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定量 CT 技术评估 COVID-19 感染患者肺部异常的动态演变。

Dynamic evolution of lung abnormalities evaluated by quantitative CT techniques in patients with COVID-19 infection.

机构信息

Department of Anesthesiology, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Sichuan, Nanchong637000, China.

Department of Radiology, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Sichuan, Nanchong637000, China.

出版信息

Epidemiol Infect. 2020 Jul 6;148:e136. doi: 10.1017/S0950268820001508.

Abstract

Chest CT evaluation is often vital to determine patients suspected of COVID-19 pneumonia. The aim of this study was to determine the evolution of lung abnormalities evaluated by quantitative CT techniques in patients with COVID-19 infection from initial diagnosis to recovery. This retrospective study included 16 patients with COVID-19 infection from 30 January 2020 through 11 March 2020. Repeat chest CT examinations were obtained for three or more scans per patient. We measured total volume and mean CT value of lung lesions in each patient per scan, and then calculated the mass, which equals to volume × (CT value + 1000). Dynamic evolution of chest CT imaging as a function of time was fitted by non-linear regression model in terms of mass, volume and CT value, respectively. According to the fitting curves, we redefined the evolution of lung abnormalities: progressive stage (0-5 days), infection emerged and rapidly aggravated; peak stage (5-15 days), the greatest severity at approximate 7-8 days after onset; and absorption stage (15-30 days), the lesions slowly and gradually resolved.

摘要

胸部 CT 评估对于疑似 COVID-19 肺炎的患者通常至关重要。本研究旨在确定从初始诊断到康复过程中,定量 CT 技术评估的 COVID-19 感染患者肺部异常的演变情况。本回顾性研究纳入了 2020 年 1 月 30 日至 2020 年 3 月 11 日期间的 16 名 COVID-19 感染患者。每位患者均进行了 3 次或以上的胸部 CT 复查。我们在每次扫描时测量了每位患者肺病变的总体积和平均 CT 值,然后计算了质量,即体积乘以(CT 值+1000)。分别采用非线性回归模型拟合了胸部 CT 影像学随时间的动态变化与质量、体积和 CT 值的关系。根据拟合曲线,我们重新定义了肺部异常的演变:进展期(0-5 天),感染出现并迅速加重;高峰期(5-15 天),发病后约 7-8 天达到最严重程度;吸收期(15-30 天),病变缓慢逐渐吸收。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2fb/7360949/5cb90331d46f/S0950268820001508_fig1.jpg

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