An Artificial Intelligence System for Screening and Recommending the Treatment Modalities for Retinopathy of Prematurity

Liu, Yaling1; Du, Yueshanyi1,2; Wang, Xi3,4,5; Zhao, Xinyu1; Zhang, Sifan6; Yu, Zhen1; Wu, Zhenquan1; Ntentakis, Dimitrios P.7,8; Tian, Ruyin1; Chen, Yi1; Wang, Cui1; Yao, Xue1; Li, Ruijiang5; Heng, Pheng-Ann4; Zhang, Guoming1

2023-10-01

10.1097/APO.0000000000000638

ASIA-PACIFIC JOURNAL OF OPHTHALMOLOGY   影响因子和分区

2162-0989

Purpose: The purpose of this study was to develop an artificial intelligence (AI) system for the identification of disease status and recommending treatment modalities for retinopathy of prematurity (ROP).Methods: This retrospective cohort study included a total of 24,495 RetCam images from 1075 eyes of 651 preterm infants who received RetCam examination at the Shenzhen Eye Hospital in Shenzhen, China, from January 2003 to August 2021. Three tasks included ROP identification, severe ROP identification, and treatment modalities identification (retinal laser photocoagulation or intravitreal injections). The AI system was developed to identify the 3 tasks, especially the treatment modalities of ROP. The performance between the AI system and ophthalmologists was compared using extra 200 RetCam images.Results: The AI system exhibited favorable performance in the 3 tasks, including ROP identification [area under the receiver operating characteristic curve (AUC), 0.9531], severe ROP identification (AUC, 0.9132), and treatment modalities identification with laser photocoagulation or intravitreal injections (AUC, 0.9360). The AI system achieved an accuracy of 0.8627, a sensitivity of 0.7059, and a specificity of 0.9412 for identifying the treatment modalities of ROP. External validation results confirmed the good performance of the AI system with an accuracy of 92.0% in all 3 tasks, which was better than 4 experienced ophthalmologists who scored 56%, 65%, 71%, and 76%, respectively.Conclusions: The described AI system achieved promising outcomes in the automated identification of ROP severity and treatment modalities. Using such algorithmic approaches as accessory tools in the clinic may improve ROP screening in the future.

artificial intelligence RetCam images retinopathy of prematurity screening treatment modalities

SCI

英语

其他

Shenzhen-Hong Kong[SGDX20190920110403741] ; Guangdong Basic and Applied Basic Research Foundation[2022A1515012326] ; Shenzhen Key Medical Discipline Construction Fund[SZXK038] ; Shenzhen Fund for Guangdong Provincial High-Level Clinical Key Specialties[SZGSP014] ; Shenzhen Science and Technology Program[JSGG20201102174200001] ; National Natural Science Foundation of China[82271103\]

Ophthalmology

Ophthalmology

WOS:001105054100006

ASIA-PACIFIC ACAD OPHTHALMOLOGY-APAO

Web of Science

1.Jinan Univ, Shenzhen Eye Hosp, Shenzhen Eye Inst, Shenzhen 518040, Peoples R China
2.Guizhou Med Univ, Guiyang, Guizhou, Peoples R China
3.Zhejiang Lab, Hangzhou, Peoples R China
4.Chinese Univ Hong Kong, Dept Comp Sci & Engn, Hong Kong 999077, Peoples R China
5.Stanford Univ, Sch Med, Dept Radiat Oncol, Palo Alto, CA USA
6.Southern Univ Sci & Technol, Sch Med, Shenzhen, Peoples R China
7.Ines & Fred Yeatts Retina Res Lab, Retina Serv, Boston, MA USA
8.Harvard Med Sch, Dept Ophthalmol, Angiogenesis Lab, Massachusetts Eye & Ear, Boston, MA USA

Liu, Yaling,Du, Yueshanyi,Wang, Xi,et al. An Artificial Intelligence System for Screening and Recommending the Treatment Modalities for Retinopathy of Prematurity[J]. ASIA-PACIFIC JOURNAL OF OPHTHALMOLOGY,2023,12(5).

Liu, Yaling.,Du, Yueshanyi.,Wang, Xi.,Zhao, Xinyu.,Zhang, Sifan.,...&Zhang, Guoming.(2023).An Artificial Intelligence System for Screening and Recommending the Treatment Modalities for Retinopathy of Prematurity.ASIA-PACIFIC JOURNAL OF OPHTHALMOLOGY,12(5).

Liu, Yaling,et al."An Artificial Intelligence System for Screening and Recommending the Treatment Modalities for Retinopathy of Prematurity".ASIA-PACIFIC JOURNAL OF OPHTHALMOLOGY 12.5(2023).