Optical coherence tomography (OCT) provides non-contact, rapid in vivo imaging of ocular structures, and has become a key part of evaluating the anterior segment of the eye. Over the years, improvements to technology have increased the speed of capture and resolution of images, leading to the increasing impact of anterior segment OCT imaging on clinical practice. In this review, we summarize the historical development of anterior segment OCT, and provide an update on the research and clinical applications of imaging the ocular surface, cornea, anterior chamber structures, aqueous outflow system, and most recently anterior segment vessels. We also describe advancements in anterior segment OCT technology that have improved understanding with greater detail, such as tear film in dry eye disease evaluation, intra-operative real-time imaging for anterior segment surgery, and aqueous outflow with angle assessment for glaucoma. Improvements to image processing and software have also improved the ease and utility of interpreting anterior segment OCT images in everyday clinical practice. Future developments include refinement of assessing vascular networks for the anterior segment, in vivo ultra-high resolution anterior segment optical coherence tomography with histology-like detail, en-face image with 3-dimensional reconstruction as well as functional extensions of the technique.

Deep learning has dramatically improved object recognition, speech recognition, medical image analysis and many other fields. Optical coherence tomography (OCT) has become a standard of care imaging modality for ophthalmology. We asked whether deep learning could be used to segment cornea OCT images. Using a custom-built ultrahigh-resolution OCT system, we scanned 72 healthy eyes and 70 keratoconic eyes. In total, 20,160 images were labeled and used for the training in a supervised learning approach. A custom neural network architecture called CorneaNet was designed and trained. Our results show that CorneaNet is able to segment both healthy and keratoconus images with high accuracy (validation accuracy: 99.56%). Thickness maps of the three main corneal layers (epithelium, Bowman’s layer and stroma) were generated both in healthy subjects and subjects suffering from keratoconus. CorneaNet is more than 50 times faster than our previous algorithm. Our results show that deep learning algorithm scan be used for OCT image segmentation and could be applied in various clinical settings. In particular, CorneaNet could be used for early detection of keratoconus and more generally to study other diseases altering corneal morphology.

We present imaging of corneal pathologies using optical coherence tomography (OCT) with high resolution. To this end, an ultrahigh-resolution spectral domain OCT (UHR-OCT) system based on a broad bandwidth Ti:sapphire laser is employed. With a central wavelength of 800 nm, the imaging device allows to acquire OCT data at the central, paracentral and peripheral cornea as well as the limbal region with 1.2 µm x 20 µm (axial x lateral) resolution at a rate of 140 000 A-scans/s. Structures of the anterior segment of the eye, not accessible with commercial OCT systems, are visualized. These include corneal nerves, limbal palisades of Vogt as well as several corneal pathologies. Cases such as keratoconus and Fuchs’s endothelial dystrophy as well as infectious changes caused by diseases like Acanthamoeba keratitis and scarring after herpetic keratitis are presented. We also demonstrate the applicability of our system to visualize epithelial erosion and intracorneal foreign body after corneal trauma as well as chemical burns. Finally, results after Descemet’s membrane endothelial keratoplasty (DMEK) are imaged. These clinical cases show the potential of UHR-OCT to help in clinical decision-making and follow-up. Our results and experience indicate that UHR-OCT of the cornea is a promising technique for the use in clinical practice, but can also help to gain novel insight in the physiology and pathophysiology of the human cornea.

We present a system capable of measuring the total retinal blood flow using a combination of dual beam Fourier-domain Doppler optical coherence tomography with orthogonal detection planes and a fundus camera-based retinal vessel analyzer. Our results show a high degree of conformity of venous and arterial flows, which corroborates the validity of the measurements. In accordance with Murray’s law, the log-log regression coefficient between vessel diameter and blood flow was found to be ~3. The blood’s velocity scaled linearly with the vessel diameter at higher diameters (> 60 µm), but showed a clear divergence from the linear dependence at lower diameters. Good agreement with literature data and the large range and high measurement sensitivity point to a high potential for further investigations.

To assess the feasibility and reliability of Laser Speckle Flowgraphy (LSFG) to measure ocular perfusion in a sample of healthy white subjects and to elucidate the age-dependence of the parameters obtained. This cross-sectional study included 80 eyes of 80 healthy, non-smoking white subjects of Western European descent between 19 and 79 years of age. A commercial LSFG instrument was applied to measure ocular blood flow at the optic nerve head (ONH) three successive times before and after pharmacological pupil dilation. The mean blur rate (MBR), a measure of relative blood flow velocity, was obtained for different regions of the ONH. Eight parameters of ocular perfusion derived from the pulse-waveform analysis of MBR including blowout time (BOT) and falling rate (FR) were also recorded. Artifact-free LSFG images meeting the quality criteria for automated image analysis were obtainable in 93.8% without pupil dilation and in 98.8% with pharmacological pupil dilation. Measurements of MBR showed excellent repeatability with intraclass correlation coefficients ≥ 0.937 and were barely affected by pupil dilation. The majority of pulse-waveform derived variables exhibited equally high repeatability. MBR-related blood flow indices exhibited significant age dependence (p<0.001). FR (r = 0.747, p<0.001) and BOT (r = -0.714, p<0.001) most strongly correlated with age. LSFG represents a reliable method for the quantitative assessment of ocular blood flow in white subjects. Our data affirms that the LSFG-derived variables FR and BOT may be useful biomarkers for age-related changes in ocular perfusion.

Aims/hypothesis The aim of this study was to compare retinal oxygen extraction in individuals with diabetes with no or mild non-proliferative diabetic retinopathy and healthy age- and sex-matched volunteers. Methods A total of 24 participants with type 1 diabetes and 24 healthy age- and sex-matched volunteers were included in this cross-sectional study. Retinal oxygen extraction was measured by combining total retinal blood flow measurements using a custom-built bi-directional Doppler optical coherence tomography system with measurements of oxygen saturation using spectroscopic reflectometry. Based on previously published mathematical modelling, the oxygen content in retinal vessels and total retinal oxygen extraction were calculated. Results Total retinal blood flow was higher in diabetic participants (46.4 ± 7.4 μl/min) than in healthy volunteers (40.4 ± 5.3 μl/min, p = 0.002 between groups). Oxygen content in retinal arteries was comparable between the two groups, but oxygen content in retinal veins was higher in participants with diabetes (0.15 ± 0.02 ml O₂/ml) compared with healthy control participants (0.13 ± 0.02 ml O₂/ml, p < 0.001). As such, the arteriovenous oxygen difference and total retinal oxygen extraction were reduced in participants with diabetes compared with healthy volunteers (total retinal oxygen extraction 1.40 ± 0.44 vs 1.70 ± 0.47 μl O₂/min, respectively, p = 0.03). Conclusions/interpretation Our data indicate early retinal hypoxia in individuals with type 1 diabetes with no or mild diabetic retinopathy as compared with healthy control individuals. Further studies are required to fully understand the potential of the technique in risk stratification and treatment monitoring. Trial registration: ClinicalTrials.gov NCT01843114.