基于磁共振ADC图像的深度学习和ADC值评估慢性乙型肝炎肝纤维化程度价值比较  

Comparison of Deep Learning Based on Magnetic Resonance ADC Image and ADC Value in Evaluating the Degree of Liver Fibrosis in Chronic Hepatitis B

作　　者：朱桂娟 张鑫[1] 叶晓航[1] 李锋 ZHU Guijuan;ZHANG Xin;YE Xiaohang;LI Feng(Department of Medical Imaging,Huai’an No.4 People’s Hospital,Huai’an Jiangsu 223000,China)

机构地区：[1]淮安市第四人民医院影像科,江苏淮安223000

出　　处：《中国医疗设备》2023年第2期12-16,24,共6页China Medical Devices

基　　金：2020年江苏省高层次卫生人才“六一工程”(LGY2020059);中国公共卫生联盟项目(GWLM202016)。

摘　　要：目的采用基于深度学习的卷积神经网络自动检测方法对MRI的表观弥散系数(Apparent Diffusion Coefficient,ADC)图像进行分析,探究ADC图像特征与肝纤维化程度的关系。方法选取123例慢性乙型肝炎患者作为研究对象,根据肝穿刺活检,确定了5组肝纤维化阶段(F0~F4)。分别采用5层深度卷积神经网络结构对ADC图像进行分析,MRI工作站测量ADC值,2种方法进行十折交叉验证比较。结果基于深度学习采集ADC图像的准确度、敏感度、特异性、精密度、F1值(F1-Score,F1)、马修斯相关系数(Matthews Correlation Coefficient,MCC)、福尔克斯–马洛斯指数(Fowlkes–Mallows Index,FMI)分别为88.13%±1.47%、81.45%±3.69%、91.12%±1.72%、80.49%±2.94%、80.90%±2.39%、72.36%±3.39%、80.94%±2.37%,MRI工作站测量的ADC值的准确度、敏感度、特异性、精密度、F1、MCC和FMI分别为75.07%±13.35%、90.03%±9.24%、42.67%±35.42%、78.44%±11.42%、83.30%±8.18%、16.00%±60.46%、83.77%±7.98%。5层深度卷积神经网络的准确度显著高于MRI工作站测量的ADC值的准确度(P<0.01)。结论基于深度学习卷积神经网络自动检测方法的准确度优于MRI测量的ADC值,卷积神经网络自动检测方法在慢性乙型肝炎肝纤维化分期中具有较高的诊断价值。Objective To explore the apparent diffusion coefficient(ADC)image characteristic and the degree of liver fibrosis,by the analysis of convolutional neural network based on deep learning automatic detection method for MRI of the ADC image.Methods A total of 123 patients with chronic hepatitis B were selected as research subjects.5 groups of hepatic fibrosis stages(F0~F4)were determined according to liver biopsy.The ADC images were analyzed using 5-layer depth convolutional neural network structure,and the ADC values were measured by MRI workstation,and the two methods were compared for cross-validation.Results The accuracy,sensitivity,specificity,precision,F1 value,Matthews correlation coefficient(MCC)and Fowlkes–Mallows index(FMI)of ADC images acquired by depth learning were 88.13%±1.47%,81.45%±3.69%,91.12%±1.72%,80.49%±2.94%,80.90%±2.39%,72.36%±3.39%and 80.94%±2.37%.The accuracy,sensitivity,specificity,precision,F1,MCC and FMI of ADC values measured by MRI workstation were 75.07%±13.35%,90.03%±9.24%,42.67%±35.42%,78.44%±11.42%,83.30%±8.18%,16.00%±60.46%and 83.77%±7.98%.The accuracy of 5-layer deep convolutional neural network was significantly higher than that of ADC measured by MRI workstation(P<0.01).Conclusion The accuracy of ADC value obtained by the deep learning convolutional neural network automatic detection method is better than that obtained by MRI measurement method.The deep learning convolutional neural network automatic detection method has a high diagnostic value for chronic hepatitis B liver fibrosis.

关 键 词：肝纤维化 深度卷积神经网络 表观弥散系数图像 磁共振成像 

分 类 号：R445.2[医药卫生—影像医学与核医学] R512.6[医药卫生—诊断学]