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人工智能分析了多发性硬化症患者的病变动态和大脑体积
Clemens Bettray1, Thanos Tsaktanis2, Angelika Mennecke1
1Department of Neuroradiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
Multiple sclerosis and related disorders
|February 11, 2026
概括
多发性硬化症 (MS) 中的人工智能 (AI) 揭示了灰质缩,而不仅仅是损伤负载,与残疾有很强的相关性. 这种人工智能驱动的MRI分析支持对亚临床进展的定量监测.
科学领域:
- 神经成像是一种神经成像.
- 人工智能的人工智能
- 量化MRI是指数量化的MRI.
背景情况:
- 定量MRI标记对于评估多发性硬化症 (MS) 进展至关重要.
- 基于人工智能的体积测量在临床实践中提供了对病变负担和脑缩的标准化评估.
研究的目的:
- 调查人工智能衍生体积测量和MS残疾之间的联系.
- 为了确定每年大脑体积损失 (ABVL) 和病变动态是否预测缩.
- 在现实世界MS队列中比较放射学和临床表现型.
主要方法:
- 888张来自455名多发性硬化症患者的MRI扫描的回顾性分析 (2016-2020年).
- 自动人工智能细分 (mdbrain®) 用于病变指标和大脑体积.
- 使用通用估计方程 (GEE) 进行纵向分析,以预测缩.
主要成果:
- EDSS (残疾分数) 与病变体积 (ρ=0.28) 和大脑总体积 (ρ=-0.32) 相相关.
- 更高的EDSS和更长的随访独立预测了缩;ABVL显示边界显著性.
- 观察到灰质占主导地位的缩,通常没有新的病变,表明神经退行.
结论:
- 灰质缩是MS残疾的更强的相关比损伤负担.
- 基于人工智能的定量MRI为现实世界监测提供可重现的缩评估.
- 人工智能工具可以通过量化大脑体积损失来帮助检测亚临床进展.
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