比其部分的总和还要多:多发性硬化症中多重脑网络的核心外周受损
Giuseppe Pontillo1,2,3, Ferran Prados1,4,5, Alle Meije Wink2
1Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, University College London, London, UK.
Human brain mapping
|December 31, 2024
概括
多模式脑MRI分析显示,多发性硬化症 (PwMS) 患者的网络组织中断. 这种核心-外围结构的破坏是 PwMS 疾病严重程度和认知障碍的潜在生物标志物.
科学领域:
- 神经成像是一种神经成像.
- 在Connectomics上,我们提供了连接.
- 系统神经科学 系统神经科学
背景情况:
- 在使用各种MRI技术的多发性硬化症 (PwMS) 患者中观察到大脑网络中断,但结果在连接领域各不相同.
- 现有研究通常独立分析结构,扩散或功能MRI数据,可能缺少集成网络的改变.
研究的目的:
- 开发和应用一个多层网络方法,整合结构MRI (sMRI),扩散MRI (dMRI) 和功能MRI (fMRI),以更好地描述大脑组织.
- 在PwMS中使用这种多式模式方法来调查大脑核心-外围组织的变化.
- 探索这些网络改变与临床结果的关联,包括残疾和认知功能.
主要方法:
- 一项回顾性横截面研究,利用PwMS的多式脑MRI数据和MAGNIMS网络中的健康对照.
- 将sMRI,dMRI和静止状态fMRI数据集成到一个多层网络框架中,以计算区域正确性和正确性破坏指数 (κ).
- 使用线性模型和随机森林分析来评估 κ 与疾病状况,身体残疾 (EDSS) 和认知障碍 (SDMT) 的关联.
主要成果:
- 普华永道展示了多重核心-外围组织 (κ) 的显著破坏,表明与控制相比,全球核心-外围结构减弱.
- 干扰干扰指数 (κ) 与临床表型,身体残疾 (EDSS) 和认知障碍 (SDMT) 有显著的相关性.
- 多重体 κ 成为疾病状况和认知障碍的关键预测指标,优于传统的MRI测量和单层网络分析.
结论:
- 多层网络分析为整合多模式MRI数据提供了全面的框架,揭示了对大脑组织的生物学和临床有意义的见解.
- 多重核心-外围结构的破坏是PwMS中疾病严重程度和认知障碍的强有力的指标.
- 这种连接的方法有望成为评估疾病进展和指导多发性硬化症治疗策略的潜在成像生物标志物.
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