CT-based radiomics combined with signs: a valuable tool to help radiologist discriminate COVID-19 and influenza pneumonia

Yilong Huang,Xiang Li,Jialong Zhou,Zhipeng Li,Bo He,Zhenguang Zhang,Yunhui Yang,Yuanming Jiang,Jiyao Ma,Siyun Liu

doi:10.1186/s12880-021-00564-w

Abstract

BackgroundIn this COVID-19 pandemic, the differential diagnosis of viral pneumonia is still challenging. We aimed to assess the classification performance of computed tomography (CT)-based CT signs and radiomics features for discriminating COVID-19 and influenza pneumonia.MethodsA total of 154 patients with confirmed viral pneumonia (COVID-19: 89 cases, influenza pneumonia: 65 cases) were collected retrospectively in this study. Pneumonia signs and radiomics features were extracted from the initial unenhanced chest CT images to build independent and combined models. The predictive performance of the radiomics model, CT sign model, the combined model was constructed based on the whole dataset and internally invalidated by using 1000-times bootstrap. Diagnostic performance of the models was assessed via receiver operating characteristic (ROC) analysis.ResultsThe combined models consisted of 4 significant CT signs and 7 selected features and demonstrated better discrimination performance between COVID-19 and influenza pneumonia than the single radiomics model. For the radiomics model, the area under the ROC curve (AUC) was 0.888 (sensitivity, 86.5%; specificity, 78.4%; accuracy, 83.1%), and the AUC was 0.906 (sensitivity, 86.5%; specificity, 81.5%; accuracy, 84.4%) in the CT signs model. After combining CT signs and radiomics features, AUC of the combined model was 0.959 (sensitivity, 89.9%; specificity, 90.7%; accuracy, 90.3%).ConclusionsCT-based radiomics combined with signs might be a potential method for distinguishing COVID-19 and influenza pneumonia with satisfactory performance.

Highlights

In this COVID-19 pandemic, the differential diagnosis of viral pneumonia is still challenging
The 16 computed tomography (CT) signs of COVID-19 and influenza pneumonia were gradually screened by using Chi-square test or Fisher exact test (Additional file 5: Table 2), univariate and multivariate logistic regression analysis (Additional file 6: Table 3)
Shen and Liu et al found that the clinical manifestations of COVID-19 and influenza pneumonia were very similar, but the monocyte percentage increased and the eosinophil count decreased in COVID19 patients, and the ground-glass opacities (GGO) of COVID-19 on the CT

Summary

Introduction

In this COVID-19 pandemic, the differential diagnosis of viral pneumonia is still challenging. We aimed to assess the classification performance of computed tomography (CT)-based CT signs and radiomics features for discriminating COVID-19 and influenza pneumonia. Huang et al BMC Med Imaging (2021) 21:31 pandemic, the differential diagnosis between COVID-19 and influenza pneumonia is difficult but highly important in the early stages of the disease. Recent reports have shown that RT-PCR detection of COVID-19 has low sensitivity [9], and the high falsenegative rate limits the rapid identification of viral pneumonia by RT-PCR. Studies have shown that the CT signs of COVID-19 and influenza pneumonia are different [12, 13]. Little is known about the prediction performance of CT signs in distinguishing COVID-19 from influenza pneumonia in previous studies. It is necessary to further develop a rapid quantitative auxiliary diagnostic method to identify COVID-19 and influenza pneumonia

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