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.
肥厚型脉络膜谱系疾病(pachychoroid disease, PCD)是一组以病理性脉络膜增厚为共同特征的疾病谱系。其特征性改变包括Haller层脉络膜血管扩张，脉络膜毛细血管层和Sattler层变薄，以及肥厚血管(pachyvessels)上视网膜色素上皮(retinal pigment epithelium, RPE)的异常。PCD主要包括单纯肥厚型脉络膜病变(uncomplicated pachychoroid, UCP)、肥厚型脉络膜色素上皮病变(pachychoroid pigment epitheliopathy, PPE)、中心性浆液性脉络膜视网膜病变(central serous chorioretinopathy, CSC)、肥厚型脉络膜新生血管病变(pachychoroid neovasculopathy, PNV)和息肉状脉络膜血管病变(polypoidal choroidal vasculopathy, PCV)。传统眼底检查因单张成像局限于后极部，难以全面评估病变范围。广角影像技术突破了这一局限，其成像范围覆盖后极部至赤道部涡静脉壶腹部(约60°~100°)，而超广角成像更可达后极部至锯齿缘(约 110°~220°)。这一技术的进步不仅扩大了PCD眼底病灶的观察范围，更提升了对脉络膜结构和功能的评估能力，为深化研究PCD的发病机制提供了新的视角。近年来，基于深度学习的人工智能技术在PCD辅助诊断方面取得重要突破，展现出优异的PCD相关疾病识别和分类能力，有助于显著提升基层医疗机构诊断效率，并推动医疗资源优化配置。文章综述了广角眼底影像技术在PCD评估与诊断中的研究进展，旨在为眼科临床工作者和研究者提供最新的技术应用视角，并为进一步探索PCD的病理机制和诊疗方法奠定科学基础。
Pachychoroid disease (PCD) represents a group of disorders characterized by pathological choroidal thickening. The characteristic changes include dilated choroidal vessels in Haller's layer, thinning of the choriocapillaris and Sattler's layer, and retinal pigment epithelium (RPE) abnormalities overlying the pachyvessels. The PCD primarily encompasses uncomplicated pachychoroid (UCP), pachychoroid pigment epitheliopathy (PPE), central serous chorioretinopathy (CSC), pachychoroid neovasculopathy (PNV), and polypoidal choroidal vasculopathy (PCV). Traditional fundus examination is limited to the posterior pole in single-frame imaging, making it challenging to comprehensively evaluate the extent of lesions. Wide-field imaging technology has overcome this limitation, with its imaging range covering from the posterior pole to the ampulla of vortex veins at the equator (approximately 60-100°), while ultra-wide-field imaging can extend from the posterior pole to the pars plana (approximately 110-220°). This technological advancement has not only expanded the observation range of PCD fundus lesions but also enhanced the assessment capabilities of choroidal structure and function, providing new perspectives for investigating PCD pathogenesis. In recent years, deep learning-based artificial intelligence technology has achieved significant breakthroughs in PCD-assisted diagnosis, demonstrating excellent capability in identifying and classifying PCD-related diseases. This has contributed to significantly improving diagnostic efficiency in primary healthcare institutions and optimizing medical resource allocation. This review summarizes the advances in wide-field fundus imaging technologies for the assessment and diagnosis of PCD.
眼缺血综合征(ocular ischemia syndrome，OIS)是由一系列诱因引发的以慢性眼部低灌注为主要临床表现的眼部疾病。临床相对少见，但对视力的影响较大，其症状主要包括一过性黑朦、缺血性眼痛、永久性视力丧失等。近年来医疗美容行业逐步兴起，自体脂肪填充技术使用逐渐增多，其所引起的OIS不可忽视。本文分析1例自体脂肪填充患者术后致OIS病例，研究该类疾病眼底影像学特征。
Ocular ischemia syndrome (OIS), featuring as chronic ocular hypoperfusion, is an eye disease caused by a series of incentives. It is relatively rare in clinical practice, but has a great impact on vision. The symptoms of OIS mainly include transient amaurosis, ischemic eye pain, permanent vision loss, etc. In recent years, with the rise of the Aesthetic Medicine industry, the technology of autologous fat filling has been increasingly adopted. The OIS caused by the surgery of autologous fat filling is nonnegligible. In this paper, by means of analyzing a case that an autologous fat filling surgery resulted in the OIS, discusses features of fundus angiography of OIS.
