Department of Radiology, Hangzhou Xixi Hospital, Hangzhou 310000, Zhejiang, China.
Department of Radiology, Hangzhou 6th People's Hospital, the Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou 310000, Zhejiang, China.
Aging (Albany NY). 2021 Mar 13;13(7):9186-9224. doi: 10.18632/aging.202735.
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.
随着严重急性呼吸综合征冠状病毒 2 (SARS-CoV-2) 在全球范围内的持续传播，识别高度疑似 COVID-19 患者仍然是当务之急。在这项研究中，我们开发并验证了 COVID-19 风险评分，以识别 COVID-19 患者。在这项研究中，对于患者个体分析，三个特征，包括仅使用放射组学特征的风险评分、仅使用临床因素的风险评分以及结合放射组学特征和临床变量的风险评分，在验证集中区分 COVID-19 与其他病毒性肺炎方面表现出优异的性能。对于病变个体分析，仅使用三个放射组学特征的风险评分也获得了优异的 AUC 值。相比之下，与开发的风险评分相比，基于胸部 CT 图像但不包括临床特征的 130 名放射科医生的表现则为中等。描绘 CT 放射组学与 COVID-19 之间相关性的风险评分可用于准确识别 COVID-19 患者，从精准医学的角度来看，这将具有临床可转化的诊断和治疗意义。
