基于人工智能的计算机辅助诊断在病毒性肺炎中的应用价值

Application value of computer aided diagnosis based on artificial intelligence in viral pneumonia

目的探讨基于人工智能的计算机辅助诊断(computer-aided diagnosis,CAD)在病毒性肺炎(viral pneumonia)CT诊断中的应用价值。方法选取潍坊医学院附属医院就诊并确诊为病毒性肺炎的患者10例,共计37例次的胸部CT数据,随访同一患者前后两次胸部高分辨率CT(High resolution CT,HRCT)的扫描结果;将所得CT图像按照1组(CAD系统)、2组(低年资影像科医师)、3组(低年资影像科医师结合CAD系统)3种诊断方式对肺炎病灶的检出数、漏诊率、误诊率及平均诊断时间差异进行分析;利用CAD系统病变体积测量数值的变化对疾病转归进行评价。结果1组误诊率高于2、3两组;2组漏诊率高于1、3两组,1、3两组的诊断时间较2组明显缩短,差异均有统计学意义(P值均<0.05);CAD系统测量病灶体积变化与对照组判断病灶转归情况具有一致性。结论基于人工智能的CAD系统协助影像科医师阅片可降低肺炎病灶漏诊率、缩短诊断时间、辅助病情监测。

Objective To investigate the application value of computer-aided diagnosis(CAD)based on artificial intelligence in CT diagnosis of viral pneumonia.Methods The chest CT data of 10 patients with viral pneumonia diagnosed in the affiliated hospital of weifang medical college were analyzed.The results of two high resolution CT(HRCT)scans before and after the same patient were followed up.The CT images were analyzed according to three diagnostic methods:group 1(CAD system),group 2(junior radiologists),and group 3(junior radiologists combined with CAD system).The differences of detection number,missed diagnosis rate,misdiagnosis rate and average diagnosis time of pneumonia lesions were analyzed.The disease outcome was evaluated by the change of volume measurement in CAD system.Results The misdiagnosis rate of group 1 was higher than that of group 2 and group 3,the missed diagnosis rate of group 2 was higher than that of group 1 and group 3,the diagnosis time of group 1 and group 3 was significantly shorter than that of group 2,the difference was statistically significant(P<0.05);The change of lesion volume measured by CAD system was consistent with that judged by control group.Conclusion The CAD system based on artificial intelligence can reduce the missed diagnosis rate,shorten the diagnosis time and assist the disease monitoring.