The three-dimensional structural configuration of the central retinal vessel trunk and branches as a glaucoma biomarker.

PURPOSE: To assess whether the 3-dimensional (3D) structural configuration of the central retinal vessel trunk and its branches (CRVT&B) could be used as a diagnostic marker for glaucoma. DESIGN: Retrospective, deep-learning approach diagnosis study. METHODS: We trained a deep learning network to automatically segment the CRVT&B from the B-scans of the optical coherence tomography (OCT) volume of the optic nerve head. Subsequently, 2 different approaches were used for glaucoma diagnosis using the structural configuration of the CRVT&B as extracted from the OCT volumes. In the first approach, we aimed to provide a diagnosis using only 3D convolutional neural networks and the 3D structure of the CRVT&B. For the second approach, we projected the 3D structure of the CRVT&B orthographically onto sagittal, frontal, and transverse planes to obtain 3 two-dimensional (2D) images, and then a 2D convolutional neural network was used for diagnosis. The segmentation accuracy was evaluated using the Dice coefficient, whereas the diagnostic accuracy was assessed using the area under the receiver operating characteristic curves (AUCs). The diagnostic performance of the CRVT&B was also compared with that of retinal nerve fiber layer (RNFL) thickness (calculated in the same cohorts). RESULTS: Our segmentation network was able to efficiently segment retinal blood vessels from OCT scans. On a test set, we achieved a Dice coefficient of 0.81 ± 0.07. The 3D and 2D diagnostic networks were able to differentiate glaucoma from nonglaucoma subjects with accuracies of 82.7% and 83.3%, respectively. The corresponding AUCs for the CRVT&B were 0.89 and 0.90, higher than those obtained with RNFL thickness alone (AUCs ranging from 0.74 to 0.80). CONCLUSIONS: Our work demonstrated that the diagnostic power of the CRVT&B is superior to that of a gold-standard glaucoma parameter, that is, RNFL thickness. Our work also suggested that the major retinal blood vessels form a "skeleton"-the configuration of which may be representative of major optic nerve head structural changes as typically observed with the development and progression of glaucoma.

Describing the Structural Phenotype of the Glaucomatous Optic Nerve Head Using Artificial Intelligence.

PURPOSE: To develop a novel deep-learning approach that can describe the structural phenotype of the glaucomatous optic nerve head (ONH) and can be used as a robust glaucoma diagnosis tool. DESIGN: Retrospective, deep-learning approach diagnosis study. METHOD: We trained a deep-learning network to segment 3 neural-tissue and 4 connective-tissue layers of the ONH. The segmented optical coherence tomography images were then processed by a customized autoencoder network with an additional parallel branch for binary classification. The encoder part of the autoencoder reduced the segmented optical coherence tomography images into a low-dimensional latent space (LS), whereas the decoder and the classification branches reconstructed the images and classified them as glaucoma or nonglaucoma, respectively. We performed principal component analysis on the latent parameters and identified the principal components (PCs). Subsequently, the magnitude of each PC was altered in steps and reported how it impacted the morphology of the ONH. RESULTS: The image reconstruction quality and diagnostic accuracy increased with the size of the LS. With 54 parameters in the LS, the diagnostic accuracy was 92.0 ± 2.3% with a sensitivity of 90.0 ± 2.4% (at 95% specificity), and the corresponding Dice coefficient for the reconstructed images was 0.86 ± 0.04. By changing the magnitudes of PC in steps, we were able to reveal how the morphology of the ONH changes as one transitions from a "nonglaucoma" to a "glaucoma" condition. CONCLUSIONS: Our network was able to identify novel biomarkers of the ONH for glaucoma diagnosis. Specifically, the structural features identified by our algorithm were found to be related to clinical observations of glaucoma.

Towards label-free 3D segmentation of optical coherence tomography images of the optic nerve head using deep learning.

Recently proposed deep learning (DL) algorithms for the segmentation of optical coherence tomography (OCT) images to quantify the morphological changes to the optic nerve head (ONH) tissues during glaucoma have limited clinical adoption due to their device specific nature and the difficulty in preparing manual segmentations (training data). We propose a DL-based 3D segmentation framework that is easily translatable across OCT devices in a label-free manner (i.e. without the need to manually re-segment data for each device). Specifically, we developed 2 sets of DL networks: the 'enhancer' (enhance OCT image quality and harmonize image characteristics from 3 devices) and the 'ONH-Net' (3D segmentation of 6 ONH tissues). We found that only when the 'enhancer' was used to preprocess the OCT images, the 'ONH-Net' trained on any of the 3 devices successfully segmented ONH tissues from the other two unseen devices with high performance (Dice coefficients > 0.92). We demonstrate that is possible to automatically segment OCT images from new devices without ever needing manual segmentation data from them.

Bilateral, Simultaneous, Acute Angle Closure Glaucoma in Pseudophakia Induced by Chlorthalidone.

UNLABELLED: Purpose. To report two persons with acute, bilateral, and simultaneous angle closure glaucoma in pseudophakia secondary to uveal effusions induced by administration of chlorthalidone. Methods. CASE REPORTS: Results. Bilateral shallow anterior chambers and high intraocular pressure with decline in visual acuity were reported in two patients within days of intake of chlorthalidone for systemic hypertension. Gonioscopy confirmed appositional angle closure while choroidal detachment and ciliochoroidal detachment were revealed on ultrasonographic studies. Discontinuing chlorthalidone and institution of aqueous suppressants to reduce IOP and cycloplegics reversed angle closure and glaucoma. Conclusions. Reports of angle closure glaucoma in pseudophakic eyes induced by idiosyncratic reaction to chlorthalidone confirms that osmotic changes in the crystalline lens has no role in the pathogenesis of drug induced glaucoma and reaffirms that glaucoma is secondary to ciliochoroidal detachment and ciliary body rotation and edema.

Evaluation of patient age as a risk factor for intraocular pressure elevation after intravitreal triamcinolone.

PURPOSE: To evaluate the effect of patient age on intraocular pressure (IOP) response after intravitreal injection of triamcinolone acetonide (IVTA). DESIGN: Interventional case series. METHODS: A total of 164 outpatients (164 eyes) aged 21 to 80 years (mean, 56.8 years), presenting with exudative age-related maculopathy (51) or macular edema of various etiologies (113), received IVTA (4 mg/0.1 ml). The primary outcome measure was IOP elevation >21 mm Hg. Patients were re-evaluated at one week, and one, three, and six months. RESULTS: The mean baseline IOP was 15.07 mm Hg; the mean rise was 6.6 mm Hg. IOP >21 mm Hg was observed in 42 (25.6%) patients. In the age group