Quantitative Analysis of Mouse Retinal Layers Using Automated Segmentation of Spectral Domain Optical Coherence Tomography Images.

PURPOSE Quantification of retinal layers using automated segmentation of optical coherence tomography (OCT) images allows for longitudinal studies of retinal and neurological disorders in mice. The purpose of this study was to compare the performance of automated retinal layer segmentation algorithms with data from manual segmentation in mice using the Spectralis OCT. METHODS Spectral domain OCT images from 55 mice from three different mouse strains were analyzed in total. The OCT scans from 22 C57Bl/6, 22 BALBc, and 11 C3A.Cg-Pde6b(+)Prph2(Rd2) /J mice were automatically segmented using three commercially available automated retinal segmentation algorithms and compared to manual segmentation. RESULTS Fully automated segmentation performed well in mice and showed coefficients of variation (CV) of below 5% for the total retinal volume. However, all three automated segmentation algorithms yielded much thicker total retinal thickness values compared to manual segmentation data (P < 0.0001) due to segmentation errors in the basement membrane. CONCLUSIONS Whereas the automated retinal segmentation algorithms performed well for the inner layers, the retinal pigmentation epithelium (RPE) was delineated within the sclera, leading to consistently thicker measurements of the photoreceptor layer and the total retina. TRANSLATIONAL RELEVANCE The introduction of spectral domain OCT allows for accurate imaging of the mouse retina. Exact quantification of retinal layer thicknesses in mice is important to study layers of interest under various pathological conditions.

Multimodal Registration Procedure for the Initial Spatial Alignment of a Retinal Video Sequence to a Retinal Composite Image

Accurate placement of lesions is crucial for the effectiveness and safety of a retinal laser photocoagulation treatment. Computer assistance provides the capability for improvements to treatment accuracy and execution time. The idea is to use video frames acquired from a scanning digital ophthalmoscope (SDO) to compensate for retinal motion during laser treatment. This paper presents a method for the multimodal registration of the initial frame from an SDO retinal video sequence to a retinal composite image, which may contain a treatment plan. The retinal registration procedure comprises the following steps: 1) detection of vessel centerline points and identification of the optic disc; 2) prealignment of the video frame and the composite image based on optic disc parameters; and 3) iterative matching of the detected vessel centerline points in expanding matching regions. This registration algorithm was designed for the initialization of a real-time registration procedure that registers the subsequent video frames to the composite image. The algorithm demonstrated its capability to register various pairs of SDO video frames and composite images acquired from patients.

Comparison between confocal scanning laser tomography, scanning laser polarimetry and optical coherence tomography on the ability to detect localised retinal nerve fibre layer defects in glaucoma patients

BACKGROUND/AIM: To compare the ability of confocal scanning laser tomography (CSLT), scanning laser polarimetry (SLP) and optical coherence tomography (OCT) in recognising localised retinal nerve fibre layer (RNFL) defects. METHODS: 51 eyes from 43 patients with glaucoma were identified by two observers as having RNFL defects visible on optic disc photographs. 51 eyes of 32 normal subjects were used as controls. Three masked observers evaluated CSLT, SLP and OCT images to determine subjectively the presence of localised RNFL defects. RESULTS: Interobserver agreement was highest with OCT, followed by SLP and CSLT (mean kappa: 0.83, 0.69 and 0.64, respectively). RNFL defects were identified in 58.8% of CSLT, 66.7% of SLP and 54.9% of OCT (p = 0.02 between SLP and OCT) by at least two observers. In the controls, 94.1% of CSLT, 84.3% of SLP and 94.1% of OCT scans, respectively, were rated as normal (p = 0.02 between CSLT and SLP, and SLP and OCT). CONCLUSION: Approximately 20-40% of localised RNFL defects identified by colour optic disc photographs are not detected by CSLT, SPL or OCT. SLP showed a higher number of false-positive results than the other techniques, but also had a higher proportion of correctly identified RNFL defects in the glaucoma population.

Vision-based Proximity Detection in Retinal Surgery

In retinal surgery, surgeons face difficulties such as indirect visualization of surgical targets, physiological tremor, and lack of tactile feedback, which increase the risk of retinal damage caused by incorrect surgical gestures. In this context, intraocular proximity sensing has the potential to overcome current technical limitations and increase surgical safety. In this paper, we present a system for detecting unintentional collisions between surgical tools and the retina using the visual feedback provided by the opthalmic stereo microscope. Using stereo images, proximity between surgical tools and the retinal surface can be detected when their relative stereo disparity is small. For this purpose, we developed a system comprised of two modules. The first is a module for tracking the surgical tool position on both stereo images. The second is a disparity tracking module for estimating a stereo disparity map of the retinal surface. Both modules were specially tailored for coping with the challenging visualization conditions in retinal surgery. The potential clinical value of the proposed method is demonstrated by extensive testing using a silicon phantom eye and recorded rabbit in vivo data.

Fluorescence lifetime imaging in retinal artery occlusion.

PURPOSE Fluorescence lifetime imaging ophthalmoscopy is a technique to measure decay times of endogenous retinal fluorophores. The purpose of this study was to investigate fluorescence lifetimes in eyes with central and branch retinal artery occlusion. METHODS Twenty-four patients with central or branch retinal artery occlusion were included in this study. The contralateral unaffected fellow eye was used as control. Measurements were performed using a fluorescence lifetime imaging ophthalmoscope based on a HRA Spectralis system. Fluorescence excitation wavelength was 473 nm, and mean lifetimes were measured in a short (498-560 nm) and in a long (560-720 nm) spectral channel. Fluorescence lifetimes in the area of retinal artery occlusion were measured and compared to corresponding areas in contralateral unaffected eyes. Additionally, findings were correlated to optical coherence tomography measurements. RESULTS Retinal lifetime images of 24 patients with retinal artery occlusion were analyzed. Mean retinal fluorescence lifetimes were prolonged by 50% in the short and 20% in the long spectral channel in ischemic retinal areas up to 3 days after retinal artery occlusion compared to the contralateral unaffected eyes. In the postacute disease stage there was no difference between the lifetimes of affected areas and unaffected fellow eyes. CONCLUSIONS Retinal artery occlusion leads to significantly longer fluorescence lifetimes of the retina in the acute phase and may serve as a useful indicator for acute ischemic retinal damage.

Retinal slit lamp video mosaicking

Purpose To this day, the slit lamp remains the first tool used by an ophthalmologist to examine patient eyes. Imaging of the retina poses, however, a variety of problems, namely a shallow depth of focus, reflections from the optical system, a small field of view and non-uniform illumination. For ophthalmologists, the use of slit lamp images for documentation and analysis purposes, however, remains extremely challenging due to large image artifacts. For this reason, we propose an automatic retinal slit lamp video mosaicking, which enlarges the field of view and reduces amount of noise and reflections, thus enhancing image quality. Methods Our method is composed of three parts: (i) viable content segmentation, (ii) global registration and (iii) image blending. Frame content is segmented using gradient boosting with custom pixel-wise features. Speeded-up robust features are used for finding pair-wise translations between frames with robust random sample consensus estimation and graph-based simultaneous localization and mapping for global bundle adjustment. Foreground-aware blending based on feathering merges video frames into comprehensive mosaics. Results Foreground is segmented successfully with an area under the curve of the receiver operating characteristic curve of 0.9557. Mosaicking results and state-of-the-art methods were compared and rated by ophthalmologists showing a strong preference for a large field of view provided by our method. Conclusions The proposed method for global registration of retinal slit lamp images of the retina into comprehensive mosaics improves over state-of-the-art methods and is preferred qualitatively.

Automatic assessment of time-resolved OCT images for selective retina therapy

Purpose In recent years, selective retina laser treatment (SRT), a sub-threshold therapy method, avoids widespread damage to all retinal layers by targeting only a few. While these methods facilitate faster healing, their lack of visual feedback during treatment represents a considerable shortcoming as induced lesions remain invisible with conventional imaging and make clinical use challenging. To overcome this, we present a new strategy to provide location-specific and contact-free automatic feedback of SRT laser applications. Methods We leverage time-resolved optical coherence tomography (OCT) to provide informative feedback to clinicians on outcomes of location-specific treatment. By coupling an OCT system to SRT treatment laser, we visualize structural changes in the retinal layers as they occur via time-resolved depth images. We then propose a novel strategy for automatic assessment of such time-resolved OCT images. To achieve this, we introduce novel image features for this task that when combined with standard machine learning classifiers yield excellent treatment outcome classification capabilities. Results Our approach was evaluated on both ex vivo porcine eyes and human patients in a clinical setting, yielding performances above 95 % accuracy for predicting patient treatment outcomes. In addition, we show that accurate outcomes for human patients can be estimated even when our method is trained using only ex vivo porcine data. Conclusion The proposed technique presents a much needed strategy toward noninvasive, safe, reliable, and repeatable SRT applications. These results are encouraging for the broader use of new treatment options for neovascularization-based retinal pathologies.

SPECTRAL DOMAIN-OPTICAL COHERENCE TOMOGRAPHY IMAGE CONTRAST AND BACKGROUND COLOR SETTINGS INFLUENCE IDENTIFICATION OF RETINAL STRUCTURES.

PURPOSE To evaluate image contrast and color setting on assessment of retinal structures and morphology in spectral-domain optical coherence tomography. METHODS Two hundred and forty-eight Spectralis spectral-domain optical coherence tomography B-scans of 62 patients were analyzed by 4 readers. B-scans were extracted in 4 settings: W + N = white background with black image at normal contrast 9; W + H = white background with black image at maximum contrast 16; B + N = black background with white image at normal contrast 12; B + H = black background with white image at maximum contrast 16. Readers analyzed the images to identify morphologic features. Interreader correlation was calculated. Differences between Fleiss-kappa correlation coefficients were examined using bootstrap method. Any setting with significantly higher correlation coefficient was deemed superior for evaluating specific features. RESULTS Correlation coefficients differed among settings. No single setting was superior for all respective spectral-domain optical coherence tomography parameters (P = 0.3773). Some variables showed no differences among settings. Hard exudates and subretinal fluid were best seen with B + H (κ = 0.46, P = 0.0237 and κ = 0.78, P = 0.002). Microaneurysms were best seen with W + N (κ = 0.56, P = 0.025). Vitreomacular interface, enhanced transmission signal, and epiretinal membrane were best identified using all color/contrast settings together (κ = 0.44, P = 0.042, κ = 0.57, P = 0.01, and κ = 0.62, P ≤ 0.0001). CONCLUSION Contrast and background affect the evaluation of retinal structures on spectral-domain optical coherence tomography images. No single setting was superior for all features, though certain changes were best seen with specific settings.

Quantification of retinal layer thickness changes in acute macular neuroretinopathy.

PURPOSE To quantitatively evaluate retinal layer thickness changes in acute macular neuroretinopathy (AMN). METHODS AMN areas were identified using near-infrared reflectance (NIR) images. Intraretinal layer segmentation using Heidelberg software was performed. The inbuilt ETDRS -grid was moved onto the AMN lesion and the mean retinal layer thicknesses of the central grid were recorded and compared with the corresponding area of the fellow eye at initial presentation and during follow-up. RESULTS Eleven patients were included (mean age 26±6 years). AMN lesions at baseline had a significantly thinner outer nuclear layer (ONL) (51±21 µm vs 73±17 µm, p=0.002). The other layers, including inner nuclear layer (37±8 µm vs 38±6 µm, p=0.9) and outer plexiform layer (OPL) (45±19 µm vs 33±16 µm, p=0.1) did not show significant differences between the study eyes and fellow eyes. Adjacent to NIR image lesions, areas of OPL thickening were identified (study eye: 50±14 µm vs fellow eye: 39±16 µm, p=0.005) with corresponding thinning of ONL (study eye: 52±16 µm vs fellow eye: 69±16 µm, p=0.002). CONCLUSIONS AMN presents with characteristic quantitative retinal changes and the extent of the lesion may be more extensive than initially presumed from NIR image lesions.