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COVID-19 肺炎肺部病变负荷的定量和半定量 CT 评估。

Quantitative and semi-quantitative CT assessments of lung lesion burden in COVID-19 pneumonia.

机构信息

Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou, 31009, China.

Department of Radiology, Yueqing People's Hospital, Yueqing, Wenzhou, Zhejiang, China.

出版信息

Sci Rep. 2021 Mar 4;11(1):5148. doi: 10.1038/s41598-021-84561-7.

Abstract

This study aimed to clarify and provide clinical evidence for which computed tomography (CT) assessment method can more appropriately reflect lung lesion burden of the COVID-19 pneumonia. A total of 244 COVID-19 patients were recruited from three local hospitals. All the patients were assigned to mild, common and severe types. Semi-quantitative assessment methods, e.g., lobar-, segmental-based CT scores and opacity-weighted score, and quantitative assessment method, i.e., lesion volume quantification, were applied to quantify the lung lesions. All four assessment methods had high inter-rater agreements. At the group level, the lesion load in severe type patients was consistently observed to be significantly higher than that in common type in the applications of four assessment methods (all the p < 0.001). In discriminating severe from common patients at the individual level, results for lobe-based, segment-based and opacity-weighted assessments had high true positives while the quantitative lesion volume had high true negatives. In conclusion, both semi-quantitative and quantitative methods have excellent repeatability in measuring inflammatory lesions, and can well distinguish between common type and severe type patients. Lobe-based CT score is fast, readily clinically available, and has a high sensitivity in identifying severe type patients. It is suggested to be a prioritized method for assessing the burden of lung lesions in COVID-19 patients.

摘要

本研究旨在明确并提供临床证据,以确定哪种计算机断层扫描(CT)评估方法更能准确反映 COVID-19 肺炎的肺部病变负担。从当地的三家医院共招募了 244 名 COVID-19 患者。所有患者均被分为轻症、普通型和重症。采用半定量评估方法,如基于肺叶、节段的 CT 评分和不透明度加权评分,以及定量评估方法,即病变体积量化,来量化肺部病变。所有四种评估方法的观察者间一致性均较高。在组水平上,严重型患者的病变负荷在四种评估方法的应用中均明显高于普通型(均 P < 0.001)。在个体水平上区分重症和普通型患者时,基于肺叶、基于节段和基于不透明度的评估的真阳性率较高,而定量病变体积的真阴性率较高。总之,半定量和定量方法在测量炎症性病变方面具有极好的可重复性,并且能够很好地区分普通型和重症型患者。基于肺叶的 CT 评分快速、易于临床应用,且在识别重症患者方面具有较高的敏感性。建议将其作为评估 COVID-19 患者肺部病变负担的优先方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3db3/7933172/322704288362/41598_2021_84561_Fig1_HTML.jpg

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