visual field testing.
Feasibility of objective glaucoma damage assessment in patients unable to perform visual field tests, such as very young or elderly patients with limitations.
Highly reproducible automated segmentation and quantification of retinal layers and optic nerve head structures improving diagnostic accuracy.
Documented Applications
Assessment of glaucoma damage by mapping retinal ganglion cell body and axonal complex damage along defined anatomical trajectories using SD-OCT imaging.
Prediction of visual function from structural OCT parameters to reduce the need for frequent subjective functional testing like Humphrey visual field.
Use of multi-field OCT registered composite images (7- or 9-field) correlated with 24-2 visual field test data for improved glaucoma evaluation.
Automated segmentation and quantification of intraretinal layers and optic nerve head structures to provide objective metrics for glaucoma diagnosis and monitoring.
Development of predictive and classification models relating OCT structural indices to functional visual field sensitivity to improve clinical decision-making.
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