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Correlation between gray matter density‐adjusted brain perfusion and age using brain MR images of 202 healthy children

机译:使用202名健康儿童的脑MR图像对灰质密度调整后的脑灌注与年龄之间的相关性

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摘要

We examined the correlation between brain perfusion and age using pulsed arterial spin‐labeling (ASL) magnetic resonance images (MRI) in a large number of healthy children. We collected data on brain structural and ASL perfusion MRI in 202 healthy children aged 5–18 years. Structural MRI data were segmented and normalized, applying a voxel‐based morphometric analysis. Perfusion MRI was normalized using the normalization parameter of the corresponding structural MRI. We calculated brain perfusion with an adjustment for gray matter density (BP‐GMD) by dividing normalized ASL MRI by normalized gray matter segments in 22 regions. Next, we analyzed the correlation between BP‐GMD and age in each region by estimating linear, quadratic, and cubic polynomial functions, using the Akaike information criterion. The correlation between BP‐GMD and age showed an inverted U shape followed by a U‐shaped trajectory in most regions. In addition, age at which BP‐GMD was highest was different among the lobes and gray matter regions, and the BP‐GMD association with age increased from the occipital to the frontal lobe via the temporal and parietal lobes. Our results indicate that higher order association cortices mature after the lower order cortices, and may help clarify the mechanisms of normal brain maturation from the viewpoint of brain perfusion. Hum Brain Mapp, 2011. © 2011 Wiley‐Liss, Inc.
机译:我们使用脉冲动脉自旋标记(ASL)磁共振图像(MRI)检查了许多健康儿童的脑灌注与年龄之间的相关性。我们收集了202名5-18岁健康儿童的大脑结构和ASL灌注MRI数据。使用基于体素的形态计量学分析对结构MRI数据进行分段和标准化。使用相应结构MRI的归一化参数对灌注MRI进行归一化。通过将归一化的ASL MRI除以归一化的灰质段(在22个区域中),我们计算了脑灌注量并调整了灰质密度(BP-GMD)。接下来,我们使用Akaike信息准则通过估计线性,二次和三次多项式函数来分析每个区域中BP-GMD与年龄之间的相关性。 BP-GMD与年龄之间的相关性在大多数地区呈倒U形,然后呈U形轨迹。此外,在肺叶和灰质区域中,BP-GMD最高的年龄有所不同,并且BP-GMD与年龄的关联通过颞叶和顶叶从枕骨到额叶增加。我们的结果表明,高阶缔合皮质在低阶皮质之后成熟,并且可能有助于从脑灌注的角度阐明正常大脑成熟的机制。嗡嗡的脑图,2011年。©2011 Wiley-Liss,Inc.

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