کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6025842 1580899 2015 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Reliability and statistical power analysis of cortical and subcortical FreeSurfer metrics in a large sample of healthy elderly
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی علوم اعصاب شناختی
پیش نمایش صفحه اول مقاله
Reliability and statistical power analysis of cortical and subcortical FreeSurfer metrics in a large sample of healthy elderly
چکیده انگلیسی
FreeSurfer is a tool to quantify cortical and subcortical brain anatomy automatically and noninvasively. Previous studies have reported reliability and statistical power analyses in relatively small samples or only selected one aspect of brain anatomy. Here, we investigated reliability and statistical power of cortical thickness, surface area, volume, and the volume of subcortical structures in a large sample (N = 189) of healthy elderly subjects (64 + years). Reliability (intraclass correlation coefficient) of cortical and subcortical parameters is generally high (cortical: ICCs > 0.87, subcortical: ICCs > 0.95). Surface-based smoothing increases reliability of cortical thickness maps, while it decreases reliability of cortical surface area and volume. Nevertheless, statistical power of all measures benefits from smoothing. When aiming to detect a 10% difference between groups, the number of subjects required to test effects with sufficient power over the entire cortex varies between cortical measures (cortical thickness: N = 39, surface area: N = 21, volume: N = 81; 10 mm smoothing, power = 0.8, α = 0.05). For subcortical regions this number is between 16 and 76 subjects, depending on the region. We also demonstrate the advantage of within-subject designs over between-subject designs. Furthermore, we publicly provide a tool that allows researchers to perform a priori power analysis and sensitivity analysis to help evaluate previously published studies and to design future studies with sufficient statistical power.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroImage - Volume 108, March 2015, Pages 95-109
نویسندگان
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