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

被引:11
|
作者
Chen, Zuhua [1 ,2 ]
Li, Xiadong [3 ,4 ]
Li, Jiawei [5 ]
Zhang, Shirong [4 ]
Zhou, Pengfei [3 ]
Yu, Xin [3 ]
Ren, Yao [3 ]
Wang, Jiahao [3 ]
Zhang, Lidan [3 ]
Li, Yunjiang [1 ]
Wu, Baoliang [1 ]
Hou, Yanchun [1 ]
Zhang, Ke [3 ]
Tang, Rongjun [3 ]
Liu, Yongguang [1 ]
Ding, Zhongxian [4 ]
Yang, Bin [4 ]
Deng, Qinghua [3 ]
Lin, Qin [8 ]
Nie, Ke [6 ]
Cai, Zhaobin [1 ,2 ]
Ma, Shenglin [3 ,4 ]
Kuang, Yu [7 ]
机构
[1] Hangzhou Xixi Hosp, Dept Radiol, Hangzhou 310000, Zhejiang, Peoples R China
[2] Zhejiang Chinese Med Univ, Affiliated Hosp, Hangzhou Peoples Hosp 6, Dept Radiol, Hangzhou 310000, Zhejiang, Peoples R China
[3] Zhejiang Univ, Canc Ctr, Hangzhou Peoples Hosp Grp 1, Dept Radiat Oncol,Hangzhou Canc Hosp, Hangzhou 310000, Zhejiang, Peoples R China
[4] Zhejiang Univ, Sch Med, Affiliated Hangzhou Peoples Hosp 1, Dept Radiat Oncol, Hangzhou 310000, Zhejiang, Peoples R China
[5] Zhejiang Chinese Med Univ, Clin Med Coll 4, Dept Radiol, Hangzhou 310000, Zhejiang, Peoples R China
[6] Rutgers State Univ, Rutgers Canc Inst New Jersey, Dept Radiat Oncol, New Brunswick, NJ 07097 USA
[7] Univ Nevada, Med Phys Program, Las Vegas, NV 89154 USA
[8] Fujian Med Univ, Xiamen Univ, Dept Radiat Oncol, Affiliated Hosp 1,Xiamen Canc Hosp,Teaching Hosp, Xiamen 361003, Fujian, Peoples R China
来源
AGING-US | 2021年 / 13卷 / 07期
关键词
coronavirus disease 2019; COVID-19; severe acute respiratory syndrome coronavirus 2; chest CT; radiomics; nomogram; TOOL;
D O I
10.18632/aging.202735
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
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.
引用
收藏
页码:9186 / 9224
页数:39
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