红光是波长范围在620~760 nm的可见光，兼有良好的光化学和热作用，其穿透力较强，能够达到皮肤深层及组织内部，从而产生一系列的生物效应。在眼科领域，红光疗法最初主要应用于弱视和眼睑皮肤相关疾病的治疗，随着研究的进一步深入，红光逐渐被应用于控制近视进展和视网膜相关疾病。目前，重复低强度红光(repeat low-level red-light, RLRL)在近视进展的控制效果得到充分肯定，成为红光疗法在眼科应用最受关注的热点之一，其主要可能机制包括红光照射能激活线粒体中的细胞色素C氧化酶的活性，促进三磷酸腺苷(adenosine triphosphate, ATP) 生成，改善网膜缺氧状况；促进一氧化氮 (nitric oxide, NO)的合成和释放，引起脉络膜血管的扩张及血流量的增加；诱导巩膜细胞外基质的重塑，增加巩膜的强度。此外，红光疗法可抑制视网膜感光细胞调节通路中的氧化应激、炎症和细胞凋亡，减轻眼表炎症反应和疼痛，有助于周围神经损伤后修复等。文章针对红光疗法在近视、视网膜相关疾病、弱视及眼睑皮肤相关疾病的治疗机制、有效性及安全性进行综述，为红光疗法在眼科领域的应用提供重要的参考价值和依据。
Red light is visible light with a wavelength range of 620-760 nm, which has excellent photochemical and thermal effects. It can penetrate deeply into the skin and tissues with strong power, resulting in a series of biological effects. In the field of ophthalmology, red-light therapy was initially mainly used in the treatment of amblyopia and eyelid skin-related diseases, and with the further development of research, red light has been gradually used in the myopia control and the study of retina-related diseases. At present, the effect of repeated low-intensity red light (RLRL) on myopia progression has been fully recognized, and it has become one of the most concerned hotspots in the application of red-light therapy in ophthalmology. The main possible mechanisms include that red light therapy can activate the activity of cytochrome C oxidase in mitochondria, promote ATP production, and improve retinal hypoxia. It can also induce the synthesis and release of NO, cause the expansion of choroidal vessels with improvement of blood flow, and increase scleral strength by remodeling of scleral extracellular matrix. In addition, red- light therapy can reduce oxidative stress, inflammation and apoptosis in the regulatory pathways of photoreceptor cells, reduce eye inflammation and pain, and help repair peripheral nerves after injury. This article will review the mechanism, effectiveness and safety of red-light therapy in myopia, retinal diseases, amblyopia, and eyelid skin-related diseases, in order to provide important reference value and basis for the application of red-light therapy in ophthalmology.
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.
白内障是世界范围内致盲的主要原因之一，占中低收入国家致盲病例的50%。随着人口老龄化程度的加深，到2050年中国白内障致盲病例预计达到2 000万。卫生支出占比低、医疗设备及眼科医生紧缺、筛查费用昂贵仍是中低收入国家无法开展大规模白内障筛查的主要原因。人工智能(artificial intelligence，AI)协助白内障诊断具有便捷、低成本、可远程进行等优点，有望减少甚至避免白内障致盲的发生。文章将对AI通过结合裂隙灯眼前节图像、眼底照片及扫频源光学相干层析图像进行白内障自动诊断等研究进行简要综述。
Cataract is a primary cause of blindness globally, particularly accounting for 50% of blindness cases in low- and middle- income countries. As the population ages, it is predicated that cataract blindness cases in China will rise to 20 million by 2050. However, low health expenditures, scarcity of medical equipment and ophthalmologists, and high screening costs continue to hinder mass cataract screening in these countries. Artificial intelligence(AI)-assisted cataract diagnosis offers significant advantages, including convenience, cost-effectiveness, and remote accessibility, potentially reducing or even eliminating cataract blindness. This review aims to concisely summarize the research on automatic cataract diagnosis utilizing AI, incorporating slit lamp images of anterior eye segment, fundus photographs, and swept source optical coherence tomography images.
近视防控已经上升到我国国家战略层面，高度近视引起的视神经病变会损害视功能，但在临床上常常被忽视。OCT可以非侵入、高分辨率、快速以及可重复地定量视网膜各层厚度，是评估高度近视相关视神经病变的有力工具。由于高度近视常合并视盘和盘周的改变，视神经纤维层厚度的定量常出现误差。近年来，学者开始聚焦于黄斑区神经节细胞复合体(ganglion cell complex,GCC)厚度的研究，但其在高度近视眼中的变化规律尚不统一。该文针对近年来高度近视眼黄斑区GCC的测量规范、诊断价值、变化规律等进行综述，以期提高眼科医师对高度近视视神经病变的重视和研究水平。
Myopia prevention and control has risen to the national strategic level in China. Optic neuropathy caused by high myopia can damage visual function, but it is often ignored in clinical practice Optical coherence tomography (OCT) characterized by non-invasiveness, high resolution, rapid, and repeatable quantifying the thickness of each layer in the retina has emerged as a powerful tool for evaluating high myopia related optic neuropathy. Due to the changes in and near the optic disc in high myopia, errors often occur in the quantification of the thickness of the optic nerve fiber layer. In recent years, researchers have gradually focused on the study of the thickness of ganglion cell complex (GCC), but the regularity of its changes in high myopia is not yet unified. This article reviews the measurement specifications, diagnostic values, and change rules of GCC in the macular region of high myopia in recent years, in order to improve the attention and research level of ophthalmologists on high myopia optic neuropathy.
眼睛由屈光系统和视觉神经系统两大部分构成，是人体最重要的感觉器官之一。眼部各组织的发育或功能异常都可能造成不同程度的视力损害。目前主要通过动物实验或体外细胞培养的方法探究眼病的病理生理机制和治疗手段，但上述两种方法都存在一定的局限性。体外细胞培养不能完全反映器官的形态、结构和生化特征，而动物模型的物种和遗传背景具有异质性。近年来，随着原代组织、胚胎干细胞、诱导多能干细胞衍生的体外三维结构类器官和器官微流控芯片技术的不断发展，构建出了与在体器官的结构、功能更为相似的器官克隆模型，能够提供更敏感、定量、规模化的表型分析，更好地应用于眼的发育、生理结构、疾病机制、个性化医学诊断和治疗方法等方面的研究。目前，眼科的微流控器官芯片与类器官技术在角膜、晶状体、泪腺、视网膜结构发育和疾病模型均展现出巨大的应用潜力。
The eye is composed of refractive system and visual nervous system. It is one of the most important sensory organs of the human body. The abnormal development or function of eye tissues may cause various degrees of visual impairment. At present, the pathophysiological mechanism and treatment of eye diseases are mainly explored through animal experiments and in-vitro cell culture. However, they are of certain limitations. The in-vitro cell culture cannot fully reflect the morphological, structural and biochemical characteristics of organs, whereas the animal models are heterogeneous of species and genetic background. In recent years, with the continuous development of in-vitro three-dimensional structure organoids and organ microfluidic organ-on-a-chip technology derived from primary tissues, embryonic stem cells and induced pluripotent stem cells, organ cloning models more similar to in vivo organs in terms of the structure and function have been constructed. These models can provide more sensitive, quantitative and large-scale phenotypic analysis, and can be better applied to the research of eye development, physiological structure, disease mechanism, personalized medical diagnosis and treatment. At present, microfluidic organ-on-a-chip and organoids technologies have shown great application potential in the structural development and disease models’ construction of cornea, lens, lacrimal gland and retina.
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.
当下，我国眼科的发展存在失衡现象，大城市与农村及偏远地区在眼科相关诊疗设施水平、诊疗技术等方面存在巨大差异，仍需探寻新的智能诊疗模式以解决失衡问题。由于眼球是唯一可以直接观察人体血管和神经的器官，眼部可反映其他脏器的健康状态，部分眼科检查的医学图像可对眼部疾病做出诊断等特点，眼科开展人工智能(artificial intelligence，AI)具有独到的优势。此外，人工智能可在一定程度上提高跨时间空间传递信息的精准度及效率。人工智能在眼科及远程信息传递的优势为解决眼科发展失衡状况提供了助力。本文从眼科人工智能在眼科远程医疗相关应用的角度，主要分析并总结当下我国人工智能在眼科相关疾病远程医疗中的发展程度、所具优势以及存在问题，并讨论眼科人工智能在远程医疗的应用展望。
At present, there is an imbalance in the development of ophthalmology in China. There are huge differences in the level of ophthalmology related facilities, diagnosis and treatment technologies between big cities and rural, remote areas. New intelligent diagnosis and treatment models are still needed to solve the imbalance. Since the eye is the only organ that can directly observe the blood vessels and nerves of the human body, the eye can reflect the health status of other organs and diagnosis of eye diseases based on medical images of some ophthalmic examinations can be made as well as other characteristics. Therefore, the development of artificial intelligence in ophthalmology has unique advantages. In addition, artificial intelligence can improve the accuracy and efficiency of information transmission across time and space to a certain extent. The advantages of artificial intelligence in ophthalmology and telematics are helping to solve the imbalance in ophthalmology development. From the perspective of the application of ophthalmic artificial intelligence in telemedicine, this paper mainly analyzes and summarizes the development degree, advantages and existing problems of artificial intelligence in the telemedicine of ophthalmic diseases in China, and discusses the prospect of the application of ophthalmic artificial intelligence in telemedicine.
大型语言模型（large language models, LLMs）在眼科的应用为医疗领域带来了巨大的潜力，尤其是在提升诊断效率、优化医患沟通和促进个性化医疗方面。通过自然语言处理技术，LLMs可以协助医生进行临床数据的归纳和分析，可以结合患者的病史、影像资料和症状描述，提供精准的辅助诊断，并在复杂病例中提供参考。LLMs还可以帮助医生快速撰写病历报告，改善医疗记录管理效率。在医患沟通中，LLMs能够通过生成通俗易懂的解释，帮助患者理解疾病状况及治疗方案，缩短医生与患者之间的沟通障碍。在远程医疗场景下，LLMs可通过实时分析患者上传的图像文本信息，提供初步诊断建议，助力医生远程诊疗。个性化医疗也是LLMs的重要应用方向，借助患者的遗传数据和生活习惯，可以帮助医生制定更为精准的个性化治疗方案，并预测手术后的恢复情况。此外，LLMs可以通过与临床数据的不断交互进行自我优化，提升其在眼科诊疗中的智能化程度。尽管LLMs在眼科领域的应用前景广阔，但仍面临数据隐私、模型解释性、语言理解等方面的挑战。未来LLMs将继续作为医生的辅助工具，形成“人机协同”的诊疗新模式，为患者提供更好、更精准的医疗服务。
The application of Large Language Models (LLMs) in ophthalmology presents tremendous potential for the healthcare field, particularly in enhancing diagnostic efficiency, optimizing doctor-patient communication, and promoting personalized medicine. Through natural language processing technology, LLMs can assist doctors in summarizing and analyzing clinical data. They can integrate a patient's medical history, imaging data, and symptom descriptions to provide precise diagnostic support and reference for complex cases. LLMs can also help physicians quickly draft case reports, improving the management efficiency of medical records. In doctor-patient communication, LLMs can generate easy-to-understand explanations that help patients comprehend their conditions and treatment plans, thereby reducing communication barriers between doctors and patients. In telemedicine scenarios, LLMs can provide preliminary diagnostic suggestions by real-time analyzing images and textual information uploaded by patients, aiding doctors in remote diagnosis and treatment.Personalized medicine is another significant application direction for LLMs. By utilizing patients' genetic data and lifestyle habits, LLMs can assist physicians in formulating more precise personalized treatment plans and predicting postoperative recovery outcomes. Additionally, LLMs can self-optimize through continuous interaction with clinical data, enhancing their intelligence in ophthalmic diagnosis and treatment. Despite the broad application prospects of LLMs in the field of ophthalmology, challenges remain, including data privacy, model interpretability, and language understanding. In the future, LLMs will continue to serve as auxiliary tools for physicians, forming a new model of "human-machine collaboration" in diagnosis and treatment, ultimately providing better and more precise medical services to patients.
泪器疾病是一类常见的眼科疾病，其诊疗过程复杂，治疗方法精细，涉及多种临床数据及影像资料。现有研究表明，随着人工智能（artificial intelligence，AI）技术，尤其是机器学习和深度学习的发展，AI在泪器疾病的早期筛查、精确诊断和个性化治疗中展现了巨大的应用潜力。AI能够通过高效的图像分析、多模态数据融合及深度学习算法，提供更加精确的疾病识别和治疗方案，并且能够对患者的病情进行定期监测和动态调整，提升治疗效果。然而，其仍面临诸多挑战，如多模态数据融合的复杂性、模型泛化能力的局限以及实时预测和动态调整的需求等，需要通过持续的技术创新、算法优化和跨学科合作来实现。文章对当前AI在泪器疾病诊疗中的应用现状进行了全面梳理和总结，深入分析了AI技术在诊断与治疗中的优势与局限，特别强调了AI与新兴技术的结合在优化临床决策支持系统方面的重要性。通过分析现有的挑战与技术融合策略，文章提出了AI在泪器疾病诊疗中的发展方向，旨在为未来的研究者提供创新性的思路，为眼科领域的临床实践提供有价值的参考，助力泪器疾病的精准医疗和个性化治疗的发展。
Lacrimal disorders are common ophthalmic conditions characterized by complex diagnostic and treatment processes, involving intricate therapeutic approaches and diverse clinical and imaging data. Recent studies have indicated that with the advancements in artificial intelligence (AI) technologies, particularly in machine learning and deep learning, AI demonstrates significant potential in the early screening, accurate diagnosis, and personalized treatment of lacrimal disorders. AI has the ability to provide more precise disease identification and treatment strategies through efficient image analysis, multimodal data fusion, and deep learning algorithms. Additionally, it enables regular monitoring and dynamic adjustment of patients' conditions, improving treatment outcomes. However, several challenges persist, such as the complexity of multimodal data integration, limitations in model generalization capabilities, and the need for real-time prediction and dynamic adjustments, all of which necessitate continuous technological innovations, algorithm optimization, and interdisciplinary collaborations. This paper provides a comprehensive review of the current status of AI applications in the diagnosis and treatment of lacrimal disorders, analyzing the advantages and limitations of AI in clinical practice. It especially emphasizes the importance of integrating AI with emerging technologies to optimize clinical decision support systems. By addressing the existing challenges and exploring strategies for technological integration, this paper proposes future directions for the development of AI in lacrimal disorder diagnosis and treatment, aiming to offer innovative perspectives for future researchers and valuable references for clinical practice in the field of ophthalmology, ultimately contributing to the advancement of precision medicine and personalized treatment for lacrimal disorders.
二氧化碳(carbon dioxide, CO2)激光通过气体混合物激发产生红外光，组织水分高度吸收后引发汽化和局部热效应，能够精确封闭小血管和淋巴管。这些特性使得CO2激光在组织切割过程中能够最大限度地减少出血，提高术中视野的清晰度，缩短手术时间，并减轻术后肿胀、瘀斑及疼痛。在眼整形外科，特别是处理眼周复杂病例方面，CO2激光展现了显著的优势。文章对CO2激光在眼整形外科中的应用进行综述，包括眼睑肿物切除、泪小管炎治疗、瘢痕治疗、皮肤松弛治疗以及眼袋去除等，旨在为临床医生和研究人员提供关于CO2激光在眼整形外科中的全面参考，帮助其了解该项技术的优势、效果及术后并发症，以更有效地应用于实践并探索未来发展。
The carbon dioxide (CO2) laser generates infrared light through the excitation of a gaseous mixture. When this infrared light is highly absorbed by tissue water, it triggers vaporization and localized thermal effects, enabling precise sealing of small blood vessels and lymphatic vessels. These properties allow the CO2 laser to minimize bleeding during tissue dissection, enhance intraoperative visual field clarity, reduce operative time, and alleviate postoperative swelling, ecchymosis, and pain. The CO2 laser has demonstrated significant advantages in oculoplastic surgery, particularly in the management of complex periorbital cases. This article reviews the applications of the CO2 laser in oculoplastic surgery, including eyelid tumor excision, treatment of canaliculitis, scar management, skin laxity treatment, and removal of eye bags. It aims to provide clinicians and researchers with a comprehensive reference on the use of the CO2 laser in oculoplastic surgery, helping them understand the advantages, effects, and postoperative complications of this technology, in order to more effectively apply it in practice and explore future developments.
