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在糖尿病视网膜病变筛查项目中,AirDoc便携式视网膜相机与eyer的图像质量比较。

Image quality comparison of AirDoc portable retina camera versus eyer in a diabetic retinopathy screening program.

作者信息

Brant Rodrigo, Nakayama Luis Filipe, de Oliveira Talita Virgínia Fernandes, de Oliveira Juliana Angelica Estevão, Ribeiro Lucas Zago, Richter Gabriela Dalmedico, Rodacki Rafael, Penha Fernando Marcondes

机构信息

Ophthalmology and Visual Science Department, Sao Paulo Federal University, Sao Paulo, SP, Brazil.

Keck School of Medicine, Roski Eye Institute, University of Southern California, Los Angeles, USA.

出版信息

Int J Retina Vitreous. 2024 Jun 14;10(1):43. doi: 10.1186/s40942-024-00559-z.

DOI:10.1186/s40942-024-00559-z
PMID:38877585
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11177418/
Abstract

BACKGROUND

Diabetic retinopathy (DR) stands as the foremost cause of preventable blindness in adults. Despite efforts to expand DR screening coverage in the Brazilian public healthcare system, challenges persist due to various factors including social, medical, and financial constraints. Our objective was to evaluate the quality of images obtained with the AirDoc, a novel device, compared to Eyer portable camera which has already been clinically validated.

METHODS

Images were captured by two portable retinal devices: AirDoc and Eyer. The included patients had their fundus images obtained in a screening program conducted in Blumenau, Santa Catarina. Two retina specialists independently assessed image's quality. A comparison was performed between both devices regarding image quality and the presence of artifacts.

RESULTS

The analysis included 129 patients (mean age of 61 years), with 29 (43.28%) male and an average disease duration of 11.1 ± 8 years. In Ardoc, 21 (16.28%) images were classified as poor quality, with 88 (68%) presenting artifacts; in Eyer, 4 (3.1%) images were classified as poor quality, with 94 (72.87%) presenting artifacts.

CONCLUSIONS

Although both Eyer and AirDoc devices show potential as screening tools, the AirDoc images displayed higher rates of ungradable and low-quality images, that may directly affect the DR and DME grading. We must acknowledge the limitations of our study, including the relatively small sample size. Therefore, the interpretations of our analyses should be approached with caution, and further investigations with larger patient cohorts are warranted to validate our findings.

摘要

背景

糖尿病视网膜病变(DR)是成年人可预防失明的首要原因。尽管巴西公共医疗系统努力扩大DR筛查覆盖范围,但由于社会、医疗和经济等各种因素,挑战依然存在。我们的目标是评估一种新型设备AirDoc与已通过临床验证的Eyer便携式相机相比所获得图像的质量。

方法

图像由两种便携式视网膜设备采集:AirDoc和Eyer。纳入的患者在圣卡塔琳娜州布卢梅瑙开展的一项筛查项目中获取了眼底图像。两位视网膜专家独立评估图像质量。对两种设备在图像质量和伪影存在情况方面进行了比较。

结果

分析纳入了129例患者(平均年龄61岁),其中男性29例(43.28%),平均病程11.1±8年。在AirDoc设备中,21幅(16.28%)图像被归类为质量差,88幅(68%)存在伪影;在Eyer设备中,4幅(3.1%)图像被归类为质量差,94幅(72.87%)存在伪影。

结论

尽管Eyer和AirDoc设备都显示出作为筛查工具的潜力,但AirDoc设备的图像不可分级和低质量图像的比例更高,这可能直接影响DR和糖尿病性黄斑水肿(DME)的分级。我们必须承认我们研究的局限性,包括样本量相对较小。因此,对我们分析结果的解释应谨慎对待,有必要进行更大患者队列的进一步研究以验证我们的发现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/663a/11177418/bece2a342ddb/40942_2024_559_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/663a/11177418/5d44a55bb513/40942_2024_559_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/663a/11177418/fb8e6e48b28b/40942_2024_559_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/663a/11177418/bece2a342ddb/40942_2024_559_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/663a/11177418/5d44a55bb513/40942_2024_559_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/663a/11177418/fb8e6e48b28b/40942_2024_559_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/663a/11177418/bece2a342ddb/40942_2024_559_Fig3_HTML.jpg

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本文引用的文献

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Clin Ophthalmol. 2024 Feb 9;18:431-440. doi: 10.2147/OPTH.S442414. eCollection 2024.
2
Diabetic Retinopathy Screening Using a Portable Retinal Camera in Vanuatu.在瓦努阿图使用便携式视网膜相机进行糖尿病视网膜病变筛查。
Clin Ophthalmol. 2023 Oct 4;17:2919-2927. doi: 10.2147/OPTH.S410425. eCollection 2023.
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Artificial intelligence for telemedicine diabetic retinopathy screening: a review.人工智能在远程医疗糖尿病视网膜病变筛查中的应用:综述
Ann Med. 2023;55(2):2258149. doi: 10.1080/07853890.2023.2258149. Epub 2023 Sep 21.
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Single retinal image for diabetic retinopathy screening: performance of a handheld device with embedded artificial intelligence.用于糖尿病视网膜病变筛查的单张视网膜图像:一款嵌入人工智能的手持设备的性能
Int J Retina Vitreous. 2023 Jul 10;9(1):41. doi: 10.1186/s40942-023-00477-6.
5
Clinical validation of a smartphone-based retinal camera for diabetic retinopathy screening.基于智能手机的视网膜相机用于糖尿病视网膜病变筛查的临床验证。
Acta Diabetol. 2023 Aug;60(8):1075-1081. doi: 10.1007/s00592-023-02105-z. Epub 2023 May 7.
6
Handheld Fundus Camera for Diabetic Retinopathy Screening: A Comparison Study with Table-Top Fundus Camera in Real-Life Setting.用于糖尿病视网膜病变筛查的手持式眼底相机:在实际应用中与台式眼底相机的比较研究
J Clin Med. 2022 Apr 22;11(9):2352. doi: 10.3390/jcm11092352.
7
Comparison of Handheld Retinal Imaging with ETDRS 7-Standard Field Photography for Diabetic Retinopathy and Diabetic Macular Edema.手持式视网膜成像与 ETDRS 7 标准视野摄影在糖尿病视网膜病变和糖尿病黄斑水肿中的比较。
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8
Real-time diabetic retinopathy screening by deep learning in a multisite national screening programme: a prospective interventional cohort study.深度学习在多中心全国性筛查项目中实时筛查糖尿病视网膜病变:一项前瞻性干预性队列研究。
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