Background: Previous studies have proposed an automated customized program named MATLAB used in the foveal avascular zone (FAZ) measurements in Triton optical coherence tomography angiography (OCTA) images. But it is not open-source and not easy to obtain, which will largely restrict its application in clinical practice and medical research. In this study, we aimed to investigate the feasibility of the Smooth Level Sets macro (SLSM), a free and open-source program, and compared with the manual measurements and MATLAB in the FAZ quantification in Triton OCTA. Methods: Thirty-five eyes of 35 healthy subjects were scanned four times continuously using Triton OCTA. Manual and automated methods including the SLSM and MATLAB were used in the FAZ metrics (area, perimeter, and circularity) of the superficial capillary plexus. The accuracy, repeatability of all methods, and agreement between automated and manual methods were analyzed. Results: The SLSM presented higher accuracy with a higher average Dice coefficient (0.9506) than MATLAB (0.9483), which was just second to the manual method (0.9568). Both the SLSM [intraclass correlation coefficient (ICC) =0.987; coefficient of variation (CoV) =3.935%] and MATLAB (ICC =0.983; CoV =4.165%) showed excellent repeatability for the FAZ area. They also had excellent agreement with manual measurement (SLSM, ICC =0.973; MATLAB, ICC =0.968). Conclusion: The SLSM exhibits better accuracy than MATLAB in the automated FAZ measurement in Triton OCTA, the results of which were comparable to those obtained by manual measurement. This free and open-source program may be an accessible and feasible option for automated FAZ segmentation on Triton OCTA images.

With the rapid development of artificial intelligence (AI) technology, the application of AI technology based on deep learning (DL) and machine learning (ML) in the medical field has received widespread attention. The application of AI in ophthalmology is gradually being shifted to a more comprehensive and in-depth level. Trained on corneal tomography, optical coherence tomography (OCT), slit-lamp images, and other techniques. AI can achieve robust performance in the diagnosis and treatment of corneal lesions, conjunctival lesions, cataract, glaucoma and other ophthalmic diseases. However, there are also some challenges in the application of AI in ophthalmology, including the lack of interpretability of results, lack of standardization of data sets, uneven quality of data sets, insufficient applicability of models and ethical issues. In the era of 5G and telemedicine, there are also many new opportunities for ophthalmic AI. In this review, we provided a summary of the state-of-the-art AI application in anterior segment ophthalmic diseases, potential challenges in clinical implementation and its development prospects, and provides reference information for the further development of artificial intelligence in the field of ophthalmology.

Optic nerves are a part of the central nervous system, which is difficult to regenerate after injury. Optic nerve injury is usually accompanied by continuous apoptosis of retinal ganglion cells (RGCs) and degeneration or necrosis of optic nerves, resulting in visual impairment or even complete blindness. At present, the basic research on optic nerve regeneration mainly focuses on protecting and maintaining the survival of RGCs after optic nerve injury, promoting RGCs axon regeneration, and reconstructing optic nerve function. In this paper, RGCs protection,axon regeneration, and optic nerve function reconstruction are used as key words to collect the latest domestic and foreign literatures on optic nerve regeneration. The research progress of optic nerve regeneration in recent years was reviewed from the aspects of antioxidant stress, provision of exogenous cytokines, inflammatory stimulation, anti-glial scar, gene regulation and so on, in order to help the follow-up basic research and clinical translation.

Artificial intelligence (AI) has been widely used in cataract surgery. The combination of the two can play a great role in improving preoperative diagnosis, grading management of cataract surgery, intraoperative intraocular lens selection and location prediction, postoperative management (vision prediction, complication prediction and follow-up), surgical training and teaching. It is true that AI still faces many problems in the management, analysis and research related to cataract surgery, but its broad application prospects cannot be ignored. This review summarizes the application of AI in cataract surgery and teaching, and the future prospects of AI.

Objective: To elucidate the expression of long non-coding RNAs (lncRNAs) and their roles as competing endogenous RNAs (ceRNAs) in uveal melanoma (UM) metastasis. Methods: RNA sequencing data and clinical information of 80 patients with UM were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed (DE) mRNAs, microRNAs (miR), and lncRNAs between metastatic and non-metastatic individuals with UM were screened using the edgeR algorithm. Gene enrichment analysis was conducted for the DE mRNAs. LncRNA-miR-mRNA regulatory triples and a ceRNA network were constructed. Betweenness centrality was used to screen hub genes and lncRNAs for subnetwork analysis. Kaplan-Meier survival analysis was conducted to explore correlations between the expression of hub RNAs and overall survival in the TCGA UM cohort. Results: A total of 346 upregulated mRNAs, 118 downregulated miRs, and 45 upregulated lncRNAs were identified in samples with systemic metastasis. Among them, 67 mRNAs, 7 miRs, and 30 lncRNAs mapped to 616 ceRNA triples, thus forming an interconnected ceRNA network with 181 edges. Gene enrichment analysis revealed that mRNAs in the network were enriched in multiple gene ontology terms and pathways associated with carcinogenesis and metastasis. Topological analysis identified 6 hub lncRNAs (LINC00861, LINC02421, BHLHE40-AS1, LINC01252, LINC00513, and LINC02389) and 3 hub mRNAs (UNC5D, BCL11B, and MTDH). The expression levels of all hub genes and 5 DEmiRs (miR-221, miR-222, miR-506, miR-507, miR-876) were significantly associated with the overall survival probability. Conclusion: This bioinformatic study revealed the functions of several lncRNAs and their associated ceRNA network in UM metastasis. It provides a novel in silicon evidence for future experimental study on the pathogenesis of systemic metastasis in uveal melanoma, especially from the perspective of non-coding RNA.

Objective: To investigate the predictive accuracy and effect of capsular tension ring (CTR) implantation with five new generation intraocular lens (IOL) calculation formulas [Barrett Universal Ⅱ (BU Ⅱ), Emmetropia Verifying Optical(EVO), Kane, Pearl-DGS and Hill-RBF 2.0] in high myopia patients. Methods: This is a prospective case-control study. The patients were enrolled with an axial length (AL)≥27.00 mm, and underwent cataract surgery with AR40E IOL implantation at the Shaanxi Eye Hospital from December 2020 to September 2021. The patients were randomly assigned to the CTR implantation group (group A) and the non-CTR implantation group (group B). With the ocular parameters measured by the IOLMaster700, the IOL power was calculated with the BUⅡformula before surgery. The postoperative actual equivalent spherical diopter (SE) were recorded,and the predicted error (PE) and absolute error (AE) using the five formulas were recorded and compared at 1 week, 1 month, and 3 months, repsectively. Group A was divided to A1 (27.00 mm ≤ AL ≤ 30.00 mm) and A2 (AL>30.00 mm), and group B was divided to B1 (27.00 mm ≤ AL ≤ 30.00 mm) and B2 (AL>30.00 mm). The effects of CTR implantation and the accuracy of the formulas were analyzed with different AL ranges. Results: A total of 63 patients (89 eyes) were included, aged (55.93±10.17) years old, with preoperative AL (30.30± 2.18)mm. There was no statistically significant difference in SE between groups A, A1, and A2 (P>0.05) at different postoperative times. While there was a statistically significant difference in SE between groups B, B1, and B2 (P < 0.05) at 1 week and 1 month after surgery, and between 1 week and 3 months after surgery. There was no statistically significant difference between 1 month and 3 months after suergery (P>0.05). There was no significant difference in the AE using the five formulas among groups A, B, A1, A2, B1, and B2 (P>0.05). There was no statistically significant difference in prediction error changes among the five formulas after CTR implantation (P>0.05). Conclusion: For cataract patients with AL ≥ 27.00 mm, the refractionvalue in the CTR implantation group tended to stabilizeafter one week of surgery. While in the non-CTR implantation group, the refractionvalue tended to stabilize after one month. CTR implantation had no effect on the accuracy and selection of the five formula, and the five IOL calculation formulas can be normally selected.

In recent years, artificial intelligence (AI) in ophthalmology has developed rapidly. Fundus image has become a research hotspot due to its easy access and rich biological information. The application of AI analysis in fundus image is under continuous development and exploration. At present, there have been many AI studies on clinical screening, diagnosis and prediction of common fundus diseases such as diabetic retinopathy (DR), age-related macular degeneration (AMD), and glaucoma, and related achievements have been gradually applied in clinical practice. In addition to ophthalmic diseases, exploring the relationship between fundus features and various diseases and developing AI diagnostic systems based on this has become another popular research field. The application of AI in fundus image analysis will improve the shortage of medical resources and low diagnostic efficiency, and open up a “new track” for screening and diagnosis of various diseases. In the future, research on AI analysis of fundus image should focus on the intelligent and comprehensive diagnosis of multiple fundus diseases, and comprehensive auxiliary diagnosis of complex diseases, and lays emphasis on the integration of standardized and high-quality data resources, improve algorithm performance, and design clinically appropriate research program.

Objective: To compare the effective optical zone (EOZ) and the changes in corneal high order aberrations (HOAs) after small incision lenticule extraction (SMILE) with those after femtosecond laser-assisted in situ keratomileuses (FS-LASIK). Methods: This study included 80 subjects who underwent laser refractive surgery at the Second People’s Hospital of Foshan between February 2019 and May 2020. Only data from the right eye of each subject were analyzed. A total of 43 eyes underwent SMILE while 37 eyes received FS-LASIK. The eyes were further stratified into subgroups based on different programmed optical zones: the 6.5 mm group and the 6.0 mm group. EOZ, coma, and spherical aberration were measured with Pentacam 3D anterior segment analysis system preoperatively and one month postoperatively. In addition, the relationship between EOZ and corneal HOAs was analyzed and compared between different optical-zone groups after SMILE and FS-LASIK. Results: For the same programmed optical zone, the SMILE group achieved a significantly greater EOZ than the FS-LASIK group who was measured 1-month postoperatively did (P<0.05). Meanwhile, corneal HOAs, spherical aberration, and coma in the SMILE group are significantly lower than those in the FS-LASIK group (P<0.05). For the same procedure (SMILE or FS-LASIK), the 6.0 mm group demonstrated significantly higher corneal total HOAs, spherical aberration, and coma than the 6.5 mm group did 1-month after the surgery (P<0.05). Conclusion: In both the SMILE and the FS-LASIK groups, 1-month postoperative EOZ was smaller than the programmed optical zone. EOZ in the SMILE group was larger than that in the FS-LASIK group. The larger the 1-month postoperative EOZ was, the lower corneal HOAs were. For the same programmed optical zone, 1-month postoperative corneal HOAs in the SMILE group is lower than that in the FS-LASIK group.

Objective: To analyze risk factors for endophthalmitis occurred after 23G/25G minimally invasive vitrectomy. Methods: Retrospective analysis of the clinical characteristics of patients with endophthalmitis (except patients with open eye trauma) after minimally invasive vitrectomy in General Hospital of Central Theater Command(Wuhan,430064) from June 2014 to May 2023. Results: This study included 8,955 patients, of which 11 cases occurred endophthalmitis after minimally invasive vitrectomy, with an incidence rate of 0.12%. The average age was (60.8±7.6) years, and 5 patients (45.4%) were complicated with diabetes; The composition of primary eye diseases: 7 cases (63.6%) of macular disease, 2 cases (18.2%) of vitreous hemorrhage secondary to proliferative diabetic retinopathy and 1 case (9.1%) vitreous hemorrhage secondary to retinal fissure, 1 case (9.1%) of retinal detachment; During the operation, 3 cases (27.3%) underwent combined cataract surgery; After the operation, 8 cases (72.7%) were filled with sterile air in the vitreous cavity of affected eye, the other 3 cases (27.3%) were filled with equilibrium liquid,and sclera puncture incision was not sutured in all patients; 3 cases (27.3%) had low intraocular pressure after operation. The time for postoperative endophthalmitis to occur after operation was 2.8±1.1day. 11 patients had poor inflammation control after local and systemic anti-inflammatory treatments, and all underwent vitrectomy combined with intraoperative injection of vancomycin solution. Among them, 9 patients were filled with silicone oil in the vitreous cavity after the surgery. After the operation, all the endophthalmitis were controlled and final corrected visual acuity of 10 patients improved. Conclusions: Minimally invasive vitrectomy and suture-free scleral incision may be a potential way for pathogenic microorganisms to invade the eye and cause endophthalmitis. Particular attention should be paid to the ‘Vitreous Wick Syndrome’ at the scleral incision caused by incomplete vitrectomy in macular surgery, which may be one of the risk factors for postoperative endophthalmitis.

Objective: To investigate the long-term effect of orthokeratology on the choroidal thickness and choroidal contour in myopic children. Methods:Subjects were from a conducted 2-year Randomized Clinical Trial. Children (n=80) aged 8-12 years with spherical equivalent refraction of -1.00 to -6.00 D were randomly assigned to the control group (n=40) and ortho-k group (n=40). OCT images were collected at the baseline, 1-, 6-, 12-, 18-, and 24-month visits, then the choroidal thickness and choroid contour were calculated. Axial length (AL) and other ocular biometrics were also measured. Results: During two years, in the control group, the choroidal thickness became thinning and the choroidal contour became prolate with time at all visits (all P<0.001). Ortho-k can improve the choroidal thickness (all P<0.001) and maintain the choroidal contour at all visits (all P<0.05). In the ortho-k group, the choroidal contour was less changed in the temporal than nasal (P=0.008), and the choroidal thickness was more thickening in the temporal 3 mm (P<0.001). Two-year change in choroidal thickness was significantly associated with the two-year AL change in the control group (r=-0.52, P<0.001), however, this trend was broken by ortho-k (r=-0.05, P=0.342). After being adjusted by other variables in the multivariable regression model, the effect of ortho-k on choroidal thickness was stable. Conclusions: In a short term, ortho-k can improve the choroidal thickness and maintain the choroidal contour, but this effect diminished in a long term. Further study with larger sample size and longer follow-up is warranted to refine this issue.