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-10354384-B2
Publication Date
2019-07-16
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), specifically spectral-domain OCT (SD-OCT). These methods involve receiving OCT image data, segmenting retinal layers such as the macular ganglion cell layer (GCL) and nerve fiber layer (NFL), and mapping structural characteristics along patient-specific retinal ganglion cell-axonal complex (RGC-AC) trajectories to predict glaucoma visual function. By analyzing SD-OCT images, the systems derive structural indices that correlate better with visual field (VF) loss than existing OCT measurements, enabling automated, objective assessment of functional glaucoma damage.
The problem addressed is the limitation in current clinical methods for detecting and monitoring glaucoma. Visual field testing, the standard functional assessment, has high test-retest variability especially in moderate to advanced glaucoma, reducing reliability. Existing OCT structural parameters like global NFL and GCL thickness have limited dynamic range and correlate poorly with functional loss when the VF deficit exceeds about −10 dB. There is a need for tighter structural-functional (S-F) correlation and increased dynamic range of OCT structural measures that align better with visual function to improve disease staging and monitoring of progression.
The invention addresses these problems by introducing more sophisticated structural indices based on RGC anatomy and by mapping RGC-AC trajectories that connect the macular GCL, nerve fiber bundles in the NFL, and optic nerve head (ONH) regions. The systems employ automated graph-based segmentation and multi-field OCT registration to quantify layer thickness and texture regionally. By correlating these with visual field thresholds and identifying connectivity paths with maximum structural correlation, the methods improve functional prediction from structure, minimize patient testing burden, and provide assessment options for patients unable to perform reliable perimetry.
Claims Coverage
The patent contains two independent claims, one method claim and one system claim, both covering the assessment of glaucoma damage from spectral-domain OCT images through mapping structural correlations within the retinal ganglion cell-axonal complex.
Mapping retinal ganglion cell-axonal complex connectivity to assess glaucoma damage
Receiving SD-OCT images and determining macular ganglion cell layer thickness in regions of interest; calculating correlation sets between GCL thickness and multiple optic nerve head (ONH) regions; selecting ONH regions exhibiting highest correlation as indicative of macular damage; determining connectivity paths between GCL and multiple nerve fiber bundle (NFB) segments within regions; and identifying retinal ganglion cell-axonal complex (RGC-AC) segment paths having highest cumulative correlation among all possible paths.
Defining and utilizing retinal grids based on scaling factor for regional analysis
Generating retinal grids including nerve fiber bundle (NFB) grid, macular grid (a subset of the NFB grid), and ONH grid, with grid region sizes scaled according to a distance between image landmarks such as the fovea and center of the neural canal opening; using these grids to partition SD-OCT images into functionally and structurally relevant regions for analysis.
Mapping structural connectivity within the retina and optic nerve head using OCT
Mapping connectivity between GCL and neural rim of the ONH, mapping connectivity between GCL and initial and final NFB segments to the ONH, and mapping connectivity between at least two NFBs within an NFB region to characterize the structural-functional relationships in glaucoma.
The independent claims cover methods and systems that process SD-OCT images to segment retinal layers, define region-based retinal grids scaled to anatomical landmarks, and construct retinal ganglion cell-axonal complex connectivity paths based on structural correlations for improved assessment of glaucoma damage.
Stated Advantages
Improved ability to stage glaucoma over the entire spectrum using both structural and functional measures.
Enhanced detection of functional changes confirmed by corresponding structural changes leading to better monitoring of disease progression.
Reduced within-individual variability of OCT measurements allowing easier and more frequent structural testing with better patient tolerance than functional testing.
Feasibility of objective assessment of glaucoma damage in patients unable to perform visual field tests, such as very young children or elderly with limitations.
Highly reproducible automated segmentation of retinal layers and optic nerve head structures from multi-field SD-OCT scans.
Tighter structure-function correlations resulting in improved prediction of visual function from OCT structural indices.
Documented Applications
Detection and monitoring of glaucoma progression by quantifying retinal ganglion cell-axonal complex damage.
Objective assessment of glaucoma damage for patients who cannot perform reliable visual field tests.
Clinical staging of glaucoma severity across a wide dynamic range combining structural OCT and functional visual field data.
Mapping and quantifying regional structure-function relationships in glaucoma patients to predict localized visual field losses.
Multi-field 7-field and 9-field SD-OCT imaging protocols registered and segmented for comprehensive retinal and optic nerve head analysis.
Development of predictive classifiers linking OCT-derived structural and textural features to visual field sensitivity values.
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