Dickerson B C, Fenstermacher E, Salat D H, Wolk D A, Maguire R P, Desikan R, Pacheco J, Quinn B T, Van der Kouwe A, Greve D N, Blacker D, Albert M S, Killiany R J, Fischl B
Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Neuroimage. 2008 Jan 1;39(1):10-8. doi: 10.1016/j.neuroimage.2007.08.042. Epub 2007 Sep 5.
In normal humans, relationships between cognitive test performance and cortical structure have received little study, in part, because of the paucity of tools for measuring cortical structure. Computational morphometric methods have recently been developed that enable the measurement of cortical thickness from MRI data, but little data exist on their reliability. We undertook this study to evaluate the reliability of an automated cortical thickness measurement method to detect correlates of interest between thickness and cognitive task performance. Fifteen healthy older participants were scanned four times at 2-week intervals on three different scanner platforms. The four MRI data sets were initially treated independently to investigate the reliability of the spatial localization of findings from exploratory whole-cortex analyses of cortical thickness-cognitive performance correlates. Next, the first data set was used to define cortical ROIs based on the exploratory results that were then applied to the remaining three data sets to determine whether the relationships between cognitive performance and regional cortical thickness were comparable across different scanner platforms and field strengths. Verbal memory performance was associated with medial temporal cortical thickness, while visuomotor speed/set shifting was associated with lateral parietal cortical thickness. These effects were highly reliable - in terms of both spatial localization and magnitude of absolute cortical thickness measurements - across the four scan sessions. Brain-behavior relationships between regional cortical thickness and cognitive task performance can be reliably identified using an automated data analysis system, suggesting that these measures may be useful as imaging biomarkers of disease or performance ability in multicenter studies in which MRI data are pooled.
在正常人类中,认知测试表现与皮质结构之间的关系鲜有研究,部分原因是缺乏测量皮质结构的工具。最近开发了计算形态测量方法,能够从MRI数据测量皮质厚度,但关于其可靠性的数据很少。我们进行这项研究是为了评估一种自动皮质厚度测量方法检测厚度与认知任务表现之间感兴趣的相关性的可靠性。15名健康的老年参与者在三个不同的扫描仪平台上每隔2周扫描4次。最初对这四个MRI数据集进行独立处理,以研究从皮质厚度-认知表现相关性的探索性全皮质分析中得出的结果的空间定位的可靠性。接下来,使用第一个数据集根据探索性结果定义皮质ROI,然后将其应用于其余三个数据集,以确定不同扫描仪平台和场强下认知表现与区域皮质厚度之间的关系是否具有可比性。言语记忆表现与内侧颞叶皮质厚度相关,而视觉运动速度/定势转换与外侧顶叶皮质厚度相关。就空间定位和绝对皮质厚度测量的大小而言,这些效应在四个扫描阶段都高度可靠。使用自动数据分析系统可以可靠地识别区域皮质厚度与认知任务表现之间的脑-行为关系,这表明在汇集MRI数据的多中心研究中,这些测量可能作为疾病或表现能力的成像生物标志物有用。