[Preliminary study on automatic quantification and grading of leopard spots fundus based on deep learning technology]

Objective: To achieve automatic segmentation, quantification, and grading of different regions of leopard spots fundus (FT) using deep learning technology. The analysis includes exploring the correlation between novel quantitative indicators, leopard spot fundus grades, and various systemic and ocular parameters. Methods: This was a cross-sectional study. The data were sourced from the Beijing Eye Study, a population-based longitudinal study. In 2001, a group of individuals aged 40 and above were surveyed in five urban communities in Haidian District and three rural communities in Daxing District of Beijing. A follow-up was conducted in 2011. This study included individuals aged 50 and above who participated in the second 5-year follow-up in 2011, considering only the data from the right eye. Color fundus images centered on the macula of the right eye were input into the leopard spot segmentation model and macular detection network. Using the macular center as the origin, with inner circle diameters of 1 mm, 3 mm, and outer circle diameter of 6 mm, fine segmentation of the fundus was achieved. This allowed the calculation of the leopard spot density (FTD) and leopard spot grade for each region. Further analyses of the differences in ocular and systemic parameters among different regions' FTD and leopard spot grades were conducted. The participants were categorized into three refractive types based on equivalent spherical power (SE): myopia (SE<-0.25 D), emmetropia (-0.25 D≤SE≤0.25 D), and hyperopia (SE>0.25 D). Based on axial length, the participants were divided into groups with axial length<24 mm, 24-26 mm, and>26 mm for the analysis of different types of FTD. Statistical analyses were performed using one-way analysis of variance, Kruskal-Wallis test, Bonferroni test, and Spearman correlation analysis. Results: The study included 3 369 participants (3 369 eyes) with an average age of (63.9±10.6) years; among them, 1 886 were female (56.0%) and 1, 483 were male (64.0%). The overall FTD for all eyes was 0.060 (0.016, 0.163); inner circle FTD was 0.000 (0.000, 0.025); middle circle FTD was 0.030 (0.000, 0.130); outer circle FTD was 0.055 (0.009, 0.171). The results of the univariate analysis indicated that FTD in various regions was correlated with axial length (overall: r=0.38, P<0.001; inner circle: r=0.31, P<0.001; middle circle: r=0.36, P<0.001; outer circle: r=0.39, P<0.001), subfoveal choroidal thickness (SFCT) (overall: r=-0.69, P<0.001; inner circle: r=-0.57, P<0.001; middle circle: r=-0.68, P<0.001; outer circle: r=-0.72, P<0.001), age (overall: r=0.34, P<0.001; inner circle: r=0.30, P<0.001; middle circle: r=0.31, P<0.001; outer circle: r=0.35, P<0.001), gender (overall: r=-0.11, P<0.001; inner circle: r=-0.04, P<0.001; middle circle: r=-0.07, P<0.001; outer circle: r=-0.11, P<0.001), SE (overall: r=-0.20; P<0.001; inner circle: r=-0.19, P<0.001; middle circle: r=-0.20, P<0.001; outer circle: r=-0.20, P<0.001), uncorrected visual acuity (overall: r=-0.18, P<0.001; inner circle: r=-0.26, P<0.001; middle circle: r=-0.24, P<0.001; outer circle: r=-0.22, P<0.001), and body mass index (BMI) (overall: r=-0.11, P<0.001; inner circle: r=-0.13, P<0.001; middle circle: r=-0.14, P<0.001; outer circle: r=-0.13, P<0.001). Further multivariate analysis results indicated that different region FTD was correlated with axial length (overall: β=0.020, P<0.001; inner circle: β=-0.022, P<0.001; middle circle: β=0.027, P<0.001; outer circle: β=0.022, P<0.001), SFCT (overall: β=-0.001, P<0.001; inner circle: β=-0.001, P<0.001; middle circle: β=-0.001, P<0.001; outer circle: β=-0.001, P<0.001), and age (overall: β=0.002, P<0.001; inner circle: β=0.001, P<0.001; middle circle: β=0.002, P<0.001; outer circle: β=0.002, P<0.001). The distribution of overall (H=56.76, P<0.001), inner circle (H=72.22, P<0.001), middle circle (H=75.83, P<0.001), and outer circle (H=70.34, P<0.001) FTD differed significantly among different refractive types. The distribution of overall (H=373.15, P<0.001), inner circle (H=367.67, P<0.001), middle circle (H=389.14, P<0.001), and outer circle (H=386.89, P<0.001) FTD differed significantly among different axial length groups. Furthermore, comparing various levels of FTD with systemic and ocular parameters, significant differences were found in axial length (F=142.85, P<0.001) and SFCT (F=530.46, P<0.001). Conclusions: The use of deep learning technology enables automatic segmentation and quantification of different regions of theFT, as well as preliminary grading. Different region FTD is significantly correlated with axial length, SFCT, and age. Individuals with older age, myopia, and longer axial length tend to have higher FTD and more advanced FT grades.

Lens-induced myopization and body weight in young guinea pigs

BACKGROUND

To investigate the relationship between body weight and Axial length in guinea pigs.

METHODS

Forty pigmented guinea pigs were randomly divided into two groups, namely control group and negative lens-induced myopization (LIM) group. After measuring the baseline axial length and body weight (BW), guinea pigs of LIM group received bilateral negative lens-induced myopization using - 10.0 diopters lenses. One week later, the lenses were removed and biometric and ophthalmoscopic examinations were repeated.

RESULTS

Two groups of guinea pigs showed no statistical difference in initial body weight and eye axis length. Compared to the control group, the lens-induced group had a lower weight (P = 0.02) and a longer axial length (P < 0.01) at the end of study Neither at baseline nor at week 1 did AL correlate with BW in both groups (Control Baseline: r = 0.306, P = 0.19; Control Week1: r = 0.333, P = 0.15; LIM Baseline: r=-0.142, P = 0.55; LIM Week 1: r = 0.189, P = 0.42). Lens-induction had a significant effect on axial elongation (P < 0.01) while body weight had no impact on such aspect (P > 0.05).

CONCLUSION

In guinea pigs of the same age, axial length was not correlated with body weight. Also, baseline body weight had no impact on natural axial length growth or lens-induced myopia. Lens-induction caused a significant reduction in body weight gain.

Comparative Study of Ultrasonography and Ultra-Widefield Fundus Photographs for Measurements of the Diameter of Choroidal and Retinal Tumors

INTRODUCTION

Measurement of the largest basal dimension (LBD) of intraocular tumors is important as a prognostic parameter. To evaluate the potential value of true color ultra-widefield fundus photography for measuring tumors, we compared LBD measurements of choroidal and retinal tumors using a color ultra-widefield fundus camera with clinical estimation based on indirect ophthalmoscopy and standardized ophthalmic ultrasound.

METHODS

The LBD of 148 choroidal and retinal tumors in 148 patients seen at Tongren Hospital were measured using ultra-widefield fundus photography and compared with measurements obtained using B-scan ultrasonography and clinical estimates based on indirect ophthalmoscopy.

RESULTS

Paired t-tests and Bland-Altman plots reveal that measurements from ultra-widefield fundus photographic images are not statistically different from clinical estimates and ultrasound measurements. The results also showed that, although not statistically significant, when the tumor boundary was clear, the height was < 3 mm, or the tumor was pigmented, measurement from ultra-widefield fundus photography tended to be greater than those obtained by ultrasound.

CONCLUSIONS

The LBD measurement using ultra-widefield fundus photography correlated well with ultrasonography and clinical estimation and could be used as a reliable tool for measuring the LBD of choroidal and retinal tumors.

[Analysis of the correlation between peripapillary retinal nerve fiber layer cross-sectional area and myopia in individuals aged 50 years and above]

Objective: To measure the peripapillary retinal nerve fiber layer (RNFL) cross-sectional area in individuals aged 50 years and above with different refractive errors, and analyze its correlation with axial length and refractive error. Methods: This was a cross-sectional study conducted as part of the "Beijing Eye Study". The study was population-based and longitudinally designed. In 2001, a cohort of individuals aged 40 years and above from five urban communities in Haidian District and three rural communities in Daxing District, Beijing, were surveyed. Follow-up examinations were conducted in 2011. In this study, the follow-up data from 2011 were collected and analyzed. One eye of each participant was randomly selected, and the participants were categorized into four groups based on their spherical equivalent: emmetropia group (-0.50 D≤spherical equivalent≤0.50 D), low myopia group (-3.00 D≤spherical equivalent<-0.50 D), moderate myopia group (-6.00 D≤spherical equivalent<-3.00 D), and high myopia group (spherical equivalent<-6.00 D). Spectral-domain optical coherence tomography (OCT) was used to perform circular scans with a diameter of 12° centered on the optic disc. ImageJ software and Heidelberg Eye Explorer software were used to calculate the RNFL cross-sectional area. One-way analysis of variance was used to compare the differences in RNFL thickness and RNFL cross-sectional area among different groups. Linear regression analysis was performed to analyze the correlation between RNFL thickness and axial length and spherical equivalent, as well as the correlation between RNFL cross-sectional area and axial length and spherical equivalent. Results: A total of 184 participants (184 eyes) were included in the study, including 88 males and 96 females. The median age was 59 (54, 66) years, with 87 right eyes and 97 left eyes. There were 50 participants (50 eyes) in the emmetropia group, low myopia group, and moderate myopia group, and 34 participants (34 eyes) in the high myopia group. There were no significant differences in age, gender, and eye laterality among the groups (all P>0.05). The RNFL cross-sectional areas in the emmetropia, low myopia, moderate myopia, and high myopia groups were (1.115±0.106), (1.122±0.136), (1.105±0.105), and (1.096±0.106) mm², respectively, with no significant differences observed (F=0.43, P=0.730). The RNFL thickness in the emmetropia, low myopia, moderate myopia, and high myopia groups were (102.5±9.5), (102.5±12.1), (94.2±8.3), and (90.2±8.9) μm, respectively, with a significant difference observed (F=16.42, P<0.001). Univariate linear regression analysis was performed with spherical equivalent as the independent variable and peripapillary RNFL thickness as the dependent variable, yielding the regression equation: peripapillary RNFL thickness=102.651+1.634 × spherical equivalent (R²=0.21, P<0.001). Similarly, when axial length was used as the independent variable and peripapillary RNFL thickness as the dependent variable, the regression equation was: peripapillary RNFL thickness=174.161-3.147 × axial length (R²=0.18, P<0.001). There was no significant correlation between RNFL cross-sectional area and spherical equivalent (P=0.065) or axial length (P=0.846). Conclusions: There were no significant differences in peripapillary RNFL cross-sectional area among individuals aged 50 years and above with different axial lengths or refractive errors.