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用于糖尿病视网膜病变筛查的全局覆盖视网膜相机的综述。

Review of retinal cameras for global coverage of diabetic retinopathy screening.

机构信息

Department of Ophthalmology, Dr. Mohan's Diabetes Specialities Centre and Madras Diabetes Research Foundation, Chennai, India.

出版信息

Eye (Lond). 2021 Jan;35(1):162-172. doi: 10.1038/s41433-020-01262-7. Epub 2020 Nov 9.

DOI:10.1038/s41433-020-01262-7
PMID:33168977
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7852572/
Abstract

The global burden of diabetes has resulted in an increase in the prevalence of diabetic retinopathy (DR), a microvascular complication of diabetes. Lifelong repetitive screening for DR is essential for early detection and timely management to prevent visual impairment due to the silent sight-threatening disorder. Colour fundus photography (CFP) is helpful for documentation of the retinopathy as well as for counselling the patient. CFP has established roles in DR screening, detection, progression and monitoring of treatment response. DR screening programmes use validated mydriatic or non-mydriatic fundus cameras for retinal imaging and trained image graders identify referable DR. Smartphone-based fundus cameras and handheld fundus cameras that are cost-effective, portable and easy to handle in remote places are gaining popularity in recent years. The images captured with these low-cost devices can be immediately sent to trained ophthalmologists for grading of DR. Recent increase in numbers of telemedicine programmes based on imaging with digital fundus cameras and remote interpretation has facilitated larger population coverage of DR screening and timely referral of those with sight-threatening DR to ophthalmologists. Good-quality retinal imaging and accurate diagnosis are essential to reduce inappropriate referrals. Advances in digital imaging such as ultra-wide field imaging and multi-modal imaging have opened new avenues for assessing DR. Fundus cameras with integrated artificial intelligence (AI)-based automated algorithms can also provide instant DR diagnosis and reduce the burden of healthcare systems. We review the different types of fundus cameras currently used in DR screening and management around the world.

摘要

全球糖尿病负担增加导致糖尿病视网膜病变(DR)的患病率上升,DR 是糖尿病的一种微血管并发症。终身重复筛查 DR 对于早期发现和及时治疗至关重要,可预防因这种隐匿性致盲性疾病导致的视力损害。彩色眼底照相术(CFP)有助于记录视网膜病变,并为患者提供咨询。CFP 在 DR 的筛查、检测、进展和治疗反应监测方面发挥着重要作用。DR 筛查计划使用经过验证的散瞳或不散瞳眼底相机进行视网膜成像,经过培训的图像分级员识别可转诊的 DR。近年来,基于智能手机的眼底相机和手持眼底相机因其具有成本效益、便携性和易于在偏远地区操作的特点而受到欢迎。这些低成本设备拍摄的图像可以立即发送给经过培训的眼科医生进行 DR 分级。最近,基于数字眼底相机成像和远程解读的远程医疗计划数量增加,这促进了更大范围的 DR 筛查人群覆盖,并及时将有视力威胁性 DR 的患者转诊给眼科医生。高质量的视网膜成像和准确的诊断对于减少不适当的转诊至关重要。数字成像技术的进步,如超广角成像和多模态成像,为评估 DR 开辟了新途径。集成基于人工智能(AI)的自动算法的眼底相机也可以提供即时的 DR 诊断,并减轻医疗保健系统的负担。我们回顾了目前在全球范围内用于 DR 筛查和管理的不同类型的眼底相机。

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Insights into the growing popularity of artificial intelligence in ophthalmology.洞察人工智能在眼科学领域日益普及的原因。
Indian J Ophthalmol. 2020 Jul;68(7):1339-1346. doi: 10.4103/ijo.IJO_1754_19.
2
The ORNATE India Project: United Kingdom-India Research Collaboration to tackle visual impairment due to diabetic retinopathy.ORNATE 印度项目:英国-印度研究合作,以解决糖尿病视网膜病变导致的视力障碍问题。
Eye (Lond). 2020 Jul;34(7):1279-1286. doi: 10.1038/s41433-020-0854-8. Epub 2020 May 12.
3
Accuracy of the smartphone-based nonmydriatic retinal camera in the detection of sight-threatening diabetic retinopathy.基于智能手机的免散瞳视网膜相机检测威胁视力的糖尿病视网膜病变的准确性。
Indian J Ophthalmol. 2020 Feb;68(Suppl 1):S42-S46. doi: 10.4103/ijo.IJO_1937_19.
4
Correlation of multicolor images and conventional color fundus photographs with foveal autofluorescence patterns in diabetic macular edema.糖尿病性黄斑水肿中多光谱图像与传统眼底彩色照片和中心凹自发荧光模式的相关性。
Indian J Ophthalmol. 2020 Jan;68(1):141-144. doi: 10.4103/ijo.IJO_608_19.
5
New imaging systems in diabetic retinopathy.糖尿病视网膜病变的新型成像系统。
Acta Diabetol. 2019 Sep;56(9):981-994. doi: 10.1007/s00592-019-01373-y. Epub 2019 Jun 15.
6
Use of Telemedicine Technologies in Diabetes Prevention and Control in Resource-Constrained Settings: Lessons Learned from Emerging Economies.资源有限环境下利用远程医疗技术进行糖尿病预防和控制:新兴经济体的经验教训。
Diabetes Technol Ther. 2019 Jun;21(S2):S29-S216. doi: 10.1089/dia.2019.0038.
7
Update on Screening for Sight-Threatening Diabetic Retinopathy.筛查威胁视力的糖尿病视网膜病变进展。
Ophthalmic Res. 2019;62(4):218-224. doi: 10.1159/000499539. Epub 2019 May 27.
8
Diagnostic test accuracy of diabetic retinopathy screening by physician graders using a hand-held non-mydriatic retinal camera at a tertiary level medical clinic.在三级医疗诊所,由医生分级人员使用手持式免散瞳视网膜相机进行糖尿病视网膜病变筛查的诊断测试准确性。
BMC Ophthalmol. 2019 Apr 8;19(1):89. doi: 10.1186/s12886-019-1092-3.
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Advances in Retinal Imaging and Applications in Diabetic Retinopathy Screening: A Review.视网膜成像进展及其在糖尿病视网膜病变筛查中的应用:综述
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Systematic review and meta-analysis of diagnostic accuracy of detection of any level of diabetic retinopathy using digital retinal imaging.系统评价和 Meta 分析:利用数字视网膜成像检测任何程度糖尿病视网膜病变的诊断准确性。
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