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A new handheld fundus camera combined with visual artificial intelligence facilitates diabetic retinopathy screening

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International Journal of Ophthalmology(English edition) 2022年第4期15卷 620-627页

作者： Shang Ruan Yang Liu Wei-Ting Hu Hui-Xun Jia Shan-Shan Wang Min-Lu Song Meng-Xi Shen Da-Wei Luo Tao Ye Feng-Hua Wang Department of Ophthalmology Shanghai General HospitalShanghai Jiao Tong UniversitySchool of MedicineShanghai 200080China Shanghai Phoebus Medical Co.Ltd. Shanghai 200000China West Nanjing Road Community Health Center Shanghai 200000China Shanghai Key Laboratory of Ocular Fundus Diseases Shanghai Engineering Center for Visual Science and PhotomedicineNational Clinical Research Center for Eye DiseasesShanghai Engineering Center for Precise Diagnosis and Treatment of Eye DiseasesShanghai 200025China

AIM: To explore the performance in diabetic retinopathy(DR) screening of artificial intelligence(AI) system by evaluating the image quality of a handheld Optomed Aurora fundus camera in comparison to traditional tabletop fundus cameras and the diagnostic accuracy of DR of the two modalities. METHODS: Overall, 630 eyes were included from three centers and screened by a handheld camera(Aurora, Optomed, Oulu, Finland) and a table-top camera. Image quality was graded by three masked and experienced ophthalmologists. The diagnostic accuracy of the handheld camera and AI system was evaluated in assessing DR lesions and referable ***: Under nonmydriasis status, the handheld fundus camera had better image quality in centration, clarity, and visible range(1.47, 1.48, and 1.40) than conventional tabletop cameras(1.30, 1.28, and 1.18;Phandheld fundus camera slightly lower. The sensitivity and specificity for the detection of referable DR with the handheld camera were 82.1%(95%CI: 72.1%-92.2%) and 97.4%(95%CI: 95.4%-99.5%), respectively. The performance of AI detection of DR using the Phoebus Algorithm was satisfactory;however, Phoebus showed a high sensitivity(88.2%, 95%CI: 79.4%-97.1%) and low specificity(40.7%, 95%CI: 34.1%-47.2%) when detecting referable ***: The handheld Aurora fundus camera combined with autonomous AI system is well-suited in DR screening without mydriasis because of its high sensitivity of DR detection as well as its image quality, but its specificity needs to be improved with better modeling of the data. Use of this new system is safe and effective in the detection of referable DR in real world practice.

关键词： diabetic retinopathy image quality handheld camera artificial intelligence

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