糖尿病患者眼底照相人工与人工智能分析结果比较

Analysis and comparison of artificial and artificial intelligence in diabetic fundus photography

目的对比人工与人工智能分析对糖尿病患者眼底照相眼底病变判别的一致性。方法回顾性研究。2018年5月至2019年5月郑州大学第一附属医院内分泌科连续收治的糖尿病患者1053例2106只眼纳入研究。其中,男性888例,女性165例;年龄20~70岁,平均年龄53岁。所有患者均采用日本Kowa无散瞳眼底照相机进行眼底检查。采用上工眼科云网筛查平台人工智能分析自动检测渗出、出血、微动脉瘤等糖尿病视网膜病变(DR)的特质性病变,并根据DR国际分期标准对图像检测结果进行自动分级。由两位主治医师进行人工分析,并由主任医师审核,以保证人工分析的准确性。两种分析方法分析结果存在差异时,以人工分析结果为标准。计算并对比两种分析方法的一致率。一致率=(诊断结果相同眼数/总收集有效眼数)×100%。对人工分析和人工智能分析结果进行Kappa一致性检验,0.0≤κ<0.2为一致性程度很差,0.2≤κ<0.4为一致性较差,0.4≤κ<0.6为一致性中等,0.6≤κ<1.0为一致性较好。结果 2106只眼中,排除因病情严重人工智能无法识别64只眼,最终纳入分析2042只眼。人工分析与人工智能分析结果完全一致者1835只眼,占89.86%;分析有差异者207只眼,占10.14%。两者差异主要表现为:(1)人工智能分析为点状出血、渗出,而人工分析为正常96只眼(96/2042 ,4.70% );(2)人工智能分析为玻璃膜疣,而人工分析为点状渗出71只眼(71/2042,3.48% );(3 )人工智能分析为正常或玻璃体变性,而人工分析为点状渗出或出血或微动脉瘤40只眼(40/2042,1.95% )。人工分析、人工智能分析对DR的诊断率分别为23.2%、20.2%,对非DR的诊断率分别为76.8%、79.8%。人工智能判读符合度达87.8%。Kappa一致性检验结果显示,人工分析和人工智能分析诊断结果呈中等一致性(κ=0.576,P<0.01 )。结论人工分析与人工智能分析对糖尿病患者眼底照相眼底病变判别呈中等一致性。人工智能判读符合度达87.8%。

Objective To compare the consistency of artificial analysis and artificial intelligence analysis in the identification of fundus lesions in diabetic patients.Methods A retrospective study.From May 2018 to May 2019,1053 consecutive diabetic patients(2106 eyes)of the endocrinology department of the First Affiliated Hospital of Zhengzhou University were included in the study.Among them,888 patients were males and 165 were females.They were 20-70 years old,with an average age of 53 years old.All patients were performed fundus imaging on diabetic Inspection by useing Japanese Kowa non-mydriatic fundus cameras.The artificial intelligence analysis of Shanggong's ophthalmology cloud network screening platform automatically detected diabetic retinopathy(DR)such as exudation,bleeding,and microaneurysms,and automatically classifies the image detection results according to the DR international staging standard.Manual analysis was performed by two attending physicians and reviewed by the chief physician to ensure the accuracy of manual analysis.When differences appeared between the analysis results of the two analysis methods,the manual analysis results shall be used as the standard.Consistency rate were calculated and compared.Consistency rate=(number of eyes with the same diagnosis result/total number of effective eyes collected)×100%.Kappa consistency test was performed on the results of manual analysis and artificial intelligence analysis,0.0≤κ<0.2 was a very poor degree of consistency,0.2≤κ<0.4 meant poor consistency,0.4≤κ<0.6 meant medium consistency,and 0.6≤κ<1.0 meant good consistency.Results Among the 2106 eyes,64 eyes were excluded that cannot be identified by artificial intelligence due to serious illness,2042 eyes were finally included in the analysis.The results of artificial analysis and artificial intelligence analysis were completely consistent with 1835 eyes,accounting for 89.86%.There were differences in analysis of 207 eyes,accounting for 10.14%.The main differences between the two are as follows:(1)Artificial intelligence analysis points Bleeding,oozing,and manual analysis of 96 eyes(96/2042,4.70%);(2)Artificial intelligence analysis of drusen,and manual analysis of 71 eyes(71/2042,3.48%);(3)Artificial intelligence analyzes normal or vitreous degeneration,while manual analysis of punctate exudation or hemorrhage or microaneurysms in 40 eyes(40/2042,1.95%).The diagnostic rates for non-DR were 23.2%and 20.2%,respectively.The diagnostic rates for non-DR were 76.8%and 79.8%,respectively.The accuracy of artificial intelligence interpretation is 87.8%.The results of the Kappa consistency test showed that the diagnostic results of manual analysis and artificial intelligence analysis were moderately consistent(κ=0.576,P<0.01).Conclusions Manual analysis and artificial intelligence analysis showed moderate consistency in the diagnosis of fundus lesions in diabetic patients.The accuracy of artificial intelligence interpretation is 87.8%.