Research Paper|Volume 13, Issue 7|pp 9186—9224

A COVID-19 risk score combining chest CT radiomics and clinical characteristics to differentiate COVID-19 pneumonia from other viral pneumonias

Zuhua Chen^1,², Xiadong Li^3,⁴, Jiawei Li⁵, Shirong Zhang⁴, Pengfei Zhou³, Xin Yu³, Yao Ren³, Jiahao Wang³, Lidan Zhang³, Yunjiang Li¹, Baoliang Wu¹, Yanchun Hou¹, Ke Zhang³, Rongjun Tang³, Yongguang Liu¹, Zhongxian Ding⁴, Bin Yang⁴, Qinghua Deng³, Qin Lin⁸, Ke Nie⁶, Zhaobin Cai^1,², Shenglin Ma^3,⁴, Yu Kuang⁷

¹Department of Radiology, Hangzhou Xixi Hospital, Hangzhou 310000, Zhejiang, China
²Department of Radiology, Hangzhou 6th People’s Hospital, the Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou 310000, Zhejiang, China
³Department of Radiation Oncology, Hangzhou Cancer Hospital, Zhejiang University Cancer Centre, Hangzhou First People’s Hospital Group, Hangzhou 310000, Zhejiang, China
⁴Department of Radiation Oncology, Affiliated Hangzhou First People’s Hospital, Zhejiang University School of Medicine, Hangzhou 310000, Zhejiang, China
⁵Department of Radiology, The Fourth Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou 310000, Zhejiang, China
⁶Department of Radiation Oncology, Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ 07097, USA
⁷Medical Physics Program, University of Nevada, Las Vegas, NV 89154, USA
⁸Department of Radiation Oncology, Xiamen Cancer Hospital, The First Affiliated Hospital of Xiamen University, Teaching Hospital of Fujian Medical University, Xiamen 361003, Fujian, China

* Equal contribution

Received: September 24, 2020Accepted: January 4, 2021Published: March 13, 2021

https://doi.org/10.18632/aging.202735

Copyright: © 2021 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

With the continued transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) throughout the world, identification of highly suspected COVID-19 patients remains an urgent priority. In this study, we developed and validated COVID-19 risk scores to identify patients with COVID-19. In this study, for patient-wise analysis, three signatures, including the risk score using radiomic features only, the risk score using clinical factors only, and the risk score combining radiomic features and clinical variables, show an excellent performance in differentiating COVID-19 from other viral-induced pneumonias in the validation set. For lesion-wise analysis, the risk score using three radiomic features only also achieved an excellent AUC value. In contrast, the performance of 130 radiologists based on the chest CT images alone without the clinical characteristics included was moderate as compared to the risk scores developed. The risk scores depicting the correlation of CT radiomics and clinical factors with COVID-19 could be used to accurately identify patients with COVID-19, which would have clinically translatable diagnostic and therapeutic implications from a precision medicine perspective.