人工智能应用于基层医院糖尿病视网膜病变大规模筛查的临床价值研究

Clinical value of artificial intelligence in large-scale screening of diabetic retinopathy in grassroots hospitals

目的探讨人工智能(AI)系统用于基层医院糖尿病视网膜病变(DR)筛查的临床价值。方法选取2020年7月至2021年12月在海宁市人民医院行DR筛查的28300例(56600眼)糖尿病患者为研究对象,采用分层随机取样法抽取3512例(7024眼)糖尿病患者进行研究。以AFC-330自动免散瞳眼底照相机拍摄的眼底图片作为图片库,由AI系统(浙大睿医AI系统视网膜阅片系统)行DR诊断、DR分级诊断和有转诊意义的DR(RDR)诊断。并由本院眼科医师在眼底照相、光学相干断层扫描成像(OCT)和荧光素眼底血管造影(FFA)检查结果参考下给予DR诊断、DR分级诊断和RDR诊断。比较AI系统阅片与眼科医师阅片对DR诊断、DR分级诊断、RDR诊断效能及单张阅片平均耗时。采用Kappa检验评估AI系统与眼科医师诊断DR、DR分级及RDR的一致性。结果7024眼中,以眼科医师诊断为金标准,AI系统诊断DR的灵敏度为91.69%,特异度为98.63%,两者对DR诊断的一致性比较差异有统计学意义(Kappa=0.831,P<0.001)。AI系统诊断轻度NPDR、中度NP-DR、重度NPDR及PDR的灵敏度分别为82.72%、84.36%、86.11%、86.95%,特异度分别为98.93%、99.27%、99.92%、99.97%,两者对DR分级诊断的一致性比较差异有统计学意义(Kappa=0.847,P<0.001)。AI系统诊断RDR的灵敏度为88.16%,特异度为99.32%,两者对RDR诊断的一致性比较差异有统计学意义(Kappa=0.828,P<0.001)。AI系统单张阅片平均耗时为(1.58±0.22)s,短于眼科医师的(5.83±2.11)s,差异有统计学意义(P<0.001)。结论AI系统用于糖尿病患者DR诊断、DR分级诊断以及RDR诊断的灵敏度、特异度与眼科医师相当,两者具有高度一致性,可用于基层医院大规模的DR初筛工作。

Objective To explore the clinical value of artificial intelligence(AI)system in screening diabetic retinopathy(DR)in grassroots hospitals.Methods A total of 28300 diabetic patients(56600 eyes)underwent DR screening in Haining People's Hospital from July 2020 to December 2021.Among them 3512 cases(7024 eyes)were selected for the study by stratified random sampling method.Using fundus pictures from AFC 330 automatic mydriasis fundus camera as a picture library,the AI system(Zhejiang Ruiyi Medical AI System Retina Reading System)provided diagnosis of DR,DR grading and referable diabetic retinopathy(RDR).DR diagnosis,DR grading diagnosis and RDR diagnosis were given by ophthalmologists based on the results of fundus photography,optical coherence tomography(OCT)and fluorescein fundus angiography(FFA).DR diagnosis,DR grading diagnosis,RDR diagnosis and the average time consuming were compared between the efficacy of AI system and ophthalmologist.Kappa test was used to evaluate the consistency of AI system with ophthalmologist's diagnosis of DR,DR grading and RDR.Results With ophthalmologists'manual diagnosis as the gold standard,the sensitivity and specificity of the AI system in diagnosing DR were 91.69%and 98.63%,respectively;the Kappa value of the consistency analysis of the two diagnostic results was 0.831(P<0.001).The sensitivity and specificity of AI system in diagnosing mild non-proliferative diabetic retinopathy(NPDR),moderate NPDR,severe NPDR,and proliferative diabetic retinopathy(PDR)were 82.72%,84.36%,86.11%,86.95%and 98.93%,99.27%,99.92%,99.97%,respectively;the Kappa value of the consistency analysis between the two methods for DR grading diagnosis was 0.847(P<0.001).The sensitivity and specificity of the AI system for diagnosing RDR are 88.16%and 99.32%,respectively.The Kappa value of the consistency analysis between the two for RDR diagnosis is 0.828(P<0.001).The average time taken for a single film reading in the AI system was(1.58±0.22)s,which is shorter than that of the manual reading(5.83±2.11)s(P<0.001).Conclusion AI system has the same sensitivity and specificity as manual reading in DR diagnosis,DR grading and RDR diagnosis of diabetes patients with high consistency,indicating that AI system may be used for large-scale DR screening in grassroots hospitals.