Faculty Bibliography

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.

OBJECTIVE:Although artificial intelligence (AI) models may offer innovative and powerful ways to use the wealth of data generated by diagnostic tools, there are important challenges related to their development and validation. Most notable is the lack of a perfect reference standard for glaucomatous optic neuropathy (GON). Because AI models are trained to predict presence of glaucoma or its progression, they generally rely on a reference standard that is used to train the model and assess its validity. If an improper reference standard is used, the model may be trained to detect or predict something that has little or no clinical value. This article summarizes the issues and discussions related to the definition of GON in AI applications as presented by the Glaucoma Workgroup from the Collaborative Community for Ophthalmic Imaging (CCOI) US Food and Drug Administration Virtual Workshop, on September 3 and 4, 2020, and on January 28, 2022. DESIGN/METHODS:Review and conference proceedings. SUBJECTS/METHODS:No human or animal subjects or data therefrom were used in the production of this article. METHODS:A summary of the Workshop was produced with input and approval from all participants. MAIN OUTCOME MEASURES/METHODS:Consensus position of the CCOI Workgroup on the challenges in defining GON and possible solutions. RESULTS:The Workshop reviewed existing challenges that arise from the use of subjective definitions of GON and highlighted the need for a more objective approach to characterize GON that could facilitate replication and comparability of AI studies and allow for better clinical validation of proposed AI tools. Different tests and combination of parameters for defining a reference standard for GON have been proposed. Different reference standards may need to be considered depending on the scenario in which the AI models are going to be applied, such as community-based or opportunistic screening versus detection or monitoring of glaucoma in tertiary care. CONCLUSIONS:The development and validation of new AI-based diagnostic tests should be based on rigorous methodology with clear determination of how the reference standards for glaucomatous damage are constructed and the settings where the tests are going to be applied. FINANCIAL DISCLOSURE(S)/BACKGROUND:Proprietary or commercial disclosure may be found after the references.

Plasticity in the brain is impacted by an individual's age at the onset of the blindness. However, what drives the varying degrees of plasticity remains largely unclear. One possible explanation attributes the mechanisms for the differing levels of plasticity to the cholinergic signals originating in the nucleus basalis of Meynert. This explanation is based on the fact that the nucleus basalis of Meynert can modulate cortical processes such as plasticity and sensory encoding through its widespread cholinergic projections. Nevertheless, there is no direct evidence indicating that the nucleus basalis of Meynert undergoes plastic changes following blindness. Therefore, using multiparametric magnetic resonance imaging, we examined if the structural and functional properties of the nucleus basalis of Meynert differ between early blind, late blind and sighted individuals. We observed that early and late blind individuals had a preserved volumetric size and cerebrovascular reactivity in the nucleus basalis of Meynert. However, we observed a reduction in the directionality of water diffusion in both early and late blind individuals compared to sighted individuals. Notably, the nucleus basalis of Meynert presented diverging patterns of functional connectivity between early and late blind individuals. This functional connectivity was enhanced at both global and local (visual, language and default-mode networks) levels in the early blind individuals, but there were little-to-no changes in the late blind individuals when compared to sighted controls. Furthermore, the age at onset of blindness predicted both global and local functional connectivity. These results suggest that upon reduced directionality of water diffusion in the nucleus basalis of Meynert, cholinergic influence may be stronger for the early blind compared to the late blind individuals. Our findings are important to unravelling why early blind individuals present stronger and more widespread cross-modal plasticity compared to late blind individuals.

BACKGROUND:Spectral-domain (SD-) optical coherence tomography (OCT) can reliably measure axonal (peripapillary retinal nerve fiber layer [pRNFL]) and neuronal (macular ganglion cell + inner plexiform layer [GCIPL]) thinning in the retina. Measurements from 2 commonly used SD-OCT devices are often pooled together in multiple sclerosis (MS) studies and clinical trials despite software and segmentation algorithm differences; however, individual pRNFL and GCIPL thickness measurements are not interchangeable between devices. In some circumstances, such as in the absence of a consistent OCT segmentation algorithm across platforms, a conversion equation to transform measurements between devices may be useful to facilitate pooling of data. The availability of normative data for SD-OCT measurements is limited by the lack of a large representative world-wide sample across various ages and ethnicities. Larger international studies that evaluate the effects of age, sex, and race/ethnicity on SD-OCT measurements in healthy control participants are needed to provide normative values that reflect these demographic subgroups to provide comparisons to MS retinal degeneration. METHODS:Participants were part of an 11-site collaboration within the International Multiple Sclerosis Visual System (IMSVISUAL) consortium. SD-OCT was performed by a trained technician for healthy control subjects using Spectralis or Cirrus SD-OCT devices. Peripapillary pRNFL and GCIPL thicknesses were measured on one or both devices. Automated segmentation protocols, in conjunction with manual inspection and correction of lines delineating retinal layers, were used. A conversion equation was developed using structural equation modeling, accounting for clustering, with healthy control data from one site where participants were scanned on both devices on the same day. Normative values were evaluated, with the entire cohort, for pRNFL and GCIPL thicknesses for each decade of age, by sex, and across racial groups using generalized estimating equation (GEE) models, accounting for clustering and adjusting for within-patient, intereye correlations. Change-point analyses were performed to determine at what age pRNFL and GCIPL thicknesses exhibit accelerated rates of decline. RESULTS:The healthy control cohort (n = 546) was 54% male and had a wide distribution of ages, ranging from 18 to 87 years, with a mean (SD) age of 39.3 (14.6) years. Based on 346 control participants at a single site, the conversion equation for pRNFL was Cirrus = -5.0 + (1.0 × Spectralis global value). Based on 228 controls, the equation for GCIPL was Cirrus = -4.5 + (0.9 × Spectralis global value). Standard error was 0.02 for both equations. After the age of 40 years, there was a decline of -2.4 μm per decade in pRNFL thickness ( P < 0.001, GEE models adjusting for sex, race, and country) and -1.4 μm per decade in GCIPL thickness ( P < 0.001). There was a small difference in pRNFL thickness based on sex, with female participants having slightly higher thickness (2.6 μm, P = 0.003). There was no association between GCIPL thickness and sex. Likewise, there was no association between race/ethnicity and pRNFL or GCIPL thicknesses. CONCLUSIONS:A conversion factor may be required when using data that are derived between different SD-OCT platforms in clinical trials and observational studies; this is particularly true for smaller cross-sectional studies or when a consistent segmentation algorithm is not available. The above conversion equations can be used when pooling data from Spectralis and Cirrus SD-OCT devices for pRNFL and GCIPL thicknesses. A faster decline in retinal thickness may occur after the age of 40 years, even in the absence of significant differences across racial groups.

PURPOSE/UNASSIGNED:Lamina cribrosa (LC) deformations caused by elevated intraocular pressure (IOP) are believed to contribute to glaucomatous neuropathy and have therefore been extensively studied, in many conditions, from in vivo to ex vivo. We compare acute IOP-induced global and local LC deformations immediately before (premortem) and after (postmortem) sacrifice by exsanguination. METHODS/UNASSIGNED:The optic nerve heads of three healthy monkeys 12 to 15 years old were imaged with spectral-domain optical coherence tomography under controlled IOP premortem and postmortem. Volume scans were acquired at baseline IOP (8-10 mm Hg) and at 15, 30, and 40 mm Hg IOP. A digital volume correlation technique was used to determine the IOP-induced three-dimensional LC deformations (strains) in regions visible premortem and postmortem. RESULTS/UNASSIGNED:Both conditions exhibited similar nonlinear relationships between IOP increases and LC deformations. Median effective and shear strains were, on average, over all eyes and pressures, smaller postmortem than premortem, by 14% and 11%, respectively (P's < 0.001). Locally, however, the differences in LC deformation between conditions were variable. Some regions were subjected premortem to triple the strains observed postmortem, and others suffered smaller deformations premortem than postmortem. CONCLUSIONS/UNASSIGNED:Increasing IOP acutely caused nonlinear LC deformations with an overall smaller effect postmortem than premortem. Locally, deformations premortem and postmortem were sometimes substantially different. We suggest that the differences may be due to weakened mechanical support from the unpressurized central retinal vessels postmortem. TRANSLATIONAL RELEVANCE/UNASSIGNED:Additional to the important premortem information, comparison with postmortem provides a unique context essential to understand the translational relevance of all postmortem biomechanics literature.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Recent studies have suggested that inter-eye differences (IEDs) in peripapillary retinal nerve fiber layer (pRNFL) or ganglion cell+inner plexiform (GCIPL) thickness by spectral-domain optical coherence tomography (SD-OCT) may identify people with a history of unilateral optic neuritis (ON). However, this requires further validation. Machine learning classification may be useful for validating thresholds for OCT IEDs and for examining added utility for visual function tests, such as low-contrast letter acuity (LCLA), in the diagnosis of people with multiple sclerosis (PwMS) and for unilateral ON history. METHODS:Participants were from 11 sites within the International Multiple Sclerosis Visual System (IMSVISUAL) consortium. pRNFL and GCIPL thicknesses were measured using SD-OCT. A composite score combining OCT and visual measures was compared individual measurements to determine the best model to distinguish PwMS from controls. These methods were also used to distinguish those with history of ON among PwMS. ROC curve analysis was performed on a training dataset (2/3 of cohort), then applied to a testing dataset (1/3 of cohort). Support vector machine (SVM) analysis was used to assess whether machine learning models improved diagnostic capability of OCT. RESULTS:Among 1,568 PwMS and 552 controls, variable selection models identified GCIPL IED, average GCIPL thickness (both eyes), and binocular 2.5% LCLA as most important for classifying PwMS vs. controls. This composite score performed best, with AUC=0.89 (95% CI 0.85, 0.93), sensitivity=81% and specificity=80%. The composite score ROC curve performed better than any of the individual measures from the model (p<0.0001). GCIPL IED remained the best single discriminator of unilateral ON history among PwMS (AUC=0.77, 95% CI 0.71,0.83, sensitivity=68%, specificity=77%). SVM analysis performed comparably to standard logistic regression models. CONCLUSIONS:A composite score combining visual structure and function improved the capacity of SD-OCT to distinguish PwMS from controls. GCIPL IED best distinguished those with history of unilateral ON. SVM performed as well as standard statistical models for these classifications. CLASSIFICATION OF EVIDENCE/METHODS:The study provides Class III evidence that SD-OCT accurately distinguishes multiple sclerosis from normal controls as compared to clinical criteria.

On September 3^rd, 2020, the Collaborative Community on Ophthalmic Imaging (CCOI) conducted its first two-day virtual workshop on the role of artificial intelligence (AI) and related machine learning (ML) techniques for the diagnosis and treatment of various ophthalmic conditions. In a session entitled, "Artificial Intelligence For Glaucoma", a panel of glaucoma specialists, researchers, industry experts, and patients convened to share current research on the application of AI to commonly used diagnostic modalities including fundus photography, optical coherence tomography imaging, standard automated perimetry, and gonioscopy. The conference participants focused on the use of AI as a tool for disease prediction, highlighted its ability to address inequalities, and presented the limitations and challenges to its real-world clinical application. The panelists' discussion addressed AI and health equities from the clinical, societal and regulatory perspectives.

Purpose : Glaucoma is a widespread neurodegenerative disease affecting the retinal ganglion cells, optic nerve, distal visual pathways and beyond. Recent studies suggest that cerebrospinal fluid (CSF) plays a role in clearing wastes from the brain and that CSF dynamics may be altered in neurodegenerative diseases. Since CSF dynamics can be facilitated by the global brain activity, in the present study, we investigated how the dynamics of CSF and its coupling with global brain activity may be altered in glaucoma using functional magnetic resonance imaging (fMRI). Methods : 19 early glaucoma patients (62.3+/-1.7 yrs) (mean+/-SEM), 19 advanced glaucoma patients (64.7+/-2.4 yrs), and 19 healthy subjects (59+/-2.4 yrs) underwent anatomical MRI and resting-state fMRI with eyes closed. Age did not differ across groups (P=0.188). We extracted the CSF signal time profiles from the fourth ventricle (Fig. 1A) and the global brain activity [blood-oxygenation-level-dependent signal time profiles] from the entire gray matter (Fig. 1B). Following previous literature (Han F, et al. PLOS Biol 2021;19), the coupling between the CSF signals and the global brain activity (CSF-BOLD coupling) was examined via cross correlation at the 4s time lag, where more negative values indicate stronger coupling. We also associated these correlations with the volumes of the anterior visual pathway in anatomical MRI. Results : A significant group difference was observed in the power (i.e., strength) of the low frequency (0.01-0.03Hz) in the CSF signals (P=0.013; Fig.1C). Specifically, early glaucoma patients showed significantly greater power than advanced glaucoma patients (Bonferroni P=0.010). The power of the global brain activity showed similar trends but did not reach significance (P=0.390; Fig.1D). The CSF-BOLD coupling at the 4s lag differed significantly across groups (P=0.007; Fig. 1E). Early glaucoma patients had significantly stronger coupling than advanced glaucoma patients (Bonferroni P=0.025) and healthy controls (Bonferroni P=0.013). Further, CSF-BOLD coupling was correlated with the volumes of optic nerve (right: R=-0.342, P=0.009; left: R=-0.344, P=0.009, Fig. 2D,E) and optic chiasm (R=0.264, P=0.047, Fig. 2F). Conclusions : Our observations of the altered CSF dynamics and CSF-BOLD coupling provide physiological evidence to support the recent hypothesis of widespread brain involvements in the early stage of glaucoma

Purpose : Glaucoma is an eye disease with widespread involvement of the brain. Since visual cortex (VC) may possess lower choline levels in glaucoma, and basal forebrain (BF) has cholinergic projections to VC for modulating cerebral blood flow and visual processing, we postulate that the vascular functions of the VC and BF are involved in glaucoma (PMID: 31242454). Recently, we used a novel whole-brain relative cerebrovascular reactivity (rCVR) mapping technique via resting-state functional MRI (rsfMRI) without gas challenge, and observed rCVR decrease in VC and rCVR increase in BF in patients with increasing glaucoma severity (PMID: 34892116). However, the underlying mechanisms remain to be elucidated. Here, we applied a hydrogel-induced glaucoma mouse model to elevate intraocular pressure (IOP) (PMID: 31176841), mapped wholebrain rCVR using rsfMRI, and measured optomotor responses (OMR). We hypothesize that chronic IOP elevation can lead to rCVR changes in the glaucomatous brain along with visual impairments. Methods : For the glaucoma model, C57BL/6J mice (male, 15-weeks, n=15) received intracameral injection of cross-linking hydrogel to the right eye to obstruct aqueous outflow and induce chronic IOP elevation. Controls (male, 15-weeks, n=13) were untreated. IOP was measured in both eyes 2-3 times per week for 3 weeks, followed by OMR and rsfMRI experiments at 7 Tesla (Fig. 1A). Results : Sustained IOP elevation was confirmed in the right eyes of the glaucoma model (Fig. 1B). Over 90% of mouse optic nerve fibers are known to project to the contralateral visual brain; rCVR decreased in the left but not right VC, whereas rCVR increased in the right BF in the glaucoma model but not the controls (Fig. 2A). These rCVR changes were inversely coupled (Fig. 2B). In addition, IOP of the injected eye was inversely correlated with rCVR in the left VC, while positively correlated with rCVR in the right BF (Fig. 2C). OMR revealed a decrease in visual acuity and an increase in visual contrast threshold for the injected eye (Fig. 2D) indicating visual impairment. The decrease in visual acuity was inversely correlated with rCVR in the BF (Fig. 2E). Conclusions : Mouse rCVR mapping using rsfMRI detects widespread brain changes induced by chronic IOP elevation, and demonstrates vascular involvement in glaucoma both within and beyond the primary visual pathways