OCT for glaucoma diagnosis, screening and detection of glaucoma progression.

Optical coherence tomography (OCT) is a commonly used imaging modality in the evaluation of glaucomatous damage. The commercially available spectral domain (SD)-OCT offers benefits in glaucoma assessment over the earlier generation of time domain-OCT due to increased axial resolution, faster scanning speeds and has been reported to have improved reproducibility but similar diagnostic accuracy. The capabilities of SD-OCT are rapidly advancing with 3D imaging, reproducible registration, and advanced segmentation algorithms of macular and optic nerve head regions. A review of the evidence to date suggests that retinal nerve fibre layer remains the dominant parameter for glaucoma diagnosis and detection of progression while initial studies of macular and optic nerve head parameters have shown promising results. SD-OCT still currently lacks the diagnostic performance for glaucoma screening

A feature agnostic approach for glaucoma detection in OCT volumes

Optical coherence tomography (OCT) based measurements of retinal layer thickness, such as the retinal nerve fibre layer (RNFL) and the ganglion cell with inner plexiform layer (GCIPL) are commonly used for the diagnosis and monitoring of glaucoma. Previously, machine learning techniques have utilized segmentation-based imaging features such as the peripapillary RNFL thickness and the cup-to-disc ratio. Here, we propose a deep learning technique that classifies eyes as healthy or glaucomatous directly from raw, unsegmented OCT volumes of the optic nerve head (ONH) using a 3D Convolutional Neural Network (CNN). We compared the accuracy of this technique with various feature-based machine learning algorithms and demonstrated the superiority of the proposed deep learning based method. Logistic regression was found to be the best performing classical machine learning technique with an AUC of 0.89. In direct comparison, the deep learning approach achieved a substantially higher AUC of 0.94 with the additional advantage of providing insight into which regions of an OCT volume are important for glaucoma detection. Computing Class Activation Maps (CAM), we found that the CNN identified neuroretinal rim and optic disc cupping as well as the lamina cribrosa (LC) and its surrounding areas as the regions significantly associated with the glaucoma classification. These regions anatomically correspond to the well established and commonly used clinical markers for glaucoma diagnosis such as increased cup volume, cup diameter, and neuroretinal rim thinning at the superior and inferior segments.Comment: 13 pages,3 figure

The use of ocular coherence tomography in evaluating optic nerve health in eyes with large disc size

Large discs are often associated with large cups; in order to exclude glaucomatous cupping a good objective tool is needed. The purpose of this study is to evaluate ocular coherence tomography (OCT) optic nerve head (ONH) parameters as indicators of ocular health in subjects with large discs. Eighty-one eyes of 53 healthy patients were evaluated; 46 eyes had large discs (disc area ≥2.6 mm2) and 35 eyes had regular size discs (disc area <2.6 mm2). All subjects underwent OCT. All ONH parameters were documented, including vertical integrated rim area (VIRA), horizontal integrated rim width (HIRW), rim area, cup area, cup-to-disc (CD) area ratio, horizontal cup to disc ratio (HCDR), vertical cup to disc ratio (VCDR), cup area topography, and cup volume. In addition, OCT retinal nerve fiber layer (RNFL) global mean thickness and four quadrants mean thicknesses were analyzed. All cup parameters were significantly higher in the large disc group compared to the normal disc group. The parameters estimating the rim varied between the groups: in the large disc group VIRA was significantly lower while HIRW was significantly higher, compared to the control group. Rim area was the only parameter with similar values in both groups (1.52±0.24 mm2 and 1.6±0.3 mm2 in the large and regular disc groups, respectively). Correlation analysis revealed significant positive association between disc area and cup parameters in the large disc group. In contrast, in the regular disc group, disc area was positively associated with rim parameters. Rim area might serve as an indicator for ocular health in large discs with large cups

Three-Dimensional Spectral-Domain Optical Coherence Tomography Data Analysis for Glaucoma Detection

Purpose: To develop a new three-dimensional (3D) spectral-domain optical coherence tomography (SD-OCT) data analysis method using a machine learning technique based on variable-size super pixel segmentation that efficiently utilizes full 3D dataset to improve the discrimination between early glaucomatous and healthy eyes. Methods: 192 eyes of 96 subjects (44 healthy, 59 glaucoma suspect and 89 glaucomatous eyes) were scanned with SD-OCT. Each SD-OCT cube dataset was first converted into 2D feature map based on retinal nerve fiber layer (RNFL) segmentation and then divided into various number of super pixels. Unlike the conventional super pixel having a fixed number of points, this newly developed variable-size super pixel is defined as a cluster of homogeneous adjacent pixels with variable size, shape and number. Features of super pixel map were extracted and used as inputs to machine classifier (LogitBoost adaptive boosting) to automatically identify diseased eyes. For discriminating performance assessment, area under the curve (AUC) of the receiver operating characteristics of the machine classifier outputs were compared with the conventional circumpapillary RNFL (cpRNFL) thickness measurements. Results: The super pixel analysis showed statistically significantly higher AUC than the cpRNFL (0.855 vs. 0.707, respectively, p = 0.031, Jackknife test) when glaucoma suspects were discriminated from healthy, while no significant difference was found when confirmed glaucoma eyes were discriminated from healthy eyes. Conclusions: A novel 3D OCT analysis technique performed at least as well as the cpRNFL in glaucoma discrimination and even better at glaucoma suspect discrimination. This new method has the potential to improve early detection of glaucomatous damage. © 2013 Xu et al

Effects of Age on Optical Coherence Tomography Measurements of Healthy Retinal Nerve Fiber Layer, Macula, and Optic Nerve Head

Purpose—To determine the effects of age on global and sectoral peripapillary retinal nerve fiber layer (RNFL), macular thicknesses and optic nerve head (ONH) parameters in healthy subjects using optical coherence tomography (OCT). Design—Retrospective, cross-sectional observational study. Participants—226 eyes from 124 healthy subjects were included. Methods—Healthy subjects were scanned using the Fast RNFL, Fast Macula, and Fast ONH scan patterns on a Stratus OCT. All global and sectoral RNFL and macular parameters and global ONH parameters were modeled in terms of age using linear mixed effects models. Normalized slopes were also calculated by dividing the slopes by the mean value of the OCT parameter for inter-parameter comparison. Main Outcome Measures—Slope of each OCT parameter across age. Results—All global and sectoral RNFL thickness parameters statistically significantly decreased with increasing age, except for the temporal quadrant and clock hours 8-10, which were not statistically different from a slope of zero. Highest absolute slopes were in the inferior and superior quadrant RNFL and clock hour 1 (superior nasal). Normalized slopes showed similar rate in all sectors except for the temporal clock hours (8-10). All macular thickness parameters statistically significantly decreased with increasing age, except for the central fovea sector, which had a slight positive slope that was not statistically significant. The nasal outer sector had the greatest absolute slope. Normalized macular slope in the outer ring was similar to the normalized slopes in the RNFL. Normalized inner ring had shallower slope than the outer ring with similar rate in all quadrants. Disc area remained nearly constant across the ages, but cup area increased and rim area decreased with age, both of which were statistically significant. Conclusions—Global and regional changes due to the effects of age on RNFL, macula and ONH OCT measurements should be considered when assessing eyes over time.National Institutes of Health (U.S.) (R01-EY13178-09)National Institutes of Health (U.S.) (R01-EY11289-23)National Institutes of Health (U.S.) (P30-EY008098