生物标志物 生物标志物
Bénédicte Maréchal1,2,3, Tommaso Di Noto1,2,3, Thanchanok Jomsak4
1Swiss Innovation Hub, Siemens Healthineers International AG, Lausanne, Switzerland.
Alzheimer's & dementia : the journal of the Alzheimer's Association
|December 24, 2025
概括
在MRI上的海马缩与阿尔茨海默氏病 (AD) 诊断的PET扫描中的低代谢有很强的相关性. 海马体积显示出良好的区分能力,可能作为一个查工具,如果PET是不可用的.
科学领域:
- 神经成像是一种神经成像.
- 人工智能的人工智能
- 阿尔茨海默氏症疾病研究研究
背景情况:
- 海马缩和低代谢是早期阿尔茨海默病 (AD) 诊断的关键神经成像生物标志物.
- 人工智能 (AI) 能够对脑MRI进行定量自动体积分析,以客观评估脑缩.
- 这项研究将MRI中的海马体积与早期AD诊断的18F-FDG PET低代谢进行比较.
研究的目的:
- 为了比较来自MRI的海马体积与18F-FDG PET低代谢.
- 评估这些生物标志物在早期诊断阿尔茨海默病的有用性.
- 评估海马体体积与低代谢之间的诊断区分能力.
主要方法:
- 22名阿尔茨海默症患者和26名对照人群在3T MR-PET系统上接受了结构性MRI和18F-FDG PET扫描.
- 一个深度学习工具 (MorphoBox) 从MRI量化了正常化的大脑体积;p-mod软件从PET计算了SUVR.
- 执行了皮尔森相关性和ROC分析,以比较成像模式并评估歧视.
主要成果:
- 在多个大脑区域,包括海马 (p < 0.001) 中,在AD和对照组之间观察到SUVR的显著差异.
- 在SUVR和正常的大脑体积之间发现了强烈的相关性 (ρ=0.60-0.73),特别是在海马,额叶,叶和叶.
- 海马相对体积显示出良好的区分能力,AUC为0.79.
结论:
- 在阿尔茨海默病中,海马体体积 (MRI) 和低代谢 (FDG PET) 之间存在强烈的相关性.
- 人工智能驱动的海马体积测量可以作为一种有价值的查工具,特别是当PET访问有限时.
- 在这项研究中,海马体积测量显示出优越的区分能力,这需要在更大的队列中进行进一步的研究.
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