AIM: To ensure the diagnostic value of computer aided techniques in diabetic retinopathy(DR) detection based on ophthalmic photography(OP). METHODS: PubM ed, EMBASE, Ei village, IEEE Xplore and Cochrane Library databa...AIM: To ensure the diagnostic value of computer aided techniques in diabetic retinopathy(DR) detection based on ophthalmic photography(OP). METHODS: PubM ed, EMBASE, Ei village, IEEE Xplore and Cochrane Library database were searched systematically for literatures about computer aided detection(CAD) in DR detection. The methodological quality of included studies was appraised by the Quality Assessment Tool for Diagnostic Accuracy Studies(QUADAS-2). Meta-Di Sc was utilized and a random effects model was plotted to summarize data from those included studies. Summary receiver operating characteristic curves were selected to estimate the overall test performance. Subgroup analysis was used to identify the efficiency of CAD in detecting DR, exudates(EXs), microaneurysms(MAs) as well as hemorrhages(HMs), and neovascularizations(NVs). Publication bias was analyzed using STATA. RESULTS: Fourteen articles were finally included in this Meta-analysis after literature review. Pooled sensitivity and specificity were 90%(95%CI, 85%-94%) and 90%(95%CI, 80%-96%) respectively for CAD in DR detection. With regard to CAD in EXs detecting, pooled sensitivity, specificity were 89%(95%CI, 88%-90%) and99%(95%CI, 99%-99%) respectively. In aspect of MAs and HMs detection, pooled sensitivity and specificity of CAD were 42%(95%CI, 41%-44%) and 93%(95%CI, 93%-93%) respectively. Besides, pooled sensitivity and specificity were 94%(95%CI, 89%-97%) and 87%(95%CI, 83%-90%) respectively for CAD in NVs detection. No potential publication bias was observed. CONCLUSION: CAD demonstrates overall high diagnostic accuracy for detecting DR and pathological lesions based on OP. Further prospective clinical trials are needed to prove such effect.展开更多
基金Supported by National Key R&D Program of China (No.2018YFC1314900 No.2018YFC1314902)+2 种基金Nantong “226 Project”Excellent Key Teachers in the “Qing Lan Project” of Jiangsu Colleges and UniversitiesJiangsu Students’ Platform for Innovation and Entrepreneurship Training Program (No.201910304108Y)
文摘AIM: To ensure the diagnostic value of computer aided techniques in diabetic retinopathy(DR) detection based on ophthalmic photography(OP). METHODS: PubM ed, EMBASE, Ei village, IEEE Xplore and Cochrane Library database were searched systematically for literatures about computer aided detection(CAD) in DR detection. The methodological quality of included studies was appraised by the Quality Assessment Tool for Diagnostic Accuracy Studies(QUADAS-2). Meta-Di Sc was utilized and a random effects model was plotted to summarize data from those included studies. Summary receiver operating characteristic curves were selected to estimate the overall test performance. Subgroup analysis was used to identify the efficiency of CAD in detecting DR, exudates(EXs), microaneurysms(MAs) as well as hemorrhages(HMs), and neovascularizations(NVs). Publication bias was analyzed using STATA. RESULTS: Fourteen articles were finally included in this Meta-analysis after literature review. Pooled sensitivity and specificity were 90%(95%CI, 85%-94%) and 90%(95%CI, 80%-96%) respectively for CAD in DR detection. With regard to CAD in EXs detecting, pooled sensitivity, specificity were 89%(95%CI, 88%-90%) and99%(95%CI, 99%-99%) respectively. In aspect of MAs and HMs detection, pooled sensitivity and specificity of CAD were 42%(95%CI, 41%-44%) and 93%(95%CI, 93%-93%) respectively. Besides, pooled sensitivity and specificity were 94%(95%CI, 89%-97%) and 87%(95%CI, 83%-90%) respectively for CAD in NVs detection. No potential publication bias was observed. CONCLUSION: CAD demonstrates overall high diagnostic accuracy for detecting DR and pathological lesions based on OP. Further prospective clinical trials are needed to prove such effect.
基金Project supported by the National Natural Science Foundation of China(Nos.81472504,81401822,and 81572177)the Science and Technology Foundation of Zhejiang Province(No.2016C33151)+1 种基金the Medical Science and Technology Project of Zhejiang Province of China(Nos.2016146428,2016KYA096,and 2017KY071)the Zhejiang Provincial Natural Science Foundation of China(Nos.Y17H160033,LQ14H060002,and LY14H060004)
