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血液动力学反应作为2型糖尿病生物标志物的功能:基于数据的方法.

Pedro Guimarães1, Pedro Serranho1,2, João V Duarte1,3

  • 1University of Coimbra, Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute for Nuclear Sciences Applied to Health (ICNAS), Coimbra, Portugal.

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概括

我们可以通过分析大脑血液动力学反应功能 (HRF) 改变来准确识别2型糖尿病患者 (T2DM). 这些独特的HRF模式显示出作为T2DM神经生理变化的早期生物标志物具有前途.

关键词:
深度学习是一种深度学习.功能性磁共振成像技术 功能性磁共振成像技术血液动力学反应反应神经成像是一种神经成像.2 型糖尿病 2 型糖尿病

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科学领域:

  • 神经科学是一个神经科学.
  • 医疗成像医学成像
  • 生物标志物发现发现

背景情况:

  • 2型糖尿病 (T2DM) 与早期神经生理变化有关,这些变化先于结构性或血管损伤.
  • 了解这些早期的大脑变化对于及时干预至关重要.
  • 目前的方法可能无法完全捕捉微妙的,早期的神经功能障碍.

研究的目的:

  • 开发和验证一种无偏见的,数据驱动的方法来检测和表征T2DM患者的血液动力反应功能 (HRF) 改变.
  • 探索这些HRF变化作为T2DM早期生物标志物的潜力.
  • 确定在早期T2DM中受到影响的特定大脑区域和神经机制.

主要方法:

  • 使用基于任务的与事件相关的功能磁共振成像 (fMRI) 与视觉速度区分任务.
  • 采用深度学习 (DL) 和可解释性技术结合解卷化通用线性模型.
  • 进行了相关性分析,以确定与歧视有关的关键大脑区域.

主要成果:

  • 根据HRF,在区分T2DM患者方面达到高达95%的准确性.
  • 在增加刺激对比度和在左视觉半球中表现出更高的分类性能.
  • 确定了外层视觉皮质,顶层皮质和岛屿作为歧视的关键区域.

结论:

  • 基于数据的HRF分类可以准确地区分T2DM患者.
  • HRF变化是T2DM早期神经生理学变化的有希望的生物标志物.
  • 这种方法为了解T2DM相关的大脑功能障碍提供了一种新的方法.