微观结构损伤的网络预测了多发性硬化症中的残疾.
Elisa Colato1, Ferran Prados2,3,4,5, Jonathan Stutters2
1Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK elisa.colato.18@ucl.ac.uk.
Journal of neurology, neurosurgery, and psychiatry
|July 19, 2023
概括
白质和灰质的基于网络的MRI标记器预测了多发性硬化症 (MS) 的残疾和认知衰退. 这种方法可以识别患有症状恶化风险较高的患者,并有助于临床试验分层.
科学领域:
- 神经成像是一种神经成像.
- 神经学 神经学
- 生物标志物 生物标志物
背景情况:
- 基于网络的磁共振成像 (MRI) 测量越来越被认为是多发性硬化症 (MS) 的重要标记.
- 识别受损害的特定白质 (WM) 和灰质 (GM) 网络对于了解疾病进展至关重要.
研究的目的:
- 确定微观结构损伤的WM和GM网络,预测MS患者的残疾进展和认知恶化.
- 利用数据驱动的方法来发现预测性网络标记.
主要方法:
- 从发现和复制队伍中分析了1836名MS参与者的数据.
- 在GM和WM中计算标准化的T1w/T2w比率图,然后进行空间独立组件分析来定义损伤网络.
- 使用考克斯的比例危险模型来评估网络措施的预测价值,以确定残疾进展 (CDP) 和符号数字模式测试 (SDMT) 的恶化.
主要成果:
- 识别了8个WM和7个GM网络,显示了两个队列中sT1w/T2w措施的区域共变.
- 前冠状辐射和temporo-parieto-frontal区域的特定网络负载预测了较高的CDP风险.
- 弧形囊,体,深层GM和皮质大脑区域的网络负载,以及病变负载,预测SDMT恶化的风险更高.
结论:
- 在GM和WM中微观结构变化的网络作为MS中残疾和认知恶化的可靠预测器.
- 这种基于网络的方法对于识别高风险多发性硬化患者和临床试验参与者的分层有价值.
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