Hemodialysis-induced positional changes in lamina cribrosa.

This study is aimed to investigate the effect of hemodialysis (HD) on the lamina cribrosa (LC) of the optic nerve head (ONH) using swept-source optical coherence tomography (SS-OCT) and other ophthalmological parameters in patients with end-stage kidney disease (ESKD). This prospective observational study included 29 patients who underwent HD for ESKD. ONH parameters including neural canal diameter (NCD), peripapillary vertical height (PVH), and anterior LC depth (LCD), were assessed using SS-OCT. Changes in the ONH parameters before and after HD were statistically analysed. Correlations between changes in the LCD and other ocular and systemic measurements were identified using Pearson's correlation analyses. The mean anterior LCD significantly decreased from 441.6 ± 139.8 µm before HD to 413.5 ± 141.7 µm after HD (P = 0.001). Mean NCD and PVH did not show significant changes after HD (P = 0.841 and P = 0.574, respectively). A significant correlation was found between changes in the anterior LCD and the mean ocular perfusion pressure (r = 0.397, P = 0.036). We observed a significant decrease in anterior LCD after HD. Our study suggests that HD can influence the ONH, especially in the LC.

Demographic and clinical characteristics associated with screening practices for hydroxychloroquine retinopathy.

In this nationwide population-based cohort study, we investigated the demographic and clinical characteristics associated with hydroxychloroquine retinopathy screening using the National Health Insurance Review and Assessment database in South Korea. This study included a total of 32,732 at-risk patients, identified based on having been prescribed hydroxychloroquine for at least 6 months, and 15,477 long-term (> 5 years) users between January 2010 and December 2020. Participants were categorized based on the performance of baseline examinations (within 1 year of hydroxychloroquine use) and monitoring examinations (after 5 years of hydroxychloroquine use). Demographic and clinical factors, including hospitals and medical specialties prescribing hydroxychloroquine, indications for hydroxychloroquine use, and prescription details, were compared between groups. Significant differences were found in sex, residence, departments and hospitals (primary vs. referral centers) where hydroxychloroquine was prescribed, diagnosis for hydroxychloroquine therapy, and mean daily dose between patients who did and did not undergo baseline or monitoring examinations (all P < 0.01). Patients who received hydroxychloroquine prescriptions from referral hospitals were more likely to undergo baseline and monitoring examinations compared to those from primary clinics (both P < 0.001). Additionally, patients who received hydroxychloroquine prescriptions from the rheumatology department and had systemic lupus erythematosus were more likely to undergo baseline and monitoring examinations compared to other patients (all P < 0.001). There were notable differences in the number of modalities used for retinopathy screening between primary and referral centers (P < 0.001). Our findings suggest that several clinical factors related to hydroxychloroquine prescription and screening centers are associated with retinopathy screening practices.

Wide-field optical coherence tomography deviation map for early glaucoma detection.

BACKGROUND/AIMS: This study aimed to establish a wide-field optical coherence tomography (OCT) deviation map obtained from swept-source OCT (SS-OCT) scans. Moreover, it also aimed to compare the diagnostic ability of this wide-field deviation map with that of the peripapillary and macular deviation maps currently being used for the detection of early glaucoma (EG). METHODS: Four hundred eyes, including 200 healthy eyes and 200 eyes with EG were enrolled in this retrospective observational study. Patients underwent a comprehensive ocular examination, including wide-field SS-OCT (DRI-OCT Triton; Topcon, Tokyo, Japan). The individual wide-field scan was converted into a uniform template using the fovea and optic disc centres as fixed landmarks. Subsequently, the wide-field deviation map was obtained via the comparison between individual wide-field data and a normative wide-field database that had been created by combining images of healthy eyes into a uniform template in a previous study. The ability of the new wide-field deviation map to distinguish between EG and healthy eyes was assessed by comparing it with conventional deviation maps based on the area under the receiver operating characteristic curve (AUC). RESULTS: The wide-field deviation map obtained using the normative wide-field database showed the highest diagnostic ability for the diagnosis of EG (AUC=0.980 and 961 for colour-coded pixels presenting <5% and <1%, respectively) among various deviation maps. Its AUC was significantly superior to that of most conventional deviation maps (p<0.05). The wide-field deviation map demonstrated early structural glaucomatous damage well over a wider area. CONCLUSION: The wide-field SS-OCT deviation map exhibited good performance for distinguishing between eyes with EG and healthy eyes. The visualisation of the wider damaged area on the wide-field deviation map could be useful for the diagnosis of EG in clinical settings.

Deep Learning-based Diagnosis of Glaucoma Using Wide-field Optical Coherence Tomography Images.

PURPOSE: (1) To evaluate the performance of deep learning (DL) classifier in detecting glaucoma, based on wide-field swept-source optical coherence tomography (SS-OCT) images. (2) To assess the performance of DL-based fusion methods in diagnosing glaucoma using a variety of wide-field SS-OCT images and compare their diagnostic abilities with that of conventional parameter-based methods. METHODS: Overall, 675 eyes, including 258 healthy eyes and 417 eyes with glaucoma were enrolled in this retrospective observational study. Each single-page wide-field report (12×9 mm) of wide-field SS-OCT imaging provides different types of images that reflect the state of the eyes. A DL-based automated diagnosis system was proposed to detect glaucoma and identify its stage based on such images. We applied the convolutional neural network to each type of image to detect glaucoma. In addition, 2 fusion strategies, fusion by convolution network (FCN) and fusion by fully connected network (FFC) were developed; they differ in terms of the level of fusion of features derived from convolutional neural networks. The diagnostic models were trained using 382 and 293 images in the training and test data sets, respectively. The diagnostic ability of this method was compared with conventional parameters of the thickness of the retinal nerve fiber layer and ganglion cell complex. RESULTS: FCN achieved an area under the receiver operating characteristic curve (AUC) of 0.987 (95% confidence interval, CI: 0.968-0.996) and an accuracy of 95.22%. In contrast, FFC achieved an AUC of 0.987 (95% CI, 0.971-0.998) and an accuracy of 95.90%. Both FCN and FFC outperformed the conventional method (P<0.001). In detecting early glaucoma, both FCN and FFC achieved significantly higher AUC and accuracy than the conventional approach (P<0.001). In addition, the classification performance of the DL-based fusion methods in identifying the 5 stages of glaucoma is presented via a confusion matrix. CONCLUSION: DL protocol based on wide-field OCT images outperformed the conventional method in terms of both AUC and accuracy. Therefore, DL-based diagnostic methods using wide-field OCT images are promising in diagnosing glaucoma in clinical practice.