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在神经血管压缩下分析单边三角神经疼痛的危险因素

Juncheng Yan¹, Luoyu Wang², Lei Pan²

¹Department of Rehabilitation, Hangzhou First People's Hospital, Hangzhou, China.

Frontiers in human neuroscience

|May 3, 2024

概括

神经血管压缩侧,血管类型和三角神经微观结构是三角神经疼痛的关键危险因素. 这些因素,包括未受影响侧的变化,为病情的发展提供了洞察力.

科学领域:

神经学神经学
医疗成像医学成像
机器学习机器学习

背景情况:

三神经疼痛 (TN) 是一种使人虚弱的面部疼痛状况.
单边经典或异常性三角神经疼痛 (C-ITN) 的风险因素和原因仍然不完全理解.
神经血管压缩 (NVC) 与TN病变发生有关.

研究的目的:

确定C-ITN的风险因素和潜在原因.
使用机器学习 (ML) 将C-ITN患者和健康对照 (HC) 与NVC患者进行比较.

主要方法:

招募了84名C-ITN患者和78名年龄/性别匹配的HC.
评估了三角骨角,确定了压缩容器 (位置,严重程度).
利用ML分析三神经 (CN V) 的水部分.

主要成果:

确定了NVC侧面,压缩容器和纹理特征作为C-ITN风险因素.
在C-ITN患者中,在未受影响的侧面发现了CN V微观结构的差异.
在53名C-ITN患者中观察到未受影响侧的NVC和25名HC患者的双边NVC.

结论:

NVC侧,压缩容器和CN V微结构与C-ITN风险有关.
在未受影响的CN V中微观结构变化表明间接影响.
这些发现提高了对C-ITN病原体和潜在诊断标记物的理解.

关键词:

机器学习是机器学习.磁共振成像技术的使用神经血管压缩是一种神经血管压缩.有关风险因素的风险因素.三胞胎神经疼痛三胞胎神经疼痛

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