机构：[1]Doheny Image Reading Center, Doheny Eye Institute, Los Angeles, CA, USA[2]Department of Ophthalmology, Beijing Friendship Hospital, Capital Medical University, Beijing, China首都医科大学附属北京友谊医院[3]Narayana Nethralaya, Bangalore, India[4]Eyenuk Inc., Los Angeles, CA, USA[5]Department of Ophthalmology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
PurposeWe examined the sensitivity and specificity of an automated algorithm for detecting referral-warranted diabetic retinopathy (DR) on Optos ultrawidefield (UWF) pseudocolour images. MethodsPatients with diabetes were recruited for UWF imaging. A total of 383 subjects (754 eyes) were enrolled. Nonproliferative DR graded to be moderate or higher on the 5-level International Clinical Diabetic Retinopathy (ICDR) severity scale was considered as grounds for referral. The software automatically detected DR lesions using the previously trained classifiers and classified each image in the test set as referral-warranted or not warranted. Sensitivity, specificity and the area under the receiver operating curve (AUROC) of the algorithm were computed. ResultsThe automated algorithm achieved a 91.7%/90.3% sensitivity (95% CI 90.1-93.9/80.4-89.4) with a 50.0%/53.6% specificity (95% CI 31.7-72.8/36.5-71.4) for detecting referral-warranted retinopathy at the patient/eye levels, respectively; the AUROC was 0.873/0.851 (95% CI 0.819-0.922/0.804-0.894). ConclusionDiabetic retinopathy (DR) lesions were detected from Optos pseudocolour UWF images using an automated algorithm. Images were classified as referral-warranted DR with a high degree of sensitivity and moderate specificity. Automated analysis of UWF images could be of value in DR screening programmes and could allow for more complete and accurate disease staging.
基金：
Carl Zeiss Meditec; Optos; AllerganAllergan; GenentechRoche HoldingGenentech
第一作者机构：[1]Doheny Image Reading Center, Doheny Eye Institute, Los Angeles, CA, USA[2]Department of Ophthalmology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
通讯作者：
通讯机构：[1]Doheny Image Reading Center, Doheny Eye Institute, Los Angeles, CA, USA[5]Department of Ophthalmology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA[*1]Doheny Eye Institute DVRC 211 1355 San Pablo Street Los Angeles CA 90033 USA
推荐引用方式(GB/T 7714)：
Wang Kang,Jayadev Chaitra,Nittala Muneeswar G.,et al.Automated detection of diabetic retinopathy lesions on ultrawidefield pseudocolour images[J].ACTA OPHTHALMOLOGICA.2018,96(2):e168-e173.doi:10.1111/aos.13528.
