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The clinical classification of patients with COVID-19 pneumonia was predicted by Radiomics using chest CT.
Xiong, Fei; Wang, Ye; You, Tao; Li, Han Han; Fu, Ting Ting; Tan, Huibin; Huang, Weicai; Jiang, Yuanliang.
  • Xiong F; Department of Radiology, PLA Central Theater General Hospital, Wuhan, Hubei, China.
Medicine (Baltimore) ; 100(12): e25307, 2021 Mar 26.
Article in English | MEDLINE | ID: covidwho-1150011
ABSTRACT
ABSTRACT In 2020, the new type of coronal pneumonitis became a pandemic in the world, and has firstly been reported in Wuhan, China. Chest CT is a vital component in the diagnostic algorithm for patients with suspected or confirmed COVID-19 infection. Therefore, it is necessary to conduct automatic and accurate detection of COVID-19 by chest CT.The clinical classification of patients with COVID-19 pneumonia was predicted by Radiomics using chest CT.From the COVID-19 cases in our institution, 136 moderate patients and 83 severe patients were screened, and their clinical and laboratory data on admission were collected for statistical analysis. Initial CT Radiomics were modeled by automatic machine learning, and diagnostic performance was evaluated according to AUC, TPR, TNR, PPV and NPV of the subjects. At the same time, the initial CT main features of the two groups were analyzed semi-quantitatively, and the results were statistically analyzed.There was a statistical difference in age between the moderate group and the severe group. The model cohort showed TPR 96.9%, TNR 99.1%, PPV98.4%, NPV98.2%, and AUC 0.98. The test cohort showed TPR 94.4%, TNR100%, PPV100%, NPV96.2%, and AUC 0.97. There was statistical difference between the two groups with grade 1 score (P = .001), the AUC of grade 1 score, grade 2 score, grade 3 score and CT score were 0.619, 0.519, 0.478 and 0.548, respectively.Radiomics' Auto ML model was built by CT image of initial COVID -19 pneumonia, and it proved to be effectively used to predict the clinical classification of COVID-19 pneumonia. CT features have limited ability to predict the clinical typing of Covid-19 pneumonia.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Image Processing, Computer-Assisted / Tomography, X-Ray Computed / Machine Learning / COVID-19 Type of study: Cohort study / Diagnostic study / Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Limits: Adult / Aged / Female / Humans / Male / Middle aged Language: English Journal: Medicine (Baltimore) Year: 2021 Document Type: Article Affiliation country: MD.0000000000025307

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Image Processing, Computer-Assisted / Tomography, X-Ray Computed / Machine Learning / COVID-19 Type of study: Cohort study / Diagnostic study / Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Limits: Adult / Aged / Female / Humans / Male / Middle aged Language: English Journal: Medicine (Baltimore) Year: 2021 Document Type: Article Affiliation country: MD.0000000000025307