Efficacy of artificial intelligence-based screening for diabetic retinopathy in type 2 diabetes mellitus patients
Xiaoting Pei, Xi Yao, Yingrui Yang, Hongmei Zhang, Mengting Xia, Ranran Huang, Yuming Wang, Zhijie Li
Abstract
AIM: To explore the efficacy of artificial intelligence (AI)-based screening for diabetic retinopathy (DR) in type 2 diabetes mellitus (T2DM) patients. METHODS: Data were obtained from 549 T2DM patients who visited the Fundus Disease Center at Henan Provincial People's Hospital from 2018/10-2020/09. DR identification and grading were conducted by two retina specialists, EyeWisdom®DSS and EyeWisdom®MCS, with ophthalmologist grading as reference standard, efficacy of EyeWisdom was evaluated according to sensitivity, specificity, positive predictive value, and negative predictive value. RESULTS: Ophthalmologists detected 324 DR cases. Among them, there were 43 of mild non-proliferative DR (NPDR), 79 of moderate NPDR, 61 of severe NPDR, and 141 of proliferative DR (PDR). EyeWisdom®DSS detected 337 DR and EyeWisdom®MCS detected 264 DR. Sensitivity and specificity of EyeWisdom®DSS were 91.0%(95 %CI: 87.3%-93.8%) and 81.3% (95 %CI: 75.5%-86.1%), while EyeWisdom®MCS correctly identified 76.2%(95 %CI: 71.1%-80.7%) of patients with DR and 92.4%(95 %CI: 87.9%-95.4%) of patients without DR. EyeWisdom®DSS showed 76.5%(95 %CI: 69.6%-82.3%) sensitivity and 78.4%(95 %CI: 73.7%-82.5%) specificity for detecting NPDR and 64.5%(95 %CI: 56.0%-72.3%) sensitivity and 93.1%(95 %CI: 90.1%-95.3%) specificity for diagnosing PDR. CONCLUSION: EyeWisdom®DSS is effective in screening for DR, and the accuracy of EyeWisdom®MCS was higher for identifying patients without DR. It is valuable to carry out AI-based DR screening in poorer regions.