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在COVID-19患者中改变动态和静态大脑活动和功能连接:一项初步研究

Mingxing Han¹, Chunni He¹, Tianping Li²

¹Department of Radiology, Yantai Affiliated Hospital of Binzhou Medical University, Yantai.

|February 2, 2024

概括

COVID-19影响大脑功能,改变低频波动和连接. 休息状态fMRI分析揭示了患者的独特模式,使得这些神经变化的准确检测.

科学领域:

神经科学是一个神经科学.
医疗成像医学成像
传染性疾病传染性疾病

背景情况:

众所周知,COVID-19会引起一系列的神经症状.
了解COVID-19后大脑的功能变化对于诊断和管理至关重要.

研究的目的:

通过静止状态功能性MRI (rs-fMRI) 调查COVID-19对大脑功能活动的影响.
根据大脑活动模式评估机器学习模型在识别COVID-19患者方面的能力.

主要方法:

在42名COVID-19患者和46名健康对照组 (HCs) 上进行了rs-fMRI扫描.
分析了低频波动的动态和静态振幅 (dALFF/sALFF) 和动态和静态功能连接 (dFC/sFC).
支持矢量机 (SVM) 和随机森林 (RF) 模型被用于分类和验证.

主要成果:

与HC患者相比,COVID-19患者在右舌腔和左中枢尾回形中显示sALFF降低,在右直角回形中显示dALFF增加.
在特定的大脑区域观察到减少的sFC和dFC,包括语言回转,上回转和前中心回转.
组合动态和静态ALFF和FC区分了COVID-19患者和HC患者的高精度 (0.885),灵敏度 (0.933) 和特异性 (0.818).

结论:

动态和静态ALFF和FC指标有效捕捉COVID-19患者的大脑功能异常.
使用这些神经成像特征的机器学习模型可以准确地识别COVID-19的个体.
这种方法为检测COVID-19的神经后果提供了一个有希望的工具.

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