Faculty Bibliography

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.

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: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.

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 : The ability to detect progression in eyes with advanced glaucoma is challenging because of known limitations of commonly used structural and functional parameters reaching their minimal measurable limit (floor effect) or increased measurement variability. We examined the ability of inner nuclear layer (INL) thickness measurements to demonstrate change longitudinally in eyes with early and advanced severity glaucoma. Methods : Subjects with glaucoma and >=4 visits were included in the study. Subjects in the ?Early/Moderate? group (EG) had average circumpapillary retinal nerve fiber layer (cRNFL) thicknesses >=60mum and subjects in the ?Advanced? group (AG) had average cRNFL thicknesses <=60mum. All subjects had comprehensive ophthalmic examination, Humphrey visual field (Zeiss, Dublin, CA) testing, and spectral-domain OCT (Cirrus HD-OCT; Zeiss) optic nerve head (ONH) and macula scans. Segmentation of the INL was performed using the Iowa Reference Algorithms (Retinal Image Analysis Lab, Iowa Institute for Biomedical Imaging, Iowa City, IA) and segmentation errors were manually corrected by a trained grader. Overall INL thickness along with the superior and inferior hemifields were used for analysis. Rates of progression were estimated from longitudinal OCT and visual field (VF) data using mixed effects models adjusting for baseline age, follow-up duration, and signal strength at each visit. Results : 23 eyes (23 subjects), 12 with EG and 11 with AG, were included in the study. At baseline, a statistically significant difference between groups was detected in MD, cRNFL, and GCIPL thicknesses (Table 1). In EG eyes, the rate of change was significantly different than a zero slope for cRNFL thickness, C:D ratio, and GCIPL thickness (Table 2). Inferior INL thickness was the only INL parameter showing significant rate of change. However, in the advanced group, all parameters (including both global and sectoral INL thicknesses) showed significant rate of change except for the cRNFL. Conclusions : Longitudinal measurements of INL thickness may be useful for following disease progression in subjects with advanced-stage glaucoma where cRNFL thickness is no longer useful

Purpose : Previously we described the longitudinal glaucoma relationship between structure and function using a broken stick analysis approach to identify the location where the rate of change accelerates or decelerates. In that analysis we used each measurement point as an independent point, aggregated all eyes from all visits, and treated longitudinal data as cross-sectional. Using improved statistical methodology, we accounted for repeated measurements and the use of data from both eyes in the longitudinal model. The purpose of this study is to identify the locations of tipping points and rates of change before and after them in structural and functional measurements. Methods : Subjects with comprehensive ophthalmic examination and 5 or more visits with qualified visual fields (VF; Humphrey Field Analyzer; Zeiss, Dublin, CA) and OCT (Cirrus HD-OCT; Zeiss) with ONH and macular scans were enrolled. Segmented mixed models that account for repeated measurements were utilized to estimate the tipping points and the difference-in-slope. The number of tipping points was determined by identifying the optimal model using Bayesian information criterion. Results : 216 eyes (164 open angle glaucoma, 45 glaucoma suspect, and 7 healthy eyes) of 145 subjects were analyzed (Table). Retinal nerve fiber layer (RNFL), and ganglion cell inner retinal layer (GCIPL) decreases and cup to disc ratio (CDR) increases since early stages of the disease were measured (Figure). Unlike previous cross-sectional reports, visual field mean deviation (MD) also decreases along with structural parameters since early stages of the disease. RNFL thinning stalls beyond MD<-15.63dB (Figure A) while GCIPL keeps decreasing (B), and CDR slowly increases (C) throughout the functional damage range. Direct comparison between the structural parameters shows that RNFL thinning decelerates in advanced disease compared to both GCIPL and CDR and GCIPL thinning decelerates compared to CDR. Conclusions : Structural and functional measurements (RNFL, GCIPL, CDR and MD) are useful to evaluate glaucoma change from early stages of the disease. As glaucoma progresses and RNFL reaches its minimal measurable level GCIPL, CDR and MD remain useful to evaluate the disease. The clinical routine for following subjects with glaucoma should account for the ability to measure relevant parameters at various stages of disease

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 : 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