Faculty Bibliography

TOPIC/OBJECTIVE:Understanding approaches to sustainability in cataract surgery and their risks and benefits CLINICAL RELEVANCE: In the United States, healthcare is responsible for approximately 8.5% of greenhouse gas (GHG), and cataract surgery is one of the most commonly performed surgical procedures. Ophthalmologists can contribute to reducing GHG emissions, which lead to a steadily increasing list of health concerns ranging from trauma to food instability. METHODS:We conducted a literature review to identify the benefits and risks of sustainability interventions. We then organized these interventions into a decision tree for use by individual surgeons. RESULTS:Identified sustainability interventions fall into the domains of advocacy and education, pharmaceuticals, process, and supplies and waste. Existing literature shows certain interventions may be safe, cost-effective, and environmentally friendly. These include dispensing medications home to patients after surgery, multi-dosing appropriate medications, training staff to properly sort medical waste, reducing the number of supplies used during surgery, and implementing immediate sequential bilateral cataract surgery where clinically appropriate. The literature was lacking on the benefits or risks for some interventions, such as switching specific single use supplies to reusables or implementing a hub-and-spoke style theatre setup. Many of the advocacy and education interventions have inadequate literature specific to ophthalmology but are likely to have minimal risks. CONCLUSIONS:Ophthalmologists can engage in a variety of safe and effective approaches to reduce or eliminate dangerous GHG emissions associated with cataract surgery.

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.

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 : Multiple sublayers of retina can be visualized with visible light (vis-) OCT.However, image quality can be compromised due to patient movement, cataracts, small pupil size, and light scattering causing haziness and variability in signal to noise ratio in individual A-scans and in entire B-scans.The purpose of this study was to examine the effect of conventional and deep neural network dehazing techniques on the visibility and quantitative assessment of retinal sub-layers on vis-OCT images. Methods : 9 healthy and 5 glaucoma subjects were scanned 3 times during one session.Scanning was done on the superior nasal side of para-foveal region,1.5 mm from the fovea with a 3D speckle reduction raster scanning protocol(3x3x1.6 mm with 8192x16x1024 samplings) using a prototype vis-OCT system.16 A-scan lines were averaged to reduce speckle noise.Gray-scale image dehazing guided by depth information and pretrained Dehazenet deep model following deep convolutional neural network with residual learning(DnCNN) were applied on original B-scans.Quality improvement were evaluated using quality index(QI) and contrast to noise ratio(CNR) on dehazed B-scans.For each subject, the dehazed B-scan of Dehazenet and DnCNN from a fixed location adjacent to the fovea were selected.The distances between each of 3 bright inner plexiform layers(IPL) and retinal pigment epithelium(RPE) sublayers were segmented manually for thickness measurements using a 8 A-scan averaged profile(Fig.).Coefficient of variations (CVs) were calculated to assess the measurement repeatability of the sublayers on original and dehazed B-scans. Results : Healthy and glaucoma subjects were age 45.67+/-11.7and 59.60+/-13.4(p=0.07,t-test),visual field mean deviation(MD)-1.55 to1.20 dB,and from -26.42 to -7.70dB(p= 0.003,Wilcoxon),global mean circumpapillary retinal nerve fiber layer(RNFL)thickness 96.33+/-12.20 and 59.80+/-9.09mm(p<0.001,Wilcoxon),respectively.Dehazed B-scans obtained by deep models have statistically significant better QI and CNR(Table1).Overall intra-subject CVs showed significantly improved reproducibility on all measured sub-layers of dehazed B-scans compared to original scans for all subjects(Tables 2,3). Conclusions : Vis-OCT image quality can be improved using deep neural network dehazing model resulting in higher reproducible thickness measurements of retinal sublayers within subjects in dehazed B-scans

Purpose : Deep learning of optical coherence tomography (OCT) may help discriminate glaucomatous eyes from healthy controls. However, the underlying decision making processes remain unclear. Recently, through computing class activation maps, our feature agnostic artificial intelligence of OCT images using a 3D convolutional neural network identified the optic nerve head (ONH) and its surrounding regions as structures significantly associated with glaucoma classification (PMID: 31260494). To pursue their contributions further, here we analyzed the optic nerve morphology from OCT and magnetic resonance imaging (MRI) in a subset of glaucoma and healthy subjects. Methods : Nine early glaucoma, 12 advanced glaucoma, and 4 healthy control subjects underwent spectral-domain OCT at 30x30x2 mum³ and 3-Tesla anatomical MRI at 1x1x1mm³ . Maximum intensity projection was applied to en-face OCT scans at the ONH (Fig. 1). The areas of the ONH [inner regions of interest, (ROI)] and surrounding regions (outer ROIs) visible in OCT were measured using global thresholding in ImageJ. One-way ANOVAs with post-hoc Tukey's tests were performed on the inner and outer ROIs between the 3 groups. Also, a Pearson correlation analysis was performed between the ROI areas in OCT and optic nerve volume extracted from MRI between the eye and optic chiasm. Results : For OCT of the ONH, significant group effect was observed for the areas in the inner ROIs (ANOVA: F= 7.823, p=0.00133). Post-hoc analyses revealed a significant difference between healthy controls and advanced glaucoma (p=0.0082) and between early and advanced glaucoma (p=0.0057) but no significance between healthy controls and early glaucoma (p=0.80) (Fig. 2A). No significant group effect was observed in the outer ROIs (ANOVA: F=0.004, p=0.996) (Fig. 2B). There was a negative correlation between the inner ROI area in OCT and optic nerve volume in MRI (R=-0.47, p=0.0011) (Fig. 2C). Conclusions : The ONH tissues visible on OCT appeared to contribute more than their surrounding regions to distinguishing between glaucomatous eyes and healthy eyes. The negative correlation between ONH area in OCT and optic nerve volume in MRI suggested the need to further understand the interactions between ONH and deeper brain structures in glaucoma. (Figure Presented)

Purpose : The lamina cribrosa (LC) is hypothesized to be the site of initial axonal damage in glaucoma with the peripapillary retinal nerve fiber layer (RNFL) thickness is widely used as a standard metric for quantifying this damage. The purpose of this study was to determine in vivo changes in the microstructure of the LC in eyes of non-human primates (NHP) with naturally occurring RNFL thinning. Methods : Spectral-domain OCT scans (Leica, Chicago, IL) of the optic nerve head (ONH) were acquired in vivo from a colony of 50 adult rhesus monkeys, suspected of having high prevalence of naturally occurring glaucoma. The circumpapillary global and quadrant RNFL thickness was analyzed using a custom automated segmentation software. From the set of 100 eyes, the 10 eyes with the thinnest global RNFL values were selected as the study group, while 10 eyes with RNFL values around the 50 percentile were used as the control group. A previously described automated segmentation algorithm was used for LC microstructure analysis. The LC microstructure was analyzed globally and in the th following volumetric sectors: quadrants, central and peripheral lamina, and 3 depth slabs (anterior, middle, posterior; Figure). Beam thickness/pore diameter ratio (BPR) and connective tissue volume fraction (CTVF: beam volume/total volume) were calculated globally and in sectors. Results : 20 eyes (15 animals) were analyzed (Table 1). While no significant difference was detected between groups for age, weight or disc size, the study group had significantly thinner RNFL than the control group (p<0.01). The study group had significantly larger BPR and CTVF compared with the control group (Table 2). Significant sectoral differences between study and control group RNFL thickness were noted for BPR and CTVF in the nasal and temporal quadrants, central LC, and in LC depth. Across eyes, the global RNFL thickness was moderately negatively correlated only with the global CTVF (lower RNFL thickness associated with higher CTVF; r² =0.63, p=0.045). Conclusions : Eyes with thinner circumpapillary RNFL had thicker LC BPR and CTVF globally and in various sectors when compared to eyes with normal RNFL thickness. Whether these LC changes are the cause of RNFL damage or the result of remodeling of the LC requires further investigation. (Figure Presented)