Catherine A. Cukras

Deep learning-enabled volumetric cone photoreceptor segmentation in adaptive optics optical coherence tomography images of normal and diseased eyes

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Deep learning-enabled volumetric cone photoreceptor segmentation in adaptive optics optical coherence tomography images of normal and diseased eyes Objective quantification of photoreceptor cell morphology, such as cell diameter and outer segment length, is crucial for early, accurate, and sensitive diagnosis and prognosis of retinal neurodegenerative diseases. Adaptive optics optical coherence tomography (AO-OCT) provides three-dimensional (3-D) visualization of photoreceptor cells in the living human eye. The current gold standard for extracting cell morphology from AO-OCT images involves the tedious process of 2-D manual marking. To automate this process and extend to 3-D analysis of the volumetric data, we propose a comprehensive deep learning framework to segment individual cone cells in AO-OCT scans. Our automated method achieved human-level performance in assessing cone photoreceptors of healthy and diseased participants captured with three different AO-OCT systems representing two different types of point scanning OCT: spectral domain and swept source.

Quantitative analysis of optical coherence tomography imaging in patients with different severities of hydroxychloroquine toxicity

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Purpose: To determine the diagnostic validity of quantitative measures derived from optical coherence tomography (OCT) images in their ability to discriminate between cohorts of eyes unaffected by hydroxychloroquine (HCQ) and those with a range of toxicity severities, including mild toxicity. Methods: Prospective, single-centre, case-control study conducted between August 2010 and May 2017. Participants were exposed to HCQ for at least 5 years (mean±SD =14±7.2 years) and classified into affected and unaffected cohorts based on the American Academy of Ophthalmology's 2016 recommendations. For affected eyes, severity (groups 1-4) was assigned based on the extent of ellipsoid zone loss. For all eyes, spectral domain-OCT scans were analysed quantitatively to compute inner retinal thickness (IRT), outer retinal thickness (ORT), and minimum signal intensity (MI) and compared across toxicity groups. Results: Of the 85 participants (mean age 59±12 years, 93% female), 30...

Multimodal assessments of drusenoid pigment epithelial detachments in the Age-Related Eye Disease Study 2 Ancillary (A2A) spectral-domain optical coherence tomography (SD-OCT) study cohort

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Purpose: To identify features correlating with drusenoid pigment epithelial detachment (DPED) progression in the AREDS2 Ancillary (A2A) spectral-domain optical coherence tomography (SD-OCT) study cohort. Methods: In this retrospective analysis of a prospective longitudinal study, eyes with intermediate age-related macular degeneration (AMD) and DPEDs were followed longitudinally with annual multimodal imaging. Results: Thirty-one eyes of 25 participants (mean age 72.6 years) in the A2A AREDS2 substudy had DPED identified in color fundus images. SD-OCT inspection confirmed a sub-retinal pigment epithelium drusenoid elevation of ≥433 µm diameter in 25 (80.6%) eyes. Twenty-four of these eyes were followed longitudinally (median 4.0 years) during which 7 eyes (29.2%) underwent DPED collapse (with 3/7 further progressing to geographic atrophy), 6 (25.0%) developing neovascular AMD, and 11 (45.8%) maintaining DPED persistence without late AMD. On Kaplan-Meier analysis, mean time ...

Visual Field Sensitivity Prediction Using Optical Coherence Tomography Analysis in Hydroxychloroquine Toxicity

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Purpose: This study investigates the association between local retina structure and visual function in a cohort with long-term hydroxychloroquine (HCQ) use. Methods: The study included 84 participants (54 participants without toxicity and 30 participants with toxicity) with history of chronic HCQ use (14.5 ± 7.4 years) who had testing with spectral-domain optical coherence tomography (SD-OCT) imaging and Humphrey 10-2 visual fields. Optical coherence tomography (OCT) metrics (total and outer retina thickness [TRT and ORT], minimum intensity [MinI], and ellipsoid zone [EZ] loss) were sampled in regions corresponding to visual field test locations. Univariate linear correlations were investigated and a multivariate random forest regression using a combination of OCT metrics was used to predict visual field sensitivity by locus using a leave-one-out cross-validation strategy. Results: In univariate linear regression, EZ loss demonstrated the strongest relationship with visual fi...

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