چاپ صفحه |  صفحه نخست سامانه |  نویسندگان |  اطلاعات تفضیلی |  دانلود مقاله | دانشگاه علوم پزشکی تبریز |
| نویسنده | نفر چندم مقاله |
|---|---|
| یونس سلیمانی کیچی قلعه سی | اول |
| داود خضرلو | دوم |
| عنوان | متن |
|---|---|
| کلمات کلیدی | “COVID-19”, “Radiomics”, “Pneumonia”, “Lung CT” |
| خلاصه مقاله | Abstract: Introduction: The Coronavirus Disease 2019 (COVID–19) has widely and rapidly spread throughout the world since late December 2019. It is highly contagious and may cause severe acute respiratory infection such as pneumonia. At present, the gold standard for the diagnosis of COVID–19 is reverse-transcription polymerase chain reaction (RT-PCR). However, a high false negative rate and the shortage of RT-PCR assay in the early stage of the outbreak limited the early detection and treatment of the presumptive patients. Computed tomography (CT), as a non-invasive imaging approach, is of great sensitivity in detecting lung lesions in patients with COVID–19 pneumonia. However, we should not neglect the fact that COVID–19 pneumonia may have certain similar CT imaging features with other types of pneumonia, thus making it hard to differentiate. The main purpose of this study is to investigate the radiomics features of COVID-19 pneumonia in lung CT images and compare it with the features of pneumonia of non-COVID diseases and investigate whether textural radiomics features extracted from lung CT images can help to differentiate COVID-19 from non-COVID pneumonia? Materials and methods: Lung CT images of 33 patients with COVID-19 pneumonia and 20 with non-COVID pneumonia were investigated. For radiomics analysis, the regions of interest (ROIs) were identified inside the pulmonary opacities manually. For each ROI, 12 textural features were obtained. The non-parametric Mann Whitney U test with p-value<0.05 was performed to assess the differences in these features between COVID-19 and non-COVID groups. Results: 8 of the 12 texture features demonstrated a significant difference (P<0.05), with COVID-19 pneumonia lesions tending to be more heterogeneous and more invasive when compared with the non-COVID cases. Conclusions: The results of the present study may provide a noninvasive means to a better differentiation of COVID-19 pneumonia from non-COVID pneumonia, so it can reduce the false-positive rate of CT images. |
| نام فایل | تاریخ درج فایل | اندازه فایل | دانلود |
|---|---|---|---|
| Abstract Book 2020 - 06.pdf | 1399/11/20 | 9487377 | دانلود |
| radiomic lung.pdf | 1399/11/20 | 127967 | دانلود |
| first page.pdf | 1399/11/20 | 476864 | دانلود |
