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Abstract Excitotoxicity from the impairment of glutamate uptake constitutes an important mechanism in neurodegenerative diseases such as Alzheimer’s, multiple sclerosis, and Parkinson's disease. Within the eye, excitotoxicity is thought to play a critical role in retinal ganglion cell death in glaucoma, diabetic retinopathy, retinal ischemia, and optic nerve injury, yet how excitotoxic injury impacts different retinal layers is not well understood. Here, we investigated the longitudinal effects of N-methyl-D-aspartate (NMDA)-induced excitotoxic retinal injury in a rat model using deep learning-assisted retinal layer thickness estimation. Before and after unilateral intravitreal NMDA injection in nine adult Long Evans rats, spectral-domain optical coherence tomography (OCT) was used to acquire volumetric retinal images in both eyes over 4 weeks. Ten retinal layers were automatically segmented from the OCT data using our deep learning-based algorithm. Retinal degeneration was evaluated using layer-specific retinal thickness changes at each time point (before, and at 3, 7, and 28 days after NMDA injection). Within the inner retina, our OCT results showed that retinal thinning occurred first in the inner plexiform layer at 3 days after NMDA injection, followed by the inner nuclear layer at 7 days post-injury. In contrast, the retinal nerve fiber layer exhibited an initial thickening 3 days after NMDA injection, followed by normalization and thinning up to 4 weeks post-injury. Our results demonstrated the pathological cascades of NMDA-induced neurotoxicity across different layers of the retina. The early inner plexiform layer thinning suggests early dendritic shrinkage, whereas the initial retinal nerve fiber layer thickening before subsequent normalization and thinning indicates early inflammation before axonal loss and cell death. These findings implicate the inner plexiform layer as an early imaging biomarker of excitotoxic retinal degeneration, whereas caution is warranted when interpreting the ganglion cell complex combining retinal nerve fiber layer, ganglion cell layer, and inner plexiform layer thicknesses in conventional OCT measures. Deep learning-assisted retinal layer segmentation and longitudinal OCT monitoring can help evaluate the different phases of retinal layer damage upon excitotoxicity.

Abstract Glaucoma is an age-related neurodegenerative disease of the visual system, affecting both the eye and the brain. Yet its underlying metabolic mechanisms and neurobehavioral relevance remain largely unclear. Here, using proton magnetic resonance spectroscopy and functional magnetic resonance imaging, we investigated the GABAergic and glutamatergic systems in the visual cortex of glaucoma patients, as well as neural specificity, which is shaped by GABA and glutamate signals and underlies efficient sensory and cognitive functions. Our study shows that among the older adults, both GABA and glutamate levels decrease with increasing glaucoma severity regardless of age. Further, our study shows that the reduction of GABA but not glutamate predicts the neural specificity. This association is independent of the impairments on the retina structure, age, and the gray matter volume of the visual cortex. Our results suggest that glaucoma-specific decline of GABA undermines neural specificity in the visual cortex and that targeting GABA could improve the neural specificity in glaucoma.

Abstract Background Retinal oxygen saturation (sO2) provides essential information about the eye’s response to pathological changes that can result in vision loss. Visible-light optical coherence tomography (vis-OCT) is a noninvasive tool that has the potential to measure retinal sO2 in a clinical setting. However, its reliability is currently limited by unwanted signals referred to as spectral contaminants (SCs), and a comprehensive strategy to isolate true oxygen-dependent signals from SCs in vis-OCT is lacking. Methods We develop an adaptive spectroscopic vis-OCT (ADS-vis-OCT) technique that can adaptively remove SCs and accurately measure sO2 under the unique conditions of each vessel. We also validate the accuracy of ADS-vis-OCT using ex vivo blood phantoms and assess its repeatability in the retina of healthy volunteers. Results In ex vivo blood phantoms, ADS-vis-OCT agrees with a blood gas machine with only a 1% bias in samples with sO2 ranging from 0% to 100%. In the human retina, the root mean squared error between sO2 values in major arteries measured by ADS-vis-OCT and a pulse oximeter is 2.1% across 18 research participants. Additionally, the standard deviations of repeated ADS-vis-OCT measurements of sO2 values in smaller arteries and veins are 2.5% and 2.3%, respectively. Non-adaptive methods do not achieve comparable repeatabilities from healthy volunteers. Conclusions ADS-vis-OCT effectively removes SCs from human images, yielding accurate and repeatable sO2 measurements in retinal arteries and veins with varying diameters. This work could have important implications for the clinical use of vis-OCT to manage eye diseases.

The cellular-level visualization of retinal microstructures such as blood vessel wall components, not available with other imaging modalities, is provided with unprecedented details by dark-field imaging configurations; however, the interpretation of such images alone is sometimes difficult since multiple structural disturbances may be present in the same time. Particularly in eyes with retinal pathology, microstructures may appear in high-resolution retinal images with a wide range of sizes, sharpnesses, and brightnesses. In this paper we show that motion contrast and phase gradient imaging modalities, as well as the simultaneous acquisition of depth-resolved optical coherence tomography (OCT) images, provide additional insight to help understand the retinal neural and vascular structures seen in dark-field images and may enable improved diagnostic and treatment plans.

This study was registered with ClinicalTrials.gov (ID: NCT03715231). A total of 20 participants (37 eyes) who were 18 or older and had glaucoma or were glaucoma suspects were enrolled from the NYU Langone Eye Center and Bellevue Hospital. During their usual ophthalmology visit, they were consented for the study and underwent 360-degree goniophotography using the NIDEK Gonioscope GS-1. Afterwards, the three ophthalmologists separately examined the images obtained and determined the status of the iridocorneal angle in four quadrants using the Shaffer grading system. Physicians were masked to patient names and diagnoses. Inter-observer reproducibility was determined using Fleiss’ kappa statistics. The interobserver reliability using Fleiss’ statistics was shown to be significant between three glaucoma specialists with fair overall agreement (Fleiss’ kappa: 0.266, p < .0001) in the interpretation of 360-degree goniophotos. Automated 360-degree goniophotography using the NIDEK Gonioscope GS-1 have quality such that they are interpreted similarly by independent expert observers. This indicates that angle investigation may be performed using this automated device and that interpretation by expert observers is likely to be similar. Images produced from automated 360-degree goniophotography using the NIDEK Gonioscope GS-1 are similarly interpreted amongst glaucoma specialists, thus supporting use of this technique to document and assess the anterior chamber angle in patients with, or suspected of, glaucoma and iridocorneal angle abnormalities.

Abstract The goal of this study was to quantify the association between sensory integration abilities relevant for standing balance and disease stage in glaucoma. The disease stage was assessed using both functional (visual field deficit) and structural (retinal nerve fiber layer thickness) deficits in the better and worse eye. Balance was assessed using an adapted version of the well-established Sensory Organization Test (SOT). Eleven subjects diagnosed with mild to moderate glaucoma stood for 3 min in 6 sensory challenging postural conditions. Balance was assessed using sway magnitude and sway speed computed based on center-of-pressure data. Mixed linear regression analyses were used to investigate the associations between glaucoma severity and balance measures. Findings revealed that the visual field deficit severity in the better eye was associated with increased standing sway speed. This finding was confirmed in eyes open and closed conditions. Balance was not affected by the extent of the visual field deficit in the worse eye. Similarly, structural damage in either eye was not associated with the balance measures. In summary, this study found that postural control performance was associated with visual field deficit severity. The fact that this was found during eyes closed as well suggests that reduced postural control in glaucoma is not entirely attributed to impaired peripheral visual inputs. A larger study is needed to further investigate potential interactions between visual changes and central processing changes contributing to reduced balance function and increased incidence of falls in adults with glaucoma.

The field of ophthalmic imaging has grown substantially over the last years. Massive improvements in image processing and computer hardware have allowed the emergence of multiple imaging techniques of the eye that can transform patient care. The purpose of this review is to describe the most recent advances in eye imaging and explain how new technologies and imaging methods can be utilized in a clinical setting. The introduction of optical coherence tomography (OCT) was a revolution in eye imaging and has since become the standard of care for a plethora of conditions. Its most recent iterations, OCT angiography, and visible light OCT, as well as imaging modalities, such as fluorescent lifetime imaging ophthalmoscopy, would allow a more thorough evaluation of patients and provide additional information on disease processes. Toward that goal, the application of adaptive optics (AO) and full-field scanning to a variety of eye imaging techniques has further allowed the histologic study of single cells in the retina and anterior segment. Toward the goal of remote eye care and more accessible eye imaging, methods such as handheld OCT devices and imaging through smartphones, have emerged. Finally, incorporating artificial intelligence (AI) in eye images has the potential to become a new milestone for eye imaging while also contributing in social aspects of eye care.

Purpose: Vivid Vision Perimetry (VVP; Vivid Vision, Inc) is a novel method for performing in-office and home-based visual field assessment using a virtual reality platform and oculokinetic perimetry. Here we examine the reproducibility of VVP Swift and compare results with conventional standard automated perimetry (SAP) and spectral-domain (SD) OCT. Design: Cross-sectional study. Participants: Fourteen eyes of 7 patients with open-angle glaucoma (OAG) (average age, 64.6 years; 29% women) and 10 eyes of 5 patients with suspected glaucoma (average age, 61.8 years; 40% women) were enrolled. Methods: Patients with OAG and suspected glaucoma were enrolled prospectively and underwent 2 VVP Swift examinations. Results were compared with 1 conventional SAP examination (Humphrey Visual Field [HVF]; Zeiss) and 1 SD OCT examination. Main Outcome Measures: Mean sensitivity (in decibels) obtained for each eye in 2 VVP Swift test sessions and a conventional SAP examination, thickness of the retinal nerve fiber layer (RNFL) and ganglion cell complex (GCC) for the SD OCT examination, and mean test durations of the VVP Swift and SAP examinations. Results: The mean test duration of VVP Swift in both eyes (8.5 minutes) was significantly shorter (P < 0.001) than SAP (12.2 minutes). The average absolute difference of the mean sensitivity between the 2 VVP Swift sessions was found to be 0.73 dB (95% confidence interval [CI], 0.40–1.06). A statistically significant association was found between average mean sensitivity measurements from the VVP and mean deviation (MD) measurements obtained by the HVF with a Pearson correlation coefficient of 0.86 (95% CI, 0.70–0.94; P < 0.001). Mean visual sensitivity measurements from the VVP Swift test were significantly associated with average RNFL thickness (r = 0.66; P = 0.014) and GCC thickness (r = 0.63; P = 0.02), whereas the correlation coefficients between HVF MD and RNFL and GCC were 0.86 (P < 0.001) and 0.83 (P < 0.001), respectively. Conclusions: Our results demonstrated that the VVP Swift test can generate reproducible results and is comparable with conventional SAP. This suggests that the device can be used by clinicians to assess visual function in glaucoma.

Purpose: Intraocular pressure (IOP) is currently the only modifiable risk factor for glaucoma, yet glaucoma can continue to progress despite controlled IOP. Thus, development of glaucoma neurotherapeutics remains an unmet need. Scutellarin is a flavonoid that can exert neuroprotective effects in the eye and brain. Here, we investigated the neurobehavioral effects of scutellarin treatment in a chronic IOP elevation model.Methods: Ten adult C57BL/6J mice were unilaterally injected with an optically clear hydrogel into the anterior chamber to obstruct aqueous outflow and induce chronic IOP elevation. Eight other mice received unilateral intracameral injection of phosphate-buffered saline only. Another eight mice with hydrogel-induced unilateral chronic IOP elevation also received daily oral gavage of 300 mg/kg scutellarin. Tonometry, optical coherence tomography, and optokinetics were performed longitudinally for 4 weeks to monitor the IOP, retinal nerve fiber layer thickness, total retinal thickness, visual acuity, and contrast sensitivity of both eyes in all three groups.Results: Intracameral hydrogel injection resulted in unilateral chronic IOP elevation with no significant inter-eye IOP difference between scutellarin treatment and untreated groups. Upon scutellarin treatment, the hydrogel-injected eyes showed less retinal thinning and reduced visual behavioral deficits when compared to the untreated, hydrogel-injected eyes. No significant difference in retinal thickness or optokinetic measures was found in the contralateral, non-treated eyes over time or between all groups.Conclusion: Using the non-invasive measuring platform, oral scutellarin treatment appeared to preserve retinal structure and visual function upon chronic IOP elevation in mice. Scutellarin may be a novel neurotherapeutic agent for glaucoma treatment.

Abstract The lamina cribrosa is a primary site of damage in glaucoma. While mechanical distortion is hypothesized to cause reduction of axoplasmic flow, little is known about how the pores, which contains the retinal ganglion cell axons, traverse the lamina cribrosa. We investigated lamina cribrosa pore paths in vivo to quantify differences in tortuosity of pore paths between healthy and glaucomatous eyes. We imaged 16 healthy, 23 glaucoma suspect and 48 glaucomatous eyes from 70 subjects using a swept source optical coherence tomography system. The lamina cribrosa pores were automatically segmented using a previously described segmentation algorithm. Individual pore paths were automatically tracked through the depth of the lamina cribrosa using custom software. Pore path convergence to the optic nerve center and tortuosity was quantified for each eye. We found that lamina cribrosa pore pathways traverse the lamina cribrosa closer to the optic nerve center along the depth of the lamina cribrosa regardless of disease severity or diagnostic category. In addition, pores of glaucoma eyes take a more tortuous path through the lamina cribrosa compared to those of healthy eyes, suggesting a potential mechanism for reduction of axoplasmic flow in glaucoma.

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 employed for the diagnosis and monitoring of glaucoma. Previously, machine learning techniques have relied on 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.

There is increasing clinical evidence that the eye is not only affected by intraocular pressure (IOP), but also by intracranial pressure (ICP). Both pressures meet at the optic nerve head of the eye, specifically the lamina cribrosa (LC). The LC is a collagenous meshwork through which all retinal ganglion cell axons pass on their way to the brain. Distortion of the LC causes a biological cascade leading to neuropathy and impaired vision in situations such as glaucoma and idiopathic intracranial hypertension. While the effect of IOP on the LC has been studied extensively, the coupled effects of IOP and ICP on the LC remain poorly understood. We investigated in-vivo the effects of IOP and ICP, controlled via cannulation of the eye and lateral ventricle in the brain, on the LC microstructure of anesthetized rhesus monkeys eyes using the Bioptigen spectral-domain optical coherence tomography (OCT) device (Research Triangle, NC). The animals were imaged with their head upright and the rest of their body lying prone on a surgical table. The LC was imaged at a variety of IOP/ICP combinations, and microstructural parameters, such as the thickness of the LC collagenous beams and diameter of the pores were analyzed. LC microstructure was confirmed by histology. We determined that LC microstructure deformed in response to both IOP and ICP changes, with significant interaction between the two. These findings emphasize the importance of considering both IOP and ICP when assessing optic nerve health.

PurposeTo investigate gold nanorods (GNRs) as a contrast agent to enhance Doppler optical coherence tomography (OCT) imaging of the intrascleral aqueous humor outflow.MethodsA serial dilution of GNRs was scanned with a spectral-domain OCT device (Bioptigen, Durham, NC) to visualize Doppler signal. Doppler measurements using GNRs were validated using a controlled flow system. To demonstrate an application of GNR enhanced Doppler, porcine eyes were perfused at constant pressure with mock aqueous alone or 1.0×10(12) GNR/mL mixed with mock aqueous. Twelve Doppler and volumetric SD-OCT scans were obtained from the limbus in a radial fashion incremented by 30°, forming a circular scan pattern. Volumetric flow was computed by integrating flow inside non-connected vessels throughout all 12 scans around the limbus.ResultsAt the GNR concentration of 0.7×10(12) GNRs/mL, Doppler signal was present through the entire depth of the testing tube without substantial attenuation. A well-defined laminar flow profile was observed for Doppler images of GNRs flowing through the glass capillary tube. The Doppler OCT measured flow profile was not statistically different from the expected flow profile based upon an autoregressive moving average model, with an error of -0.025 to 0.037 mm/s (p = 0.6435). Cross-sectional slices demonstrated the ability to view anterior chamber outflow ex-vivo using GNR-enhanced Doppler OCT. Doppler volumetric flow measurements were comparable to flow recorded by the perfusion system.ConclusionsGNRs created a measureable Doppler signal within otherwise silent flow fields in OCT Doppler scans. Practical application of this technique was confirmed in a constant pressure ex-vivo aqueous humor outflow model in porcine eyes.

To determine the reproducibility of automated segmentation of the three-dimensional (3D) lamina cribrosa (LC) microarchitecture scanned in-vivo using optical coherence tomography (OCT).Thirty-nine eyes (8 healthy, 19 glaucoma suspects and 12 glaucoma) from 49 subjects were scanned twice using swept-source (SS-) OCT in a 3.5×3.5×3.64 mm (400×400×896 pixels) volume centered on the optic nerve head, with the focus readjusted after each scan. The LC was automatically segmented and analyzed for microarchitectural parameters, including pore diameter, pore diameter standard deviation (SD), pore aspect ratio, pore area, beam thickness, beam thickness SD, and beam thickness to pore diameter ratio. Reproducibility of the parameters was assessed by computing the imprecision of the parameters between the scans.The automated segmentation demonstrated excellent reproducibility. All LC microarchitecture parameters had an imprecision of less or equal to 4.2%. There was little variability in imprecision with respect to diagnostic category, although the method tends to show higher imprecision amongst healthy subjects.The proposed automated segmentation of the LC demonstrated high reproducibility for 3D LC parameters. This segmentation analysis tool will be useful for in-vivo studies of the LC.

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.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.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.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.

Optic nerve degeneration caused by glaucoma is a leading cause of blindness worldwide. Patients affected by the normal-pressure form of glaucoma are more likely to harbor risk alleles for glaucoma-related optic nerve disease. We have performed a meta-analysis of two independent genome-wide association studies for primary open angle glaucoma (POAG) followed by a normal-pressure glaucoma (NPG, defined by intraocular pressure (IOP) less than 22 mmHg) subgroup analysis. The single-nucleotide polymorphisms that showed the most significant associations were tested for association with a second form of glaucoma, exfoliation-syndrome glaucoma. The overall meta-analysis of the GLAUGEN and NEIGHBOR dataset results (3,146 cases and 3,487 controls) identified significant associations between two loci and POAG: the CDKN2BAS region on 9p21 (rs2157719 [G], OR = 0.69 [95%CI 0.63-0.75], p = 1.86×10⁻¹⁸), and the SIX1/SIX6 region on chromosome 14q23 (rs10483727 [A], OR = 1.32 [95%CI 1.21-1.43], p = 3.87×10⁻¹¹). In sub-group analysis two loci were significantly associated with NPG: 9p21 containing the CDKN2BAS gene (rs2157719 [G], OR = 0.58 [95% CI 0.50-0.67], p = 1.17×10⁻¹²) and a probable regulatory region on 8q22 (rs284489 [G], OR = 0.62 [95% CI 0.53-0.72], p = 8.88×10⁻¹⁰). Both NPG loci were also nominally associated with a second type of glaucoma, exfoliation syndrome glaucoma (rs2157719 [G], OR = 0.59 [95% CI 0.41-0.87], p = 0.004 and rs284489 [G], OR = 0.76 [95% CI 0.54-1.06], p = 0.021), suggesting that these loci might contribute more generally to optic nerve degeneration in glaucoma. Because both loci influence transforming growth factor beta (TGF-beta) signaling, we performed a genomic pathway analysis that showed an association between the TGF-beta pathway and NPG (permuted p = 0.009). These results suggest that neuro-protective therapies targeting TGF-beta signaling could be effective for multiple forms of glaucoma.