摘要
目的探讨CT平扫图像纹理分析鉴别诊断新型冠状病毒肺炎(Corona Virus Disease 2019,COVID-19)和其他相似肺炎的价值。方法将33例COVID-19患者和33例其他相似肺炎的CT平扫图像混合,选取病变的最大层面导入MaZda 4.6软件中,手动勾画病变的感兴趣区,分别选择交互信息(Mutual Infoemation,MI)、Fisher系数、分类错误概率联合平均相关系数(Probability of Classification Error+Average Correction Coefficient,POE+ACC)以及三种方法的联合(Fisher+POE+ACC+MI)选择最佳的纹理特征参数,并构建人工神经网络(Artificial Neural Network,ANN)模型。与临床诊断结果对比,分别分析CT平扫图像纹理分析诊断结果和影像医师主观读片结果的误判率。结果MI纹理分析总误判率为34.85%(23/66),Fisher系数为25.76%(17/66),POE+ACC为19.70%(13/66),三种方法联合为10.60%(7/66),影像医师鉴别COVID-19和其他相似肺炎的误判率为31.82%(21/66)。三种方法联合分析的误判率最低,影像医师主观阅片对其他肺炎的误判率明显高于对COVID-19的误判率(P<0.05)。结论CT平扫图像纹理分析可初步应用于鉴别诊断COVID-19和其他相似肺炎。
Objective To investigate the value of CT images texture analysis in differential diagnosis of corona virus disease 2019 and other similar pneumonias.Methods The CT plain scan images of 33 patients with COVID-19 and 33 patients with other similar pneumonias were mixed.The maximum level of lesion was selected and imported into Mazda 4.6 software and ROIs were manually drawn.The optimum texture parameters were selected through Mutual information(MI),Fisher coefficient,probability of classification error and average correction coefficient(POE+ACC)and the combination of three methods(Fisher+POE+ACC+MI)respectively.The model of artificial neural network was builded.The diagnostic results of CT texture analysis and radiologist results were compared with the clinical results.And misdiagnosis rates were analyzed between texture analysis and radiologist.Results The tatal misdiagnosis rate of MI texture analysis was 34.85%(23/66),Fisher was 25.76%(17/66),POE+ACC was 19.70%(13/66),the combined value of the three methods was 10.60%(7/66),and the rate of misdiagnosis by imaging physicians in identifying COVID-19 and other similar pneumonia was 31.82%(21/66).Misdiagnosis rate of Fisher+POE+ACC+MI was lowest.Meantime,the misdiagnosis rates of other pneumonias were significantly higher than that of COVID-19 read by radiologists(P<0.05).Conclusion CT images texture analysis can be used to differential COVID-19 and other similar pneumonias.
作者
雷爱春
李光芒
王志兵
孙攀
储燕
LEI Aichun;LI Guangmang;WANG Zhibing;SUN Pan;CHU Yan(Department of CT,Huai’an Tumor Hospital,Huai’an Jiangsu 223200,China)
出处
《中国医疗设备》
2020年第12期91-94,共4页
China Medical Devices
