Faculty Bibliography

Purpose : Mutations in optineurin (OPTN) are associated with familial normal tension glaucoma and other neurodegenerative diseases. It remains unclear how OPTN loss or mutation alters visual function during aging. Here, we used transgenic mouse models and in vivo assessments to test the hypothesis that OPTN dysfunction contributes to progressive visual impairment through a toxic gain of function mechanism. Methods : Mice with C57BL/6 background were used (Fig 1): wildtype (WT; n=19), homozygous OPTN knock-out (mOPTN-KO; n=13), hemizygous mouse E50K OPTN knock-in (mE50K-het; n=8), homozygous mouse E50K OPTN knock-in (mE50K homoz; n=10), and human E50K OPTN bacterial artificial chromosome overexpression (hE50K BAC; n=6) (PMID: 31076632, 25818176). Intraocular pressure (IOP), total retinal thickness (TRT), visual acuity (VA), and contrast sensitivity (CS) were measured at 6, 12, and 18 months of age in the same mice using the TonoLab rebound tonometer, Bioptigen spectral-domain optical te uses cookies. By continuing to use our website, you are agreeing to coherence tomography imaging, and OptoMotry optokinetic virtual reality system respectively. Left and right eye data were averaged and analyzed using ANOVAs followed by posthoc tests between genotype and age groups, as well as linear regressions for VA versus contrast threshold (CT). Results : Our longitudinal study of the same mice during the aging process showed that IOP remained normal between 10-15 mmHg (Fig 2A). Small to no difference in TRT over time or compared to WT was observed (Fig 2B). mE50K-homoz, mE50K-het, and hE50K BAC mice exhibited greater age-dependent decline in VA and CT than WT or mOPTN-KO mice (Fig 2C, 2D, 2E). In contrast, mOPTN-KO mice showed preservation of VA and CT over time compared to WT. Consistently, mice with one copy of E50K OPTN (mE50K het) experienced less deterioration of VA and CT compared to mice with two copies (mE50K homoz) or mild overexpression (hE50K BAC). Conclusions : Depsite limited IOP and TRT changes between age and genotype groups, E50K OPTN was associated with differential age-dependent visual impairment (greater for CS than VA). Surprisingly, OPTN deficiency preserved visual function such that CS in knockout mice was better than WT mice. Our results suggest visual loss associated with E50K OPTN is due to a toxic gain of function mechanism, and that suppression of OPTN might constitute a therapeutic strategy for glaucomatous neurodegeneration

Purpose : Compare the speed of glaucoma progression as measured by global visual field (VF) and optical coherence tomography (OCT) metrics. Methods : Glaucoma suspect, pre-perimetric glaucoma (PPG) and perimetric glaucoma (PG) participants of Advanced Imaging for Glaucoma study, who had at least 7 visits with visual field (VF) and OCT ONH scan, were analyzed. Severity was staged by the modified Hodapp-Parrish-Anderson Criteria. Eyes with significant cataract progression were excluded. Spectral-domain OCT (RTVue, Optovue) and VF testing were performed every 6 months. The nerve fiber layer (NFL) thickness was measured from ONH scan. The NFL mean deviation (MD) were VF-equivalent dB-scale quantities based on sectorwise nonlinear regression of NFL thickness with VF deviation using cross-sectional data over a wide range of glaucoma severity. Linear regression was used to estimate the glaucoma progression speed. Results : Seventy-five glaucoma suspect eyes (VF MD-0.1+/-1.2dB), 160 PPG eyes (0.2+/-1.3 dB), 77 early PG eyes (-0.9+/-1.6dB) and 20 moderate+severe PG (-10.8+/-3.2dB) eyes were analyzed. The follow-up duration was 54 months +/- 8 months (mean +/- SD). For both VF MD and NFL MD, the speed of progression increased monotonically with glaucoma severity (Table 1). For overall NFL thickness, the progression speed was greatest in the PPG and early PG stages, but slowed down at the moderate+severe stages. The ratios of progression speed for NFL thickness relative to VF were significantly different between stages (p<0.006, one-way ANOVA). The ratios of progression speed for NFL MD relative to VF MD was generally slower (0.58-0.72), but not significantly different across disease stages (p=0.08). The progression speed of both NFL-MD and VF-MD were associated with baseline parameters (faster progression in eyes with more severe disease at baseline), while progression speed of NFL thickness was not (Table 2). Conclusions : Compared to VF MD, NFL thickness tends to overestimate the progression speed in the early stages of glaucoma and underestimate it in the later stages. Clinicians should be aware of the discrepancy in the apparent speed of disease progression as measured by structural and functional metrics, which strongly depend on the stage of disease severity. Converting the NFL thickness profile to NFL MD may provide a progression metric more consistent with VF MD over a wider range of glaucoma severity

Purpose : To assess the repeatability of estimates of mean deviation (MD) and visual field index (VFI) obtained from an automated deep-learning approach that analysed raw OCT volumes. Methods : OCT scans were acquired from both eyes of 138 healthy, 743 glaucoma suspects and 941 glaucoma patients (Cirrus HD-OCT scanner, 200x200 ONH Cubes, Zeiss, Dublin CA). The scans were acquired at multiple visits, with two or more scans acquired at each visit. Scans with signal strength < 7 were discarded, giving us a total of 19,208 OCT scans. A subset of 5207 eyes (total of 10,414 scans) had repeat scans of that met the inclusion criteria. 24-2 Humphrey visual field (VF) tests were administered at each visit. A single convolutional neural network was trained to estimate the MD and VFI (dual outputs) from downsampled OCT volumes (50x50x128 voxels). The network consisted of 5 convolutional layers, followed by a global average pooling layer and dual outputs to enable the simultaneous estimation of MD and VFI. A mean squared error loss was used to train the network using an Adam optimiser over a total of 200 epochs. A 10-fold cross-validation scheme was used, where the dataset was divided into 10 non-overlapping folds (~182 subjects per fold) - trained on 8-folds, validated on one and tested on one. Each subject was limited to a unique fold. The performance of the method was assessed by computing the median error and interquartile range. The repeatability was assessed using a set of 5207 OCT scans that had repeats available. Results : The median absolute error (Q1, Q3) for the estimates of MD and VFI were 1.66 (0.79, 2.99) dB and 3.01 (1.48, 6.63) %, respectively. In the reproducibility test, the Pearson's correlation coefficient was 0.91 (CI: [0.91, 0.92]) and 0.91 (CI: [0.90, 0.92]), for MD and VFI, respectively. The median absolute difference between the repeated estimates for MD and VFI were 0.53 (0.21, 0.51) dB and 1.17 (0.45, 1.14)%, respectively. Conclusions : The deep-learning based approach for estimating visual field test parameters shows repeatability better than expected test-to-test variability

Purpose : Lamina cribrosa (LC) deformation is hypothesized to be a major cause of glaucoma. The LC undergoes different forms of stress both anteriorly from intraocular pressure (IOP), as well as posteriorly and circumferentially from subarachnoid cerebrospinal fluid pressure (CSFP) and the sclera. The purpose of this study was to determine possible in vivo changes in the path of the lamina pores under different IOP settings while maintaining fixed CSFP. Methods : Spectral-domain OCT scans (Leica, Chicago, IL) of the optic nerve head (ONH) were acquired in vivo under different pressure settings from healthy rhesus monkeys. IOP was controlled using a gravity-based perfusion system through a needle inserted into the anterior chamber. CSFP was maintained at the baseline opening pressure via gravitybased perfusion system through cannulation of the brain's lateral ventricle (range 8- 12mmHg). Scans were acquired at baseline IOP (15mmHg), high (30 mmHg) and very high IOP (40-50 mmHg) and registered in 3D. Pores from shared regions were automatically segmented using a previously described segmentation algorithm. The path of each pore was tracked based on the calculated geometric centroid of each pore. The tortuosity of each pore path was defined as the total actual distance of the centroid path divided by the minimal distance between the first (most anterior) and last (most posterior) pore centroids. Results : 7 eyes from 6 healthy adult Rhesus macaque were analyzed. The mean value of the pore path tortuosity varies between eyes at baseline IOP levels (range: 1.16-1.68; Table). Two main overall patterns of pore path tortuosity were detected in response to increased IOP at fixed CSFP: 4 eyes became more tortuous (M2, M5, M8, M11); in the rest of the eyes (M6 OD, M6 OS, M10) the pore paths remained either unchanged or showed a variable response. No statistically significant change (p > 0.05) was observed in this small sample in either the subject-specific analysis or the analysis of the pooled combined values of the pore path tortuosity. Conclusions : Baseline pore tortuosity as well as the response of the pores to acute IOP increase varies between eyes. Further investigation is warranted to determine if these differences are associated with glaucoma susceptibility

Purpose : Alterations in retinal oxygen metabolism are implicated in blindness causing diseases, such as diabetic retinopathy and glaucoma. Therefore, a non-invasive clinical tool to assess oxygen saturation (sO2) in retinal vessels is desirable. Recent development of visible-light optical coherence tomography (vis-OCT) enabled non-invasive sO measurements in retinal blood vessels at micrometer-scale resolution by threedimensional (3D) spectroscopic analysis. Nevertheless, such measurements are susceptible to spectral contaminants from the complex retina anatomy and vis-OCT signal detection and processing, decreasing measurement reliability. To overcome limitations posed by spectral contaminants, we developed adaptive-spectroscopic OCT (AS-OCT), a processing technique that enables non-invasive, 3D, environment-independent sO measurements in the human retina. Methods : We used vis-OCT to image the retinas of 18 healthy volunteers. Light exposure in the eye was < 250 muW and imaging acquisition time was 5 sec. We used adaptive spectroscopic OCT (AS-OCT) to identify and remove contaminants from retinal tissues, chromatic aberrations, and spectrally-dependent roll-off. Then, we automatically selected the optimal depths in the vessel for sO measurement. Finally, we measured the attenuation spectrum in the blood vessel and used a least-squares regression fit with known spectra to determine the sO value. Results : We measured sO in 125 unique retinal vessels near the optic disc (vessel diameters ranging from 37 mum to 176 mum). Major arteries had sO2= 97.9 +/-2.9 % (mean +/-standard deviation) (n = 36), small arteries (diameter < 100 had sO2= 93.2 +/-5.0 % (n = 36), and veins had sO2= 58.5 +/-4.3 % (n = 53). Repeated measurement standard deviations were 2.21% and 2.32% for all arteries and veins, respectively. Fig. 1 shows an oximetry map of the optic disc in the retina of a healthy 23 year-old volunteer. Conclusions : AS-OCT enables environment-independent retinal oximetry in the clinical setting. Repeatability in arteries and veins < 2.5 % indicates robust measurements that are promising for clinical use

Purpose : Repetitive transorbital alternating current stimulation (rtACS) is an application of weak electric current near the eyes used in vision rehabilitation of optic neuropathies (ON). Conceptually rtACS entrains neuronal oscillations, augmenting neuronal function. In subjects with ON we evaluated whether rtACS influenced visual structure and function. Methods : 34 subjects with ON enrolled in a prospective trial underwent comprehensive ophthalmic evaluation, visual field (VF) 24-2 and 10-2 tests (Humphrey Field Analyzer) and OCT (Cirrus HD-OCT) retinal nerve fiber layer (RNFL) and ganglion cell inner plexiform layer (GCIPL) thicknesses at baseline and follow-up (FU) visits. Subjects received rtACS 30-to 45-minutes daily for 10 days. Sham subjects (n=4) underwent the same procedures but received no current. Point-by-point analyses of VF total deviation (TD) values were conducted between rtACS and sham groups. Regression analyses determined rate of change for each TD point per eye (significant points with positive rate of change defined as improved, negative rate of change as progressed; insignificant rate of change as no change) and the association between RNFL and GCIPL between groups. Results : The number of FU visits with VF tests ranged 2 to 7, with no significant differences detected between rtACS vs sham groups' FU duration. No significant differences were detected between groups' baseline VF 24-2 and 10-2 mean deviation (MD) values (Table 1). The average numbers of improved points (VF 10-2) and progressed points (VF 24-2) were greater for rtACS while the average number of no change points was greater for sham (VF 24-2, p0.05, Table 1). Further analysis of FU duration determined a significant interaction with rtACS; number of improved points (VF 10-2) and progressed points (VF 24-2, p<0.02) were not sustained over time. No significant differences were detected in average RNFL and GCIPL thicknesses between groups. Conclusions : Preliminary analyses of the effect of rtACS in ON indicate initial improvement but not a clear benefit over time. Detection of differences between rtACS vs sham groups may be biased due to the small sham sample and range of FU duration as VF test-to-test variability is known to increase with worsening VF MD. Future analyses will assess interim effect at early vs late FU time points to evaluate the role of rtACS in vision rehabilitation

Purpose : To improve the performance of the feature agnostic AI-based glaucoma detection algorithm by evaluating an uncertainty score for each prediction. Methods : We previously developed a 5-layer 3D Convolutional Neural Network (CNN) in using the OCT scans from both eyes of 134 healthy, 779 glaucoma patients on a Cirrus HDOCT scanner (200x200 ONH Cubes; Zeiss, Dublin CA). In our analysis, we excluded scans with signal strength less than 7 and downsampled the volumes to 64x64x128 voxels. Uncertainty of AI models can be estimated by computing the effect of randomly ignoring a set of parameters within the network. We randomly zeroed 5% of each of the 5 convolutional layers and computed the entropy in the final score over 20 forward passes. The performance of the approach was assessed using a 10-fold cross validation study. Results : Over the 10-folds, the model showed an AUC of 0.91+/-0.027. In analysing the uncertainty and the probabilistic scores generated by the model (Softmax function) for one fold (see Fig. 1), we observed that a threshold of 0.8 can be used to flag 75% of the false positives and false negatives for further review. On the other hand, only 25% of the healthy controls and 20% of glaucoma patients showed an uncertainty score above that threshold. Fig. 2 summarises the overall uncertainties scores and indicates that low scores are associated with the correctly identified cases while the errors show higher uncertainty scores. Conclusions : The quantitative uncertainty measure provides supplementary information to clinicians and can be used to flag difficult cases automatically. Given that the dataset used in this work is highly imbalanced (more positive cases compared to normal cases) the uncertainty score for true negative cases is significantly higher compared to true positive cases. We expect to achieve lower uncertainty scores for normal cases if more data for normal eyes are available. The uncertainty analysis presented here may aid clinical interpretations of AI-based glaucoma detection outcomes. A separate study will be run to measure this improvement and compare the result with experts' level of uncertainty

PURPOSE/OBJECTIVE:To describe the efficacy and safety of open versus closed conjunctival implantation of the XEN45 Gel Stent (Allergan Inc). DESIGN/METHODS:Retrospective, multicenter study. PARTICIPANTS/METHODS:A total of 137 patients with glaucoma who underwent XEN45 implantation via open or closed conjunctival methods. The XEN45 was implanted as a stand-alone procedure or at the time of cataract surgery by 5 surgeons. METHODS:Patient demographics, diagnoses, preoperative and postoperative clinical data, outcome measures including intraocular pressure (IOP), use of glaucoma medications, visual acuity, and complications were collected. Statistical analyses were performed with P < 0.05 as significant. MAIN OUTCOME MEASURES/METHODS:Failure was defined as less than 20% reduction of IOP from medicated baseline or IOP >21 mmHg at 2 consecutive visits at postoperative month 1 and beyond, the need for subsequent operative intervention or additional glaucoma surgery, or a catastrophic event such as loss of light perception. Eyes that had not failed by these criteria and were not on glaucoma medications were considered complete successes. Eyes that had not failed but required glaucoma medications were defined as qualified successes. RESULTS:Complete success was achieved in 31% and 56% of the closed and open groups, respectively (P = 0.01). Qualified success was achieved in 53% and 71% of the closed and open groups, respectively (P = 0.06). At postoperative month 12, the open conjunctiva group was using fewer glaucoma medications than the closed group (0.9 vs. 1.8, respectively; P = 0.02). At postoperative month 12, the open group had a significantly greater percentage of IOP reduction compared with the closed group (43.1% vs. 24.8%, respectively; P = 0.02). Postoperative needling rates were higher in the closed group compared with the open group (36.1% vs. 11.8%, P = 0.001). CONCLUSIONS:Implantation of the XEN45 with opening of the conjunctiva is a safe and efficacious procedure to lower IOP with comparable success rate and lower needling rate compared with the closed conjunctiva technique. Prospective evaluation of the various methods for XEN45 implantation will allow for further comparison.

BACKGROUND:This review explores the bioethical implementation of artificial intelligence (AI) in medicine and in ophthalmology. AI, which was first introduced in the 1950s, is defined as "the machine simulation of human mental reasoning, decision making, and behavior". The increased power of computing, expansion of storage capacity, and compilation of medical big data helped the AI implementation surge in medical practice and research. Ophthalmology is a leading medical specialty in applying AI in screening, diagnosis, and treatment. The first Food and Drug Administration approved autonomous diagnostic system served to diagnose and classify diabetic retinopathy. Other ophthalmic conditions such as age-related macular degeneration, glaucoma, retinopathy of prematurity, and congenital cataract, among others, implemented AI too. PURPOSE/OBJECTIVE:To review the contemporary literature of the bioethical issues of AI in medicine and ophthalmology, classify ethical issues in medical AI, and suggest possible standardizations of ethical frameworks for AI implementation. METHODS:Keywords were searched on Google Scholar and PubMed between October 2019 and April 2020. The results were reviewed, cross-referenced, and summarized. A total of 284 references including articles, books, book chapters, and regulatory reports and statements were reviewed, and those that were relevant were cited in the paper. RESULTS:Most sources that studied the use of AI in medicine explored the ethical aspects. Bioethical challenges of AI implementation in medicine were categorized into 6 main categories. These include machine training ethics, machine accuracy ethics, patient-related ethics, physician-related ethics, shared ethics, and roles of regulators. CONCLUSIONS:There are multiple stakeholders in the ethical issues surrounding AI in medicine and ophthalmology. Attention to the various aspects of ethics related to AI is important especially with the expanding use of AI. Solutions of ethical problems are envisioned to be multifactorial.