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Retinal laser therapy such as panretinal photocoagulation can be associated with complications, including rare cases of choroidal detachment. This report describes high-resolution optical coherence tomography (OCT) imaging after retinal laser panretinal photocoagulation (PRP) in patients with proliferative diabetic retinopathy (PDR) demonstrating choroidal detachment. A series of three sequential patients with high-risk proliferative diabetic retinopathy who were PRP laser naïve were examined with spectral-domain OCT immediately after green solid-state laser or PASCAL® PRP treatment. All three patients demonstrated a significant choroidal detachment immediately after PRP treatment. By one month after PRP, the choroidal detachment resolved spontaneously in all patients. OCT examinations were performed to detect and evaluate the severity and the change of choroidal detachment and thickness measurements were quantified and demonstrated a mean decrease in choroidal thickness of 122 µm (p < 0.05 in all patients). Conventional green solid-state laser and PASCAL® laser both have the risk of developing complications such as choroidal detachment. While the rate of choroidal detachment has been reported to be quite low, this could be due to subclinical, self-limited, choroidal detachments. The risk could be larger than previously reported using modern high-resolution clinical optical imaging such as OCT. [ABSTRACT FROM AUTHOR]

Purpose: To robustly segment retinal layers that are affected by complex variety of retinal diseases for optical coherence tomography angiography (OCTA) en face projection generation. Methods: In this paper, we propose a robust retinal layer segmentation model to reduce the impact of multifarious abnormalities on model performance. OCTA vascular distribution that is regarded as the supplements of spectral domain optical coherence tomography (SD‐OCT) structural information is introduced to improve the robustness of layer region encoding. To further reduce the sensitivity of region encoding to retinal abnormalities, we propose a multitask layer‐wise refinement (MLR) module that can refine the initial layer region segmentation results layer‐by‐layer. Finally, we design a region‐to‐surface transformation (RtST) module without additional training parameters to convert the encoding layer regions to their corresponding layer surfaces. This transformation from layer regions to layer surfaces can remove the inaccurate segmentation regions, and the layer surfaces are easier to be used to protect the retinal layer natures than layer regions. Results: Experimental data includes 273 eyes, where 95 eyes are normal and 178 eyes contain complex retinal diseases, including age‐related macular degeneration (AMD), diabetic retinopathy (DR), central serous chorioretinopathy (CSC), choroidal neovascularization (CNV), and so forth. The dice similarity coefficient (DSC: %) of superficial, deep and outer retina achieves 98.92, 97.48, and 98.87 on normal eyes and 98.35, 95.33, and 98.17 on abnormal eyes. Compared with other commonly used layer segmentation models, our model achieves the state‐of‐the‐art layer segmentation performance. Conclusions: The final results prove that our proposed model obtains outstanding performance and has enough ability to resist retinal abnormalities. Besides, OCTA modality is helpful for retinal layer segmentation. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the changes in vessel density in patients with unilateral congenital cataract after cataract extraction. Materials and Methods: Children with unilateral congenital cataract were enrolled in our study. All of the patients underwent congenital cataract extraction and intraocular lens (IOL) implantation successfully. Optical coherence tomography angiography (OCTA) was performed to image the retinal vasculature in the macular and optic disc areas before and after surgery. The differences in vessel density and retinal thickness between groups were compared. Results: We found that the best corrected visual acuity (BCVA) was significantly improved one month after surgery compared with that before surgery (t=5.179, p< 0.001). The axial length was also changed one month after surgery (t=5.350, p< 0.001). The vessel density in the macular and optic disc areas of the affected eyes was significantly lower than that in the normal eyes, while the vessel density at the posterior pole was significantly improved one month after cataract extraction. Conclusion: The decrease in vessel density in the macular and optic disc areas might be a consequence of the congenital cataract. Cataract extraction can relieve the form deprivation of the affected eye and increase the vessel density at the posterior pole of the affected eye significantly. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to automatically and accurately segment hyper‐reflective foci (HRF) in spectral domain optical coherence tomography (SD‐OCT) images with diabetic retinopathy (DR) using deep convolutional neural networks. Methods: An automatic HRF segmentation model for SD‐OCT images based on deep networks was constructed. The model segmented small lesions through pixel‐wise predictions based on small image patches. We used an approach for discriminative features extraction for small patches by introducing small kernels and strides in convolutional and pooling layers, which was applied on the state‐of‐the‐art deep classification networks (GoogLeNet and ResNet). The features extracted by the adapted deep networks were fed into a softmax layer to produce the probabilities of HRF. We trained different models on a dataset with 16 HRF eyes by using different sizes of patches, and then, we fused these models to generate optimal results. Results: Experimental results on 18 eyes demonstrated that our method is effective for the HRF segmentation. The dice similarity coefficient (DSC) for the foci area in B‐scan, projection images, and foci amount in B‐scan images reaches 67.81%, 74.09%, and 72.45%, respectively. Conclusions: The proposed segmentation model can accurately segment HRF in SD‐OCT images with DR and outperforms traditional methods. Our model may provide reliable segmentations for small lesions in SD‐OCT images and may be helpful in the clinical diagnosis of diseases. [ABSTRACT FROM AUTHOR]

Purpose: To quantify the preoperative neovascular change pattern on the fibrovascular membrane (FVM) within 7 days after intravitreal injection of conbercept (IVC) using optical coherence tomography angiography (OCTA) in proliferative diabetic retinopathy (PDR). Methods: Prospective, observational study of PDR patients with visible FVM receiving or not receiving IVC. Neovascular changes were assessed by OCTA pre-IVC and 1, 3, 5, and 7 days post-IVC. Vessel skeleton density (SD) and vessel density (VD) were quantified by an intensity-based optical microangiography algorithm. The interclass correlation coefficient (ICC) was calculated to assess the agreement between measurements. The SD and VD were compared between follow-ups using repeated-measures analysis in the IVC group. Results: The ICC was 0.992 (95% confidence interval [CI]: 0.982–0.996) for SD and 0.926 (95% CI: 0.838–0.912) for VD of neovascularization. The neovascularization on FVM significantly regressed in the IVC group (n = 16) compared with no IVC (n = 8) (p = 0.001 for SD and p < 0.001 for VD). The comparisons between consecutive follow-ups showed a statistically significant reduction in SD and VD at 1 and 3 days post-IVC. However, from day 3 onward, the SD and VD remained unchanged. There was no development or progression of tractional retinal detachment within the 7-day period after IVC. Conclusion: OCTA–based quantification of the neovascularization on FVM in PDR is feasible, with high inter-reader agreement. The regression of neovascularization reaches a plateau 3 days after IVC. Clinical Trial Registration: This trial is registered with the Chinese Clinical Trial Registry (http://www.chictr.org.cn, registration number ChiCTR-IPR-17014160). [ABSTRACT FROM AUTHOR]

In this paper, an automatic method is reported for simultaneously segmenting layers and fluid in 3-D OCT retinal images of subjects suffering from central serous retinopathy. To enhance contrast between adjacent layers, multiscale bright and dark layer detection filters are proposed. Due to appearance of serous fluid or pigment epithelial detachment caused fluid, contrast between adjacent layers is often reduced, and also large morphological changes are caused. In addition, 24 features are designed for random forest classifiers. Then, 8 coarse surfaces are obtained based on the trained random forest classifiers. Finally, a hypergraph is constructed based on the smoothed image and the layer structure detection responses. A modified live wire algorithm is proposed to accurately detect surfaces between retinal layers, even though OCT images with fluids are of low contrast and layers are largely deformed. The proposed method was evaluated on 48 spectral domain OCT images with central serous retinopathy. The experimental results showed that the proposed method outperformed the state-of-art methods with regard to layers and fluid segmentation. [ABSTRACT FROM AUTHOR]

Purpose: The retinal vessel visualization from spectral-domain optical coherence tomography (SDOCT) images is important for ocular disease diagnosis and multimodal retinal image processing. The purpose is to display the retinal vessel in a single projection image from 3D SD-OCT images by using the light absorption and shadow characteristics of the retinal vessel. Methods: The authors present a novel retinal vessel projection method for SD-OCT images, which utilizes the light absorption and shadow characteristics of the retinal vessel, called high-low reflectivity enhancement (HLRE) method. The reflectivity of the retinal vessel increases between the internal limiting membrane and inner nuclear layer-outer plexiform layer (INL-OPL) layers because of the light absorption, and the reflectivity below the retinal vessel decreases because of the influence of the retinal vessel shadow. A retinal vessel mask image generated based on the reflectivity characteristics of the retinal vessel is used to enhance the subvolume projection image restricted between the INL-OPL and Bruch's membrane layers. Results: Experimental results with 22 SD-OCT cubes from 12 patients and 10 normal persons demonstrate that the authors' method is more effective in displaying the retinal vessel than the summed-voxel projection and other five region restriction based projection methods. The average of the mean difference between the retinal vessel and background regions based on their HLRE method is 0.1921. Conclusions: The proposed HLRE method was more effective for the visualization of the retinal vessels than the state-of-art methods because it provides higher contrast and distinction. [ABSTRACT FROM AUTHOR]

Purpose To evaluate the impact of postoperative posturing with or without face-down on the anatomical and functional outcomes of macular hole surgery. Methods A literature-based meta-analysis was conducted to identify studies relevant to posturing following macular hole surgery ( MHS). PubMed and Web of Science databases were used to retrieve articles up to 1 June 2015. The primary measures included MH closure and ideal vision acuity improvement. Pooled odds ratios ( ORs) and 95% confidence intervals ( CIs) were estimated in Review Manager. Results Four randomized control trials ( RCTs) comprising 251 cases were included in the final meta-analysis. No face-down posturing ( FDP) after MHS revealed lower anatomic success rate compared to face-down posturing ( OR = 0.33, 95% CI [0.13, 0.81], p = 0.02). For holes smaller than 400 μm in size, the subgroup meta-analysis indicated no significant effect of FDP on successful hole closure ( OR = 0.29, 95% CI [0.01, 7.34], p = 0.45). However, when holes were larger than 400 μm, it seemed less effective on MH closure following surgery in no FDP group ( OR = 0.23, 95% CI [0.07, 0.71]), and this was statistically significant (p = 0.01). Conclusions Our work found that no FDP was not inferior to its face-down counterpart for the success of MHS when macular holes were smaller than 400 μm in size. For macular holes larger than 400 μm, statistical analysis proved that FDP might be necessary. More well-conducted randomized control trials are needed to verify our findings. [ABSTRACT FROM AUTHOR]

Purpose: In clinical research, it is important to measure choroidal thickness when eyes are affected by various diseases. The main purpose is to automatically segment choroid for enhanced depth imagingoptical coherence tomography (EDI-OCT) images with five B-scans averaging. Methods: The authors present an automated choroid segmentation method based on choroidal vasculature characteristics for EDI-OCT images with five B-scans averaging. By considering the large vascular of the Haller's layer neighbor with the choroid-sclera junction (CSJ), the authors measured the intensity ascending distance and a maximum intensity image in the axial direction from a smoothed and normalized EDI-OCT image. Then, based on generated choroidal vessel image, the authors constructed the CSJ cost and constrain the CSJ search neighborhood. Finally, graph search with smooth constraints was utilized to obtain the CSJ boundary. Results: Experimental results with 49 images from 10 eyes in 8 normal persons and 270 images from 57 eyes in 44 patients with several stages of diabetic retinopathy and age-related macular degeneration demonstrate that the proposed method can accurately segment the choroid of EDI-OCT images with five B-scans averaging. The mean choroid thickness difference and overlap ratio between the authors' proposed method and manual segmentation drawn by experts were -11.43 µm and 86.29%, respectively. Conclusions: Good performance was achieved for normal and pathologic eyes, which proves that the authors' method is effective for the automated choroid segmentation of the EDI-OCT images with five B-scans averaging. [ABSTRACT FROM AUTHOR]

Today, the widespread use of laser instruments in various fields has resulted in many accidental retinal injuries. Here we describe a rare clinical case of full-thickness macular hole (MH) and focal choroidal excavation (FCE) caused by a 1064-nm Q-switched Nd:YAG laser. After pars plana vitrectomy and the following 14 months, consecutive optical coherence tomography imagings showed closure of the MH. Visual acuity improved even in the absence of the outer retina and in the presence of FCE. We speculate that different focusing effects of the unexpected Nd:YAG lasers which target different levels of retinal tissue generate diverse prognosis. [ABSTRACT FROM AUTHOR]

Optical coherence tomography angiography (OCTA) is a novel imaging modality that has been widely utilized in ophthalmology and neuroscience studies to observe retinal vessels and microvascular systems. However, publicly available OCTA datasets remain scarce. In this paper, we introduce the largest and most comprehensive OCTA dataset dubbed OCTA-500, which contains OCTA imaging under two fields of view (FOVs) from 500 subjects. The dataset provides rich images and annotations including two modalities (OCT/OCTA volumes), six types of projections, four types of text labels (age/gender/eye/disease) and seven types of segmentation labels (large vessel/capillary/artery/vein/2D FAZ/3D FAZ/retinal layers). Then, we propose a multi-object segmentation task called CAVF, which integrates capillary segmentation, artery segmentation, vein segmentation, and FAZ segmentation under a unified framework. In addition, we optimize the 3D-to-2D image projection network (IPN) to IPN-V2 to serve as one of the segmentation baselines. Experimental results demonstrate that IPN-V2 achieves an about 10% mIoU improvement over IPN on CAVF task. Finally, we further study the impact of several dataset characteristics: the training set size, the model input (OCT/OCTA, 3D volume/2D projection), the baseline networks, and the diseases. The dataset and code are publicly available at: https://ieee-dataport.org/open-access/octa-500. • Proposed OCTA-500, which is the largest and comprehensive OCTA dataset. • The OCTA-500 includes OCTA imaging from 500 subjects and rich annotation information. • Proposed a CAVF task, which integrates multiple key segmentation tasks. • Optimized the IPN to IPN-V2 to serve as one of the competitive baselines. • The OCTA-500 dataset has great potential to promote other researches in OCTA. [ABSTRACT FROM AUTHOR]

The performance of supervised deep learning significantly relies on the volume of training samples. However, the vast majority of medical images lacks manual expert annotations. Compared to natural image annotation, the cost of medical image annotation is more expensive as it requires professional medical knowledge guidance. To tackle the predicament, semi-supervised learning and self-supervised learning are very effective technologies. In this paper, we present a twin self-supervision based semi-supervised learning (TS-SSL) approach that embeds two types of self-supervised strategies (namely generative self-supervised learning and discriminative self-supervised learning) into semi-supervised framework to simultaneously learn from few-shot labeled images and vast unlabeled images. TS-SSL is an end-to-end classification model, in which semi-supervision and self-supervision can be jointly trained. The proposed TS-SSL is applied to perform retinal anomaly classification based on spectral-domain optical coherence tomography (SD-OCT) images. The experiments demonstrate that TS-SSL yields the good classification performance on one public SD-OCT dataset and two private SD-OCT datasets with only 10% labels. We also claim that TS-SSL can be transferred to other medical imaging modalities. The code is available at https://github.com/ZhangYH0502/TS-SSL. [ABSTRACT FROM AUTHOR]

Background and Objective The measurement of choroidal volume is more related with eye diseases than choroidal thickness, because the choroidal volume can reflect the diseases comprehensively. The purpose is to automatically segment choroid for three-dimensional (3D) spectral domain optical coherence tomography (SD-OCT) images. Methods We present a novel choroid segmentation strategy for SD-OCT images by incorporating the enhanced depth imaging OCT (EDI-OCT) images. The down boundary of the choroid, namely choroid-sclera junction (CSJ), is almost invisible in SD-OCT images, while visible in EDI-OCT images. During the SD-OCT imaging, the EDI-OCT images can be generated for the same eye. Thus, we present an EDI-OCT-driven choroid segmentation method for SD-OCT images, where the choroid segmentation results of the EDI-OCT images are used to estimate the average choroidal thickness and to improve the construction of the CSJ feature space of the SD-OCT images. We also present a whole registration method between EDI-OCT and SD-OCT images based on retinal thickness and Bruch's Membrane (BM) position. The CSJ surface is obtained with a 3D graph search in the CSJ feature space. Results Experimental results with 768 images (6 cubes, 128 B-scan images for each cube) from 2 healthy persons, 2 age-related macular degeneration (AMD) and 2 diabetic retinopathy (DR) patients, and 210 B-scan images from other 8 healthy persons and 21 patients demonstrate that our method can achieve high segmentation accuracy. The mean choroid volume difference and overlap ratio for 6 cubes between our proposed method and outlines drawn by experts were −1.96µm3 and 88.56%, respectively. Conclusions Our method is effective for the 3D choroid segmentation of SD-OCT images because the segmentation accuracy and stability are compared with the manual segmentation. [ABSTRACT FROM AUTHOR]

In this study we described a new model of subretinal edema induced by single intraocular injection of DL-alpha-aminoadipic acid (DLAAA) that can be employed to study the mechanism of retinal edema and test the efficacy or potential toxicity of treatments. The progression of subretinal edema was evaluated by fundus photography, fluorescein angiography and optical coherence tomography for up to 4 weeks following DLAAA injection. The VEGF, IL-6, TNF-α, Occludin, ZO-1, AQP4, Kir4.1, GFAP and GS levels were examined in DLAAA models by immunostaining, immumohistochemical staining and Western blot. Additionally, bulk RNA-seq was used to detect the mechanism involved in DLAAA-induced retinal Müller cellular injuries. In vivo and vitro assays were further conducted to confirm the sequencing results. Subretinal edema was successfully induced by DLAAA in New Zealand White rabbits (1.29 mg/eye) and C57BL/6 mice (50 or 100 μg/eye). Our results demonstrated that the disruption of blood-retinal-barrier, including vascular hyperpermeability, inflammation, and Müller cell dysfunction of fluid clearance, was involved in subretinal edema formation in the model. Bulk RNA-seq and in vitro studies indicated the activation of p38 MAPK signaling pathway in DLAAA models. This DLAAA-induced subretinal edema model can be used for mechanistic studies or drug screening. [Display omitted] • The first report of a novel model of subretinal edema induced by DL-alpha aminoadipic acid (DLAAA) • The disruption of blood-retinal-barrier, including vascular hyperpermeability, inflammation, and Müller cell dysfunction of fluid clearance, was involved in subretinal edema formation in DLAAA models • DLAAA-induced dysfunction of Müller cells is partly via the activation of p38 MAPK signaling pathway [ABSTRACT FROM AUTHOR]

Highlights: [•] To describe a novel method for multi-parameter measurements for the mouse retina. [•] To indicate a modified combination of lenses adapted to Zeiss HD-OCT firstly. [•] To quantify the magnification of this OCT system for mouse retinal imaging firstly. [•] To replace the traditional measurement on histological sections by our method. [Copyright &y& Elsevier]