人工智能评估的高分辨率计算机断层扫描验证的 COVID-19 肺炎肺超声的价值。

The value of lung ultrasound in COVID-19 pneumonia, verified by high resolution computed tomography assessed by artificial intelligence.

机构信息

Department of Radiology, Jagiellonian University Medical College, Kopernika 19, 31-501, Krakow, Poland.

Department of Intensive Care and Perioperative Medicine, Jagiellonian University Medical College, Krakow, Poland.

出版信息

BMC Infect Dis. 2023 Mar 31;23(1):195. doi: 10.1186/s12879-023-08173-4.

DOI:10.1186/s12879-023-08173-4

PMID:37003997

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10064611/

Abstract

BACKGROUND

Lung ultrasound (LUS) is an increasingly popular imaging method in clinical practice. It became particularly important during the COVID-19 pandemic due to its mobility and ease of use compared to high-resolution computed tomography (HRCT). The objective of this study was to assess the value of LUS in quantifying the degree of lung involvement and in discrimination of lesion types in the course of COVID-19 pneumonia as compared to HRCT analyzed by the artificial intelligence (AI).

METHODS

This was a prospective observational study including adult patients hospitalized due to COVID-19 in whom initial HRCT and LUS were performed with an interval < 72 h. HRCT assessment was performed automatically by AI. We evaluated the correlations between the inflammation volume assessed both in LUS and HRCT, between LUS results and the HRCT structure of inflammation, and between LUS and the laboratory markers of inflammation. Additionally we compared the LUS results in subgroups depending on the respiratory failure throughout the hospitalization.

RESULTS

Study group comprised 65 patients, median 63 years old. For both lungs, the median LUS score was 19 (IQR-interquartile range 11-24) and the median CT score was 22 (IQR 16-26). Strong correlations were found between LUS and CT scores (for both lungs r = 0.75), and between LUS score and percentage inflammation volume (PIV) (r = 0.69). The correlations remained significant, if weakened, for individual lung lobes. The correlations between LUS score and the value of the percentage consolidation volume (PCV) divided by percentage ground glass volume (PGV), were weak or not significant. We found significant correlation between LUS score and C-reactive protein (r = 0.55), and between LUS score and interleukin 6 (r = 0.39). LUS score was significantly higher in subgroups with more severe respiratory failure.

CONCLUSIONS

LUS can be regarded as an accurate method to evaluate the extent of COVID-19 pneumonia and as a promising tool to estimate its clinical severity. Evaluation of LUS in the assessment of the structure of inflammation, requires further studies in the course of the disease.

TRIAL REGISTRATION

The study has been preregistered 13 Aug 2020 on clinicaltrials.gov with the number NCT04513210.

摘要

背景

肺部超声（LUS）在临床实践中是一种越来越流行的影像学方法。与高分辨率计算机断层扫描（HRCT）相比，它具有移动性和易用性，因此在 COVID-19 大流行期间变得尤为重要。本研究的目的是评估 LUS 在定量评估 COVID-19 肺炎中肺受累程度以及区分病变类型方面的价值，与人工智能（AI）分析的 HRCT 进行比较。

方法

这是一项前瞻性观察性研究，纳入了因 COVID-19 住院的成年患者，他们在间隔<72 小时内进行了初始 HRCT 和 LUS 检查。HRCT 评估由 AI 自动进行。我们评估了 LUS 和 HRCT 评估的炎症体积之间、LUS 结果与 HRCT 炎症结构之间以及 LUS 与炎症的实验室标志物之间的相关性。此外，我们还根据住院期间呼吸衰竭的情况，比较了 LUS 结果在亚组之间的差异。

结果

研究组包括 65 名患者，中位年龄为 63 岁。对于两肺，LUS 评分中位数为 19（IQR 11-24），CT 评分中位数为 22（IQR 16-26）。LUS 和 CT 评分之间存在很强的相关性（双侧 r=0.75），LUS 评分与炎症体积百分比（PIV）之间也存在很强的相关性（r=0.69）。如果减弱，这些相关性在各个肺叶中仍然显著。LUS 评分与实变体积百分比（PCV）与磨玻璃体积百分比（PGV）的比值（PCV/PGV）之间的相关性较弱或无统计学意义。我们发现 LUS 评分与 C 反应蛋白（r=0.55）和白细胞介素 6（r=0.39）之间存在显著相关性。在呼吸衰竭更严重的亚组中，LUS 评分显著更高。