Dou Qingli, Liu Jiangping, Zhang Wenwu, Gu Yanan, Hsu Wan-Ting, Ho Kuan-Ching, Tong Hoi Sin, Yu Wing Yan, Lee Chien-Chang
Department of Emergency Medicine, The Second Affiliated Hospital of Shenzhen University, Shenzhen, China.
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States.
Front Mol Biosci. 2021 Mar 30;8:614207. doi: 10.3389/fmolb.2021.614207. eCollection 2021.
Characteristic chest computed tomography (CT) manifestation of 2019 novel coronavirus (COVID-19) was added as a diagnostic criterion in the Chinese National COVID-19 management guideline. Whether the characteristic findings of Chest CT could differentiate confirmed COVID-19 cases from other positive nucleic acid test (NAT)-negative patients has not been rigorously evaluated.
We aim to test whether chest CT manifestation of 2019 novel coronavirus (COVID-19) can be differentiated by a radiologist or a computer-based CT image analysis system.
We conducted a retrospective case-control study that included 52 laboratory-confirmed COVID-19 patients and 80 non-COVID-19 viral pneumonia patients between 20 December, 2019 and 10 February, 2020. The chest CT images were evaluated by radiologists in a double blind fashion. A computer-based image analysis system (uAI System, Lianying Inc., Shanghai, China) detected the lesions in 18 lung segments defined by Boyden classification system and calculated the infected volume in each segment. The number and volume of lesions detected by radiologist and computer system was compared with Chi-square test or Mann-Whitney test as appropriate.
The main CT manifestations of COVID-19 were multi-lobar/segmental peripheral ground-glass opacities and patchy air space infiltrates. The case and control groups were similar in demographics, comorbidity, and clinical manifestations. There was no significant difference in eight radiologist identified CT image features between the two groups of patients. There was also no difference in the absolute and relative volume of infected regions in each lung segment.
We documented the non-differentiating nature of initial chest CT image between COVID-19 and other viral pneumonia with suspected symptoms. Our results do not support CT findings replacing microbiological diagnosis as a critical criterion for COVID-19 diagnosis. Our findings may prompt re-evaluation of isolated patients without laboratory confirmation.
2019年新型冠状病毒（COVID-19）肺炎的胸部计算机断层扫描（CT）特征性表现被列入中国国家COVID-19诊疗指南的诊断标准中。胸部CT的特征性表现能否将确诊的COVID-19病例与其他核酸检测（NAT）阴性患者区分开来，尚未得到严格评估。
我们旨在测试放射科医生或基于计算机的CT图像分析系统能否区分2019年新型冠状病毒（COVID-19）的胸部CT表现。
我们进行了一项回顾性病例对照研究，纳入了2019年12月20日至2020年2月10日期间52例实验室确诊的COVID-19患者和80例非COVID-19病毒性肺炎患者。放射科医生以双盲方式对胸部CT图像进行评估。基于计算机的图像分析系统（uAI系统，联影医疗科技有限公司，中国上海）在由博伊登分类系统定义的18个肺段中检测病变，并计算每个肺段的感染体积。将放射科医生和计算机系统检测到的病变数量和体积根据情况用卡方检验或曼-惠特尼检验进行比较。
COVID-19的主要CT表现为多叶/多段外周磨玻璃影和斑片状实变影。病例组和对照组在人口统计学、合并症和临床表现方面相似。两组患者在放射科医生识别的8项CT图像特征上无显著差异。每个肺段感染区域的绝对和相对体积也无差异。
我们记录了COVID-19与其他有疑似症状的病毒性肺炎之间初始胸部CT图像无鉴别性的特征。我们的结果不支持将CT表现作为COVID-19诊断的关键标准来取代微生物学诊断。我们的发现可能促使对未经实验室确诊的隔离患者进行重新评估。
