Purpose:To analyze Henle fiber layer (HFL) hyper-reflectivity in age-related macular degeneration (AMD) with en face optical coherence tomography (OCT). Methods:A total of 279 eyes affected by AMD were imaged with either an Optovue Avanti or Optovue Solix device. Imaging was conducted within a 3 × 3-mm area centered on the foveal avascular zone. Hyper-reflective HFL (hr-HFL) regions were segmented by binarizing en face OCT images generated by projecting a slab 45 to 65 µm below the inner nuclear layer and outer plexiform layer boundary. Pathological changes, including drusen, subretinal fluid, pigment epithelial detachments (PEDs), macular neovascularization (MNV), and geographic atrophy (GA) were semi-automatically segmented. We investigated the association of these features with the hr-HFL by measuring the overlap ratios, defined as the proportion of hr-HFL area overlapping with the pathological regions after projection onto the same plane. Results:Hyper-reflective HFL regions were distinguished by distinct patterns in AMD eyes. It consistently colocalized with drusen, subretinal fluid, PEDs, MNV, and GA. Quantitatively, hr-HFL area was significantly larger in AMD eyes compared to healthy controls (P < 0.001) but did not differ across AMD severity stages. The hr-HFL area correlated with the size of pathologic features (r = 0.64-0.93; all P < 0.001), suggesting that the hr-HFL marks outer retinal abnormalities in AMD. Conclusions:Hyper-reflective HFL regions are a robust marker of outer retinal pathology in AMD. Structural changes such as drusen, fluid, and atrophy likely alter HFL orientation, leading to hyper-reflectivity. Although not specific to any single pathology, the hr-HFL reliably reflects the presence of AMD-related pathological changes.

PURPOSE:To develop and validate an automated corneal opacity detection algorithm for optical coherence tomography (OCT) images, utilizing an incidence-angle- and depth-dependent model of corneal reflectance. DESIGN:Retrospective, cross-sectional diagnostic accuracy study. SUBJECTS:Training used 95 healthy eyes from 49 volunteers. Testing included 50 eyes from 42 patients with corneal opacities and 35 healthy eyes from 35 volunteers. METHODS:Normal-eye OCT scans were used to model normative incidence-angle-dependent reflectance across corneal layers. The algorithm detected pixels above the normal reflectance range using model-based thresholds, binned percentile analysis, and morphological operations. Eye-level performance was evaluated against slit-lamp examination as clinical ground truth and compared with 5 trained physician annotators. Pixel-level agreement with consensus annotations (≥3 of 5 annotators) was assessed with Dice similarity coefficient. MAIN OUTCOME MEASURES:Eye-level accuracy, F1-score, sensitivity, and specificity; pixel-level Dice similarity coefficient and segmented-area agreement versus consensus annotations. RESULTS:At the eye level, the algorithm achieved accuracy of 0.93, F1-score of 0.94, sensitivity of 0.96, and specificity of 0.89. Human annotators had a mean accuracy of 0.83 ± 0.06, F1-score of 0.85 ± 0.04, sensitivity of 0.84 ± 0.09, and specificity of 0.80 ± 0.27. At the pixel level, mean Dice similarity coefficient versus consensus was 0.58 for the algorithm and 0.71 ± 0.05 for annotators. The algorithm's total segmented opacity area was close to the consensus pixel count (98% of consensus). CONCLUSION:An algorithm that incorporates incidence angle and depth-specific reflectance thresholds detects and segments corneal opacities. It demonstrated favorable accuracy at the eye level and produced quantitative opacity maps on OCT.

Purpose:To develop quantitative biomarkers that characterize the effect of upper eyelid motion (lid-wiper effect) during blinking on corneal epithelial thickness. Design:A retrospective study analyzing corneal epithelium thickness maps through Zernike polynomial decomposition. Subjects:Three hundred thirty-six maps from 135 healthy eyes of 69 subjects. Methods:A total of 5-mm diameter epithelial thickness maps were acquired using spectral-domain OCT. Maps from left eyes were mirror-imaged and pooled with right eyes for analysis. Zernike polynomial decomposition was performed, and average coefficients were obtained. The lowest-order Zernike terms with single-angle dependence-tilt and primary coma-were analyzed as vectors to determine the lid-wiper axes. The lid-wiper gradient (μm/mm) and lid-wiper coma (μm) were calculated by projecting the tilt and coma vectors along their lid-wiper axes. Correlation analysis was performed between the lid-wiper gradient and lid-wiper coma, primary astigmatism, and higher-order aberrations. Main Outcome Measures:The lid-wiper gradient and lid-wiper coma, which are quantitative biomarkers of epithelial remodeling in response to the lid-wiper effect. Results:The average epithelial thickness map showed superotemporal thinning with relative inferonasal thickening. Average tilt and coma coefficients were nonzero (P = 0.004 to <0.001). The population centroids (mean ± standard deviation) of the lid-wiper gradient and lid-wiper coma were 0.51 ± 0.57 μm/mm at 298.06 ± 56˚, and 0.21 ± 0.55 μm at 311.59 ± 83.53˚, respectively. The lid-wiper gradient and coma were positively correlated with each other (R 2 = 0.08, P = 0.001). Conclusions:A significant epithelial thickness gradient exists in the average normal cornea, consistent with eyelid blink dynamics described in the literature. The significant but weak correlation between the lid-wiper gradient and coma suggests the lid-wiper effect may be among various factors contributing to higher-order aberrations in the epithelium. The lid-wiper gradient and coma may serve as quantitative biomarkers of epithelial remodeling in response to the lid-wiper effect. Financial Disclosures:Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Purpose To investigate if there is a threshold thickness of retinopathy of prematurity (ROP) stage 2 disease (elevated ridge) that correlates with progression to stage 3 disease (retinal neovascularization). Design Case-control study Subjects 35 consecutive neonates at the Oregon Health & Science University (OHSU) neonatal intensive care unit (NICU) undergoing regular screening visits for retinopathy of prematurity Methods Longitudinal ultra-widefield OCT (UWF-OCT) imaging was used to obtain images from participants (15 neonates who did not develop stage 3 disease and 20 neonates who developed stage 3 disease) during regular ROP screening visits. Using a previously validated u-net model, the ridge was segmented on en face images and the ridge height was measured on cross-sectional B-scans for those segmented regions. Statistical analysis was conducted using a two-sided unequal variance T-test (p<0.05) and Youden’s J-index. Main Outcome Measures Ridge height in microns for each study group. Threshold ridge thickness that correlates with progression to stage 3 ROP (neovascularization). Results There was a significant difference in stage 2 ridge height between the 15 neonates who peaked at stage 2 disease (282.6 microns, SD 39.7) and the 20 neonates who progressed to stage 3 (366.7 microns, SD 72.2; p < 0.001). Youden’s J-index suggests a maximum stage 2 thickness of greater than or equal to 289 microns had a 95% sensitivity and 67% specificity for progression to stage 3. Ridge heights appear similar between the two groups until 10 to 11 weeks chronological age, when ridge heights for neonates who go on to reach stage 3 disease typically pass the threshold of 289 μm. Conclusions When ROP stage 2 ridge height exceeds 289 microns, the odds of progression to stage 3 disease rise sharply. This inflection point towards retinal neovascularization may inform future OCT-based ROP risk models.

Purpose: Optical coherence tomography angiography (OCTA) has enabled detailed in vivo imaging of macular neovascularization (MNV) in neovascular age-related macular degeneration (nAMD), leading to a proliferation of morphological descriptive terms. This scoping review aimed to systematically map the existing literature on OCTA-based MNV morphology and evaluate its correlation with disease activity. Methods: A systematic literature search covering publications through 2025 was performed. After screening 2,445 titles and obtaining 60 full texts, 43 studies were included. Data on morphological terminology, study design, and correlation with disease activity were extracted and synthesized. Results: The included studies, encompassing a total of 2,712 eyes, identified a vast and heterogeneous lexicon of qualitative descriptors, including terms such as “medusa,” “sea-fan,” and “glomerulus”, characterized by significant terminological overlap and inconsistent definitions across studies. Inconsistent, low-certainty associations between specific OCTA morphologies and MNV activity were identified across studies, with findings limited by significant methodological heterogeneity. The evidence for these patterns as reliable biomarkers of disease activity is weak and often contradictory, and several studies were found to use OCTA features to define activity, creating circular arguments that undermine their conclusions. Conclusion: The current terminology for OCTA morphology in nAMD is fragmented and inconsistently applied. The link between these patterns and disease activity is poorly established, severely limiting their clinical utility. These findings highlight a need for a standardized, consensus-based framework for describing and interpreting OCTA findings in nAMD.

We developed a handheld, non-mydriatic swept-source OCT system capable of ultra-widefield and high-resolution retinal imaging across both pediatric and adult patients without pharmacologic dilation. The proposed system employed a 400 kHz VCSEL light source with an extended axial imaging range of 12 mm in air and achieved a 140 degrees visual angle with custom optics, enabling rapid, panretinal visualization with minimal beam wandering while maintaining diffraction- limited resolution across the field of view.

Purpose:To assess photoreceptor functional impairment in eyes with early-to-intermediate age-related macular degeneration (AMD) using OCT-based split-spectrum amplitude-decorrelation optoretinography (SSADOR). Design:Prospective observational comparative study. Participants:Adults ≥50 years of age with early or intermediate AMD and age-matched control subjects. Methods:Split-spectrum amplitude-decorrelation optoretinography measures flash-evoked OCT amplitude fluctuations within the photoreceptor outer segment band to objectively quantify photoreceptor light responses. We compared SSADOR mean decorrelation between AMD and control eyes within the central 3-mm macula and across ETDRS subfields and evaluated associations with best-corrected visual acuity (BCVA) and drusen volume. Main Outcome Measures:Split-spectrum amplitude-decorrelation optoretinography mean decorrelation within ETDRS subfields, as a surrogate marker of the light sensing function of photoreceptors. Results:Twenty-two eyes with early-to-intermediate AMD and 12 control eyes were enrolled in the study. Split-spectrum amplitude-decorrelation optoretinography decorrelation was significantly reduced in AMD eyes compared with controls across all ETDRS subfields (all P < 0.05), with the greatest reduction in the fovea (P < 0.001). Although visual inspection showed localized reductions over large drusen, regression analysis revealed no meaningful correlation between SSADOR and drusen volume. In AMD eyes, foveal SSADOR decorrelation was moderately associated with BCVA (R2 = 0.349, P = 0.0002). Split-spectrum amplitude-decorrelation optoretinography distinguished AMD eyes from controls with higher accuracy than BCVA (area under the receiver operating characteristic curve 0.989 vs. 0.795; DeLong test P = 0.002). Conclusions:Split-spectrum amplitude-decorrelation optoretinography detected impaired photoreceptor light responses in eyes with early-to-intermediate AMD compared with age-matched controls and outperformed BCVA in differentiating AMD from normal eyes. Split-spectrum amplitude-decorrelation optoretinography decorrelation may serve as a sensitive, objective biomarker for detecting and monitoring early or subtle photoreceptor dysfunction in AMD. Financial Disclosures:Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

We present a compact, automated, stereo-optical-sectioning imaging system for clinical assessment of the anterior segment, using a digital micromirror device (DMD) as a spatial light modulator. The platform synchronizes two CMOS cameras with the DMD, which projects programmable slit beams to produce depth-resolved cross-sectional views of the anterior eye. By adjusting the micromirror activation time, the system can also extend the dynamic range of the acquired images, accommodating both dim (e.g., the cornea) and highly reflective regions (i.e., the iris). In a pilot study, the prototype instrument produced high-contrast images from eyes with corneal disorders, including scars, opacities, and foreign bodies. In addition, it enables the visualization of the corneal stromal nerves. The combination of a compact design, automated acquisition in 3.5 seconds, and its depth-resolved cross-sectional view and 3D representation suggests strong potential for routine, comprehensive digital imaging of the entire anterior segment. This approach could eventually serve as an alternative to conventional slit-lamp examinations in regular clinical settings.

AIM:To implement a deep learning-based segmentation algorithm to quantify reticular pseudodrusen (RPD) and drusen volumes on optical coherence tomography (OCT) and investigate their association with progression to late age-related macular degeneration (AMD). METHODS:A retrospective analysis included study eyes with RPD and contralateral neovascular AMD using 6×6 mm macular OCT (Solix; Visionix/Optovue, Inc). Automated segmentation quantified RPD and drusen volumes, including large drusen and drusenoid pigment epithelial detachment (PED), and late AMD development was evaluated over 2 years. Associations between baseline volumetric biomarkers and progression were evaluated using Cox proportional hazards models. RESULTS:Fifty-one eyes (mean age 74.9±7.65 years) were included. The median (IQR) baseline RPD volume was 0.018 mm³ (0.004-0.52) and total drusen volume was 0.009 mm³ (0.001-0.064). Over 24.2±1.20 months, late AMD developed in 20 eyes (39.2%). In multivariable Cox regression models adjusted for age, each 0.01 mm³ increase in baseline RPD volume (HR: 1.082; p=0.002) and total drusen volume (HR: 1.080; p<0.001) were associated with progression to late AMD. In an exploratory drusen subtype analysis, progression to late AMD was independently associated with baseline RPD volume, large drusen volume and drusenoid PED volume. CONCLUSION:The deep learning-based volumetric segmentation tool allows OCT-derived automated volume quantification of different types of drusen based on OCT. In eyes with RPD and contralateral neovascular AMD, greater RPD volume and large drusen and/or drusenoid PED volume carried greater risk of developing late AMD in 2 years.

Purpose:To enrich stromal riboflavin concentration and reduce epithelial riboflavin in transepithelial corneal collagen crosslinking (CXL). Methods:Ex vivo experiments on rabbit corneas were performed. The control group followed the standard (epi-off) Dresden CXL: a 30-minute epi-off application of 0.1% riboflavin and 20% dextran. The transepithelial riboflavin solutions consisted of various riboflavin concentrations in 1% hydroxypropyl methylcellulose in 0.45% saline, with or without 0.01% benzalkonium chloride (BAK). The novel soak-and-rinse protocol consists of 0.8% riboflavin with 0.01% BAK and 1% hydroxypropyl methylcellulose (hypotonic) applied for 20 minutes, followed by a 10-minute saline rinse. Stromal and epithelial thicknesses were measured by optical coherence tomography; riboflavin concentrations were quantified by spectrophotometry on 3-mm stromal buttons and epithelial eluates. Statistical analysis employed one-way analysis of variance, linear regression, and one-tailed unpaired t-tests. Results:The 20-minute soak increased stromal riboflavin compared to the 10-minute soak. A 76% higher stromal concentration was achieved by adding BAK to the transepithelial 0.8% riboflavin solution (P < 0.05). The 10-minute rinse achieved a Dresden-equivalent stromal riboflavin level and reduced epithelial riboflavin by 5.9-fold compared to a 20-second rinse (P < 0.0001). Conclusions:Stromal riboflavin concentrations equivalent to those achieved with the epi-off protocol can be achieved by transepithelial application of the novel high-concentration riboflavin formulation. The additional 10-minute rinse effectively reduced epithelial riboflavin levels, facilitating the delivery of ultraviolet light and oxygen into the stroma during CXL. Translational Relevance:The novel transepithelial riboflavin soak-and-rinse protocol may potentially enhance the efficacy of transepithelial CXL by reducing epithelial consumption of ultraviolet light and oxygen and increasing the stromal CXL reaction.

Optical coherence tomography angiography (OCTA) is a signal processing and scan acquisition approach that enables OCT devices to clearly identify vascular tissue down to the capillary scale. As originally proposed, OCTA included several important limitations, including small fields of view relative to allied imaging modalities and the presence of confounding artifacts. New approaches, including both hardware and software, are solving these problems and can now produce high-quality angiograms from tissue throughout the retina and choroid. Image analysis tools have also improved, enabling OCTA data to be quantified at high precision and used to diagnose disease using deep learning models. This review highlights these advances and trends in OCTA technology, focusing on work produced since 2020.

Purpose: Retinopathy of prematurity (ROP) stage is defined by the visual appearance of the vascularavascular border, which reflects a spectrum of pathologic neurovascular tissue (NVT). Previous work demonstrated that the thickness of the ridge lesion, measured using OCT, corresponds to higher clinical diagnosis of stage. This study evaluates whether the volume of anomalous NVT (ANVTV), defined as abnormal tissue protruding from the regular contour of the retina, can be measured automatically using deep learning to develop quantitative OCT-based biomarkers in ROP. Design: Single-center retrospective case series. Participants: Thirty-three infants with ROP in the Oregon Health & Science University neonatal intensive care unit. Methods: OCT B-scans were collected using an investigational ultrawidefield OCT. The ANVTV was manually segmented. A set of 3347 B-scans and corresponding manual segmentations from 12 volumes from 6 patients were used to train an automated segmentation tool using a U-Net. An additional held-out test data set of 60 B-scans from 6 infants was used to evaluate model performance. The Dice-Sorensen coefficient (DSC) comparing manual and automated segmentation of ANVTV was calculated. Scans from 21 additional infants were used for clinical evaluation of ANVTV using the visit in which they had developed their peak stage of ROP. Each infant had every B-scan in a volume automatically segmented for ANVTV (total number of segmented voxels within the 60 degrees temporal to the optic disc). The ANVTV was compared between infants with stage 1 to 3 ROP using a Kruskal-Wallis test and tracked over time in all infants with stage 3 ROP. Main Outcome Measurements: Cross sectional and longitudinal association between ANVTV and stages 1 to 3 ROP. Results: Comparing automated and manual segmentation of ANVTV achieved a DSC of 0.61 +/- 0.13. Using the U-Net, ANVTV was associated with higher disease stage both cross sectionally and longitudinally. Median ANVTV significantly increased as ROP stage worsened from 1 (0, [interquartile range: 0-0] kilovoxels) to 2 (170.1 [interquartile range: 104.2-183.6] kilovoxels) to 3 (421.4 [interquartile range: 312.3-1110.8] kilovoxels; P < 0.001). Conclusions: Automated OCT-based measurement of ANVTV was associated with clinical disease stage in ROP, both cross sectionally and longitudinally. Ultrawidefield-OCT may facilitate more objective screening, diagnosis, and monitoring in the future. Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article. (c) 2024 by the American Academy of Ophthalmology. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).

Purpose:To train and validate a convolutional neural network (CNN) to detect the history of laser-assisted in situ keratomileusis (LASIK) surgeries using corneal optical coherence tomography (OCT) maps. Methods:Five corneal OCT maps (pachymetry, epithelial thickness, posterior mean curvature, anterior axial power, and anterior stroma reflectance) were utilized as the input of a lightweight CNN model. OCT scans of healthy volunteers and patients who had undergone myopic or hyperopic LASIK were included. Repeated fivefold cross-validation was used to train and evaluate the proposed CNN. In addition, a separate group of post-LASIK participants, who were not included in the cross-validation, was used for out-of-sample testing to assess the CNN model performance. Results:In the cross-validation, the proposed CNN model achieved an overall balanced accuracy of 90.2% ± 3.6% with 93.5% ± 5.2% sensitivity and 97.8% ± 1.7% area under the receiver operating characteristic curve (AUC) in detecting myopic LASIK and 90.2% ± 5.8% sensitivity and 98.2% ± 1.9% AUC in identifying the hyperopic LASIK. In the out-of-sample test, all eyes were classified correctively. Conclusions:The lightweight CNN model with corneal OCT maps provides a useful tool for detecting LASIK history. Translational Relevance:Artificial intelligence-assisted OCT may offer better management for patients with LASIK history who need cataract surgeries.

Objective or Purpose: To develop a lightweight neural network for automated cross-sectional and en face segmentation of ultra-widefield (UWF) OCT images acquired for retinopathy of prematurity screening. Design: Cross-sectional study. Subjects: Twenty-five infants with a birth weight <1500 g or gestational age <31 weeks were scanned using a portable, handheld, swept-source UWF-OCT device. Methods, Intervention, or Testing: For cross-sectional B-scans, 3040 B-scans from 5 OCT volumetric scans obtained from 5 patients were segmented by 2 graders for the choroid and retina using custom-built tools in the Napari image viewer. Using these segmentations, a u-net with an EfficientNet-B0 backbone was trained in combination with task-specific augmentations to perform automated segmentation of the retina and choroid data with varying levels of image processing applied. For en face scans, 40 en face images from 20 unique patients were manually segmented by a single grader for retinal vessels. Using these segmentations, a u-net with an EfficientNet-B0 backbone was trained. Validation for both B-scans and en face images was performed using fivefold cross-validation. The fivefold cross-validation metrics were then compared with the metrics obtained by comparing grader segmentations. Main Outcome Measures: The Dice similarity coefficient (DSC) was used to assess B-scan and en face segmentations. Results: The retinal and choroidal b-scan segmentations produced a DSC ± standard deviation of 0.925 ± 0.021 and 0.797 ± 0.062, respectively, averaged across the fivefolds. The en face vasculature segmentation produced a DSC ± standard deviation of 0.625 ± 0.0450. Conclusions: Using u-net convolutional neural networks trained with task-specific augmentations, we developed en face and cross-sectional segmentations for UWF-OCT images, which will facilitate automated quantitative analysis with this novel modality. Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Panretinal optical coherence tomography (PanOCT) enables rapid, widefield retinal imaging up to 140°, visualizing peripheral regions including the ora serrata. However, raw B-scan images exhibit curvature distortion, limiting quantitative accuracy. We present a curve correction method to restore geometric fidelity. Validation with a custom 3D-printed eye phantom showed average relative errors under 1%. Clinical comparisons with CT and ultrasound demonstrated errors of 2.78% and 5.97%, respectively. These results indicate strong agreement with standard imaging modalities and support the utility of PanOCT for accurate widefield retinal measurements in clinical and research applications.

Optical coherence tomography angiography (OCTA) is a volumetric, non-invasive, high-resolution vascular imaging modality capable of acquiring highly detailed visualizations of retinal microvasculature. It has become an important tool for diagnosis and prognosis in prevalent diseases and pathologies such as diabetic retinopathy, retinopathy of prematurity, and vein occlusions, as well as more rare conditions, including inherited retinal dystrophies. It is also useful for measuring treatment response and assessing which patients would benefit from treatment. Unlike dye-based angiography, OCTA eliminates risks such as anaphylaxis. It also often outperforms fundus photography in feature detection. However, conventional OCTA imaging has been limited by its small field of view, which restricts simultaneous visualization of the posterior pole and peripheral retina, causing single images to potentially miss widely spaced critical biomarkers and pathological features. Recent technological advances in widefield OCTA have addressed this limitation, extending the field of view to the mid-periphery and beyond. This breakthrough enhances the simultaneous detection of macular and peripheral retinal pathology and significantly broadens OCTA's diagnostic and research applications. This review explores the technical innovations enabling widefield OCTA and highlights its clinical utility across various conditions, emphasizing its growing importance as a powerful tool in ophthalmic practice and research.

The differential diagnosis of uveitis is broad and challenging. A key indicator of intraocular inflammation is the presence of cells in the aqueous or vitreous humor. Optical coherence tomography (OCT) methods have been developed to measure intraocular inflammatory cell composition using reflectance intensity or cell size distributions. However, these methods are ineffective at low cell densities. We developed a lightweight convolutional neural network (CNN) model to classify intraocular inflammatory cell types with ultrahigh-resolution OCT. OCT images of known cell types (mononuclear cells and granulocytes) were used to train and optimize the model. The CNN model achieved an accuracy of 88.4 +/- 0.7% with an area under the receiver operating characteristic curve of 94.3 +/- 0.4%. The inflammatory cell compositions predicted by the trained model from OCT images were consistent with the clinical diagnoses of uveitis patients. This method is valuable for uveitis diagnosis and monitoring of intraocular inflammation.