Advances in mechanism and regulatory factors of corneal stromal repair / 国际眼科杂志(Guoji Yanke Zazhi)

Corneal stromal is an important structure to maintain corneal transparency. The corneal stroma can be injured by trauma, infection and surgery. Therefore, corneal stromal wound starts repair with phenotype changes in stromal cell, extracellular matrix remodeling and immune cells migration. The corneal scar was the leading cause of blindness worldwide, which can be caused by corneal stromal fibrosis from increased myofibroblasts and deposited extracellular matrix after sever damage. At present, corneal transplantation is the main treatment for corneal scar, which has limited therapeutic effect because of corneal donor shortage, surgical requirements and the risk of postoperative immune rejection. Recently, great progress has been made in the study of control mechanism of corneal stromal wound healing with various molecules, cells and tissues. This paper reviews the repair mechanism of corneal stromal injury and the regulation mechanism of cause of corneal injury, corneal structure and molecule factors towards corneal stromal injury. It aims at providing new ideas for exploring the mechanism of corneal stromal repair and regeneration, which is supposed to help prevent corneal scar clinically.

Automatic evaluation system for ultrasound biomicroscopy images of anterior chamber angle based on deep learning algorithm / 国际眼科杂志(Guoji Yanke Zazhi)

AIM: To explore the clinical application value of analysis system for ultrasound biomicroscopy(UBM)images of anterior chamber angle(ACA)based on deep learning algorithm.METHODS: A total of 4 196 UBM images were obtained from 675 patients(1 130 eyes)at the Eye Center of Renmin Hospital of Wuhan University from January 2021 to June 2022 were collected to build an image dataset. Using Unet++network to automatically segment ACA tissue, a support vector machine(SVM)algorithm was developed to automatically classify opening and closing of chamber angle, and an algorithm to automatically locate the sclera spur and measure ACA parameters was developed. Furthermore, a total of 631 UBM images of 127 subjects(221 eyes)at Huangshi Aier Eye Hospital and 594 UBM images of 188 subjects(257 eyes)at Zhongnan Hospital of Wuhan University were selected to evaluate the performance of the system under different environments.RESULTS: The accuracy of the analysis system constructed in this study for chamber angle opening and closing was 95.71%. The intra-class correlation coefficient(ICC)values of all ACA angle parameters were greater than 0.960. ICC values of all ACA thickness parameters were greater than 0.884. The accurate measurement of ACA parameters depended in part on the accurate location of the scleral spur.CONCLUSION: The intelligent analysis system constructed in this study can accurately and effectively evaluate ACA images automatically and is a potential screening tool for the rapid identification of ACA structures.