Faculty Bibliography

Spectral imaging holds great promise for the non-invasive diagnosis of retinal diseases. However, to acquire a spectral datacube, conventional spectral cameras require extensive scanning, leading to a prolonged acquisition. Therefore, they are inapplicable to retinal imaging because of the rapid eye movement. To address this problem, we built a coded aperture snapshot spectral imaging fundus camera, which captures a large-sized spectral datacube in a single exposure. Moreover, to reconstruct a high-resolution image, we developed a robust deep unfolding algorithm using a state-of-the-art spectral transformer in the denoising network. We demonstrated the performance of the system through various experiments, including imaging standard targets, utilizing an eye phantom, and conducting in vivo imaging of the human retina.

Background/aims Demonstrate that subretinal drusenoid deposits (SDDs) in age-related macular degeneration (AMD) are linked to coexistent high-risk vascular diseases (HRVDs). Methods Cross-sectional study. Two hundred AMD subjects (aged 51-100 years; 121 women, 79 men) were recruited. Spectral domain optical coherence tomography, autofluorescence and near-infrared reflectance imaging, and lipid profiles were obtained. Subjects were assigned by health history questionnaires into those with or without HRVDs, defined as: cardiac valve defect (eg, aortic stenosis), myocardial defect (eg, myocardial infarction) and stroke/transient ischaemic attack. Masked readers assigned subjects into two groups: SDD (with or without drusen) and drusen (only). Univariate testing was performed by χ 2 test. We built multivariate regression models to test relationships of coexistent HRVD to SDD status, lipid levels and other covariates. Results The prevalence of HRVD was 41.2% (40/97) and 6.8% (7/103) in the SDD and non-SDD groups, respectively (correlation of SDD with HRVD, p=9×10 -9, OR 9.62, 95% CI 4.04 to 22.91). Multivariate regressions: only SDDs and high-density lipoprotein (HDL) in the first two HDL quartiles remained significant for HRVD (p=9.8×10 -5, 0.021, respectively). Multivariate regression model: SDDs and an HDL in Q1 or Q2 identified the presence of HRVD with the accuracy of 78.5%, 95% CI 72.2% to 84.0%. Conclusions High-risk cardiovascular and neurovascular diseases were accurately identified in an AMD cohort from SDDs and HDL levels. The SDDs may be related to inadequate ocular perfusion resulting from the systemic vasculopathies. Further research with this paradigm is warranted and might reduce mortality and morbidity from vascular disease.

PURPOSE/OBJECTIVE:Soft drusen and subretinal drusenoid deposits (SDDs) characterize two pathways to advanced age-related macular degeneration (AMD), with distinct genetic risks, serum risks and associated systemic diseases. METHODS:126 Subjects with AMD were classified as SDD (with or without soft drusen), or non-SDD (drusen only) by retinal imaging, with serum risks, genetic testing, and histories of cardiovascular disease (CVD) and stroke. RESULTS:There were 62 SDD subjects and 64 non-SDD subjects, 51 total had CVD or stroke.SDD correlated significantly with: lower mean serum HDL (61±18 vs. 69±22 mg/dl, p= 0.038, t test); CVD and stroke (34/51 SDD, p= 0.001, chi square); ARMS2 risk allele (p= 0.019, chi square), but not with CFH risk allele (p = 0.66). Non-SDD (drusen only) correlated/trended with: APOE2 (p= 0.032) and CETP (p= 0.072) risk alleles (chi square). Multivariate independent risks for SDD were: CVD and stroke (p= 0.008), and ARMS2 homozygous risk (p= 0.038). CONCLUSION/CONCLUSIONS:SDD and non-SDD subjects have distinct systemic associations, serum and genetic risks. SDD are associated with CVD and stroke, ARMS2 risk, and lower HDL; non-SDD with higher HDL, CFH risk and two lipid risk genes. These and other distinct associations suggest these lesions are markers for distinct diseases.

PURPOSE/OBJECTIVE:To describe the incidence of subretinal deposits that are similar in structure and stage on OCT imaging to subretinal drusenoid deposits (SDDs) in age-related macular degeneration (AMD) in patients with hypertensive choroidopathy secondary to severe pre-eclampsia and malignant hypertension (MHT) and the implications of this ischemic choroidopathy for the pathophysiologic characteristics of SDDs in AMD. DESIGN/METHODS:Retrospective cross-sectional study. PARTICIPANTS/METHODS:Thirty-three pre-eclampsia patients and 25 MHT patients with serous retinal detachment (SRD) in at least 1 eye were included. METHODS:Serial multimodal images, including enhanced depth imaging spectral-domain OCT of eyes with hypertensive choroidopathy secondary to pre-eclampsia and MHT, were reviewed at 2 time points, the acute phase (within 4 weeks of initial hypertensive insult) and the recovery phase (beyond 4 weeks). MAIN OUTCOME MEASURES/METHODS:Incidence of SDD-like lesions in patients with hypertensive choroidopathy secondary to pre-eclampsia and MHT. RESULTS:Subretinal drusenoid deposit-like lesions were observed exclusively in eyes with SRD. Serous retinal detachment occurred in 87.87% of eyes of pre-eclampsia patients and in 94% of eyes of MHT patients. Subretinal drusenoid deposit-like lesions occurred in 28.57% of all eyes with SRD, in 32.76% of eyes with SRD from the pre-eclampsia group, and in 23.40% of eyes with SRD from the MHT group. Vascular imaging suggested underlying choroidal ischemia in all patients (12 eyes) in which it was performed. CONCLUSIONS:Choroidal ischemia may be the underlying mechanism of SDD-like lesions in patients with pre-eclampsia and MHT choroidopathy. These findings potentially are of utmost importance in understanding the mechanism of the reticular macular disease subtype of AMD. Reticular macular disease is characterized by the known association of choroidal insufficiency and SDD, with choroidal insufficiency postulated, but not proven, to be causative. Pre-eclampsia and MHT choroidopathy seems to be a model for lesions similar to SDD in AMD developing based on choroidal insufficiency and, as such, may offer further insights into the pathoetiologic features of SDD in AMD.

Results/UNASSIGNED:The system achieved an accuracy of 89.67% (sensitivity, 83.33%; specificity, 93.89%; and AUC, 0.93). For external validation, the Retinal Fundus Image Database for Glaucoma Analysis dataset, which has 638 gradable quality images, was used. Here, the model achieved an accuracy of 83.54% (sensitivity, 80.11%; specificity, 84.96%; and AUC, 0.85). Conclusions/UNASSIGNED:Having demonstrated an accurate and fully automated glaucoma-suspect screening system that can be deployed on telemedicine platforms, we plan prospective trials to determine the feasibility of the system in primary-care settings.

The diagnosis and treatment of medical retinal disease is now inseparable from retinal imaging in all its multimodal incarnations. The purpose of this article is to present a selection of very different retinal imaging techniques that are truly translational, in the sense that they are not only new, but can guide us to new understandings of disease processes or interventions that are not accessible by present methods. Quantitative autofluorescence imaging, now available for clinical investigation, has already fundamentally changed our understanding of the role of lipofuscin in age-related macular degeneration. Hyperspectral autofluorescence imaging is bench science poised not only to unravel the molecular basis of retinal pigment epithelium fluorescence, but also to be translated into a clinical camera for earliest detection of age-related macular degeneration. The ophthalmic endoscope for vitreous surgery is a radically new retinal imaging system that enables surgical approaches heretofore impossible while it captures subretinal images of living tissue. Remote retinal imaging coupled with deep learning artificial intelligence will transform the very fabric of future medical care.

Purpose/UNASSIGNED:To build and validate artificial intelligence (AI)-based models for AMD screening and for predicting late dry and wet AMD progression within 1 and 2 years. Methods/UNASSIGNED:The dataset of the Age-related Eye Disease Study (AREDS) was used to train and validate our prediction model. External validation was performed on the Nutritional AMD Treatment-2 (NAT-2) study. First Step/UNASSIGNED:An ensemble of deep learning screening methods was trained and validated on 116,875 color fundus photos from 4139 participants in the AREDS study to classify them as no, early, intermediate, or advanced AMD and further stratified them along the AREDS 12 level severity scale. Second step: the resulting AMD scores were combined with sociodemographic clinical data and other automatically extracted imaging data by a logistic model tree machine learning technique to predict risk for progression to late AMD within 1 or 2 years, with training and validation performed on 923 AREDS participants who progressed within 2 years, 901 who progressed within 1 year, and 2840 who did not progress within 2 years. For those found at risk of progression to late AMD, we further predicted the type (dry or wet) of the progression of late AMD. Results/UNASSIGNED:For identification of early/none vs. intermediate/late (i.e., referral level) AMD, we achieved 99.2% accuracy. The prediction model for a 2-year incident late AMD (any) achieved 86.36% accuracy, with 66.88% for late dry and 67.15% for late wet AMD. For the NAT-2 dataset, the 2-year late AMD prediction accuracy was 84%. Conclusions/UNASSIGNED:Validated color fundus photo-based models for AMD screening and risk prediction for late AMD are now ready for clinical testing and potential telemedical deployment. Translational Relevance/UNASSIGNED:Noninvasive, highly accurate, and fast AI methods to screen for referral level AMD and to predict late AMD progression offer significant potential improvements in our care of this prevalent blinding disease.

PURPOSE/OBJECTIVE:To report multimodal imaging in a novel case of angioid streaks in a patient with Turner syndrome with 10-year follow-up. METHODS:Case report of a patient with Turner syndrome and angioid streaks followed at Bellevue Hospital Eye Clinic from 2007 to 2017. Fundus photography, fluorescein angiography, and optical coherence tomography angiography were obtained. RESULTS:Angioid streaks with choroidal neovascularization were noted in this patient with Turner syndrome without other systemic conditions previously correlated with angioid streaks. CONCLUSION/CONCLUSIONS:We report a case of angioid streaks with choroidal neovascularization in a patient with Turner syndrome. We demonstrate that angioid streaks, previously associated with pseudoxanthoma elasticum, Ehlers-Danlos syndrome, Paget disease of bone, and hemoglobinopathies, may also be associated with Turner syndrome, and may continue to develop choroidal neovascularization, suggesting the need for careful ophthalmic examination in these patients.

Purpose : Age-related macular degeneration (AMD), a leading cause of blindness, is characterized by the formation of drusen. Subretinal drusenoid deposits (SDD) sit over the retinal pigment epithelium, are a proven risk factor for AMD, and can be visualized on cross-sectional spectral domain optical coherence tomography (SD-OCT). We are evaluating the relationship between SDD and serum risk factors for cardiovascular disease (CVD) in AMD. Methods : 58 subjects (ages of 50-90), diagnosed with AMD on two successive examinations, were recruited prospectively, provided blood samples and underwent SDOCT. The presence of SDD was determined on SD-OCT by an experienced examiner, and a panel of serum risk factors performed: Total Cholesterol (TC), Triglycerides (TG), HDL, VLDL, LDL Direct and high sensitivity C-reactive protein (hs-CRP). Independent t-tests were performed on these results. Results : 25 of 58 subjects were found to have SDD present on SD-OCT. Independent ttests demonstrated a significant association (p<0.05) of high TC (>149 mg/dL) (p=0.01) and low HDL (<39mg/dL) (p=0.02) in subjects with SDD compared to subjects without SDD. Post hoc analysis showed that of patients with high TC, 52% had SDD and 22% did not have SDD present (p=0.02); of patients with low HDL, 4% had SDD, 12% did not (p=0.04); of patients with high LDL-direct, 72% had SDD and 55% did not have SDD (p=0.05). Results for TG and hsCRP were inconclusive. Conclusions : The relationship of TC and AMD is inconsistently reported in the literature, with no demonstrated difference between the phenotypes of AMD. Our results demonstrate that high TC is a specific and significant risk factor for AMD with SDD compared to AMD without SDD. High TC is also a strong risk factor for CVD. Therefore, the leading cause of blindness (AMD) can now be connected to the leading cause of death (CVD) through its SDD phenotype, which may be an effective ophthalmic predictor for future CVD. High LDL is a strong risk for CVD as well, and the risk for SDD also approached significance. High HDL is a known risk for AMD, and per our study, may confer even greater risk for SDD. One limitation of our study is that the groups were not matched for other independent CVD risk factors such as hypertension and smoking history, which