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To develop a classification system of visual field (VF) abnormalities in highly myopic eyes with and without glaucoma.Secondary analysis of VF data from a longitudinal cohort study.One thousand eight hundred ninety-three VF tests from 1302 eyes (825 individuals).All participants underwent VF testing (Humphrey 24-2 Swedish interactive threshold algorithm standard program; Carl Zeiss Meditec) and detailed ophthalmic examination. A comprehensive set of VF defect patterns was defined via observation of the 1893 VF reports, literature review, and consensus meetings. The classification system comprised 4 major types of VF patterns, including normal type, glaucoma-like defects (paracentral defect, nasal step, partial arcuate defect, arcuate defect), high myopia-related defects (enlarged blind spot, vertical step, partial peripheral rim, nonspecific defect), and combined defects (nasal step with enlarged blind spot). A subset (n = 1000) of the VFs was used to evaluate the interobserver and intraobserver agreement and weighted κ values of the classification system by 2 trained readers. The prevalence of various VF patterns and their associated factors were determined.The classification of VF in highly myopic eyes and its associated risk factors.We found that normal type, glaucoma-like defects, high myopia-related defects, and combined defects accounted for 74.1%, 10.8%, 15.0%, and 0.1% of all unique VF tests, respectively. The interobserver and intraobserver agreements were89%, and the corresponding κ values were 0.86 or more between readers. Both glaucoma-like and high myopia-related VF defects were associated with older age (odds ratios [ORs], 1.07 [95% confidence interval (CI), 1.04-1.10; P0.001] and 1.06 [95% CI, 1.04-1.10; P0.001]) and longer axial length (ORs, 1.65 [95% CI, 1.32-2.07; P0.001] and 1.37 [95% CI, 1.11-1.68; P = 0.003]). Longer axial length showed a stronger effect on the prevalence of glaucoma-like VF defects than on the prevalence of high myopia-related VF defects (P = 0.036).We propose a new and reproducible classification system of VF abnormalities for nonpathologic high myopia. Applying a comprehensive classification system will facilitate communication and comparison of findings among studies.

Purpose To develop and validate a multimodal artificial intelligence algorithm, FusionNet, using the pattern deviation probability plots from visual field (VF) reports and circular peripapillary OCT scans to detect glaucomatous optic neuropathy (GON). Design Cross-sectional study. Subjects Two thousand four hundred sixty-three pairs of VF and OCT images from 1083 patients. Methods FusionNet based on bimodal input of VF and OCT paired data was developed to detect GON. Visual field data were collected using the Humphrey Field Analyzer (HFA). OCT images were collected from 3 types of devices (DRI-OCT, Cirrus OCT, and Spectralis). Two thousand four hundred sixty-three pairs of VF and OCT images were divided into 4 datasets: 1567 for training (HFA and DRI-OCT), 441 for primary validation (HFA and DRI-OCT), 255 for the internal test (HFA and Cirrus OCT), and 200 for the external test set (HFA and Spectralis). GON was defined as retinal nerve fiber layer thinning with corresponding VF defects. Main Outcome Measures Diagnostic performance of FusionNet compared with that of VFNet (with VF data as input) and OCTNet (with OCT data as input). Results FusionNet achieved an area under the receiver operating characteristic curve (AUC) of 0.950 (0.931–0.968) and outperformed VFNet (AUC, 0.868 [95% confidence interval (CI), 0.834–0.902]), OCTNet (AUC, 0.809 [95% CI, 0.768–0.850]), and 2 glaucomatologists (glaucomatologist 1: AUC, 0.882 [95% CI, 0.847–0.917]; glaucomatologist 2: AUC, 0.883 [95% CI, 0.849–0.918]) in the primary validation set. In the internal and external test sets, the performances of FusionNet were also superior to VFNet and OCTNet (FusionNet vs VFNet vs OCTNet: internal test set 0.917 vs 0.854 vs 0.811; external test set 0.873 vs 0.772 vs 0.785). No significant difference was found between the 2 glaucomatologists and FusionNet in the internal and external test sets, except for glaucomatologist 2 (AUC, 0.858 [95% CI, 0.805–0.912]) in the internal test set. Conclusions FusionNet, developed using paired VF and OCT data, demonstrated superior performance to both VFNet and OCTNet in detecting GON, suggesting that multimodal machine learning models are valuable in detecting GON.

Purpose To develop and evaluate the performance of a 3-dimensional (3D) deep-learning–based automated digital gonioscopy system (DGS) in detecting 2 major characteristics in eyes with suspected primary angle-closure glaucoma (PACG): (1) narrow iridocorneal angles (static gonioscopy, Task I) and (2) peripheral anterior synechiae (PAS) (dynamic gonioscopy, Task II) on OCT scans. Design International, cross-sectional, multicenter study. Participants A total of 1.112 million images of 8694 volume scans (2294 patients) from 3 centers were included in this study (Task I, training/internal validation/external testing: 4515, 1101, and 2222 volume scans, respectively; Task II, training/internal validation/external testing: 378, 376, and 102 volume scans, respectively). Methods For Task I, a narrow angle was defined as an eye in which the posterior pigmented trabecular meshwork was not visible in more than 180° without indentation in the primary position captured in the dark room from the scans. For Task II, PAS was defined as the adhesion of the iris to the trabecular meshwork. The diagnostic performance of the 3D DGS was evaluated in both tasks with gonioscopic records as reference. Main Outcome Measures The area under the curve (AUC), sensitivity, and specificity of the 3D DGS were calculated. Results In Task I, 29.4% of patients had a narrow angle. The AUC, sensitivity, and specificity of 3D DGS on the external testing datasets were 0.943 (0.933–0.953), 0.867 (0.838–0.895), and 0.878 (0.859–0.896), respectively. For Task II, 13.8% of patients had PAS. The AUC, sensitivity, and specificity of 3D DGS were 0.902 (0.818–0.985), 0.900 (0.714–1.000), and 0.890 (0.841–0.938), respectively, on the external testing set at quadrant level following normal clinical practice; and 0.885 (0.836–0.933), 0.912 (0.816–1.000), and 0.700 (0.660–0.741), respectively, on the external testing set at clock-hour level. Conclusions The 3D DGS is effective in detecting eyes with suspected PACG. It has the potential to be used widely in the primary eye care community for screening of subjects at high risk of developing PACG.

The current dogma in ophthalmology and vision research presumes the intraocular environment to be sterile. However, recent evidence of intestinal bacterial translocation into the bloodstream and many other internal organs including the eyes, found in healthy and diseased animal models, suggests that the intraocular cavity may also be inhabited by a microbial community. Here, we tested intraocular samples from over 1000 human eyes. Using quantitative PCR, negative staining transmission electron microscopy, direct culture, and high-throughput sequencing technologies, we demonstrated the presence of intraocular bacteria. The possibility that the microbiome from these low-biomass communities could be a contamination from other tissues and reagents was carefully evaluated and excluded. We also provide preliminary evidence that a disease-specific microbial signature characterized the intraocular environment of patients with age-related macular degeneration and glaucoma, suggesting that either spontaneous or pathogenic bacterial translocation may be associated with these common sight-threatening conditions. Furthermore, we revealed the presence of an intraocular microbiome in normal eyes from non-human mammals and demonstrated that this varied across species (rat, rabbit, pig, and macaque) and was established after birth. These findings represent the first-ever evidence of intraocular microbiota in humans.

Purpose: Obtaining a better understanding of the pathogenesis of primary angle-closure disease (PACD) still requires studies that provide measurements of anterior and posterior biometric characteristics together and that assess the relationship between them. Methods: In total, 201 eyes were enrolled in this cross-sectional study: 50 normal controls, 49 primary angle-closure suspect (PACS), 38 primary angle closure (PAC), and 64 primary angle-closure glaucoma (PACG) eyes. The anterior and posterior structural features were measured by anterior segment optical coherence tomography and swept-source optical coherence tomography. Results: All PACD groups had smaller anterior chamber depth (ACD), anterior chamber area (ACA), anterior chamber volume (ACV), angle opening distance at 750 μm from the scleral spur (AOD750), trabecular–iris space area at 750 μm from the scleral spur (TISA750), and angle recess area (ARA), as well as a larger lens vault (LV), than controls (all P < 0.001). The PACS and PAC groups had thicker iris thickness at 750 μm from the scleral spur (IT750) than controls (P = 0.017 and P = 0.002, respectively). Choroidal thickness (CT) was not statistically different among normal, PACS, PAC, and PACG eyes. Univariate and multivariate linear regression analysis revealed a significant association between thinner IT750 and increased CT in PACD eyes (P = 0.031, univariate analysis; P = 0.008, multivariate analysis). Conclusion: Thinner iris thickness was associated with increased CT in PACD eyes; however, the underlying mechanism needs further investigation.

Purpose. To evaluate the impact of glaucoma on vision-related quality of life and physical activity. Methods. This study included 50 glaucoma patients and 50 healthy control subjects. Sociodemographic and clinical data were collected from all subjects. A Chinese version of the NEI VFQ-25 was used to evaluate the quality of life. Objective physical activity was assessed by wearing an accelerometer for 7 consecutive days. Results. No significant difference was found in sociodemographic data between the two groups (all p<0.05). Visual acuity and visual field scores were worse in the glaucoma group than in the control group (all p<0.001). The VFQ-25 scores indicated significantly lower scores for ocular pain, social function, mental health, role difficulties, and color vision in the glaucoma group than in the normal group (all p<0.05). The average daily step count was lower in the glaucoma group than in the normal group. High, moderate, and low average daily step counts in the glaucoma group were associated with early-, moderate-, and advanced-stage glaucoma, respectively, while the step count was significantly lower in the advanced-stage glaucoma group than in the control group p=0.037. A positive relationship was found between the average daily step count and social function and mental health (both p<0.05). Conclusions. We demonstrated an adverse impact of glaucoma on psychological function and daily physical activity. Social function and mental health showed declines in glaucoma patients, and physical activity was limited in patients with advanced-stage glaucoma.

BackgroundDeep learning has been widely used for glaucoma diagnosis. However, there is no clinically validated algorithm for glaucoma incidence and progression prediction. This study aims to develop a clinically feasible deep-learning system for predicting and stratifying the risk of glaucoma onset and progression based on color fundus photographs (CFPs), with clinical validation of performance in external population cohorts.MethodsWe established data sets of CFPs and visual fields collected from longitudinal cohorts. The mean follow-up duration was 3 to 5 years across the data sets. Artificial intelligence (AI) models were developed to predict future glaucoma incidence and progression based on the CFPs of 17,497 eyes in 9346 patients. The area under the receiver operating characteristic (AUROC) curve, sensitivity, and specificity of the AI models were calculated with reference to the labels provided by experienced ophthalmologists. Incidence and progression of glaucoma were determined based on longitudinal CFP images or visual fields, respectively.ResultsThe AI model to predict glaucoma incidence achieved an AUROC of 0.90 (0.81-0.99) in the validation set and demonstrated good generalizability, with AUROCs of 0.89 (0.83-0.95) and 0.88 (0.79-0.97) in external test sets 1 and 2, respectively. The AI model to predict glaucoma progression achieved an AUROC of 0.91 (0.88-0.94) in the validation set, and also demonstrated outstanding predictive performance with AUROCs of 0.87 (0.81-0.92) and 0.88 (0.83-0.94) in external test sets 1 and 2, respectively.ConclusionOur study demonstrates the feasibility of deep-learning algorithms in the early detection and prediction of glaucoma progression.FUNDINGNational Natural Science Foundation of China (NSFC); the High-level Hospital Construction Project, Zhongshan Ophthalmic Center, Sun Yat-sen University; the Science and Technology Program of Guangzhou, China (2021), the Science and Technology Development Fund (FDCT) of Macau, and FDCT-NSFC.

Glaucoma has become a major cause of vision loss. Early-stage diagnosis of glaucoma is critical for treatment planning to avoid irreversible vision damage. Meanwhile, interpreting the rapidly accumulated medical data from ophthalmic exams is cumbersome and resource-intensive. Therefore, automated methods are highly desired to assist ophthalmologists in achieving fast and accurate glaucoma diagnosis. Deep learning has achieved great successes in diagnosing glaucoma by analyzing data from different kinds of tests, such as peripapillary optical coherence tomography (OCT) and visual field (VF) testing. Nevertheless, applying these developed models to clinical practice is still challenging because of various limiting factors. OCT models present worse glaucoma diagnosis performances compared to those achieved by OCTVF based models, whereas VF is time-consuming and highly variable, which can restrict the wide employment of OCTVF models. To this end, we develop a novel deep learning framework that leverages the OCTVF model to enhance the performance of the OCT model. To transfer the complementary knowledge from the structural and functional assessments to the OCT model, a cross-modal knowledge transfer method is designed by integrating a designed distillation loss and a proposed asynchronous feature regularization (AFR) module. We demonstrate the effectiveness of the proposed method for glaucoma diagnosis by utilizing a public OCTVF dataset and evaluating it on an external OCT dataset. Our final model with only OCT inputs achieves the accuracy of 87.4% (3.1% absolute improvement) and AUC of 92.3%, which are on par with the OCTVF joint model. Moreover, results on the external dataset sufficiently indicate the effectiveness and generalization capability of our model.

Automatic angle-closure assessment in Anterior Segment OCT (AS-OCT) images is an important task for the screening and diagnosis of glaucoma, and the most recent computer-aided models focus on a binary classification of anterior chamber angles (ACA) in AS-OCT, i.e., open-angle and angle-closure. In order to assist clinicians who seek better to understand the development of the spectrum of glaucoma types, a more discriminating three-class classification scheme was suggested, i.e., the classification of ACA was expended to include open-, appositional- and synechial angles. However, appositional and synechial angles display similar appearances in an AS-OCT image, which makes classification models struggle to differentiate angle-closure subtypes based on static AS-OCT images. In order to tackle this issue, we propose a 2D-3D Hybrid Variation-aware Network (HV-Net) for open-appositional-synechial ACA classification from AS-OCT imagery. Specifically, taking into account clinical priors, we first reconstruct the 3D iris surface from an AS-OCT sequence, and obtain the geometrical characteristics necessary to provide global shape information. 2D AS-OCT slices and 3D iris representations are then fed into our HV-Net to extract cross-sectional appearance features and iris morphological features, respectively. To achieve similar results to those of dynamic gonioscopy examination, which is the current gold standard for diagnostic angle assessment, the paired AS-OCT images acquired in dark and light illumination conditions are used to obtain an accurate characterization of configurational changes in ACAs and iris shapes, using a Variation-aware Block. In addition, an annealing loss function was introduced to optimize our model, so as to encourage the sub-networks to map the inputs into the more conducive spaces to extract dark-to-light variation representations, while retaining the discriminative power of the learned features. The proposed model is evaluated across 1584 paired AS-OCT samples, and it has demonstrated its superiority in classifying open-, appositional- and synechial angles.

BackgroundTo determine whether dynamic changes in choroidal thickness (CT) cause shallowing of the anterior chamber.Methods34 healthy volunteers were enrolled. The participants in our study adopted the upside-down position for 1.5 min, which was the model we used to study the dynamic changes in CT. Intraocular pressure (IOP) elevation, optical coherence tomography images of the choroid and anterior chamber were obtained at baseline, after being in an upside-down position in an inversion machine and after 15 min of rest. The changes in IOP, anterior chamber and choroidal blood flow between the baseline and the upside-down position were compared.ResultsSixty-eight eyes from 34 subjects were analysed. After being in upside-down position for 1.5 min, there was a significant increase in CT from 226.39±52.44 µm to 238.34±54.84 µm (pConclusionWhen the body position changed from sitting to upside-down position, there was choroidal thickening, anterior chamber shallowing and IOP elevation with reduced choroidal blood flow. The data provide evidence about the relationship between choroid expansion and shallowing of the anterior chamber, which may be of relevance for the pathogenesis of angle closure.

Glaucoma is the leading reason for irreversible blindness. Early detection and timely treatment of glaucoma are essential for preventing visual field loss or even blindness. In clinical practice, Optical Coherence Tomography (OCT) and Visual Field (VF) exams are two widely-used and complementary techniques for diagnosing glaucoma. OCT provides quantitative measurements of the optic nerve head (ONH) structure, while VF test is the functional assessment of peripheral vision. In this paper, we propose a Deep Relation Transformer (DRT) to perform glaucoma diagnosis with OCT and VF information combined. A novel deep reasoning mechanism is proposed to explore implicit pairwise relations between OCT and VF information in global and regional manners. With the pairwise relations, a carefully-designed deep transformer mechanism is developed to enhance the representation with complementary information for each modal. Based on reasoning and transformer mechanisms, three successive modules are designed to extract and collect valuable information for glaucoma diagnosis, the global relation module, the guided regional relation module, and the interaction transformer module, namely. Moreover, we build a large dataset, namely ZOC-OCT&VF dataset, which includes 1395 OCT-VF pairs for developing and evaluating our DRT. We conduct extensive experiments to validate the effectiveness of the proposed method. Experimental results show that our method achieves 88.3% accuracy and outperforms the existing single-modal approaches with a large margin. The codes and dataset will be publicly available in the future.

Purpose To characterize longitudinal changes in macular microvasculature as quantified from optical coherence tomography angiography (OCTA) metrics in primary open-angle glaucoma (POAG) eyes with and without high myopia. Methods In total, 63 and 61 POAG eyes with and without high myopia, respectively, underwent swept-source OCTA imaging in at least four follow-up visits at an ophthalmic center, with a scanning protocol of 3- × 3-mm centered at the fovea. The foveal avascular zone (FAZ) area, FAZ circularity, and vessel density (VD) in both the superficial (SCP) and deep capillary plexuses (DCP) were measured. The rate of change in macular OCTA metrics over time was estimated using linear mixed-effects models in both groups of POAG eyes. Results The mean follow-up time and number of visits were 27.72 ± 8.57 months and 8.5 (8 to 13) times, and 30.95 ± 10.19 months and 10 (8‒13) times in POAG eyes with and without high myopia, respectively. VD in the DCP reduced significantly more quickly in POAG eyes with high myopia than in those without high myopia (−5.14%/year vs. −3.71%/year, P = 0.008). Moreover, lower baseline VD in the DCP was significantly associated with faster VD reduction in POAG with high myopia eyes (P < 0.001). Conversely, the VD reduction rate in the SCP, FAZ area, and FAZ circularity in both the SCP and DCP were similar in both groups (all Ps > 0.05). Conclusions VD in DCP reduced significantly more quickly in POAG eyes with high myopia over time. Density in the DCP reduced more quickly when baseline VD was low.

Precise characterization and analysis of anterior chamber angle (ACA) are of great importance in facilitating clinical examination and diagnosis of angle-closure disease. Currently, the gold standard for diagnostic angle assessment is observation of ACA by gonioscopy. However, gonioscopy requires direct contact between the gonioscope and patients' eye, which is uncomfortable for patients and may deform the ACA, leading to false results. To this end, in this paper, we explore a potential way for grading ACAs into open-, appositional- and synechial angles by Anterior Segment Optical Coherence Tomography (AS-OCT), rather than the conventional gonioscopic examination. The proposed classification schema can be beneficial to clinicians who seek to better understand the progression of the spectrum of angle-closure disease types, so as to further assist the assessment and required treatment at different stages of angle-closure disease. To be more specific, we first use an image alignment method to generate sequences of AS-OCT images. The ACA region is then localized automatically by segmenting an important biomarker - the iris - as this is a primary structural cue in identifying angle-closure disease. Finally, the AS-OCT images acquired in both dark and bright illumination conditions are fed into our Multi-Sequence Deep Network (MSDN) architecture, in which a convolutional neural network (CNN) module is applied to extract feature representations, and a novel ConvLSTM-TC module is employed to study the spatial state of these representations. In addition, a novel time-weighted cross-entropy loss (TC) is proposed to optimize the output of the ConvLSTM, and the extracted features are further aggregated for the purposes of classification. The proposed method is evaluated across 66 eyes, which include 1584 AS-OCT sequences, and a total of 16,896 images. The experimental results show that the proposed method outperforms existing state-of-the-art methods in applicability, effectiveness, and accuracy.

Glaucoma is a common neurodegenerative disease and a leading cause of irreversible blindness worldwide. Retinal microglia-mediated neuroinflammation is involved in the process of optic nerve damage, but the mechanisms driving this microglial activation remain mostly elusive. Previous investigations reported that microRNAs are associated with the retinal microglial reaction and neural apoptosis. In the present study, we found that microRNA-93-5p (miR-93) played a key role in the reaction of retinal microglial cells in vivo and in vitro. The miR-93 level was significantly reduced in the retinae of rat acute ocular hypertension (AOH) models, which were accompanied by retinal microglial activation, overproduction of inflammatory cytokines, and subsequent retinal ganglion cells (RGCs) death, versus the retinae of controls. The induction of miR-93 overexpression significantly reduced microglial proliferation, migration and cytokine release, inhibited the expression of the target gene signal transducer and activator of transcription 3 (STAT3) and p-STAT3, and was associated with a reduced loss of RGCs. Treatment with a STAT3 inhibitor also decreased retinal microglial activation after AOH injury. Taken together, these results suggest that the miR-93/STAT3 pathway is directly related to the downregulation of retinal microglia-mediated neuro-inflammation and showed a neuroprotective effect. Regulating microglial activation through miR-93 may serve as a target for neuroprotective therapy in pathological ocular hypertension.

Glaucoma is one of the leading causes of blindness in humans, which is not reversible, but early detection and treatment can save helpful vision. Clinicians classify glaucoma into early, moderate, and advanced stages based on the extent of the patient’s visual field deficit. The treatment of glaucoma varies with the course of the disease. With the development of deep learning technology, more and more studies focus on the automatic diagnosis of glaucoma. Most of them are based on color fundus images or OCT images. However, there are limitations in using only one modality images to analyze glaucoma due to the complexity of glaucoma. Therefore, in this paper, two modalities of images, color fundus image and 3D OCT image provided by the GAMMA Challenge, were used to design baseline algorithms for glaucoma grading. On the preliminary dataset of the GAMMA Challenge, the kappa value of the glaucoma grading results based on the two modalities of image input were improved by 0.092 and 0.075, respectively, compared with those of the model with single fundus image and single OCT image input. And on the final datasets, the corresponding improvement were 0.029 and 0.127. At the same time, considering that optic disc changes are the main features of glaucoma, we added local information of optic disc into the input module, so that the kappa values were improved respectively by 0.075 and 0.068 in the preliminary dataset and final dataset of the model based on the images of two modalities as input. In addition, this study used an ordinal regression strategy on the classification task to increase the kappa value of the results of automatic classification of glaucoma based on multi-modality images by 0.097 and 0.050 on the preliminary and final datasets of the GAMMA Challenge.

IntroductionMyopic maculopathy and glaucoma belong to the most common causes of irreversible blindness worldwide and, having an ocular axial elongation as one of their main risk factors, can occur together. The detection of glaucomatous optic neuropathy (GON) in highly myopic eyes is clinically and technically difficult, and there is no information available, neither about the natural course of GON or about the course of GON under intraocular pressure-lowering therapy. We therefore designed this study to explore the natural course of GON in highly myopic eyes.Methods and analysisIn this single-centred longitudinal registry cohort study, 813 highly myopic individuals will be recruited and undergo detailed ophthalmic examinations. High myopia is defined by a myopic refractive error of ≥−6 D or an axial length of ≥26.5 mm. GON is defined by a glaucomatous appearance of the optic nerve head or glaucomatous visual field (VF) defects. GON progression is defined by either change of the optic disc or VF.Ethics and disseminationEthical approval has been obtained from the ethical committee of the Zhongshan Ophthalmic Center (ZOC), Sun Yat-sen University, China (ID: 2019KYPJ079). All the participants are required to provide informed consents. Results will be disseminated through scientific meetings and published in peer-reviewed journals. The data will be deposited at the clinical research centre in ZOC using electronic data capture system, and a copy of paper files will also be kept. Only members of the project team will have access to these data.Trial registration numberNCT04302220.

Purpose The purpose of this study was to investigate the difference in pulsatile trabecular meshwork (TM) motion between normal and eyes with POAG using phase-sensitive optical coherence tomography (PhS-OCT). Methods In this cross-sectional study, eight healthy subjects (16 eyes) and nine patients with POAG (18 eyes) were enrolled. A laboratory-based prototype PhS-OCT system was used to measure pulsatile TM motion. PhS-OCT images were analyzed to obtain parameters of pulsatile TM motion (i.e. maximum velocity [MV] and cumulative displacement [CDisp]). Outflow facility and ocular pulse amplitude were measured using pneumotonography. Detection sensitivity was compared among various parameters by calculating the area under the receiver operating characteristic curves (AUCs). Results A pulsatile TM motion waveform synchronous with digital pulse was observed using PhS-OCT in both healthy and POAG eyes. The mean MV in eyes with glaucoma was significantly lower than healthy eyes (P < 0.001). The mean CDisp in POAG eyes was also significantly lower than healthy eyes (P < 0.001). CDisp showed a significant correlation (r = 0.46; P = 0.0088) with ocular pulse amplitude in the study. Compared with the outflow facility, both the MV and CDisp were found to have a better discrimination of glaucoma (P < 0.001 and P = 0.0074, respectively). Conclusions Pulsatile TM motion was reduced in patients with POAG compared to healthy subjects. The underlying mechanism may be due to the altered tissue stiffness or other biomechanical properties of the TM in POAG eyes. Our evidence suggests that the measurement of pulsatile TM motion with PhS-OCT may help in characterizing outflow pathway abnormalities.

BackgroundTo investigate whether quantitative optical coherence tomography angiography (OCTA) metrics of the superficial/deep macular retina and optic disc are associated with glaucoma progression risk.MethodsA total of 238 eyes from 119 patients with open angle glaucoma or ocular hypertension, and no history of systemic hypertension or diabetes mellitus were included. All participants underwent OCTA imaging with a swept-source OCT (DRI-OCT 1, Topcon, Japan). OCTA metrics of superficial capillary plexus (SCP) and deep capillary plexus (DCP) in the macular region, and radial peripapillary capillary network of the optic disc were measured by a customised MATLAB program to obtain foveal avascular zone (FAZ) area, FAZ circularity and capillary density of SCP/DCP, and capillary density of the peripapillary region. Relationships between baseline OCTA metrics, visual field (VF) metrics, intraocular pressure fluctuation and risk of glaucoma progression were analysed with the Cox proportional hazards model. A frailty model was used to adjust for intereye correlation.ResultsDuring a mean follow-up duration of 29.39 months (range 12–56 months), 50, 48 and 16 eyes were determined to have retinal nerve fibre layer (RNFL), ganglion cell-inner plexiform layer (GC-IPL) and VF progression respectively. FAZ area per SD increase at baseline were significantly associated with both RNFL thinning (HR 1.73 95% CI 1.04 to 2.90); p=0.036) and GC-IPL thinning (HR 2.62, 95% CI 1.59 to 4.31; pConclusionEnlarged FAZ area measured by OCTA was associated with a higher risk of RNFL and GC-IPL thinning associated with glaucoma, but not with functional deterioration in glaucoma.

Purpose To describe the baseline characteristics of a trial to evaluate whether selective laser trabeculoplasty (SLT), as a first-line treatment, provides superior economic and health-related quality of life outcomes to medical treatment in China. Design The LiGHT China trial is an unmasked, single-center, pragmatic, randomized controlled trial. Methods A total of 771 previously undiagnosed patients with primary open angle glaucoma (POAG, 622 patients) or ocular hypertension (OHT, 149 patients) at Zhongshan Ophthalmic Center were recruited from March 2015 to January 2019. Subjects were randomized to SLT-1st (followed by medication then surgery when required) or Medicine-1st (medication followed by surgery when required). The primary outcome was health-related quality of life (HRQL). The secondary outcomes were clinical outcomes, cost, cost-effectiveness, Glaucoma Utility Index, Glaucoma Symptom Scale, visual function, and safety. Results The mean age of POAG patients was 49.8 years and 38.8 years for OHT. The median intraocular pressure was 20 mm Hg for the 1,105 POAG eyes and 24 mm Hg for the 271 OHT eyes. POAG eyes had thinner central cornea thickness (CCT, 536 µm) than OHT eyes (545 µm). Median mean deviation of the visual field in POAG eyes was -4.2 dB. Median refractive error was -1.5 D for OHT eyes and -1.25 D for POAG eyes. There was no difference between POAG and OHT patients on baseline scores of GUI, GSS and VF-14. The difference between OHT and POAG on the EQ-5D-5L was 0.024. Conclusions Compared with participants in the LiGHT UK trial, participants in this trial were younger, more myopic and had more severe visual field defects.

PurposeOptic disc (OD) and cup (OC) segmentation are fundamental for fundus image analysis. Manual annotation is time consuming, expensive, and highly subjective, while an automated system is invaluable to the medical community. The aim of this study is to develop a deep learning system to segment OD and OC in fundus photos, and evaluate how the algorithm compares against manual annotations.MethodsA total of 1200 fundus photos with 120 glaucoma cases were collected. The OD and OC annotations were labeled by seven licensed ophthalmologists, and glaucoma diagnoses were based on comprehensive evaluations of the subject medical records. A deep learning system for OD and OC segmentation was developed. The performances of segmentation and glaucoma discriminating based on the cup-to-disc ratio (CDR) of automated model were compared against the manual annotations.ResultsThe algorithm achieved an OD dice of 0.938 (95% confidence interval (CI), 0.934-0.941), OC dice of 0.801 (95% CI, 0.793-0.809), and CDR mean absolute error (MAE) of 0.077 (95% CI, 0.073-0.082). For glaucoma discriminating based on CDR calculations, the algorithm obtained an area under receiver operator characteristic curve (AUC) of 0.948 (95% CI, 0.920-0.973), with a sensitivity of 0.850 (95% CI, 0.794-0.923) and specificity of 0.853 (95% CI, 0.798-0.918).ConclusionsWe demonstrated the potential of the deep learning system to assist ophthalmologists in analyzing OD and OC segmentation and discriminating glaucoma from non-glaucoma subjects based on CDR calculations.Translational RelevanceWe investigate the segmentation of OD and OC by deep learning system compared against the manual annotations.

Angle closure glaucoma (ACG) is a more aggressive disease than open-angle glaucoma, where the abnormal anatomical structures of the anterior chamber angle (ACA) may cause an elevated intraocular pressure and gradually lead to glaucomatous optic neuropathy and eventually to visual impairment and blindness. Anterior Segment Optical Coherence Tomography (AS-OCT) imaging provides a fast and contactless way to discriminate angle closure from open angle. Although many medical image analysis algorithms have been developed for glaucoma diagnosis, only a few studies have focused on AS-OCT imaging. In particular, there is no public AS-OCT dataset available for evaluating the existing methods in a uniform way, which limits progress in the development of automated techniques for angle closure detection and assessment. To address this, we organized the Angle closure Glaucoma Evaluation challenge (AGE), held in conjunction with MICCAI 2019. The AGE challenge consisted of two tasks: scleral spur localization and angle closure classification. For this challenge, we released a large dataset of 4800 annotated AS-OCT images from 199 patients, and also proposed an evaluation framework to benchmark and compare different models. During the AGE challenge, over 200 teams registered online, and more than 1100 results were submitted for online evaluation. Finally, eight teams participated in the onsite challenge. In this paper, we summarize these eight onsite challenge methods and analyze their corresponding results for the two tasks. We further discuss limitations and future directions. In the AGE challenge, the top-performing approach had an average Euclidean Distance of 10 pixels (10um) in scleral spur localization, while in the task of angle closure classification, all the algorithms achieved satisfactory performances, with two best obtaining an accuracy rate of 100%., Accepted to Medical Image Analysis (MedIA). AGE Challenge website at: https://age.grand-challenge.org

Purpose To measure the anterior and posterior ocular biometric characteristics concurrently and to explore the relationship between iris, ciliary body and choroid in acute primary angle closure eyes (APAC) and fellow eyes. Methods It is a prospective, cross-sectional study. Thirty patients with recent APAC were finally enroled in it. Anterior and posterior uveal parameters were measured simultaneously by anterior segment optical coherence tomography (AS-OCT), swept-source optical coherence tomography (SS-OCT) and ultrasound biomicroscopy (UBM). The parameters were measured including: pupil diameter (PD); iris thickness, curvature (ICURV), area (IAREA); anterior chamber depth (ACD), width (ACW), area (ACA), volume (ACV); lens vault (LV); choroidal thickness and retinal thickness; maximum ciliary body thickness (CBTmax); ciliary body thickness at the point of the scleral spur (CBT0) and 1000 mm away (CBT1000); anterior placement of the ciliary body (APCB); and trabecular-ciliary angle (TCA). Results Compared with fellow eyes, APAC eyes had narrower anterior biometric parameters and presented with smaller anterior segment parameters (including ACD and ACW); (p

Purpose To evaluate the frequency of and identify the factors that influence the artifacts of swept-source optical coherence tomography angiography (SS-OCTA) in glaucomatous and normal eyes. Methods Artifacts of OCTA images of open-angle glaucoma (OAG) and normal subjects were analyzed using SS-OCTA. Univariate and multivariate logistic regression analyses were performed to evaluate the association of age, sex, best-corrected visual acuity, axial length (AL), intraocular pressure, presence and severity of OAG, and image quality score (IQS) with the presence of artifacts. Results Images from 4426 subjects were included in the study. At least one type of artifact was present in 24.54% of the images. The most common artifacts were occurrence of motion (705 eyes, 15.93%), followed by defocus (628 eyes, 14.19%), decentration (134 eyes, 3.03%), masking (62 eyes,1.40%), and segmentation errors (23 eyes, 0.52%). Multivariate logistic analyses showed that the presence of OAG (odds ratio [OR] = 2.71; 95% confidence interval [CI], 2.09–3.51; P < 0.001), female sex (OR = 1.34; 95% CI, 1.12–1.61; P = 0.001), longer AL (OR = 1.09; 95% CI, 1.02–1.17; P = 0.017), and IQS < 40 (OR = 3.75; 95% CI, 3.15–4.48; P < 0.001) were significantly associated with higher odds for the presence of any artifact. The IQS had poor performance for detecting artifacts, with an area under the curve of 0.723, sensitivity of 73.04%, and specificity of 62.53%. Conclusions OAG eyes had more SS-OCTA image artifacts than normal eyes. IQS is an imperfect tool for identifying artifacts. Translational Relevance Special attention should be paid to the effect of artifacts when using SS-OCTA in the clinical setting to assess vascular parameters in patients with glaucoma.

High myopia is among the most common causes of vision impairment, and it is mainly characterized by abnormal elongation of the axial length, leading to pathologic changes in the ocular structures. Owing to the close relationship between high myopia and glaucoma, the association between intraocular pressure (IOP) and high myopia progression has garnered attention. However, whether lowering IOP can retard the progression of high myopia is unclear. On reviewing previous studies, we suggest that lowering IOP plays a role in progressive axial length elongation in high myopia, particularly in pathologic myopia, wherein the sclera is more remodeled. Based on the responses of the ocular layers, we further proposed the potential mechanisms. For the sclera, lowering the IOP could inhibit the activation of scleral fibroblasts and then reduce scleral remodeling, and a decrease in the scleral distending force would retard the ocular expansion like a balloon. For the choroid, lowering IOP results in an increase in choroidal blood perfusion, thereby reducing scleral hypoxia and slowing down scleral remodeling. The final effect of these pathways is slowing axial elongation and the development of scleral staphyloma. Further animal and clinical studies regarding high myopia with varied degree of IOP and the changes of choroid and sclera during IOP fluctuation in high myopia are needed to verify the role of IOP in the pathogenesis and progression of high myopia. It is hoped that this may lead to the development of a prospective treatment option to prevent and control high myopia progression.

To compare biometric differences between eyes with unilateral chronic primary angle-closure glaucoma (PACG) and fellow non-glaucomatous eyes in the same patient.Clinical data and imaging records of 17 patients with unilateral PACG were retrospectively reviewed. The fellow eyes with primary angle-closure (PAC) or primary angle-closure suspected (PACS) were grouped in Group 1. The PACG eyes were set as Group 2. The biometric parameters of both eyes were measured by IOL-Master, anterior segment optical coherence tomography (AS-OCT), and swept source OCT.The iris area in Group 1 was significantly thicker than that in Group 2 (1.590 ± 0.267 versus 1.365 ± 0.352, P = 0.016). Choroidal thickness in the macular region was thicker in Group 1 than in Group 2, with statistical significance at inner temporal grid (282.7 ± 121.1 versus 191.6 ± 90.3, P = 0.036), central field (297.4 ± 130.6 versus 200.1 ± 96.3, P = 0.029), inner nasal grid (283.1 ± 128.3 versus 194.8 ± 91.8, P = 0.040), and average value (265.3 ± 105.6 versus 191.1 ± 87.0, P = 0.049). Group 1 also had thicker peripapillary choroidal thickness at 1 o'clock (141.4 ± 68.4 versus 101.8 ± 39.0, P = 0.025) and 12 o'clock (141.5 ± 82.3 versus 104.5 ± 44.6, P = 0.037) compared to Group 2. The multivariate logistic regression analyses showed that only intraocular pressure was independently associated with PACG and explained 58.3% variance of PACG.In unilateral PACG, there was significant inter-eye difference in anterior and posterior segment parameters. Longitudinal comparisons are required to further understand the differences in pathology of angle closures.

Purpose To assess the efficacy and safety of different regimens, including monotherapy and double therapy, for primary open-angle glaucoma (POAG) or ocular hypertension. Methods We searched PubMed, EMBASE and clinicaltrials.gov for studies that fit our inclusion criteria in this network meta-analysis. Randomized controlled trials that report data on efficacy and safety of medications for POAG or ocular hypertension are included. Data on intra-ocular pressure (IOP) lowering effect and incidence of adverse events including hyperaemia and ocular discomfort were extracted and used in mixed-comparison analysis. Results This study includes 72 randomized trials. Data were available on 12 medical treatments of POAG or ocular hypertension. Of 66 possible comparisons of outcome efficacy, 15 treatments were compared directly. Compared to prostaglandin analogues (PGA), beta-blockers (BB) showed relatively weaker ability to lower IOP, followed by α2-adrenergic agonists (AA) and carbonic anhydrase inhibitors (CAI). For dual therapy, regimens composed of a combination of PGA with another treatment demonstrated more powerful IOP lowering efficacy, while the combination of two non-PGA drugs had lower efficacy in controlling IOP than PGA alone. There was no statistical significance in combinations that did not include PGA on efficacy of IOP control. In terms of tolerance, PGA alone leads to more severe hyperaemia than any other monotherapy regimen, while BBs have the lowest effect on the incidence of hyperaemia. Most dual therapy regimens containing PGA also lead to serious hyperaemia, with the exception of PGA + AA. Compared to regimens containing PGA, those with BB are less likely to cause hyperaemia. Conclusion Our network meta-analysis showed that PGAs provide best IOP lowering effect among all the monotherapy regimen. Combination of PGA and other category of drugs leads to better IOP decrease. Combination of BB and another non-PGA drug may have less ocular side-effects than PGA alone.

Morphological changes in the iris are one of the major causes of angle-closure glaucoma, and an anteriorly-bowed iris may be further associated with greater risk of disease progression from primary angle-closure suspect (PACS) to chronic primary angle-closure glaucoma (CPCAG). In consequence, the automated detection of abnormalities in the iris region is of great importance in the management of glaucoma. In this paper, we present a new method for the extraction of the iris region by using a local phase tensor-based curvilinear structure enhancement method, and apply it to anterior segment optical coherence tomography (AS-OCT) imagery in the presence of occludable iridocorneal angle. The proposed method is evaluated across a dataset of 200 anterior chamber angle (ACA) images, and the experimental results show that the proposed method outperforms existing state-of-the-art method in applicability, effectiveness, and accuracy.

Precise characterization and analysis of iris shape from Anterior Segment OCT (AS-OCT) are of great importance in facilitating diagnosis of angle-closure-related diseases. Existing methods focus solely on analyzing structural properties identified from an individual 2D slice, while accurate characterization of morphological changes of iris shape in 3D AS-OCT may be able to reveal in addition the risk of disease progression. In this paper, we propose a novel framework for reconstruction and quantification of 3D iris surface from AS-OCT volume. We consider it to be the first work to detect angle-closure glaucoma by means of 3D representation. An iris segmentation network with wavelet refinement block (WRB) is first proposed to generate the initial shape of the iris from single AS-OCT slice. The 3D iris surface is then reconstructed using a guided optimization method with Poisson-disk sampling. Finally, a set of surface-based features are extracted, which are used in detecting of angle-closure glaucoma. Experimental results demonstrate that our method is highly effective in iris segmentation and surface reconstruction. Moreover, we show that 3D-based representation achieves better performance in angle-closure glaucoma detection than does 2D-based feature.

The choroid provides oxygen and nourishment to the outer retina thus is related to the pathology of various ocular diseases. Optical coherence tomography (OCT) is advantageous in visualizing and quantifying the choroid in vivo. (1) The lower boundary of the choroid (choroid-sclera interface) in OCT is fuzzy, which makes the automatic segmentation difficult and inaccurate. (2) The visualization of the choroid is hindered by the vessel shadows from the superficial layers of the inner retina. In this paper, we propose to incorporate medical and imaging prior knowledge with deep learning to address these two problems. We propose a biomarker infused global-to-local network for the choroid segmentation. It leverages the choroidal thickness, a primary biomarker in clinic, as a constraint to improve the segmentation accuracy. We also design a global-to-local strategy in the choroid segmentation: a global module is used to segment all the retinal and choroidal layers simultaneously for suppressing overfitting and providing global structure information, then a local module is used to refine the segmentation with the biomarker infusion. To eliminate the retinal vessel shadows, we propose a pipeline that firstly use anatomical and OCT imaging knowledge to locate the shadows using their projection on the retinal pigment epithelium layer, then the contents of the choroidal vasculature at the shadow locations are predicted with an edge-to-texture generative adversarial inpainting network. The experiments show our method outperforms the existing methods on both the segmentation and shadow elimination tasks. We further apply the proposed method in a clinical prospective study for understanding the pathology of glaucoma by detecting the structure and vascular changes of the choroid related to the elevation of intra-ocular pressure., Comment: 14 pages. This version has been accepted for publication in the IEEE Journal of Biomedical and Health Informatics (J-BHI)

Anterior chamber angle (ACA) classification is a key step in the diagnosis of angle-closure glaucoma in Anterior Segment Optical Coherence Tomography (AS-OCT). Existing automated analysis methods focus on a binary classification system (i.e., open angle or angle-closure) in a 2D AS-OCT slice. However, clinical diagnosis requires a more discriminating ACA three-class system (i.e., open, appositional, or synechial angles) for the benefit of clinicians who seek better to understand the progression of the spectrum of angle-closure glaucoma types. To address this, we propose a novel sequence multi-scale aggregation deep network (SMA-Net) for open-appositional-synechial ACA classification based on an AS-OCT sequence. In our method, a Multi-Scale Discriminative Aggregation (MSDA) block is utilized to learn the multi-scale representations at slice level, while a ConvLSTM is introduced to study the temporal dynamics of these representations at sequence level. Finally, a multi-level loss function is used to combine the slice-based and sequence-based losses. The proposed method is evaluated across two AS-OCT datasets. The experimental results show that the proposed method outperforms existing state-of-the-art methods in applicability, effectiveness, and accuracy. We believe this work to be the first attempt to classify ACAs into open, appositional, or synechial types grading using AS-OCT sequences.

By 2040, ~100 million people will have glaucoma. To date, there are a lack of high-efficiency glaucoma diagnostic tools based on visual fields (VFs). Herein, we develop and evaluate the performance of 'iGlaucoma', a smartphone application-based deep learning system (DLS) in detecting glaucomatous VF changes. A total of 1,614,808 data points of 10,784 VFs (5542 patients) from seven centers in China were included in this study, divided over two phases. In Phase I, 1,581,060 data points from 10,135 VFs of 5105 patients were included to train (8424 VFs), validate (598 VFs) and test (3 independent test sets-200, 406, 507 samples) the diagnostic performance of the DLS. In Phase II, using the same DLS, iGlaucoma cloud-based application further tested on 33,748 data points from 649 VFs of 437 patients from three glaucoma clinics. With reference to three experienced expert glaucomatologists, the diagnostic performance (area under curve [AUC], sensitivity and specificity) of the DLS and six ophthalmologists were evaluated in detecting glaucoma. In Phase I, the DLS outperformed all six ophthalmologists in the three test sets (AUC of 0.834-0.877, with a sensitivity of 0.831-0.922 and a specificity of 0.676-0.709). In Phase II, iGlaucoma had 0.99 accuracy in recognizing different patterns in pattern deviation probability plots region, with corresponding AUC, sensitivity and specificity of 0.966 (0.953-0.979), 0.954 (0.930-0.977), and 0.873 (0.838-0.908), respectively. The 'iGlaucoma' is a clinically effective glaucoma diagnostic tool to detect glaucoma from humphrey VFs, although the target population will need to be carefully identified with glaucoma expertise input. ispartof: NPJ Digit Med vol:3 issue:1 pages:123- ispartof: location:England status: Published online

BACKGROUND: To determine how many measurements should be evaluated to determine the iris bow and evaluate changes of iris bow at 12 clock positions after LPI in primary angle closure eyes. METHODS: A total of 93 primary angle closure eyes in 93 Chinese patients were enrolled. Anterior iris bowing was evaluated at 12 clock positions and 4 clock positions (3, 6, 9, and 12 o’clock) before, 1 week and 3 months after LPI using swept source optical coherence tomography. RESULTS: At baseline, almost all of the eyes exhibited an iris bow when measured using 12 clock positions, consistent with results obtained from measurements at 4 clock positions (Cronbach’s alpha = 0.99). LPI caused a relative unified change in all of the clock positions (Cronbach’s alpha = 0.91) except the LPI site. After LPI, there was no significant difference between 12 and 4 clock position measurements for the iris bow (both p > 0.05), with ~34.1% vs. 33% of the patients remained iris bow at 1 week and 34% vs. 31.9% of the patients remained iris bow at 3 months. However, the coexisting iris bow configuration was more common when measured using 4 clock positions (16.5% vs. 3.3% at 1 week and 25.5% vs. 10.6% at 3 months). CONCLUSIONS: There was excellent consistency when measuring the iris bow at 4 or 12 clock positions. LPI caused a relatively unified iris bow change at 12 clock positions, and a single LPI relieved only ~2/3 of the iris bow configurations.

Angle-closure glaucoma is one of the major causes of blindness in Asia. In this paper, we present a new approach for the classification of the anterior chamber angles into open, narrowed, and closure, in anterior segment optical coherence tomography (AS-OCT), by learning the manual annotations from gonioscopy, so as to further assist the assessment of angle-closure glaucoma. The proposed framework firstly localizes the anterior chamber angle region automatically, which is the primary structural image cue for clinically identifying glaucoma. Then three scales of cropped chamber angle images are fed into our Multi-Scale Regions Convolutional Neural Networks (MSRCNN) architecture, in which three parallel convolutional neural networks are applied to extract feature representations. Finally, the representations are stacked to fully-connected layer for glaucoma type classification. The proposed method is evaluated across a dataset of 9728 anterior chamber angle images, and the experimental results show that the proposed method outperforms existing state-of-the-art methods in applicability, effectiveness, and accuracy.

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To compare the distance from the corneoscleral limbus to the insertion site of the superior rectus of primary angle-closure glaucoma (PACG) patients with normal controls and to identify potential characteristics associated with limbus-insertion distance.Cross-sectional study.A total of 92 subjects (eyes) were enrolled in the study: 35 were nonglaucoma controls and 57 were PACG patients.The limbus-insertion distance of the superior rectus was measured by anterior segment optical coherence tomography (AS-OCT) and intraoperative surgical caliper. The anterior chamber parameters were also measured using AS-OCT to identify potential characteristics associated with limbus-insertion distance.The limbus-insertion distance of the superior rectus was 0.40 ± 0.08 mm shorter in the PACG group than in the normal control group (p0.001). Anterior segment parameter values, including anterior chamber depth (ACD), anterior chamber width (ACW), anterior chamber area (ACA), and anterior chamber volume (ACV), were smaller in the PACG group than in the normal control group, but the lens vault was larger (all p0.001). A shorter limbus-insertion distance of the superior rectus was significantly associated with shorter axial length and "crowded" angle (smaller ACD, ACW, ACA, and ACV) (all p0.05).This is the first study to demonstrate that the limbus-insertion distance of the superior rectus was shorter in PACG eyes than in normal eyes. The shorter limbus-insertion distance may be another anatomic characteristic of PACG eyes.

To evaluate the efficacy and tolerability of Ahmed glaucoma valve (AGV) implantation with intravitreal bevacizumab injection (IVB) pretreatment in the treatment of neovascular glaucoma (NVG).A comprehensive literature search was performed according to the Cochrane collaboration methodology to identify controlled clinical trials comparing AGV implantation with (IVB group) or without IVB (control group) pretreatment for NVG. The main outcome measures were the weighted mean differences (WMDs) for intraocular pressure reduction, a reduction in glaucoma medications, odds ratio (OR) for complete success rates, and qualified success rates. Tolerability estimates were measured by OR for adverse events.The WMD of the intraocular pressure reduction when comparing the IVB group with the control group was 3.30 (-1.21 to 7.80). The IVB group was associated with numerically greater but nonsignificant IOP lowering efficacy compared with the control group (P=0.152). Both groups were comparable in the reduction of glaucoma medication, with a WMD of 0.28 (-0.03 to 0.59) at the follow-up endpoint (P=0.077). The IVB group was associated with significant greater complete success rates compared with the control group, with a pooled OR of 3.18 (1.41 to 7.19). However, it did not show a significant difference for the qualified success rate between them, with a pooled OR of 2.00 (0.95 to 4.21). The IVB group was associated with a significantly lower frequency of hyphema than the control group, with a pooled OR of 0.15 (0.07 to 0.32).The use of IVB pretreatment for NVG is a safe and effective additional step during AGV implantation surgery.

PURPOSE To measure and compare the levels of vascular endothelial growth factor (VEGF) in the aqueous humor of patients with acute primary angle closure (APAC), primary angle-closure glaucoma (PACG), and normal cataract (controls). METHODS Aqueous humor samples were prospectively collected from 38 APAC eyes, 36 PACG eyes, and 25 nonglaucomatous cataract control eyes. The levels of aqueous humor VEGF were measured using enzyme-linked immunoassays. The clinical characteristics of participants were also collected for correlation analysis. RESULTS VEGF was detected in aqueous humor samples of 35 of 38 APAC patients (mean±SE of the mean, 935±258 pg/mL), 30 of 36 PACG patients (165±37.5 pg/mL), and 16 of 25 cataract controls (69.5±13.5 pg/mL). The mean concentration of VEGF in APAC eyes was 13.5 and 5.7 times higher than that in controls and PACG eyes, respectively, and these differences were statistically significant (both P

To review the current research on microglia as it relates to glaucoma, and summarize the potential microglia-targeted therapies.The data were collected from PubMed and Google Scholar databases published in English up to July 2014. Keywords used, both alone and in combination, in the database search included retinal microglia, over-activation and inhibition of microglia, and glaucoma.Articles were selected and reviewed if they involved microglia in animal models or human patients with glaucoma. Moreover, we also cited some comprehensive amalgamation of published literature.Together with the macroglia [astrocytes, ependymal cells, oligodendrocytes, radial (Müller) cells], the microglia form the supportive tissue of the central nervous system (CNS). Glial cells are generally smaller than the neural cells, but outnumber them by a factor of 5 to 10 with marked regional differences in the CNS. Approximately half of the volume of the CNS is composed of glial cells. Because of the blood-retina barrier, blood-born immunologic cells cannot penetrate into the retina under physiological conditions; the retinal microglial cells are the primary immunocompetent cells in the retina. The microglial cells are involved in any process of cell degeneration and loss, including retinal ganglion fiber and cell loss. Surveying the retinal tissue in normal situations as "spiders in a net," the retinal microglial cells change their form from a resting dendritic-like shape to an activated ameboid form in the case of invading microorganisms or cell damage. They are involved in the process of cell apoptosis and removal of the dead cells. Studies suggested that inhibition of the microglial cell activation in the case of optic nerve damage can increase the number of surviving retinal ganglion cells and may thus be neuroprotective.Activated microglia appear early in the glaucomatous process and may contribute detrimentally to the neuronal apoptosis in the later stage. Neuroprotective strategies that inhibit activated microglia may provide novel treatment modalities for glaucomatous optic neuropathy and any other retinal and optic nerve disease.

Purpose: Aerobic exercise (AE) has been reported to decrease intraocular pressure (IOP) in healthy subjects and there are concomitant morphological changes in the anterior segment of the eye including the Schlemm's canal (SC). However, its effects on IOP and SC morphology in glaucoma patients had not been studied before. We aim to investigate the effect of AE on the IOP and SC dimension in both healthy and primary open-angle glaucoma (POAG) eyes. Methods: The area and diameter of SC and IOP were measured in 35 primary open-angle glaucoma (POAG) patients (59 eyes) and 36 healthy subjects (72 eyes) before and after performing moderate intensity of AE by running on a treadmill for 30 min. SC was imaged by swept-source optical coherence tomography (SS-OCT) for evaluation. Results: In comparison with baseline values, mean IOP decreased significantly following AE in both POAG and healthy eyes (both P < 0.001), in which POAG eyes showed a greater degree of reduction compared to healthy eyes (P = 0.002). In comparison with baseline values, in both POAG and healthy eyes, the average cross-sectional area (POAG: 80.48 +/- 59.54 vs. 99.20 +/- 54.87 pixels; healthy: 151.84 +/- 52.76 vs. 198.23 +/- 53.70 pixels; both P < 0.001) and diameter (POAG: 3.73 +/- 1.69 vs. 4.33 +/- 1.74 pixels; healthy: 5.61 +/- 1.02 vs. 6.47 +/- 1.20 pixels; both P < 0.001) of SC significantly increased after AE. In POAG, both treated and untreated with IOP-lowering medications, a significant reduction in mean IOP and increase in SC dimensions following AE were observed (all P < 0.05), and there were no significant differences of such measurements between the two subgroups (all P > 0.05). Conclusion: AE-induced reduction in IOP and an increase in SC dimensions in POAG eyes as in healthy eyes. Further studies to evaluate the long-term effect of AE on IOP control and SC morphology in POAG seem warranted.

Purpose Optic disc (OD) and optic cup (OC) segmentation are fundamental for fundus image analysis. Manual annotation is time consuming, expensive, and highly subjective, whereas an automated system is invaluable to the medical community. The aim of this study is to develop a deep learning system to segment OD and OC in fundus photographs, and evaluate how the algorithm compares against manual annotations. Methods A total of 1200 fundus photographs with 120 glaucoma cases were collected. The OD and OC annotations were labeled by seven licensed ophthalmologists, and glaucoma diagnoses were based on comprehensive evaluations of the subject medical records. A deep learning system for OD and OC segmentation was developed. The performances of segmentation and glaucoma discriminating based on the cup-to-disc ratio (CDR) of automated model were compared against the manual annotations. Results The algorithm achieved an OD dice of 0.938 (95% confidence interval [CI] = 0.934-0.941), OC dice of 0.801 (95% CI = 0.793-0.809), and CDR mean absolute error (MAE) of 0.077 (95% CI = 0.073 mean absolute error (MAE)0.082). For glaucoma discriminating based on CDR calculations, the algorithm obtained an area under receiver operator characteristic curve (AUC) of 0.948 (95% CI = 0.920 mean absolute error (MAE)0.973), with a sensitivity of 0.850 (95% CI = 0.794-0.923) and specificity of 0.853 (95% CI = 0.798-0.918). Conclusions We demonstrated the potential of the deep learning system to assist ophthalmologists in analyzing OD and OC segmentation and discriminating glaucoma from nonglaucoma subjects based on CDR calculations. Translational relevance We investigate the segmentation of OD and OC by deep learning system compared against the manual annotations.

PURPOSE To test the repeatability and reproducibility of the Zhongshan ONH Calculator (ZOC) software in terms of selected optic nerve head (ONH) parameters commonly used in clinical research of glaucoma. MATERIALS AND METHODS Forty-two horizontal single-line scans were selected to test the repeatability and reproducibility of the ZOC software. Clinically relevant 2D parameters of the ONH area were selected to test repeatability of ZOC, including length of BMO, minimum rim thickness on both sides (RIML and RIMR), optic cup depth (OCD), and depth of the anterior surface of the LC (ALCD). RESULTS Intraobserver test showed higher the intra-class correlation coefficient (ICC) of BMO ((0.991 vs. 0.777), RIML (0.988 vs. 0.890), RIMR (0.972 vs. 0.846), OCD (0.997 vs. 0.992), and ALCD (0.993 vs. 0.949) by single researcher using ZOC software than manual measurement. BA analysis showed acceptable agreement between automatic and manual measurements. SDs and limits of agreement (95% CI) of BMO, RIML, RIMR, OCD, and ALCD were 0.05 (-0.13, 0.07), 0.03 (-0.05, 0.05), 0.03 (-0.06, 0.07), 0.015 (-0.035, 0.024), and 0.04 (-0.07, 0.08), respectively. CONCLUSION This study presented the design and development of software for the automatic measurement of OCT images of ONH area with good reproducibility. In the future, with advances of OCTs and improvements to the resolution of the LC, ZOC will become a powerful tool in glaucoma research.

Glaucoma is the leading cause of irreversible blindness worldwide, which is now viewed as a disease of brain with pathogenesis not fully understood. The main diagnostic methods are examining the retinal nerve fiber layer through optical coherence tomography and investigating visual field defect, but these methods present disadvantages in clinical practice. Studies have shown that patients with glaucoma often suffer negative emotion like anxiety and depression which is related to abnormal or reduced amygdala. Moreover, selective reduction of fMRI responses to transient achromatic stimuli in the superficial layer of the superior colliculus was found in the early glaucoma patients. By summarizing previous studies, we developed a hypothesis: superior colliculus-pulvinar-amygdala subcortical visual pathway may be involved in the incidence or progression of glaucoma. Validating this hypothesis would further clarify the mechanism of glaucoma and lead to the development of a more sensitive method for making an early diagnosis of glaucoma.

Purpose To explore the microRNA (miRNA) profile and its putative role in glaucomatous optic neuropathy by using next-generation sequencing. Methods Aqueous humor (AH) samples were collected from 19 primary open-angle glaucoma (POAG) eyes and 17 cataract eyes before surgery. Next-generation sequencing was performed for RNA samples extracted from 18 AH samples, and the bioinformatics approach was applied for samples with adequate clean data output. The other 18 samples were used for quantitative PCR validation of sequencing results. Results In total, 12 (six POAG and six cataract controls) samples with sufficient clean data output after sequencing were used for further data analysis. Four hundred sixty-six and 480 mature miRNAs were detected in the POAG and cataract control groups, respectively. Among them, 164 miRNAs were detected in all POAG samples, and 96 miRNAs were detected in all cataract control samples. Furthermore, 88 miRNAs were identified as differently expressed between POAG and cataract control eyes. In addition, 16 miRNAs were differently expressed between POAG eyes with severe visual field damage and eyes with moderate visual field damage. This differential expression was predicted to regulate thiamine metabolism, purine metabolism, and transcriptional misregulation. Relative expression patterns of hsa-miR-184, hsa-miR-486-5p, and hsa-miR-93-5p were confirmed by quantitative PCR. Conclusions This study comprehensively demonstrated the miRNA expression profile in the AH of POAG eyes, especially the differential expression of miRNA in eyes with varying degrees of visual field damage, which, together with the underlying miRNA-related pathways, indicate new targets for the pathogenesis and progression of POAG.

To compare the anterior and posterior choroid thickness (ACT and PCT, respectively) in primary open-angle glaucoma (POAG), primary angle-closure disease (PACD), and healthy control subjects.A total of 29 POAG patients (56 eyes), 37 PACD patients (64 eyes), and 34 healthy volunteers (68 eyes) were enrolled in this study; 50 POAG eyes were divided into 25 early/moderate-stage and 25 advanced-stage eyes by visual field loss, while 64 PACD eyes were classified as primary angle-closure suspect (PACS), 8 eyes; primary angle closure (PAC), 18 eyes; and primary angle-closure glaucoma (PACG), 38 eyes. Ultrasound biomicroscopy (UBM) was used to measure the ACT at a distance of 4 mm from the root of iris in all participants. ACT and PCT were measured using UBM and swept-source optical coherence tomography (SS-OCT), respectively. A 4-mm distance from the iris root was self-defined as the anterior choroid that well matched the real anterior choroid.The mean ACT measured by UBM was 0.45 ± 0.057 mm in POAG eyes, 0.38 ± 0.050 mm in PACD eyes, and 0.30 ± 0.050 mm in healthy eyes. Both the POAG and PACD eyes had a thicker anterior choroid than healthy eyes (P0.01). Compared to early/moderate-stage eyes of POAG, advanced-stage eyes had similar ACT (P0.05). PACG eyes had a thinner anterior choroid than PAC/PACS eyes (P0.05). However, no statistically significant difference was noted for POAG, PACD, and normal control eyes' PCT using SS-OCT (P0.05).POAG/PACD eyes had a thicker anterior choroid than the controls. However, there was no significant difference in the PCT among the groups. The anterior choroid might play a role in the pathogenesis of glaucoma, warranting further investigation.

Primary angle closure disease (PACD), prevalent in Asian countries, is generally associated with a shallower anterior chamber, a shorter axial length, thicker lens, hyperopia, and female sex. Other physiologic factors, however, may be important, especially with regard to triggering acute primary angle closure. Thickening of the choroid has been demonstrated in untreated and treated, acute and chronic PACD eyes. Recently, there has been growing interest in studying the role of the choroid in the pathophysiology of PACD. The emergence of new imaging technology such as the enhanced depth imaging mode of spectral-domain optical coherence tomography and swept-source optical coherence tomography has contributed to understanding PACD pathologies. We summarize the functions of the choroid and choroidal changes in the pathogenesis of PACD, and discuss potential future developments.