Estimating Covid-19 Pneumonia Extent And Severity From Chest Computed Tomography

Alysson Roncally Silva Carvalho,Alan Guimarães, Thiego de Souza Oliveira Garcia, Gabriel Madeira Werberich,Victor Fraga Ceotto,Fernando Augusto Bozza,Rosana Souza Rodrigues, Joana Sofia F Pinto, Willian Rebouças Schmitt,Walter Araujo Zin,Manuela França

FRONTIERS IN PHYSIOLOGY(2021)

引用 7|浏览10
暂无评分
摘要
Background COVID-19 pneumonia extension is assessed by computed tomography (CT) with the ratio between the volume of abnormal pulmonary opacities (PO) and CT-estimated lung volume (CTLV). CT-estimated lung weight (CTLW) also correlates with pneumonia severity. However, both CTLV and CTLW depend on demographic and anthropometric variables. Purposes To estimate the extent and severity of COVID-19 pneumonia adjusting the volume and weight of abnormal PO to the predicted CTLV (pCT(LV)) and CTLW (pCT(LW)), respectively, and to evaluate their possible association with clinical and radiological outcomes. Methods Chest CT from 103 COVID-19 and 86 healthy subjects were examined retrospectively. In controls, predictive equations for estimating pCT(LV) and pCT(LW) were assessed. COVID-19 pneumonia extent and severity were then defined as the ratio between the volume and the weight of abnormal PO expressed as a percentage of the pCT(LV) and pCT(LW), respectively. A ROC analysis was used to test differential diagnosis ability of the proposed method in COVID-19 and controls. The degree of pneumonia extent and severity was assessed with Z-scores relative to the average volume and weight of PO in controls. Accordingly, COVID-19 patients were classified as with limited, moderate and diffuse pneumonia extent and as with mild, moderate and severe pneumonia severity. Results In controls, CTLV could be predicted by sex and height (adjusted R-2 = 0.57; P < 0.001) while CTLW by age, sex, and height (adjusted R-2 = 0.6; P < 0.001). The cutoff of 20% (AUC = 0.91, 95%CI 0.88-0.93) for pneumonia extent and of 50% (AUC = 0.91, 95%CI 0.89-0.92) for pneumonia severity were obtained. Pneumonia extent were better correlated when expressed as a percentage of the pCT(LV) and pCT(LW) (r = 0.85, P < 0.001), respectively. COVID-19 patients with diffuse and severe pneumonia at admission presented significantly higher CRP concentration, intra-hospital mortality, ICU stay and ventilatory support necessity, than those with moderate and limited/mild pneumonia. Moreover, pneumonia severity, but not extent, was positively and moderately correlated with age (r = 0.46) and CRP concentration (r = 0.44). Conclusion The proposed estimation of COVID-19 pneumonia extent and severity might be useful for clinical and radiological patient stratification.
更多
查看译文
关键词
computed tomography, COVID-19, deep learning, CT-estimated lung volume, CT-estimated lung weight
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要