首页> 外文会议>Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on >Small world network measures predict white matter degeneration in patients with early-stage mild cognitive impairment
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Small world network measures predict white matter degeneration in patients with early-stage mild cognitive impairment

机译:小型世界网络量度可预测患有早期轻度认知障碍的患者的白质退化

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Alzheimer''s Disease (AD) has long been considered a cortical degenerative disease, but impaired brain connectivity, due to white matter injury, may exacerbate cognitive problems. Predicting brain changes is critically important for early treatment. In a longitudinal diffusion tensor imaging study, we investigated white matter fiber integrity in 19 patients (mean age: 74.7 +/− 8.4 yrs at baseline) displaying early signs of mild cognitive impairment (eMCI). We first examined whether baseline average fractional anisotropy (FA) measures in the corpus callosum (CC) predicted changes in white matter integrity over the following 6 months. We then examined whether “small world” architecture measures — calculated from baseline connectivity maps — predicted white matter changes over the next 6 months. While average CC FA measures at baseline were not associated with future changes in FA, network measures were a sensitive biomarker for predicting white matter changes during this critical time before AD strikes.
机译:阿尔茨海默氏病(AD)长期以来一直被认为是皮质退行性疾病,但由于白质损伤,导致大脑的连通性受损,可能会加剧认知问题。预测脑部变化对于早期治疗至关重要。在纵向扩散张量成像研究中,我们调查了19例显示轻度认知障碍(eMCI)早期迹象的患者(平均年龄:基线时为74.7 +/- 8.4岁)的白质纤维完整性。我们首先检查了call体(CC)中的基线平均分数各向异性(FA)量度是否预测了接下来6个月白质完整性的变化。然后,我们检查了根据基线连通性图计算得出的“小世界”架构度量值是否预测了未来6个月内的白质变化。虽然基线时的平均CC FA测量值与FA的未来变化无关,但是网络测量值是预测AD发作前这一关键时期白质变化的敏感生物标记。

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