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新冠病毒肺炎患者大脑静息和动态活动及功能连接的改变:一项初步研究

Altered dynamic and static brain activity and functional connectivity in COVID-19 patients: a preliminary study.

作者信息

Han Mingxing, He Chunni, Li Tianping, Li Qinglong, Chu Tongpeng, Li Jun, Wang Peiyuan

机构信息

Department of Radiology, Yantai Affiliated Hospital of Binzhou Medical University, Yantai.

Department of Radiology, The Second Hospital of Jiaxing, Jiaxing, People's Republic of China.

出版信息

Neuroreport. 2024 Mar 20;35(5):306-315. doi: 10.1097/WNR.0000000000002009. Epub 2024 Feb 2.

Abstract

This study aimed to investigate the effects of COVID-19 on brain functional activity through resting-state functional MRI (rs-fMRI). fMRI scans were conducted on a cohort of 42 confirmed COVID-19-positive patients and 46 healthy controls (HCs) to assess brain functional activity. A combination of dynamic and static amplitude of low-frequency fluctuations (dALFF/sALFF) and dynamic and static functional connectivity (dFC/sFC) was used for evaluation. Abnormal brain regions identified were then used as feature inputs in the model to evaluate support vector machine (SVM) capability in recognizing COVID-19 patients. Moreover, the random forest (RF) model was employed to verify the stability of SVM diagnoses for COVID-19 patients. Compared to HCs, COVID-19 patients exhibited a decrease in sALFF in the right lingual gyrus and the left medial occipital gyrus and an increase in dALFF in the right straight gyrus. Moreover, there was a decline in sFC between both lingual gyri and the right superior occipital gyrus and a reduction in dFC with the precentral gyrus. The dynamic and static combined ALFF and FC could distinguish between COVID-19 patients and the HCs with an accuracy of 0.885, a specificity of 0.818, a sensitivity of 0.933 and an area under the curve of 0.909. The combination of dynamic and static ALFF and FC can provide information for detecting brain functional abnormalities in COVID-19 patients.

摘要

本研究旨在通过静息态功能磁共振成像(rs-fMRI)研究新型冠状病毒肺炎(COVID-19)对脑功能活动的影响。对42名确诊的COVID-19阳性患者和46名健康对照者(HCs)进行功能磁共振成像扫描,以评估脑功能活动。采用低频波动的动态和静态幅度(dALFF/sALFF)以及动态和静态功能连接(dFC/sFC)相结合的方法进行评估。然后将识别出的异常脑区用作模型中的特征输入,以评估支持向量机(SVM)识别COVID-19患者的能力。此外,采用随机森林(RF)模型验证SVM对COVID-19患者诊断的稳定性。与HCs相比,COVID-19患者右侧舌回和左侧枕内侧回的sALFF降低,右侧直回的dALFF增加。此外,两侧舌回与右侧枕上回之间的sFC下降,与中央前回的dFC减少。动态和静态联合ALFF和FC能够区分COVID-19患者和HCs,准确率为0.885,特异性为0.818,灵敏度为0.933,曲线下面积为0.909。动态和静态ALFF与FC的组合可为检测COVID-19患者的脑功能异常提供信息。

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