使用磁共振结构成像来识别轻度认知障碍患者的疾病进展:基于voxel的形态学和基于表面的形态学研究
Zihan Zhang1, Jiaxuan Peng2, Yuan Shao2
1Jinzhou Medical University Postgraduate Education Base (Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College), Hangzhou, Zhejiang Province, China.
Neuroscience
|May 3, 2025
概括
使用VBM和SBM进行结构性脑成像可以检测轻度认知障碍 (MCI) 的进展. 综合成像分析准确地识别出进展性MCI的患者,有助于早期风险分层和个性化护理.
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:
- 轻度认知障碍 (MCI) 是阿尔茨海默病的过渡阶段.
- 准确识别MCI进展对于及时干预至关重要.
- 当前的诊断工具可能无法完全捕捉与MCI进展相关的结构变化.
研究的目的:
- 研究基于Voxel的形态测量 (VBM) 和基于表面的形态测量 (SBM) 对于检测MCI患者的结构差异的实用性.
- 利用神经成像数据开发和验证用于预测MCI进展的诊断模型.
- 将结构成像模型的诊断性能与基于认知评估的模型进行比较.
主要方法:
- 从ADNI数据库中对154名MCI患者进行了回顾性分析 (62名MCI进展,92名MCI稳定).
- 应用VBM和SBM来识别渐进型和稳定的MCI组之间的结构差异.
- 使用结构指数和认知分数 (MMSE,MOCA) 开发后勤回归模型,使用NACC数据进行外部验证.
主要成果:
- 在渐进和稳定的MCI患者之间发现了显著的结构差异.
- 在渐进的MCI中观察到,额叶和叶的体积减少,叶区域的皮质稀薄,以及岛圈的缩减少.
- 结合VBM和SBM指数的结构联合模型显示,与基于MMSE和MOCA分数的模型相比,诊断准确度更高.
结论:
- 结合VBM和SBM分析提供了对MCI进展的结构生物标志物的敏感和非侵入性检测.
- 开发的结构联合模型显示了用于识别渐进性MCI的高诊断性能.
- 这些发现支持使用综合神经成像方法进行早期风险分层和个性化MCI管理.
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