当前，药物临床试验面临着两大难题：数据真实性及相关人员操作规范性。现阶段国内外在药物临床试验方面的监管主要以事后监查为主，在数据质量管理以及操作规划标准的监查方面存在一定的时延性。而区块链通过非对称加密、哈希算法及智能合约等技术，可以在保证受试者隐私信息的前提下，提高政府相关监督机构的监管效率，提升药物临床试验数据管理的透明度；同时，与物联网的紧密结合可以实现对标准操作规范的进一步核查，与人工智能的结合有望实现受试者的自动招募。

Clinical drug trials are confronted with two major issues: first, data authenticity, for instance, if any data falsification is conducted during the whole trial; second, whether the standard of procedure is accordingly conducted throughout the whole trial or not. Currently, both domestic and overseas clinical drug trials are not supervised without delay (ex-post inspection). Blockchain technology can improve the efficiency of Food and Drug Administration and the transparency of trials while the rights and safety of human research subjects are guaranteed by the integrated technology such as chained structure, asymmetry key algorithm, hash algorithm, and smart contract. Furthermore, with the assistance of internet of things (IoT) and artificial intelligence (AI), the actual supervision over the whole trial and automatic recruitment of human research subjects are expected to achieve.

传统的眼底手术要求眼科医生具备精细的操作技术，但即便拥有再精湛的操作技术，眼底手术还是存在很大的风险性。因此，为了减少手术风险，提高手术质量，对传统眼底手术进行改进是十分必要的。近年来，在我国对于人工智能产业的大力支持之下，应用于各类行业的机器人随之诞生。机器人辅助系统(robot auxiliary system，RAS)在医学领域，特别是眼科学中应用广泛。对近几年RAS应用于眼底手术的案例进行整理总结，并将RAS参与的眼底手术以及传统的眼底手术进行对比，可以发现RAS在眼底手术中的应用可以显著提高手术效率，并降低手术风险。未来RAS的发展趋势可能着重聚焦于与深度学习算法的紧密结合。通过算法对手术中的视野图像进行预测、优化，从而让高精度的眼底手术更加高效、安全。

Traditional fundus surgery requires ophthalmologists to be equipped with sophisticated operating techniques, but even with the most sophisticated operating techniques, fundus surgery still has great risks. Therefore, in order to reduce the risk of surgery and improve the quality of surgery, it is very necessary to improve the traditional fundus surgery. In recent years, with China’s strong support for the artificial intelligence industry, robots used in various industries have been born. Robot auxiliary system (RAS) is widely used in the medical field, especially in ophthalmology. By summarizing the cases of fundus surgery with RAS in recent years and comparing the fundus surgery involving RAS with traditional fundus surgery, it can be found that the application of RAS in fundus surgery can significantly improve the efficiency of surgery and reduce the risk of surgery. The future development trend of RAS may focus on the close integration with deep learning algorithms, which can predict and optimize the field of view images during surgery so that high-precision fundus surgery can be more efficient and safer.

目的：比较六种新一代人工晶状体(intraocular lens,IOL)屈光力计算公式[Barrett Universal Ⅱ(BUⅡ)、Emmetropia Verifying Optical(EVO)、Hill-Radial Basis Function (Hill-RBF)、Kane、Ladas Super Formula(LSF)、T2]和传统公式(Haigis、Hoffer Q、Holladay 1、SRK/T)的准确性。方法：纳入2022年1—6月于温州医科大学附属眼视光医院接受白内障手术患者。收集患者的年龄、性别、眼轴(axial length,AL)、平均角膜曲率(mean keratometry,Kmean)、前房深度、IOL常数和屈光力，术后医学验光结果。对上述10种公式进行准确性分析，包括平均预测误差(mean prediction error,ME)及其标准差、平均绝对预测误差(mean absolute prediction error,MAE)、绝对预测误差中位数(median absolute prediction error,MedAE)、绝对预测误差最大值(maximum absolute prediction error,MaxAE)、预测误差落在±0.25、±0.5、±0.75、±1.00 D范围内的百分比(%±0.25 D、%±0.50 D、%±0.75 D、%±1.00 D)。结果：共纳入506例(506眼)。Kane的MAE最低(0.411)。Hill-RBF的%±0.25 D最高(40.91%)，EVO的%±0.50 D或%±0.75 D最高(分别为69.37%、86.17%)，BUⅡ和Hill-RBF的%±1.00 D最高(均为94.07%)。总体上各种公式间，MAE、%±0.50 D、%±0.75 D、%±1.00 D比较差异存在统计学意义(P<0.05)，但两两比较仅发现%±0.75 D中，EVO(86.17%)、Hill-RBF(85.97%)、Kane(85.57%)与HofferQ(81.42%)比较差异存在统计学意义(均P<0.05)。AL亚组中，长AL组的EVO(0.390)、Hill-RBF(0.388)、T2(0.423)、Kane(0.393)四种公式的MAE与Hoffer Q(0.681)、Holladay 1(0.654)比较差异存在统计学意义(均P<0.05)，EVO(74.47%)的%±0.50 D与Hoffer Q(46.81%)比较差异存在统计学意义(P=0.017)。结论：新一代IOL屈光力计算公式在IOL屈光力计算上均具有较好的准确性，但对于不同的眼轴长度与角膜曲率值的眼球，需要选择适合的计算公式，以进一步提高预测准确性。

Objective: This study aimed to compare the accuracy of six new generation intraocular lenses (IOL) refractive power calculation formulas (Barrett Universal Ⅱ [BU Ⅱ ], Emmetropia Verifying Optical [EVO], Hill-Radial Basis Function [Hill-RBF], Kane, Ladas Super Formula [LSF], T2) and traditional formulas (Haigis, Hoffer Q, Holladay 1, SRK/ T). Methods: The patients who received cataract surgery in the Eye Hospital of Wenzhou Medical University from January 2022 to June 2022 were included in this study. Age, gender, axial length (AL), mean keratometry, anterior chamber depth, IOL constant and power, and postoperative refraction results were collected. The prediction accuracy of these ten IOL power calculation formulas was analyzed, including mean prediction error (ME) and its standard deviation, mean absolute prediction error (MAE), median absolute prediction error (MedAE), maximum absolute prediction error (MaxAE), the percentage of eyes of PE within the range of ±0.25 D, ±0.5 D, ±0.75 D, ±1.0 D (%±0.25 D,%±0.50 D, %±0.75 D, %±1.00 D). Results: 506 eyes of 506 patients were included. Kane has the lowest MAE (0.411).%±0.25 D of Hill-RBF was the highest (40.91%), %±0.50 D or %±0.75 D of EVO was the highest (69.37%, 86.17%), and %±1.00 D of BU Ⅱ and Hill-RBF was the highest (94.07%). There are significant differences in MAE, %±0.50 D, %±0.75 D, and %±1.00 D among all formulas (P<0.05). Still, pairwise comparison only found differences between EVO (86.17%), Hill-RBF (85.97%), Kane (85.57%), and Hoffer Q (81.42%) in %±0.75 D (all P<0.05). In AL subgroup, the MAE of EVO (0.390), Hill-RBF (0.388), T2 (0.423) and Kane (0.393) in long AL group was different from that of Hoffer Q (0.681) and Holladay 1 (0.654) (all P<0.05), the difference of %±0.50D of EVO (74.47%) compared with Hoffer Q (46.81%) (P=0.017). Conclusion: The new generation of IOL power calculation formulas have good accuracy in IOL power prediction, but for eyes with different axial lengths and keratometry, it is necessary to optimize the selection of formulas to improve the prediction accuracy further.

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.

    人工智能(artificial intelligence，AI)为解决中国患者“看病难”问题提供了可行方案。眼科AI已实现为患者提供筛查、远程诊断及治疗建议等方面的服务，能显著减轻医疗资源不足的压力和患者的经济负担。而AI的应用过程中，给医疗管理带来的挑战应引起重视。本文从医疗管理的角度，总结分析AI在眼科医疗过程中，尤其是交接环节中出现的主要问题，提出对策与建议，并讨论AI在眼科医疗的应用展望。

    Artificial intelligence (AI) has been proposed as a potential solution to address the shortage of ophthalmologists in China. With the increasingly extensive application of AI in the field of ophthalmology, many potential patients with eye diseases have access to a higher quality of medical services. At the same time, new challenges will emerge and proliferate with the advancement of AI application. This paper focuses on the patient handoffs process and discusses two challenges brought by the application of AI, namely “communication” and “standardization”. Natural language processing techniques and the development of standardized databases are proposed to solve each of these challenges. The application prospects of AI in ophthalmology are eventually discussed.

先天性晶状体不全脱位是一种较为罕见的晶状体悬韧带异常的疾病，其手术治疗极具挑战性。以人工晶状体悬吊为代表的传统手术方式易出现囊袋破裂、玻璃体疝、人工晶状体脱位和继发性青光眼等严重并发症。近年来，以重建囊袋悬韧带隔为目标，新型囊袋辅助装置的应用极大程度提高了先天性晶状体不全脱位的手术成功率。然而，以改良式张力环为代表的囊袋辅助装置在我国仍难以得到普及且操作繁琐。因此，如何最大程度利用普通张力环等最常见的装备，设计出一种安全可靠手治疗先天性晶状体不全脱位的手术方式是眼科界亟待解决的问题。本文将介绍一种二期张力环缝合固定治疗先天性晶状体不全脱位手术技术。该技术仅需使用普通张力环，具有操作简单安全、术后效果稳定和易于技术推广的优点。

Congenital ectopia lentis is a relatively rare zonular disorder of the lens, and its surgical treatment is extremely challenging. The traditional surgical procedures represented by intraocular lens suspension are prone to result in serious complications such as capsular bag rupture, vitreous hernia, intraocular lens dislocation and secondary glaucoma. In recent years, with the goal of reconstructing the capsular bag–zonules diaphragm, the application of new capsular bag-assisted devices has greatly improved the surgical success rate of congenital ectopia lentis. However, the capsular-assisted devices, such as modified capsular tension ring, are still difficult to be popularized in China and the surgical procedures are complicated. Therefore, how to maximize the use of common equipment such as normal capsular tension rings and design a safe and reliable surgical method for the treatment of congenital ectopia lentis is an urgent issue for ophthalmologists. This article aims to introduce a two-stage capsular tension ring fixation for the treatment of congenital ectopia lentis, which has many advantages such as simple and safe operation, stable postoperative effect and less requirements for special equipment, and is worth promoting in clinical practice.

人工智能是对人类智能的模拟和拓展。基于深度学习的人工智能可以很好地利用图像的内在特征，如轮廓、框架等，来分析图像。研究人员通常利用图像来诊断眼底病，因此将人工智能应用于眼底检查是有意义的。在眼科领域，人工智能通过分析光学相干断层扫描图像、眼底照片和超宽视野图像，已经在检测多种眼底疾病上取得了类似医生的性能。它也已经被广泛应用于疾病进展预测。然而，人工智能在眼科的应用也存在一些潜在的挑战，黑盒问题是其中之一。研究人员致力于开发更多的可解释的深度学习系统，并确认其临床可行性。人工智能在最流行的眼底病中的最新应用、可能遇到的挑战以及未来的道路将一一阐述。

Artificial intelligence (AI) is about simulating and expanding human intelligence. AI based on deep learning (DL) can analyze images well by using their inherent features, such as outlines, frames and so on. As researchers generally diagnoses ocular fundus diseases by images, it makes sense to apply AI to fundus examination. In ophthalmology, AI has achieved doctor-like performance in detecting multiple ocular fundus diseases through optical coherence tomography (OCT) images, fundus photographs, and ultra-wide-field (UWF) images. It has also been widely used in disease progression prediction. Nonetheless, there are also some potential challenges with AI application in ophthalmology, one of which is the black-box problem. Researchers are devoted to developing more interpretable deep learning systems (DLS) and confirming their clinical feasibility. This review describes a summary of the state-of-the-art AI application in the most popular ocular fundus diseases, potential challenges and the path forward.

目的：分析角膜后前表面曲率半径比值(B/F比值)与年龄相关性白内障患者术后屈光误差的关系，探讨B/F比值对人工晶状体(intraocular lens,IOL)度数计算精确性的影响。方法：选取2019年3—11月在天津医科大学眼科医院白内障中心就诊，并拟行单眼白内障手术的年龄相关性白内障患者共197例(197眼)，术前应用Pentacam眼前节分析仪测量患者眼前节生物参数，并以B/F比值下限25%、上限25%为界将患者分为下25%组、25%～75%组、上25%组。术后3个月应用全自动电脑验光仪评估患者术后屈光状态，并计算患者术后屈光误差(postoperative refractive error,PE)，比较三组平均屈光误差(mean refractive error,ME)、平均绝对误差(mean absolute error,MAE)、中位数绝对误差(median absolute error,MedAE)以及屈光误差在±0.25、±0.50、±0.75、±1.00、>±1.00 D范围内百分比差异。结果：B/F比值与年龄相关性白内障患者术后屈光误差呈中度相关(r=?0.445, P<0.001)。随着B/F比值增大，患者术后屈光状态由远视向近视漂移，术后3个月MAE、MedAE分别为0.55 D、0.46 D。屈光误差在±0.25、±0.50、±0.75、±1.00、>±1.00 D范围的百分比分别为29.4%、52.8%、71.6%、87.6%、12.7%。根据正常年龄相关性白内障人群B/F比值优化得到的矫正角膜折射指数计算角膜曲率后，MAE、MedAE分别为0.51、0.43 D，均低于矫正前(P<0.05)。结论：B/F比值对年龄相关性白内障患者术后屈光状态有影响。随着B/F比值的增加，白内障患者术后屈光状态由远视逐渐向近视漂移，且B/F比值越偏离正常平均值，患者的屈光误差绝对值越大。

Objective: To analyze the relationship between corneal B/F ratio and postoperative refractive error in age-related cataract patients, and to explore the impact of B/F ratio on the accuracy of intraocular lens power calculation. Methods: A total of 197 age-related cataract patients (197 eyes) who were treated in the cataract center of our hospital from March 2019 to November 2019 and were going to undergo monocular cataract surgery were selected. The biological parameters of the anterior segment were measured by Pentacam anterior segment analyzer before surgery, and the patients were divided into three groups (25% below the B/F ratio, 25%~75%, and 25% below the B/F ratio) with the lower limit and the upper limit of 25%. Three months after surgery, the postoperative refractive state of patients was evaluated by automatic computerized refractometer, and the postoperative refractive error (PE) was calculated, and the percentage differences of mean refractive error (ME), mean absolute error (MAE), median absolute error (MedAE) and refractive error in the range of ±0.25, ±0.50, ±0.75, ±1.00 and < ±1.00D were evaluated. Results: The B/F ratio was moderately correlated with postoperative refractive error in age-related cataract patients (r= ?0.445, P < 0.001). With the increase of B/F ratio, the refractive state of patients shifted from hyperopia to myopia after surgery, and the MAE and MedAE were 0.55 D and 0.46 D respectively in 3 months after surgery. The percentages of refractive error in the range of ±0.25, ±0.50, ±0.75, ±1.00 and < ±1.00 D were 29.4%, 52.8%, 71.6%, 87.6% and 12.7%, respectively. After adjusting the corneal curvature according to the B/F ratio of the population based on our previous study, MAE and MedAE were 0.51 D and 0.43 D, respectively, which were lower than those before correction (P< 0.05). Conclusions: There is a correlation between B/F ratio and postoperative refractive error in age-related cataract patients. As the B/F ratio increased, the refractive state of the patient gradually drifted from farsightedness to myopia after cataract surgery, and the more the B/F ratio deviated from the normal average, the greater the absolute value of the patient's refractive error.

目的：评估超脉冲二氧化碳(CO₂)激光治疗不同类型眼睑肿物的疗效和安全性。方法：纳入50例眼睑肿物患者，其中男12例、女38例。患者年龄4~84岁。肿物类型包括眼睑色素痣、睑黄瘤、分裂痣、眼睑疣等，其中25例累及眼睑灰线，10例肿物直径>10 mm。所有患者接受超脉冲CO₂激光治疗，并进行术后随访。治疗效果通过术后数码照片评估，同时记录术后1个月并发症发生情况。结果：50例眼睑肿物总体治愈率为92%，有效率达到100%。4例眼睑色素痣在治疗后1个月内复发。术后并发症主要包括轻微倒睫(5例)、睫毛稀疏部分缺失(4例)和瘢痕增生及色素沉着(4例)，未出现其他严重并发症。结论：对于眼睑肿物，特别是睑缘肿物及大肿物，超脉冲CO₂激光是一种更为精确、微创、安全有效的治疗方法，可作为眼睑肿物治疗的优选方案。

Objective: To evaluate the efficacy and safety of ultrapulse carbon dioxide (CO₂) laser in the treatment for various types of eyelid tumors. Methods: A total of 50 patients, including 12 males and 38 females,with eyelid tumors were included in the study The age range is  from 4 to 84 years, with an average age of 37.9±20.0 years. The tumors found in our study include eyelid pigmented nevus, xanthelasma, divided nevus, and molluscum. Among them, 25 cases involved the gray line of the eyelid,and 10 cases had a tumor diameter greater than 10 mm. All patients underwent ultrapulse CO₂ laser treatment and postoperative follow-up. The treatment outcomes were assessed through digital photos, and complications were recorded one month after surgery. Results: The total cure rate of the 50 cases of eyelid tumors in our study was 92%, with the effective rate reaching 100%. 4 cases of eyelid pigmented nevi recurred within one month after treatment, while all other patients were cured. Postoperative complications mainly included minor trichiasis (5 cases), partial sparse to absent eyelashes (4 cases), and hypertrophic scar with hyperpigmentation (4 cases). No other serious complications were reported in our study. Conclusions: For eyelid tumors, especially eyelid margin and larger tumors, the ultrapulse CO₂ laser is a more precise, minimally invasive, safe and effective treatment method. It can be used as a preferred treatment option for eyelid tumors, and should be promoted widely in clinical practice.

糖尿病视网膜病变(diabetic retinopathy,DR)是世界范围内劳动年龄人口视力损伤的主要原因。糖尿病前期和DR临床前期患者作为罹患DR的高危人群，在该阶段可发现视网膜神经元形态功能及视网膜微小血管的改变。视网膜及神经纤维层厚度的变化可部分反映视网膜神经元结构改变；色觉、对比敏感度、视野及视觉电生理等变化可反映视网膜神经元功能改变。随着光学相关断层扫描血管成像技术的发展，临床可以检测出DR之前视网膜微血管的改变。此外，许多生物标志物也可以预测和评估DR。由于目前还没有方法可以阻止DR的发生与进展，临床可以通过观察以上视网膜的改变更为及时地发现DR，以降低其患病率，最大限度地减少DR带来的视力损伤。

Diabetes retinopathy (DR) is the main cause of visual impairment in the working population worldwide. Patients with pre-diabetes and pre-clinic diabetic retinopathy are regarded as in high risk group of DR. The changes in morphology and function of renal neurons and retinal micro-vessels can be found in these patients at this stage. The changes of retinal nerve structure can be partly reflected by changes in the thickness of retina and nerve fiber layer. The changes in function of retinal neurons can be reflected by changes in color vision, contrast sensitivity, visual field and visual electrophysiology.With the development of optical coherence tomography angiography, changes in retinal micro-vessels can be observed prior to clinical detection of DR. In addition, many biomarker can also predict and evaluate DR. Since there is no way to prevent the occurrence and progress of DR at present, more attention should be paid in DR by observing the changes inthe retina mentioned above timely, to reduce its incidence and minimize the visual damage caused by DR.