近年来，眼科人工智能(artificial intelligence，AI)迅猛发展，眼底影像因易获取及其丰富的生物信息成为研究热点，眼底影像的AI分析在眼底影像分析中的应用不断深入、拓展。目前，关于糖尿病性视网膜病变(diabetic retinopathy，DR)、年龄相关性黄斑变性(age-related macular degeneration，AMD)、青光眼等常见眼底疾病的临床筛查、诊断和预测已有较多AI研究，相关成果已逐步应用于临床实践。除眼科疾病以外，探究眼底特征与全身各种疾病之间的关系并据此研发AI诊断系统已经成为当下的又一热门研究领域。AI应用于眼底影像分析将改善医疗资源紧缺、诊断效率低下的情况，为多种疾病的筛查和诊断开辟“新赛道”。未来眼底影像AI分析的研究应着眼于多种眼底疾病的智能性、全面性诊断，对复杂性疾病进行综合性的辅助诊断；注重整合标准化、高质量的数据资源，提高算法性能、设计贴合临床的研究方案。

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.

作为一种新型无创且操作简单的主观检查手段，临界闪烁融合频率(critical flicker fusionfrequency,CFF)可动态反映人眼视功能变化情况。作为早期识别脱髓鞘病变和评估视功能恢复情况的敏感指标，上个世纪已被国外学者用于视网膜和视神经疾病研究中，包括氯喹中毒性视网膜病变、糖尿病视网膜病变、中心性浆液性视网膜病变、年龄相关的黄斑病变、乙胺丁醇中毒性视神经病变、视神经炎和非动脉炎性前部缺血性视神经病变。在视网膜和视神经疾病中，CFF均有不同程度下降，依据CFF改善程度以及主要损害的色光可能有助于视网膜和视神经疾病的鉴别，且CFF与其他视功能，视力、视野、视觉诱发电位的潜时具有较好的相关性。目前国内相关研究尚处于起步阶段，本文就CFF在视网膜和视神经疾病的应用情况做一总结。

As a new non-invasive and simple subjective examination method, critical flicker fusion frequency (CFF) can dynamically reflect the changes of visual function of human eyes. As a sensitive indicator for early identification of demyelinating diseases and assessment of visual function recovery, it has been used by foreign scholars in the last century in the field of retinal and optic nerve diseases, including chloroquine toxic retinopathy, diabetic retinopathy, central serous retinopathy, age-related macular degeneration, ethambutol-induced optic neuropathy, optic neuritis and non-arteritic anterior ischemic optic neuropathy. Though there was a different decrease of CFF in retina and optic nerve diseases, it may be helpful for the differentiation of retinal and optic nerve diseases according to the degree of CFF improvement and the main damaged color light. Moreover, CFF has a good correlation with other visual functions, visual acuity, visual field, and peak time of visual evoked potential. At present, and relevant domestic studies is still in its infancy. This article summarizes the application of CFF in retinal and optic nerve diseases.

光学相干断层成像(optical coherence tomography，OCT)自1991年发明以来，在生物成像尤其在眼科和心血流成像中起越来越重要的作用。OCT的发展经历了早期的时域系统及最新的频域系统。其中频域系统又分为谱域OCT(spectral domain OCT，SD-OCT)系统和扫频OCT(swept source OCT，SS-OCT)系统。随着眼科临床应用对系统速度、灵敏度及功能化要求的不断提升，眼科扫频OCT已经走向成熟并逐步商用化。本文将简介扫频OCT的原理，并归纳扫频OCT相对于时域和谱域OCT系统的优势，并展示其在眼科临床的应用。

Optical coherence tomography (OCT) has played an important role in biomedical imaging, especially in ocular and cardiovascular imaging. OCT technology has evolved to frequency domain technology from early time-domain technology due to the advantages of high sensitivity and high speed of frequency domain techniques. The swept source OCT is a type of frequency domain OCT. With the increasing requirements for system speed, sensitivity, and functionality in clinical application, swept source OCT is gradually becoming commercially available and widespread in clinical application. In this paper, the principle of swept source OCT was introduced, the advantages of swept source OCT over time domain and spectral domain OCT systems were summarized, and its clinical application in ophthalmology was demonstrated.

角膜移植手术是治疗角膜病变重要且有效的手段。但对眼表功能完全失代偿、多次角膜移植排斥等类型的患者，常规同种异体角膜移植手术成功率却非常低。对于这类患者，人工角膜植入术成为复明的新希望。随着人工角膜的设计和植入方式的不断改进，人工角膜的功效及优点已渐渐突显。目前，波士顿I型(领扣型)人工角膜在全球范围内应用最为广泛。现就波士顿I型人工角膜的基本特征、临床应用及未来发展等方面进行阐述。

The corneal transplantation is an effective option for visually impaired patients with keratopathy to restore vision function. However, the success rate of allograft keratoplasty is still very low for those patients with end-stage ocular surface or repeated corneal graft rejection. For those patients, artificial keratoplasty might be a promising alternative option. The efficacy and advantages of artificial keratoplasty have been gradually highlighted, after consistent improvement of the product design and implantation procedure. Nowadays, the Boston type I (collar button) corneal prosthesis is the most widely used product around the world. In this review, the history, indications, postoperative complications and future prospect of Boston type I corneal prosthesis will be summarized.

近年来随着医疗领域数字化、信息化建设的加速推进，人工智能的应用越来越广泛，在眼科医学方面尤为突出。婴幼儿处于视觉系统发育的关键时期，此时发生的眼病往往会造成不可逆的视功能损伤，带来沉重的家庭和社会负担。然而，由于婴幼儿群体的特殊性以及小儿眼科医生的短缺，开展大规模小儿眼病筛查工作十分困难。最新研究表明：人工智能在先天性白内障、先天性青光眼、斜视、早产儿视网膜病变以及视功能评估等领域已经得到相关应用，在多种婴幼儿眼病的早期筛查、诊断分期、治疗建议等方面都有令人瞩目的表现，有效解决了许多临床难点与痛点。但目前婴幼儿眼科人工智能仍然不如成年人眼科发展充分，亟须进一步的探索和研发。

In recent years, with the acceleration of digitalization and informatization in medical field, artificial intelligence (AI) is more and more widely applied, especially in ophthalmology. Infants are in the critical period of visual development, during which eye diseases can lead to irreversible visual impairment and bring heavy burden to family and society. Due to the particularity of infants and the shortage of pediatric ophthalmologists, it is challenging to carry out large-scale screening for eye diseases of infants. According to the latest studies, AI has been studied and applied in the fields of congenital cataract, congenital glaucoma, strabismus, amblyopia, retinopathy of prematurity, and evaluation of visual function, and it has achieved remarkable performance in the early screening, diagnosis stage and treatment suggestions, solving many clinical difficulties and pain points effectively. However, AI for infantile ophthalmology is not as developed as for adult ophthalmology, so it needs further exploration and development.

玻璃体替代物是玻璃体切割术后的必需品，用于填充玻璃体腔，恢复玻璃体的支撑视网膜、屈光和细胞屏障等功能。严重眼外伤及复杂视网膜脱离引起的视网膜/脉络膜脱离，如选用传统的玻璃体替代物(如硅油)填充，部分患者会出现硅油依赖眼或眼球萎缩，眼球难以保全。折叠式人工玻璃体球囊(foldable capsular vitreous body,FCVB)是我国独立研发的挽救眼球的人工玻璃体，属于国际首创，可以精细模拟自然玻璃体的结构，恢复玻璃体的部分功能。目前临床研究证实FCVB不仅可以有效避免硅油的并发症，还可以维持后房空间，缓慢恢复睫状体的功能，从而治疗硅油依赖眼，阻止眼球进一步萎缩。该文综述了FCVB的研究背景、结构特点、临床应用和拓展研究进展。

Vitreous substitutes are necessary after vitrectomy to fill the vitreous cavity and restore the vitreous to support retinal, refractive, and cellular barrier functions. Severe ocular trauma-induced retinal/choroidal detachment filled with traditional vitreous substitutes (e.g., silicone oil) can lead to silicone oil-dependent eyes and ocular atrophy in some patients, making it difficult to preserve the eye. Foldable capsular vitreous body (FCVB) is an artificial vitreous body independently developed in China to save the eye, which is the first of its kind in the world and can finely simulate the structure of natural vitreous body and restore some of the functions of vitreous body. It has been clinically proven that it can not only effectively avoid the complications of silicone oil, but also maintain the posterior chamber space and slowly restore the function of the ciliary body, thus treating silicone oil-dependent eyes and preventing further atrophy of the eye. This article reviews the research background, structural features, clinical applications and extended studies of FCVB.

目的：依托最新的第5代移动通信技术(5th generation wireless systems，5G)，构建基于眼底图片的5G医疗眼科远程诊断平台，促进医疗资源上下贯通，提升基层服务能力及医疗服务体系整体效能。方法：基于5G时代医院的信息化发展战略，在海南省卫生健康委员会的资助与指导下，中山大学中山眼科中心海南眼科医院与中国联通通信集团海南有限公司等进行跨行业、多学科的技术力量研究开发，构建5G条件下的平台建设模块和技术路线，确定远程眼科诊断流程，并在海南省内多地区应用。结果：远程诊断平台运行良好。2020年12月至2021年11月，本研究共在海南省17个地区的186个卫生院中开展，共收集1561例患者眼底病图片数据，筛查阳性例数为185例，检出眼底病总阳性率为11.9%。其中有42例需要转诊治疗，转诊率为23%；143例不需要转诊治疗，非转诊率为77%。在1561例眼底图像中，采集异常的眼底图像有490例。排除490例异常眼底图像后，辅助诊断系统与人工诊断结果有1 002张眼底图像诊断相同，69张眼底图像诊断不同，其辅助诊断系统准确率为93.3%。结论：5G移动通信与远程医学影像结合，运用互联网科技催生新型医疗生产力，提高卫生经济的质量和效率，是医疗领域探索5G应用场景的一项应用典范。

Objective: Relying on the latest 5th generation wireless systems (5G), a remote primary ophthalmology care diagnosis platform based on fundus images was constructed in order to promote the connectivity of medical resources and improve the primary health service capabilities and the overall effectiveness of the medical service system. Methods: Based on the 5G informatization development strategy of hospitals, and under the funding and guidance of the Hainan Provincial Health Commission, the Hainan Eye Hospital of Zhongshan Ophthalmic Center and China Unicom Communications Group Hainan Co., Ltd. conducted a cross-industry, multi-disciplinary technical research. To build platform construction modules and technical routes under 5G networks, present the remote ophthalmological diagnosis process, and apply it in many regions in Hainan Province. Results: The performance of the remote diagnosis platform is well. From December 2020 to November 2021, this study was carried out in 186 health centers in 17 regions of Hainan Province. A total of 1 561 patients with fundus disease image data were collected. The number of positive screening fundus disease cases was 185. The total positive rate was 11.9%. Among them, 42 cases required referral for treatment, with a referral rate of 23%, and 143 cases did not require referral for treatment, with a non-referral rate of 77%. Among 1 561 cases of fundus images, 490 fundus images were excluded due to abnormal quality. Compared the results of the diagnosis platform system with manual diagnosis, 1 002 fundus images were identical, and 69 fundus images were different in diagnosis. The accuracy of the auxiliary diagnosis system was 93.3%. Conclusions: The collaboration of 5G mobile communication and telemedicine imaging, combined with internet technology to promote new medical productivity, improve quality and efficiency of the health economy. This study is an application model for exploring 5G application scenarios in the medical field.

人工智能(artificial intelligence，AI)在眼科领域的应用不断深入、拓展，目前在糖尿病性视网膜病变、白内障、青光眼以及早产儿视网膜病变在内的多种常见眼病的诊疗中逐渐成为研究热点。AI使医疗资源短缺、诊断标准缺乏、诊疗技术水平低下的现状得到改善，为白内障的诊疗开辟了一条“新赛道”。本文旨在综述AI在白内障诊疗中的应用现状、进展及局限性，为AI在白内障领域的进一步开发、应用及推广提供更多信息。

Artificial intelligence (AI) has been widely applied and promoted in ophthalmology, and has gradually become a research hotspot in the diagnosis and treatment of many common ophthalmopathies, including diabetic retinopathy, cataract, glaucoma, and retinopathy of prematurity. AI improves the shortage of medical care, the lack of diagnostic criteria and the low level of diagnosis and treatment technology, and explores a “new race track” for cataract diagnosis and treatment. The purpose of this article is to review the application status, progress and limitations of AI in the diagnosis and treatment of cataract, aiming to provide more information for further development, application and promotion of AI in the field of cataract.

目的：探讨超声乳化晶状体吸除联合囊袋上经巩膜缝线固定人工晶状体(intraocular lens,IOL)植入术治疗球形晶状体(microspherophakia,MSP)的有效性和安全性。方法：采用回顾性分析，选取2019年1月至 2020年6月期间在复旦大学附属眼耳鼻喉科医院进行治疗的MSP患者37例(37眼)，随机分为两组，纳入行超声乳化晶状体吸除联合囊袋上巩膜缝线固定IOL植入术(supra-capsular and scleral-fixated intraocular lens implantation,SCSF-IOL)的MSP患者20例(20眼)和行超声乳化晶状体吸除联合改良型囊袋张力环植入术(transscleral-fixated modified capsular tension ring and in-the-bag intraocular lens implantation,MCTR-IOL)的MSP患者17例(17眼)，观察两组术后最佳矫正视力及并发症等情况。结果：两组术后最佳矫正视力比术前均有改善(P<0.001)，而组间比较差异无统计学意义(P=0.326)。两组的IOL倾斜度相当(P=0.216)。预防性Nd:YAG激光后囊膜切开术在SCSFIOL术后1周至1个月进行。在SCSF-IOL组，2眼(10.00%)需要重复激光治疗，1眼(5.00%)出现囊口偏心。后囊膜混浊是MCTR组最常见并发症(6眼,35.29%)。随访期间两组均未出现IOL脱位、继发性青光眼和视网膜脱离。结论：SCSF-IOL是治疗球形晶状体的简单易行的手术方式，疗效与MCTR-IOL相当。Nd:YAG激光后囊膜切开术是预防SCSF-IOL术后囊袋并发症的必要手段。

Objective: To investigate the efficacy and safety of phacoemulsification combined with supra-capsular and scleral-fixated intraocular lens (IOL) implantation in the treatment of microspherophakia (MSP). Methods: by retrospective analysis, 37 MSP patients (37 eyes) who were treated in our hospital from January 2019 to June 2020 were randomly divided into two groups, including 20 MSP patients (20 eyes) who treated by SCSF-IOL and 17 MSP patients (17 eyes) who treated by transscleral-fixated modified capsular tension ring and in-the-bag intraocular lens implantation (MCTR-IOL). The best corrected vision and complications were observed. Results: the best corrected vision was significantly improved in both groups (P < 0.001), but there was no remarkable difference between the two groups (P = 0.326). The IOL tilt was also comparable (P = 0.216). Prophylactic Nd: YAG laser posterior capsulotomy was performed from 1 week to 1 month after the SCSF-IOL procedure. In the SCSF-IOL group, two eyes (10.00%) needed repeated laser treatment, and one eye (5.00%) had a decentered capsule opening. Posterior capsular opacification was the most common complication (6, 35.29%) in the MCTR group. No IOL dislocation, secondary glaucoma, or retinal detachment was observed during follow-up. Conclusions: SCSF-IOL is a simple and viable surgical option for managing MSP and is comparable with the MCTR-IOL. Nd: YAG laser posterior capsulotomy is a necessary mean to prevent residual capsule complications after the SCSF-IOL procedure.

近年来，使用人工智能(artificial intelligence，AI)技术对临床大数据及图像进行分析，对疾病做出智能诊断、预测并提出诊疗决策，AI正逐步成为辅助临床及科研的先进技术。生物样本库作为收集临床信息和样本供科研使用的平台，是临床与科研的桥梁，也是临床信息与科研数据的集成平台。影响生物样本库使用效率及合理共享的因素有信息化建设水平不均衡、获取的临床及检验信息不完全、各库之间信息不对称等。本文对AI和区块链技术在生物样本库建设中的具体应用场景进行探讨，展望大数据时代智能生物样本库信息化建设的核心方向。

In recent years, artificial intelligence (AI) technology has been applied to analyze clinical big data and images and then make intelligent diagnosis, prediction and treatment decisions. It is gradually becoming an advanced technology to assist clinical and scientific research. Biobank is a platform for collecting clinical information and samples for scientific research, serving as a bridge between clinical and scientific research. It is also an integrated platform of clinical information and scientific research data. However, there are some challenges. First, clinical and laboratory information obtained is incomplete. Additionally, the information among different databases is asymmetric, which seriously impedes the information sharing among different Biobanks. In this article, the specific application scenarios of AI technology and blockchain in the construction of a Biobank were discussed, aiming to pinpoint the core direction of the information construction of an intelligent Biobank in the era of big data.