Functional Alterations Due to COVID-19 Lung Lesions-Lessons From a Multicenter V/Q Scan-Based Registry

COVID-19肺部病变引起的功能改变——来自多中心V/Q扫描注册研究的启示

阅读:1

Abstract

PURPOSE: In coronavirus disease 2019 (COVID-19) patients, clinical manifestations as well as chest CT lesions are variable. Lung scintigraphy allows to assess and compare the regional distribution of ventilation and perfusion throughout the lungs. Our main objective was to describe ventilation and perfusion injury by type of chest CT lesions of COVID-19 infection using V/Q SPECT/CT imaging. PATIENTS AND METHODS: We explored a national registry including V/Q SPECT/CT performed during a proven acute SARS-CoV-2 infection. Chest CT findings of COVID-19 disease were classified in 3 elementary lesions: ground-glass opacities, crazy-paving (CP), and consolidation. For each type of chest CT lesions, a semiquantitative evaluation of ventilation and perfusion was visually performed using a 5-point scale score (0 = normal to 4 = absent function). RESULTS: V/Q SPECT/CT was performed in 145 patients recruited in 9 nuclear medicine departments. Parenchymal lesions were visible in 126 patients (86.9%). Ground-glass opacities were visible in 33 patients (22.8%) and were responsible for minimal perfusion impairment (perfusion score [mean ± SD], 0.9 ± 0.6) and moderate ventilation impairment (ventilation score, 1.7 ± 1); CP was visible in 43 patients (29.7%) and caused moderate perfusion impairment (2.1 ± 1.1) and moderate-to-severe ventilation impairment (2.5 ± 1.1); consolidation was visible in 89 patients (61.4%) and was associated with moderate perfusion impairment (2.1 ± 1) and severe ventilation impairment (3.0 ± 0.9). CONCLUSIONS: In COVID-19 patients assessed with V/Q SPECT/CT, a large proportion demonstrated parenchymal lung lesions on CT, responsible for ventilation and perfusion injury. COVID-19-related pulmonary lesions were, in order of frequency and functional impairment, consolidations, CP, and ground-glass opacity, with typically a reverse mismatched or matched pattern.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。