Research advances in screening methods for retinopathy of prematurity

doi:10.3877/cma.j.issn.2095-2007.2026.03.008

Abstract

Abstract:

Retinopathy of prematurity (ROP) is a common yet preventable and treatable cause of childhood blindness. Fundus examination serves as a critical tool for early diagnosis, treatment, and follow-up of ROP. Notably, economic development and advances in medical technology have led to significant progress in ROP screening, including refinements in screening criteria, techniques, indications, and equipment portability. The current research and advances in ROP screening, discusses methodologies and their clinical significance, and analyzes challenges in current practice was reviewed, aiming to inform clinical decision-making.

Key words: Retinopathy of Prematurity, Fundus Screening, Newborn, Fundus Lesion

Yinglian Deng, Jie Li, Li Miao, Minhui Zhang, Weidan Yin, Liwei Zhang. Research advances in screening methods for retinopathy of prematurity[J]. Chinese Journal of Ophthalmologic Medicine(Electronic Edition), 2026, 16(03): 169-173.

/ / Recommend

Add to citation manager EndNote|Ris|BibTeX

URL: https://zhykyxzz.cma-cmc.com.cn/EN/10.3877/cma.j.issn.2095-2007.2026.03.008

https://zhykyxzz.cma-cmc.com.cn/EN/Y2026/V16/I03/169

Figures/Tables 2

References 55

[1]	Sen P, Wu WC, Chandra P, et al. Retinopathy of prematurity treatment: Asian perspectives[J]. Eye, 2020, 34(4): 632-642.
[2]	Blencowe H, Lawn JE, Vazquez T, et al. Preterm-associated visual impairment and estimates of retinopathy of prematurity at regional and global levels for 2010[J]. Pediatr Res, 2013, 74(1): 35-49.
[3]	Committee on Practice and Ambulatory Medicine Section on Ophthalmology, American Association of Certified Orthoptists, American Association for Pediatric Ophthalmology and Strabismus, et al. Eye examination in infants, children, and young adults by pediatricians[J]. Pediatrics, 2003, 111(4): 902-907.
[4]	黎晓新. 我国早产儿视网膜病变特点和筛查指南[J]. 中华眼底病杂志，2004，20(6)：384-386.
[5]	陈宜，黎晓新. 严重早产儿视网膜病变的临床特征分析[J]. 中华眼科杂志，2006, 42(9)：838-840.
[6]	中华医学会眼科学分会眼底病学组，中国医师协会眼科医师分会眼底病专委会. 中国早产儿视网膜病变分类和治疗专家共识(2023年)[J]. 中华眼底病杂志，2023，39(9)：720-727.
[7]	Gilbert C. Retinopathy of prematurity: a global perspective of the epidemics, population of babies at risk and implications for control[J]. Early Hum Dev, 2008, 84(2): 77-82.
[8]	Afarid M, Hosseini H, Abtahi B. Screening for retinopathy of prematurity in South of Iran[J]. Middle East Afr J Ophthalmol, 2012, 19(3): 277-281.
[9]	Bolón-Canedo V, Ataer-Cansizoglu E, Erdogmus D, et al. Dealing with inter-expert variability in retinopathy of prematurity: a machine learning approach[J]. Comput Methods Programs Biomed, 2015, 122(1): 1-15.
[10]	Wong ES, Choy RW, Zhang Y, et al. Global and regional trends in retinopathy of prematurity[J]. JAMA ophthalmology, 2025, PMID: 41452606.
[11]	中华医学会眼科学分会眼底病学组. 中国早产儿视网膜病变筛查指南(2014年)[J]. 中华眼科杂志，2014，50(12)：933-935.
[12]	Garner A, Ben-Sira I, Konen W, et al. An international classification of retinopathy of prematurity[J]. Pediatrics (Evanston), 1984, 74(1): 127-133.
[13]	International Committee for the Classification of Retinopathy of Prematurity. The international classification of retinopathy of prematurity revisited[J]. Arch Ophthalmol, 2005, 123(7): 991-999.
[14]	Chiang MF, Quinn GE, Fielder AR, et al. International classification of retinopathy of prematurity[J]. Ophthalmology, 2021, 128(10): e51-e68.
[15]	American Academy of Pediatrics. Screening examination of premature infants for retinopathy of prematurity[J]. Pediatrics, 2001, 108: 809-811.
[16]	Fierson WM, American Academy of Pediatrics Section on Ophthalmology, American Academy of Ophthalmology, et al. Screening examination of premature infants for retinopathy of prematurity[J]. Pediatrics, 2013, 131(1): 189-195.
[17]	Fierson WM, American Academy of Pediatrics Section on Ophthalmology, American Academy of Ophthalmology, et al. Screening examination of premature infants for retinopathy of prematurity[J]. Pediatrics, 2018, 142(6): e20183061.
[18]	中华医学会儿科学分会新生儿学组，中华儿科杂志编辑委员会. 高危新生儿眼病筛查分类管理专家共识(2024)[J]. 中华儿科杂志，2024，62(6)：509-513.
[19]	中华医学会儿科学分会新生儿学组. 早产儿视网膜病预防管理专家共识(2024)[J]. 中华新生儿科杂志(中英文)，2024，39(11)：641-646.
[20]	Zhong Y, Lin X, Yang Y, et al. Screening for retinopathy of prematurity in China: a five-year cohort study in seven screening centers[J]. BMC Ophthalmol, 2025, 25(1): 3.
[21]	卢海，刘敬花，焦永红，等. 重视儿童眼底病的规范筛查，诊断和治疗[J]. 中华眼科医学杂志(电子版)，2020，10(4)：193-197.
[22]	Cheng QE, Daniel E, Pan W, et al. Plus disease in telemedicine approaches to evaluating acute-phase ROP (e-ROP) study: Characteristics, predictors, and accuracy of image grading[J]. Ophthalmology, 2019, 126(6): 868-875.
[23]	Timkoviĉ J, Nowaková J, Kubíĉek J, et al. Retinal image dataset of infants and retinopathy of prematurity [J]. Sci Data, 2024, 11(1): 814.
[24]	Vinekar A, Rao SV, Murthy S, et al. A novel, low-cost, wide-field, infant retinal camera，" Neo" ：Technical and safety report for the use on premature infants[J]. Transl Vis Sci Technol, 2019, 8(2): 2.
[25]	Patel SN, Shi A, Wibbelsman TD, et al. Ultra-widefield retinal imaging: an update on recent advances[J]. Ther Adv Ophthalmol, 2020, PMID: 32010879.
[26]	Wakabayashi T, Patel SN, Campbell J, et al. Advances in retinopathy of prematurity imaging[J]. Saudi J Ophthalmol, 2022, 36(3): 243-250.
[27]	Kvopka M, Chan W, Lake SR, et al. Fundus fluorescein angiography imaging of retinopathy of prematurity in infants: A review[J]. Surv Ophthalmol, 2023, 68(5): 849-860.
[28]	Prakalapakorn SG, Wallace DK, Freedman SF. Retinal imaging in premature infants using the Pictor noncontact digital camera[J]. J AAPOS, 2014, 18(4): 321-326.
[29]	李萌，张坚，严宏. 早产儿视网膜病变眼底检查方法及眼底图像特征研究进展[J]. 国际眼科杂志，2023，23(5)：783-786.
[30]	叶海昀，王斯颖，李苑，等. Optomed手持式数码相机在早产儿视网膜病变筛查中的临床应用[J]. 中国斜视与小儿眼科杂志，2017，25(3)：15-17，6.
[31]	Wintergerst MW, Jansen LG, Holz FG, et al. A novel device for smartphone-based fundus imaging and documentation in clinical practice: comparative image analysis study[J]. JMIR Mhealth Uhealth, 2020, 8(7): e17480.
[32]	Lin JY, Kang EC, Banker AS, et al. Comparison of RetCam and smartphone-based photography for retinopathy of prematurity screening[J]. Diagnostics, 2022, 12(4): 945
[33]	Kaur R, Singh H, Samria S, et al. MII RetCam assisted smartphone-based fundus imaging (MSFI)-A boon for paediatric retinal imaging[J]. Eye, 2020, 34(8): 1307-1309.
[34]	Brown JM, Campbell JP, Beers A, et al. Automated diagnosis of plus disease in retinopathy of prematurity using deep convolutional neural networks[J]. JAMA Ophthalmol, 2018, 136(7): 803-810.
[35]	Gensure RH, Chiang MF, Campbell JP. Artificial intelligence for retinopathy of prematurity[J]. Curr Opin Ophthalmol, 2020, 31(5): 312-317.
[36]	Wang J, Ju R, Chen Y, et al. Automated retinopathy of prematurity screening using deep neural networks[J]. EBioMedicine, 2018, 35: 361-368.
[37]	Attallah O. DIAROP: automated deep learning-based diagnostic tool for retinopathy of prematurity[J]. Diagnostics, 2021, 11(11): 2034.
[38]	Tong Y, Lu W, Deng QQ, et al. Automated identification of retinopathy of prematurity by image-based deep learning[J]. Eye Vis, 2020, 7(1): 40.
[39]	Ramanathan A, Athikarisamy SE, Lam GC. Artificial intelligence for the diagnosis of retinopathy of prematurity: a systematic review of current algorithms[J]. Eye, 2023, 37(12): 2518-2526.
[40]	Klran-Yenice E, Kara C, Erdaᶊ ÇB. Automated detection of type 1 ROP, type 2 ROP and A-ROP based on deep learning[J]. Eye, 2024, 38(13): 2644-2648.
[41]	Coyner AS, Young BK, Ostmo SR, et al. Use of an artificial intelligence-generated vascular severity score improved plus disease diagnosis in retinopathy of prematurity[J]. Ophthalmology, 2024, 131(11): 1290-1296.
[42]	Agrawal R, Kulkarni S, Deshpande M, et al. Classification of stages 1, 2, 3 and preplus, plus disease of ROP using MultiCNN_LSTM classifier[J]. MethodsX, 2025, 14: 103182.
[43]	Peng Y, Zhu W, Chen Z, et al. Automatic staging for retinopathy of prematurity with deep feature fusion and ordinal classification strategy[J]. IEEE Trans Med Imaging, 2021, 40(7): 1750-1762.
[44]	Jia X, Qiu J, Ning Y, et al. ROP lesion segmentation via sequence coding and block balancing[J]. Med Image Anal, 2025, PMID：103723.
[45]	Agrawal R, Kulkarni S, Walambe R, et al. Assistive framework for automatic detection of all the zones in retinopathy of prematurity using deep learning[J]. J Digit Imaging, 2021, 34(4): 932-947.
[46]	Peng Y, Xu H, Zhao L, et al. Automatic zoning for retinopathy of prematurity with a key area location system[J]. Biomed Opt Express, 2024, 15(2): 725-742.
[47]	Rashidian P, Karami S, Salehi SA. A review on retinopathy of prematurity[J]. Med Hypothesis Discov Innov Ophthalmol, 2025, 13(4): 201.
[48]	Wu Q, Hu Y, Mo Z, et al. Development and validation of a deep learning model to predict the occurrence and severity of retinopathy of prematurity[J]. JAMA Netw Open, 2022, 5(6): e2217447.
[49]	姜海涛，李国仁. 我国早产儿视网膜病变的筛查现状[J]. 国际眼科杂志，2021，21(8)：1386-1389.
[50]	Wu X, Wu Y, Tu Z, et al. Cost-effectiveness and cost-utility of a digital technology-driven hierarchical healthcare screening pattern in China[J]. Nat Commun, 2024, 15(1): 3650.
[51]	Fei P, Liu Z, He L, et al. Early detection of ocular abnormalities in a Chinese multicentre neonatal eye screening programme-1-year result[J]. Acta Ophthalmol, 2021, 99(3): e415-e422.
[52]	Gu C, Wang Y, Jiang Y, et al. Application of artificial intelligence system for screening multiple fundus diseases in Chinese primary healthcare settings: a real-world, multicentre and cross-sectional study of 4795 cases[J]. Br J Ophthalmol, 2024, 108(3): 424-431.
[53]	Zhang Y, Song X, Xie J, et al. Large depth-of-field ultra-compact microscope by progressive optimization and deep learning[J]. Nat Commun, 2023, 14(1): 4118.
[54]	Zhang R, Dong L, Fu X, et al. Trends in the prevalence of common retinal and optic nerve diseases in China: An artificial intelligence based national screening[J]. Transl Vis Sci Technol, 2024, 13(4): 28.
[55]	Xuan Q, Ouyang Y, Wang Y, et al. Multiplatform metabolomics reveals novel serum metabolite biomarkers in diabetic retinopathy subjects[J]. Adv Sci, 2020, 7(22): 2001714.

参数	生产商	视野范围	图片分辨率(像素)	眼底造影功能	重量(探头)及操作方式
RetCam	Natus Medical	130°、120°、80°及30°，可更换镜头	640×68	可选配	手持探头，约800 g
RetCam Envision	Natus Medical	130°	1440×1080	标配，一键切换	手持探头，脚踏＋触摸屏双操作
3netraneo	Forus Health	120°	2040×2020	无	单手持握，约740 g
Phoenix ICON	Forus Health	120°	1240×1240	内置模块	手持探头，较RetCam轻20%
Panocam(LT/Pro)	Visunex Medical Systems	120°	800万	可选配	手持探头＋无线连接，约200 g

参数	生产商	视野范围	图片分辨率(像素)	眼底造影功能	重量(探头)及操作方式
RetCam	Natus Medical	130°、120°、80°及30°，可更换镜头	640×68	可选配	手持探头，约800 g
RetCam Envision	Natus Medical	130°	1440×1080	标配，一键切换	手持探头，脚踏＋触摸屏双操作
3netraneo	Forus Health	120°	2040×2020	无	单手持握，约740 g
Phoenix ICON	Forus Health	120°	1240×1240	内置模块	手持探头，较RetCam轻20%
Panocam(LT/Pro)	Visunex Medical Systems	120°	800万	可选配	手持探头＋无线连接，约200 g

参数	制造商	视野范围	图片分辨率(像素)	瞳孔要求	重量及操作方式
超广角眼底成像	Optos	200°，眼位引导可达220°~240°	3900×3072	≥2 mm	手持一体化，<500 g
Pictor	Volk Optical	45°	1920×1440	≥3mm	50°
Optomed	Optomed	40°	2560×1920	≥2.5mm	手持一体化，<500 g
RetinaScope	Dino-Lite Europe	单张50°，拼接200°	1280×720	≥3 mm	手持＋智能手机连接，<300 g
MII RetCam	MII RetCam Inc	50°	依赖手机摄像头	≥3 mm	手机＋专用适配器

参数	制造商	视野范围	图片分辨率(像素)	瞳孔要求	重量及操作方式
超广角眼底成像	Optos	200°，眼位引导可达220°~240°	3900×3072	≥2 mm	手持一体化，<500 g
Pictor	Volk Optical	45°	1920×1440	≥3mm	50°
Optomed	Optomed	40°	2560×1920	≥2.5mm	手持一体化，<500 g
RetinaScope	Dino-Lite Europe	单张50°，拼接200°	1280×720	≥3 mm	手持＋智能手机连接，<300 g
MII RetCam	MII RetCam Inc	50°	依赖手机摄像头	≥3 mm	手机＋专用适配器

Please choose a citation manager

Content to export