PurposeThe purpose of this study was to investigate changes in visual function following surgery and identify predictors of postoperative visual function in patients with idiopathic epiretinal membrane (iERM).MethodsThis retrospective study included 37 eyes with iERM. Macular structure was assessed using optical coherence tomography (OCT) and OCT angiography (OCTA), whereas visual function was evaluated using best-corrected visual acuity (BCVA) and microperimetry. All parameters were measured preoperatively (baseline) and at 3 and 6 months postoperatively. Associations between macular structural parameters and visual function outcomes were analyzed.ResultsCentral retinal thickness (CRT) decreased significantly at both 3 and 6 months postoperatively. Parafoveal vessel density (PFVD) of the deep capillary plexus (DCP) and BCVA improved significantly at 3 months, with no significant changes observed between 3 and 6 months. Retinal sensitivity (RS) and fixation stability (FS) demonstrated significant improvement at 6 months, whereas macular integrity (MI) showed no significant postoperative changes. Multiple linear regression analysis revealed that baseline PFVD of the DCP was a significant predictor of postoperative BCVA. Logistic regression analysis identified baseline PFVD of the DCP as an independent predictor of postoperative FS improvement.ConclusionsBCVA, RS, and FS improve significantly following iERM surgery, with BCVA improving earlier than microperimetry parameters. A higher baseline PFVD of the DCP is a significant prognostic factor for better BCVA and FS improvement.Translational RelevanceMicroperimetry offers an objective and quantitative evaluation of macular functional changes after iERM surgery. PFVD of the DCP, as measured by OCTA, can serve as a valuable predictor of BCVA and FS outcomes postoperatively.

PurposeThe purpose of this study was to evaluate the performance of large language models (LLMs)—GPT-4, GPT-4o, Qwen2, and Qwen2.5—in addressing patient- and clinician-focused questions on ptosis-related inquiries, emphasizing cross-lingual applicability and patient-centric assessment.MethodsWe collected 11 patient-centric and 50 doctor-centric questions covering ptosis symptoms, treatment, and postoperative care. Responses generated by GPT-4, GPT-4o, Qwen2, and Qwen2.5 were evaluated using predefined criteria: accuracy, sufficiency, clarity, and depth (doctor questions); and helpfulness, clarity, and empathy (patient questions). Clinical assessments involved 30 patients with ptosis and 8 oculoplastic surgeons rating responses on a 5-point Likert scale.ResultsFor doctor questions, GPT-4o outperformed Qwen2.5 in overall performance (53.1% vs. 18.8%, P = 0.035) and completeness (P = 0.049). For patient questions, GPT-4o scored higher in helpfulness (mean rank = 175.28 vs. 155.72, P = 0.035), with no significant differences in clarity or empathy. Qwen2.5 exhibited superior Chinese-language clarity compared to English (P = 0.023).ConclusionsLLMs, particularly GPT-4o, demonstrate robust performance in ptosis-related inquiries, excelling in English and offering clinically valuable insights. Qwen2.5 showed advantages in Chinese clarity. Although promising for patient education and clinician support, these models require rigorous validation, domain-specific training, and cultural adaptation before clinical deployment. Future efforts should focus on refining multilingual capabilities and integrating real-time expert oversight to ensure safety and relevance in diverse healthcare contexts.Translational RelevanceThis study bridges artificial intelligence (AI) advancements with clinical practice by demonstrating how optimized LLMs can enhance patient education and cross-linguistic clinician support tools in ptosis-related inquiries.

PurposeFlickering light stimulation induces functional hyperemia, characterized by vasodilation, blood flow augmentation, and venous oxygen elevation. We present a new method to investigate the frequency dependence of metrics associated with functional hyperemia.MethodsA novel optical imaging system was developed to quantify retinal blood vessel diameter (D), oxygen saturation (SO2), and the inner retinal oxygen extraction fraction (OEF) before and after light flicker at different frequencies. Measurements were performed in 10 visually normal subjects (20–62 years) at flicker frequencies from 2 to 30 Hz. In addition, a measure of neural function was obtained by steady-state pattern electroretinography (ssPERG) across a similar range of frequencies.ResultsFlicker stimulation greater than 2 Hz increased D, increased SO2 in veins, and decreased OEF. The maximum response for all metrics was obtained between 16 and 30 Hz, indicating that vascular and oxygenation metrics share a similar frequency response with light flicker. ssPERG amplitudes were positively correlated with flicker-induced increases in venous D and SO2. ssPERG amplitude was negatively correlated with flicker-induced decreases in OEF.ConclusionsWe present a novel retinal imaging method to evaluate the frequency dependence of changes in D, SO2, and OEF to light flicker stimulation. The relationship between these metrics and ssPERG amplitudes was evaluated.Translational RelevanceThe frequency-dependent response of retinal D, SO2, and OEF established in healthy individuals herein has the potential to serve as a biomarker of vascular and tissue abnormality in future studies of retinal disease.

PurposeTo investigate factors associated with bleb morphology and postoperative intraocular pressure (IOP) in eyes with inferotemporal PreserFlo MicroShunt implantation.MethodsWe analyzed 94 eyes that underwent PreserFlo in the inferotemporal quadrant. Slit-lamp photographs of the bleb approximately 6 months after surgery were used for bleb morphology analysis. Bleb vascularity was assessed via two classification criteria. Multivariate analysis was performed to identify factors associated with bleb morphology and 6-month postoperative IOP.ResultsThe mean age of the patients was 71.6 ± 12.0 years, and 46 patients (64%) were male. Primary open-angle glaucoma was observed in 69 eyes (73%), the mean axial length was 25.4 ± 2.2 mm, and 54 eyes (57%) underwent standalone surgery. The IOP significantly decreased from 24.9 ± 6.8 mm Hg preoperatively to 14.4 ± 2.8 mm Hg at the time of photography (P < 0.001). Avascular blebs were observed in seven eyes (7%) according to both classification systems. There was no significant difference in IOP between avascular and vascularized blebs (13.5 ± 0.9 mm Hg vs. 14.4 ± 2.9 mm Hg; P = 0.08). No preoperative factors predict bleb morphology. Age was the only factor significantly associated with 6-month postoperative IOP (P < 0.001), with a 0.157 mm Hg decrease in IOP for each 1-year increase in age.ConclusionsAlthough inferotemporal PreserFlo may result in avascular blebs in a small proportion of patients, postoperative IOP is associated primarily with age rather than with bleb morphology.Translational RelevanceWe provide valuable surgical information for inferotemporal PreserFlo implantation.

PurposeScotopic microperimetry measures retinal sensitivity under very low light and may be useful in conditions characterized by nyctalopia, such as retinitis pigmentosa and age-related macular degeneration. The Scotopic Macular Integrity Assessment device enables two-color perimetry to isolate rod and cone responses. This study assesses the reliability, test–retest repeatability, and sensitivity in healthy participants aiming to establish normative values.MethodsScotopic microperimetry was performed using cyan and red stimuli on a 37-point radial grid after dark adaptation on control participants with no history of eye disease and visual acuity of 0.1 logarithm of the minimum angle of resolution or better. Fixation stability, fixation losses, and identification of the rod-free zone were used as reliability metrics. A subset underwent repeat testing within 4 weeks.ResultsThirty-nine participants (19 male and 20 female), median age 24 years (interquartile range, 9.5 years) and 23 years (interquartile range, 9 years) for the right and left eyes, respectively, completed testing. Overall 77 eyes underwent scotopic testing, with 82% meeting reliability criteria. Mean cyan and red sensitivities were 19.9 ± 1.1 dB and 20.9 ± 1.2 dB in right eyes, and 20.1 ± 1.4 dB and 21.3 ± 1.4 dB in left eyes, respectively. Volumetric cyan and red sensitivities were 2868 ± 157 dB.deg2 and 3077 ± 176 dB.deg2 in the right eyes, respectively, and 2892 ± 205 dB.deg2 and 3126 ± 207 dB.deg2 in the left eyes, respectively. Mean sensitivity coefficients of repeatability (CoR) were ± 1.4 dB (cyan) and ± 2.1 dB (red) while pointwise coefficients of repeatability were ± 7.2 dB (95% confidence interval, 6.5–7.6 dB) for cyan and ± 7.9 dB (95% confidence interval, 7.3–8.4 dB) for red, with no significant differences between eyes or genders. Fixation stability assessed using the 95% bivariate contour ellipse area for cyan was 2.9 ± 5.9 deg2 and 2.3 ± 2.2 deg2 for the right and left eyes, respectively, and for red were 0.7 ± 0.6 deg2 and 0.9 ± 0.8 deg2 for the right and left eyes, respectively. Again, there were no significant differences between cyan and red tests (Friedman test, bivariate contour ellipse area 63%, P = 0.455; bivariate contour ellipse area 95%, P = 0.432).ConclusionsScotopic microperimetry using the Scotopic Macular Integrity Assessment device was feasible and well-tolerated. Repeatability metrics demonstrated limitations in fine spatial mapping of scotopic retinal sensitivity.Translational RelevanceThis study highlights potential areas for future improvements in scotopic microperimetry before its use as an outcome measure in clinical trials for retinal disease.

PurposeTo quantitatively re-evaluate the natural progression of homonymous visual defects in occipital stroke patients using metrics derived from automated perimetry.MethodsWe performed a retrospective chart review of stroke patients with homonymous hemianopia who underwent repeated, monocular Humphrey perimetry using the 24-2 SITA standard pattern from 2011 to 2019 at a large US academic medical center. Reliable tests in either eye were analyzed to track progression of the perimetric mean deviation (PMD) and deficit area before and after a temporal boundary set at 6 ± 1 months post-stroke.ResultsOut of 532 patients diagnosed with homonymous hemianopia, repeated Humphrey tests meeting reliability criteria were available for 73 individuals, who ranged from 0 to 2986 days post-stroke. Over 77% of these patients experienced spontaneous perimetric improvements in the subacute post-stroke period (<6 months), much larger for partial than complete visual field defects. In the chronic period (>6 months), perimetric measurements were stable overall, but spontaneous changes > ±1 dB in PMD were seen in about half of the cohort.ConclusionsQuantitative analysis of Humphrey perimetry confirmed prior reports of prevalent spontaneous improvements early after occipital stroke in adults. Though much less frequent, improvements as well as worsening of the visual defects still occurred in the chronic period.Translational RelevanceOur quantification of perimetric changes over time after occipital stroke provides an empirical and methodological basis for future studies aiming to better understand and prognostically manage patient expectations regarding recovery. It also provides a necessary benchmark against which to contrast the impact of restorative therapies being developed for this condition.

PurposeTo demonstrate high-resolution, motion-corrected, volume-fused optical coherence tomography (OCT) for assessing longitudinal changes in macular dot form subretinal drusenoid deposits (SDDs).MethodsSix consecutive isotropic volume raster scans over 6 × 6 mm (500 × 500 A-scans) were acquired using a high-resolution (2.7 µm axial resolution) spectral domain OCT prototype instrument. OCT volumes were computationally motion-corrected and fused. The distribution and longitudinal changes in dot SDDs were evaluated using en face OCT in a 50-µm-thick slab, from 27 µm above Bruch's membrane.ResultsComputational motion correction and volume fusion methods improve visibility of small en face features and compensate for motion artifacts to facilitate longitudinal assessment. In total, 326 SDDs were identified in a representative series of four eyes from four patients with intermediate age-related macular degeneration (AMD) and assessed with a 3- to 12-month follow-up. Of the SDDs, 85.3% remained stable over the follow-up, while 9.8% regressed, 3.4% fused, and 1.5% new SDDs appeared.ConclusionsComputational motion correction and volume fusion combined with high-resolution OCT B-scans and en face slabs facilitate visualization and longitudinal tracking of focal pathologies, such as SDDs.Translational RelevanceThe methods presented have the potential to improve OCT analysis of focal features, such as quantification of SDDs and other AMD biomarkers.

PurposeFuchs endothelial corneal dystrophy (FECD) is a common, age-related cause of visual impairment. This systematic review synthesizes evidence from the literature on artificial intelligence (AI) models developed for the diagnosis and management of FECD.MethodsWe conducted a systematic literature search in MEDLINE, PubMed, Web of Science, and Scopus from January 1, 2000, to June 31, 2024. Full-text studies utilizing AI for various clinical contexts of FECD management were included. Data extraction covered model development, predicted outcomes, validation, and model performance metrics. We graded the included studies using the Quality Assessment of Diagnostic Accuracies Studies 2 tool. This review adheres to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) recommendations.ResultsNineteen studies were analyzed. Primary AI algorithms applied in FECD diagnosis and management included neural network architectures specialized for computer vision, utilized on confocal or specular microscopy images, or anterior segment optical coherence tomography images. AI was employed in diverse clinical contexts, such as assessing corneal endothelium and edema and predicting post-corneal transplantation graft detachment and survival. Despite many studies reporting promising model performance, a notable limitation was that only three studies performed external validation. Bias introduced by patient selection processes and experimental designs was evident in the included studies.ConclusionsDespite the potential of AI algorithms to enhance FECD diagnosis and prognostication, further work is required to evaluate their real-world applicability and clinical utility.Translational RelevanceThis review offers critical insights for researchers, clinicians, and policymakers, aiding their understanding of existing AI research in FECD management and guiding future health service strategies.

PurposeStandard deep learning (DL) models often suffer significant performance degradation on out-of-distribution (OOD) data, where test data differs from training data, a common challenge in medical imaging due to real-world variations.MethodsWe propose a unified self-censorship framework as an alternative to the standard DL models for glaucoma classification using deep evidential uncertainty quantification. Our approach detects OOD samples at both the dataset and image levels. Dataset-level self-censorship enables users to accept or reject predictions for an entire new dataset based on model uncertainty, whereas image-level self-censorship refrains from making predictions on individual OOD images rather than risking incorrect classifications. We validated our approach across diverse datasets.ResultsOur dataset-level self-censorship method outperforms the standard DL model in OOD detection, achieving an average 11.93% higher area under the curve (AUC) across 14 OOD datasets. Similarly, our image-level self-censorship model improves glaucoma classification accuracy by an average of 17.22% across 4 external glaucoma datasets against baselines while censoring 28.25% more data.ConclusionsOur approach addresses the challenge of generalization in standard DL models for glaucoma classification across diverse datasets by selectively withholding predictions when the model is uncertain. This method reduces misclassification errors compared to state-of-the-art baselines, particularly for OOD cases.Translational RelevanceThis study introduces a tunable framework that explores the trade-off between prediction accuracy and data retention in glaucoma prediction. By managing uncertainty in model outputs, the approach lays a foundation for future decision support tools aimed at improving the reliability of automated glaucoma diagnosis.

PurposeQuantitative assessment of inflammation is critical for the accurate diagnosis and effective management of uveitis. This study aims to introduce a novel three-dimensional vision transformer approach using anterior segment optical coherence tomography (AS-OCT) to quantify anterior chamber (AC) inflammation in uveitis patients.MethodsThis cross-sectional study was conducted from January 2022 to December 2023 at a single tertiary eye center in Singapore, analyzing 830 AS-OCT B-scans from 180 participants, including uveitis patients at various stages of inflammation and healthy controls. The primary outcomes measured were central corneal thickness (CCT), Iris Vascularity Index (IVI), and Anterior Chamber Particle Index (ACPI). These parameters were assessed using the Swin Transformer V2 artificial intelligence algorithm on AS-OCT images.ResultsThe study included 180 participants, including uveitis patients and healthy controls. We observed significant differences between these groups in CCT (P = 0.01), ACPI (P < 0.001), and IVI (P < 0.001). Affected eyes showed elevated CCT and ACPI, along with a significant decrease in IVI, especially in severe inflammation cases. Linear regression analysis underscored a robust correlation between these biometric parameters and inflammation severity in the AC (R = 0.481, P < 0.001). A 6-month longitudinal study further validated the stability and repeatability of these measurements, affirming their reliability over time.ConclusionsThis study introduces a novel, objective method to quantify ocular inflammation using ACPI, IVI, and CCT, which enhances the precision of assessments over traditional subjective methods prone to interobserver variability. Demonstrated through significant biomarker stability over a 6-month period, our findings support the use of these metrics for reliable long-term monitoring of inflammation progression and treatment efficacy in clinical practice.Translational RelevanceOur artificial intelligence algorithm objectively quantifies AC inflammation reliably over the time and could be used in the clinic as well as in clinical trials as an objective biomarker.