摘要目的:构建并评估基于彩色眼底像和人工智能（AI）辅助筛查视神经炎（ON）及非动脉炎性前部缺血性视神经病变（NAION）的筛查诊断系统。方法:诊断性试验研究。2016年至2020年于中山大学中山眼科中心检查确诊的NAION患者178例267只眼（NAION组）、ON患者204例346只眼（ON组），以及2018年至2020年经视力、眼压及光相干断层扫描（OCT）检查为眼底正常的健康者513名1 160只眼（正常对照组）共2 909张彩色眼底像作为筛查诊断系统的数据集，其中NAION组、ON组、正常对照组分别为730、805、1 374张。将正确标注后的彩色眼底像作为输入数据，选用EfficientNet-B0算法进行系统训练并验证，最终构建是否存在异常视盘、是否存在ON和是否存在NAION的3个筛查系统（二分法）。采用受试者工作特征（ROC）曲线、ROC下面积（AUC）、准确度、灵敏度、特异性和热力图作为诊断效能和科学性的判断指标。结果:测试集中，诊断是否存在异常视盘、是否存在ON、是否存在NAION的AUC分别为0.967 [95%可信区间（ CI）0.947~0.980]、0.964（95% CI 0.938~0.979）、0.979（95% CI 0.958~0.989），并且系统在决策过程中的激活区域主要位于视盘。 结论:基于彩色眼底像的异常视盘、ON和NAION筛查诊断系统具有准确高效的诊断性能。

abstractsObjective:To construct and evaluate a screening and diagnostic system based on color fundus images and artificial intelligence (AI)-assisted screening for optic neuritis (ON) and non-arteritic anterior ischemic optic neuropathy (NAION).Methods:A diagnostic test study. From 2016 to 2020, 178 cases 267 eyes of NAION patients (NAION group) and 204 cases 346 eyes of ON patients (ON group) were examined and diagnosed in Zhongshan Ophthalmic Center of Sun Yat-sen University; 513 healthy individuals of 1 160 eyes (the normal control group) with normal fundus by visual acuity, intraocular pressure and optical coherence tomography examination were collected from 2018 to 2020. All 2 909 color fundus images were as the data set of the screening and diagnosis system, including 730, 805, and 1 374 images for the NAION group, ON group, and normal control group, respectively. The correctly labeled color fundus images were used as input data, and the EfficientNet-B0 algorithm was selected for model training and validation. Finally, three systems for screening abnormal optic discs, ON, and NAION were constructed. The subject operating characteristic (ROC) curve, area under the ROC (AUC), accuracy, sensitivity, specificity, and heat map were used as indicators of diagnostic efficacy.Results:In the test data set, the AUC for diagnosing the presence of an abnormal optic disc, the presence of ON, and the presence of NAION were 0.967 [95% confidence interval ( CI) 0.947-0.980], 0.964 (95% CI 0.938-0.979), and 0.979 (95% CI 0.958-0.989), respectively. The activation area of the systems were mainly located in the optic disc area in the decision-making process. Conclusion:Abnormal optic disc, ON and NAION, and screening diagnostic systems based on color fundus images have shown accurate and efficient diagnostic performance.