A Three-Dimensional-reconstruction-based study on the ocular volume of Chinese children with high myopia.

BACKGROUND: Highly myopic eyes differ in morphology from emmetropic eyes, and the correct estimation of the vitreous volume is difficult. To explore an effective method to estimate ocular volume using refractive factors in children. METHODS: This is a retrospective study of children with high myopia who visited the Shenzhen Shekou People's Hospital (July-December 2018) before undergoing posterior scleral reinforcement surgery. Data on refractive factors and ocular 3D reconstruction imaging based on high-end CT were collected for linear correlation and linear regression analyses. RESULTS: Ten patients (20 eyes) were included. There are nine males and one female. They were 4 to 12 years of age. The spherical equivalent ranges from + 0.25 to -20.00 D. The cylindrical equivalent ranges from - 0.50 to -6.25 D. The AL(axial length, AL) ranges from 21.78 to 33.90 mm. The corneal curvature (mean) ranges from 42.44 to 46.75. The 3D reconstruction of the CT images shows that the ocular volume ranges from 4.591 to 10.988 ml. The ocular volume of the 20 eyes decreases with the increase of diopter and total curvature, both presenting a linear trend, with the Pearson correlation coefficients being - 0.776 (P < 0.001) and - 0.633 (P = 0.003), respectively. The ocular volume of the 20 eyes increases with the increasing AL, also presenting a linear trend, with the Pearson correlation coefficient being 0.939 (P < 0.001). CONCLUSIONS: In children, the ocular volume is negatively and linearly correlated with the diopter and curvature, and positively and linearly correlated with the AL.

Longitudinal Choriocapillaris Vascular Density Changes in Different Types of Primary Open-Angle Glaucoma.

Purpose: To evaluate longitudinal changes in choriocapillaris perfusion in patients with glaucoma with four phenotypes of optic disc damage and to explore associated factors with decreased choriocapillaris vessel density (CVD). Methods: This prospective longitudinal study included 96 eyes of 96 patients with primary open-angle glaucoma (POAG). Patients with POAG was differentiated into the optic disc phenotypes of focal ischemic type (FI), myopic type (MY), senile sclerotic type (SS), and generalized enlargement type (GE). Patients were followed up every three months. Simple linear regression was used to investigate the factors associated with a reduction in CVD. Results: The median follow-up time was 2.5 years (range, 2.0-3.0 years). Choriocapillaris perfusion tended to decrease over time, with CVD decreasing significantly faster in the FI type than in the other three types (P < 0.001). The percentage decrease in the FI type was 7.85%, 10.89%, and 8.88% faster than MY, SS and GE, respectively, after correcting for age, gender, axial length, intraocular pressure, mean deviation, retinal nerve fiber layer (RNFL), and image quality score. In multivariate regression, decreased CVD was independently associated with the rate of RNFL thinning. Conclusions: FI type had the fastest rate of CVD decline in the four phenotypes of optic disc damage, and decreased CVD was positively correlated with the rate of RNFL thinning. Translational Relevance: The role of the choriocapillaris in the pathogenesis and therapeutic potential of glaucoma require further attention to facilitate better management of glaucoma patients.

Assessment of Artifacts in Swept-Source Optical Coherence Tomography Angiography for Glaucomatous and Normal Eyes.

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.

A deep-learning system predicts glaucoma incidence and progression using retinal photographs.

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.

Longitudinal Macular Retinal and Choroidal Microvasculature Changes in High Myopia.

Purpose: The purpose of this study was to determine the longitudinal changes in macular retinal and choroidal microvasculature in normal healthy and highly myopic eyes. Methods: Seventy-one eyes, including 32 eyes with high myopia and 39 healthy control eyes, followed for at least 12 months and examined using optical coherence tomography angiography imaging in at least 3 visits, were included in this study. Fovea-centered 6 × 6 mm scans were performed to measure capillary density (CD) of the superficial capillary plexus (SCP), deep capillary plexus (DCP), and choriocapillaris (CC). The rates of CD changes in both groups were estimated using a linear mixed model. Results: Over a mean 14-month follow-up period, highly myopic eyes exhibited a faster rate of whole image CD (wiCD) loss (-1.44%/year vs. -0.11%/year, P = 0.001) and CD loss in the outer ring of the DCP (-1.67%/year vs. -0.14%/year, P < 0.001) than healthy eyes. In multivariate regression analysis, baseline axial length (AL) was negatively correlated with the rate of wiCD loss (estimate = -0.27, 95% confidence interval [CI] = -0.48 to -0.06, P = 0.012) and CD loss in the outer ring (estimate = -0.33, 95% CI = -0.56 to -0.11, P = 0.005), of the DCP. The CD reduction rates in the SCP and CC were comparable in both groups (all P values > 0.05). Conclusions: The rate of CD loss in the DCP is significantly faster in highly myopic eyes than in healthy eyes and is related to baseline AL. The CD in the outer ring reduces faster in eyes with longer baseline AL.