In Vivo Sublayer Analysis of Human Retinal Inner Plexiform Layer Obtained by Visible-Light Optical Coherence Tomography

Diagnostic Performance for Detection of Glaucomatous Structural Damage Using Pixelwise Analysis of Retinal Thickness Measurements

Purpose

To compare the diagnostic accuracy of thickness measurements of individual and combined macular retinal layers to discriminate 188 glaucomatous and 148 glaucoma suspect eyes from 362 healthy control (HC) eyes on a pixel-by-pixel basis.

Methods

For this retrospective study, we manually corrected the segmentations of posterior pole optical coherence tomography (OCT) scans to determine the thickness of the nerve fiber layer (NFL), ganglion cell layer (GCL), inner plexiform layer (IPL), the ganglion cell complex (GCC), and the total neural retina (TR). For each eye, the total number of pixels with thickness values less than the fifth percentile of the HC distribution was used to create a receiver operating characteristic (ROC) curve for each layer and for layer combinations.

Results

Using total abnormal pixel count criteria to discriminate glaucoma from HC eyes, the individual layers with the highest area under the ROC curve (AUC) were the NFL and GCL; IPL performance was significantly lower (P < 0.05). GCC had a significant higher AUC (94.3%) than individual the AUC of the NFL (92.3%) (P = 0.0231) but not higher than AUC of the GCL (93.4%) (P = 0.3487). The highest AUC (95.4%) and sensitivity (85.1%) at 95% specificity was found for the Boolean combination of NFL or GCL. The highest AUC is not significantly higher (P = 0.0882) than the AUC of the GCC but the highest sensitivity is significantly higher than the sensitivity of the GCC. This pattern was similar for discriminating between suspect and HC eyes (P = 0.0356).

Conclusions

Using pixel-based methods, the diagnostic accuracy of NFL and GCL exceeded that of IPL and TR. GCC had equivalent performance as NFL and GCL. The specific spatial locations within the posterior pole that exhibit best performance vary depending on which layer is being assessed. Recognizing this dependency highlights the importance of considering multiple layers independently, as they offer complementary information for effective and comprehensive diagnosis.

Glaucoma classification through SSVEP derived ON- and OFF-pathway features

Recent evidence from small animal models and human electrophysiology suggests that the OFF-pathway is more vulnerable to glaucomatous insult than the ON-pathway. Thus, OFF-pathway based measurements of visual function may be useful in the diagnosis of Glaucoma. The steady-state visually evoked potential (SSVEP) can be used to non-invasively make such functional measurements. Here, we examine whether OFF- and ON-pathway biasing SSVEP measurements differently predict glaucoma diagnosis using a large cohort of 98 glaucoma patients and 71 controls. Using both a logistic regression with k-fold cross-validation and a random forest classifier, we show that OFF-pathway biasing features produce a small improvement in predictive accuracy over ON-pathway biasing features. However, despite our inclusion of many more response features and the retention of both participants' eyes, our classifier did not perform as well as previous reports that used the isolated-check VEP. This is likely a result of the relatively small amount of data we collected for each participant, but may also be explained by the absence of any train-test splitting in preexisting work. Nevertheless, our results support further exploration of the diagnostic potential of OFF-pathway biasing functional biomarkers for glaucoma.

Hyperreflective Dots in Central Fovea Visualized by a Novel Application of Visible-Light Optical Coherence Tomography

Visible-light optical coherence tomography (vis-OCT) is a novel noninvasive retinal imaging system that offers improved resolution compared to conventional near-infrared (NIR) OCT systems. Here, we utilized vis-OCT to produce fibergrams (vis-OCTF) for the first time in human patients, enabling en face visualization and precise quantification of hyperreflective dots in the central fovea in two patients. We also directly compare the imaging qualities of conventional vis-OCT and NIR-OCT. Vis-OCT generated a 3 × 3 mm2 en face image with an impressive axial resolution of 1.3 μm, whereas NIR-OCT produced an en face image with a larger field of view (FOV) (9 × 9 mm2) but a lower resolution of 7.0 μm. Moreover, vis-OCTF unveiled clear images of hyperreflective dots in the fovea of both patients, which were not discernible in the NIR-OCT en face images. Foveal dots have often been linked to several age-related and pathological conditions. The high-resolution images generated by vis-OCTF enable more precise characterization of changes in retinal sublayers within the central fovea.

Sub2Full: split spectrum to boost optical coherence tomography despeckling without clean data

Optical coherence tomography (OCT) suffers from speckle noise, causing the deterioration of image quality, especially in high-resolution modalities such as visible light OCT (vis-OCT). Here, we proposed an innovative self-supervised strategy called Sub2Full (S2F) for OCT despeckling without clean data. This approach works by acquiring two repeated B-scans, splitting the spectrum of the first repeat as a low-resolution input, and utilizing the full spectrum of the second repeat as the high-resolution target. The proposed method was validated on vis-OCT retinal images visualizing sublaminar structures in the outer retina and demonstrated superior performance over state-of-the-art Noise2Noise (N2N) and Noise2Void (N2V) schemes.

Comparative In Vivo Imaging of Retinal Structures in Tree Shrews, Humans, and Mice

Rodent models, such as mice and rats, are commonly used to examine retinal ganglion cell damage in eye diseases. However, as nocturnal animals, rodent retinal structures differ from primates, imposing significant limitations in studying retinal pathology. Tree shrews (Tupaia belangeri) are small, diurnal paraprimates that exhibit superior visual acuity and color vision compared with mice. Like humans, tree shrews have a dense retinal nerve fiber layer (RNFL) and a thick ganglion cell layer (GCL), making them a valuable model for investigating optic neuropathies. In this study, we applied high-resolution visible-light optical coherence tomography to characterize the tree shrew retinal structure in vivo and compare it with that of humans and mice. We quantitatively characterize the tree shrew's retinal layer structure in vivo, specifically examining the sublayer structures within the inner plexiform layer (IPL) for the first time. Next, we conducted a comparative analysis of retinal layer structures among tree shrews, mice, and humans. We then validated our in vivo findings in the tree shrew inner retina using ex vivo confocal microscopy. The in vivo and ex vivo analyses of the shrew retina build the foundation for future work to accurately track and quantify the retinal structural changes in the IPL, GCL, and RNFL during the development and progression of human optic diseases.

Early inner plexiform layer thinning and retinal nerve fiber layer thickening in excitotoxic retinal injury using deep learning-assisted optical coherence tomography

Excitotoxicity from the impairment of glutamate uptake constitutes an important mechanism in neurodegenerative diseases such as Alzheimer's, multiple sclerosis, and Parkinson's disease. Within the eye, excitotoxicity is thought to play a critical role in retinal ganglion cell death in glaucoma, diabetic retinopathy, retinal ischemia, and optic nerve injury, yet how excitotoxic injury impacts different retinal layers is not well understood. Here, we investigated the longitudinal effects of N-methyl-D-aspartate (NMDA)-induced excitotoxic retinal injury in a rat model using deep learning-assisted retinal layer thickness estimation. Before and after unilateral intravitreal NMDA injection in nine adult Long Evans rats, spectral-domain optical coherence tomography (OCT) was used to acquire volumetric retinal images in both eyes over 4 weeks. Ten retinal layers were automatically segmented from the OCT data using our deep learning-based algorithm. Retinal degeneration was evaluated using layer-specific retinal thickness changes at each time point (before, and at 3, 7, and 28 days after NMDA injection). Within the inner retina, our OCT results showed that retinal thinning occurred first in the inner plexiform layer at 3 days after NMDA injection, followed by the inner nuclear layer at 7 days post-injury. In contrast, the retinal nerve fiber layer exhibited an initial thickening 3 days after NMDA injection, followed by normalization and thinning up to 4 weeks post-injury. Our results demonstrated the pathological cascades of NMDA-induced neurotoxicity across different layers of the retina. The early inner plexiform layer thinning suggests early dendritic shrinkage, whereas the initial retinal nerve fiber layer thickening before subsequent normalization and thinning indicates early inflammation before axonal loss and cell death. These findings implicate the inner plexiform layer as an early imaging biomarker of excitotoxic retinal degeneration, whereas caution is warranted when interpreting the ganglion cell complex combining retinal nerve fiber layer, ganglion cell layer, and inner plexiform layer thicknesses in conventional OCT measures. Deep learning-assisted retinal layer segmentation and longitudinal OCT monitoring can help evaluate the different phases of retinal layer damage upon excitotoxicity.

Multiscale imaging of corneal endothelium damage and Rho-kinase inhibitor application in mouse models of acute ocular hypertension

We developed a multiscale optical imaging workflow, integrating and correlating visible-light optical coherence tomography, confocal laser scanning microscopy, and single-molecule localization microscopy to investigate mouse cornea damage from the in-vivo tissue level to the nanoscopic single-molecule level. We used electron microscopy to validate the imaged nanoscopic structures. We imaged wild-type mice and mice with acute ocular hypertension and examined the effects of Rho-kinase inhibitor application. We defined four types of intercellular tight junction structures as healthy, compact, partially-distorted, and fully-distorted types by labeling the zonula occludens-1 protein in the corneal endothelial cell layer. We correlated the statistics of the four types of tight junction structures with cornea thickness and intraocular pressure. We found that the population of fully-distorted tight junctions correlated well with the level of corneal edema, and applying Rho-kinase inhibitor reduced the population of fully-distorted tight junctions under acute ocular hypertension. Together, these data point to the utility of multiscale optical imaging in revealing fundamental biology relevant to disease and therapeutics.

Deep learning network for parallel self-denoising and segmentation in visible light optical coherence tomography of the human retina

Visible light optical coherence tomography (VIS-OCT) of the human retina is an emerging imaging modality that uses shorter wavelengths in visible light range than conventional near-infrared (NIR) light. It provides one-micron level axial resolution to better separate stratified retinal layers, as well as microvascular oximetry. However, due to the practical limitation of laser safety and comfort, the permissible illumination power is much lower than NIR OCT, which can be challenging to obtain high-quality VIS-OCT images and subsequent image analysis. Therefore, improving VIS-OCT image quality by denoising is an essential step in the overall workflow in VIS-OCT clinical applications. In this paper, we provide the first VIS-OCT retinal image dataset from normal eyes, including retinal layer annotation and "noisy-clean" image pairs. We propose an efficient co-learning deep learning framework for parallel self-denoising and segmentation simultaneously. Both tasks synergize within the same network and improve each other's performance. The significant improvement of segmentation (2% higher Dice coefficient compared to segmentation-only process) for ganglion cell layer (GCL), inner plexiform layer (IPL) and inner nuclear layer (INL) is observed when available annotation drops to 25%, suggesting an annotation-efficient training. We also showed that the denoising model trained on our dataset generalizes well for a different scanning protocol.

Large-scale survey of excitatory synapses reveals sublamina-specific and asymmetric synapse disassembly in a neurodegenerative circuit

In the nervous system, parallel circuits are organized in part by the lamina-specific compartmentalization of synaptic connections. In sensory systems such as mammalian retina, degenerating third-order neurons remodel their local presynaptic connectivity with second-order neurons. To determine whether there are sublamina-specific perturbations after injury of adult retinal ganglion cells, we comprehensively analyzed excitatory synapses across the inner plexiform layer (IPL) where bipolar cells connect to ganglion cells. Here, we show that pre- and postsynaptic component loss occurs throughout the IPL in a sublamina-dependent fashion after transient intraocular pressure elevation. Partnered synaptic components are lost as neurodegeneration progresses, while unpartnered synaptic components remain stable. Furthermore, presynaptic components are either lost first or simultaneously with the postsynaptic component. Our results demonstrate that this degenerating neural circuit exhibits differential vulnerability of excitatory synapses depending on IPL depth, highlighting the ordered disassembly of synapses that is specific to laminar compartments of the retina.

Derivation of human retinal cell densities using high-density, spatially localized optical coherence tomography data from the human retina

This study sought to identify demographic variations in retinal thickness measurements from optical coherence tomography (OCT), to enable the calculation of cell density parameters across the neural layers of the healthy human macula. From macular OCTs (n = 247), ganglion cell (GCL), inner nuclear (INL), and inner segment-outer segment (ISOS) layer measurements were extracted using a customized high-density grid. Variations with age, sex, ethnicity, and refractive error were assessed with multiple linear regression analyses, with age-related distributions further assessed using hierarchical cluster analysis and regression models. Models were tested on a naïve healthy cohort (n = 40) with Mann-Whitney tests to determine generalizability. Quantitative cell density data were calculated from histological data from previous human studies. Eccentricity-dependent variations in OCT retinal thickness closely resemble topographic cell density maps from human histological studies. Age was consistently identified as significantly impacting retinal thickness (p = .0006, .0007, and .003 for GCL, INL and ISOS), with gender affecting ISOS only (p < .0001). Regression models demonstrated that age-related changes in the GCL and INL begin in the 30th decade and were linear for the ISOS. Model testing revealed significant differences in INL and ISOS thickness (p = .0008 and .0001; however, differences fell within the OCT's axial resolution. Qualitative comparisons show close alignment between OCT and histological cell densities when using unique, high-resolution OCT data, and correction for demographics-related variability. Overall, this study describes a process to calculate in vivo cell density from OCT for all neural layers of the human retina, providing a framework for basic science and clinical investigations.

Multiscale imaging of corneal endothelium damage and effects of Rho Kinase inhibitor application in mouse models of acute ocular hypertension

We developed a multiscale optical imaging workflow, integrating and correlating visible-light optical coherence tomography, confocal laser scanning microscopy, and single-molecule localization microscopy to investigate the mouse cornea damages from the in-vivo tissue level to the nanoscopic single-molecule level. We used electron microscopy to validate the imaged nanoscopic structures. We imaged wild-type mice and mice with acute ocular hypertension and examined the effects of Rho Kinase inhibitor application. We defined four types of intercellular tight junction structures as healthy, compact, partially-distorted, and fully-distorted types by labeling the Zonula occludens-1 protein in the corneal endothelial cell layer. We correlated the statistics of the four types of tight junction structures with cornea thickness and intraocular pressure. We found that the population of fully-distorted tight junctions correlated well with the level of cornea edema, and applying Rho Kinase inhibitor reduced the population of fully-distorted tight junctions under acute ocular hypertension.

High sampling resolution optical coherence tomography reveals potential concurrent reductions in ganglion cell-inner plexiform and inner nuclear layer thickness but not in outer retinal thickness in glaucoma

PURPOSE

To analyse optical coherence tomography (OCT)-derived inner nuclear layer (INL) and outer retinal complex (ORC) measurements relative to ganglion cell-inner plexiform layer (GCIPL) measurements in glaucoma.

METHODS

Glaucoma participants (n = 271) were categorised by 10-2 visual field defect type. Differences in GCIPL, INL and ORC thickness were calculated between glaucoma and matched healthy eyes (n = 548). Hierarchical cluster algorithms were applied to generate topographic patterns of retinal thickness change, with agreement between layers assessed using Cohen's kappa (κ). Differences in GCIPL, INL and ORC thickness within and outside GCIPL regions showing the greatest reductions and Spearman's correlations between layer pairs were compared with 10-2 mean deviation (MD) and pattern standard deviation (PSD) to determine trends with glaucoma severity.

RESULTS

Glaucoma participants with inferior and superior defects presented with concordant GCIPL and INL defects demonstrating mostly fair-to-moderate agreement (κ = 0.145-0.540), which was not observed in eyes with no or ring defects (κ = -0.067-0.230). Correlations (r) with MD and PSD were moderate and weak in GCIPL and INL thickness differences, respectively (GCIPL vs. MD r = 0.479, GCIPL vs. PSD r = -0.583, INL vs. MD r = 0.259, INL vs. PSD r = -0.187, p = <0.0001-0.002), and weak in GCIPL-INL correlations (MD r = 0.175, p = 0.004 and PSD r = 0.154, p = 0.01). No consistent patterns in ORC thickness or correlations were observed.

CONCLUSIONS

In glaucoma, concordant reductions in macular INL and GCIPL thickness can be observed, but reductions in ORC thickness appear unlikely. These findings suggest that trans-synaptic retrograde degeneration may occur in glaucoma and could indicate the usefulness of INL thickness in evaluating glaucomatous damage.

Comparison of Ganglion Cell Layer and Inner Plexiform Layer Rates of Change in Suspected and Established Glaucoma

PURPOSE

We compared ganglion cell layer (GCL) and inner plexiform layer (IPL) rates of change (RoC) in patients with glaucoma suspect (GS) and established glaucoma (EG) to test the hypothesis that IPL thickness changes would occur earlier than GCL changes in eyes with early damage.

DESIGN

Prospective, cohort study.

METHODS

A total of 64 GS eyes (46 patients) and 112 EG eyes (112 patients) with ≥2 years of follow-up and ≥3 macular optical coherence tomography scans were included. GCL and IPL superpixel thickness measurements were exported. A Bayesian hierarchical model with random intercepts/slopes and random residual variances was fitted to estimate RoC in individual superpixels. Normalized RoC and proportions of superpixels with significantly negative and positive GCL and IPL RoC were compared within the groups.

RESULTS

The average (SD) follow-up time and number of scans were 3.5 (0.7) years and 4.2 (1.0), respectively, in the GS group and 3.6 (0.4) years and 7.3 (1.1) in the EG group. Mean (SD) normalized RoC was faster for GCL than IPL (-0.69 [0.05] vs -0.33 [0.04]) in the GS group, whereas it was faster for IPL (-0.47 [0.03] vs -0.28 [0.02]) in EG eyes. GCL RoC were significantly negative in 24 of 36 superpixels compared with 8 of 36 for IPL (P < .001) in GS eyes. In the EG group, 23 of 36 superpixels had significant negative IPL RoC compared with 13 of 36 superpixels for GCL (P = .006).

CONCLUSIONS

GCL thickness is more likely to demonstrate change over time compared with IPL in glaucoma suspects. There is no evidence of preferential IPL thinning in eyes with suspected early glaucoma damage.

High-Speed Balanced-Detection Visible-Light Optical Coherence Tomography in the Human Retina Using Subpixel Spectrometer Calibration

Increases in speed and sensitivity enabled rapid clinical adoption of optical coherence tomography (OCT) in ophthalmology. Recently, visible-light OCT (vis-OCT) achieved ultrahigh axial resolution, improved tissue contrast, and provided new functional imaging capabilities, demonstrating the potential to improve clinical care further. However, limited speed and sensitivity caused by the high relative intensity noise (RIN) in supercontinuum lasers impeded the clinical adoption of vis-OCT. To overcome these limitations, we developed balanced-detection vis-OCT (BD-vis-OCT), which uses two calibrated spectrometers to cancel RIN and other noises. We analyzed the RIN to achieve robust subpixel calibration between the two spectrometers and showed that BD-vis-OCT reduced the A-line noise floor by up to 20.5 dB. Metrics comparing signal-to-noise-ratios showed similar image qualities across multiple reference arm powers, a hallmark of operation near the shot-noise limit. We imaged healthy human retinas at an A-line rate of 125 kHz and a field-of-view up to 10 mm ×4 mm. We found that BD-vis-OCT revealed retinal anatomical features previously obscured by the noise floor.

The Development and Clinical Application of Innovative Optical Ophthalmic Imaging Techniques

The field of ophthalmic imaging has grown substantially over the last years. Massive improvements in image processing and computer hardware have allowed the emergence of multiple imaging techniques of the eye that can transform patient care. The purpose of this review is to describe the most recent advances in eye imaging and explain how new technologies and imaging methods can be utilized in a clinical setting. The introduction of optical coherence tomography (OCT) was a revolution in eye imaging and has since become the standard of care for a plethora of conditions. Its most recent iterations, OCT angiography, and visible light OCT, as well as imaging modalities, such as fluorescent lifetime imaging ophthalmoscopy, would allow a more thorough evaluation of patients and provide additional information on disease processes. Toward that goal, the application of adaptive optics (AO) and full-field scanning to a variety of eye imaging techniques has further allowed the histologic study of single cells in the retina and anterior segment. Toward the goal of remote eye care and more accessible eye imaging, methods such as handheld OCT devices and imaging through smartphones, have emerged. Finally, incorporating artificial intelligence (AI) in eye images has the potential to become a new milestone for eye imaging while also contributing in social aspects of eye care.

Functional Optical Coherence Tomography for Intrinsic Signal Optoretinography: Recent Developments and Deployment Challenges

Intrinsic optical signal (IOS) imaging of the retina, also termed as optoretinogram or optoretinography (ORG), promises a non-invasive method for the objective assessment of retinal function. By providing the unparalleled capability to differentiate individual retinal layers, functional optical coherence tomography (OCT) has been actively investigated for intrinsic signal ORG measurements. However, clinical deployment of functional OCT for quantitative ORG is still challenging due to the lack of a standardized imaging protocol and the complication of IOS sources and mechanisms. This article aims to summarize recent developments of functional OCT for ORG measurement, OCT intensity- and phase-based IOS processing. Technical challenges and perspectives of quantitative IOS analysis and ORG interpretations are discussed.

Are There Static-Structural Biomarkers for Glaucoma with OCT?

Glaucomas lead to uniform, specific and slowly developing atrophy of the optic nerve with progressing visual field defects in late stages. Early diagnosis is challenging, but necessary as optic nerve damage is irreparable. Biomarkers with structural optical coherence tomography (OCT) flag optic atrophy but do not prove to be specific in the differential diagnosis to other forms of optic atrophy. Combination of OCT parameters and their correlation to other variables facilitate glaucoma diagnosis. Use of artificial intelligence (AI) in structural OCT images may prove to be superior and as biomarker more specific to thickness measurements of neuronal tissues alone.