Cortical thickness analysis examined through power analysis and a population simulation
Cortical thickness analysis examined through power analysis and a population simulation
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DOI：
10.1016/j.neuroimage.2004.07.045
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发表时间：
2005-01-01
期刊：
影响因子：
5.7
通讯作者：
Evans, AC
中科院分区：
文献类型：
--
作者：
Lerch, JP;Evans, AC
我们之前开发了一种使用 3-D MRI 数据和全自动表面提取 (ASP) 算法来测量整个大脑大脑皮层厚度的程序。本文检验了该算法的精度、其最佳性能参数以及该方法对皮质厚度的细微、焦点变化的敏感性。使用模拟人群研究和单受试者再现性指标研究了皮质厚度测量的精度。皮质厚度被证明是一种可靠的方法，灵敏度（真阳性概率）为 0.93。比较了六种不同的皮质厚度指标。最简单、最精确的方法是测量从白质到灰质表面的相应顶点之间的距离。给定两组 25 名受试者，使用 3-D 高斯核（半高全宽 = 30 毫米）模糊后可以恢复 0.6 毫米 (15%) 的厚度变化。二维表面流形的平滑也提高了精度；在本实验中，最佳颗粒大小为 30 毫米。 (C) 2004 年，爱思唯尔公司出版。
We have previously developed a procedure for measuring the thickness of cerebral cortex over the whole brain using 3-D MRI data and a fully automated surface-extraction (ASP) algorithm. This paper examines the precision of this algorithm, its optimal performance parameters, and the sensitivity of the method to subtle, focal changes in cortical thickness.The precision of cortical thickness measurements was studied using a simulated population study and single subject reproducibility metrics. Cortical thickness was shown to be a reliable method, reaching a sensitivity (probability of a true-positive) of 0.93. Six different cortical thickness metrics were compared. The simplest and most precise method measures the distance between corresponding vertices from the white matter to the gray matter surface. Given two groups of 25 subjects, a 0.6-mm (15%) change in thickness can be recovered after blurring with a 3-D Gaussian kernel (full-width half max = 30 mm). Smoothing across the 2-D surface manifold also improves precision; in this experiment, the optimal kernel size was 30 mm. (C) 2004 Published by Elsevier Inc.