Diffusion Tensor-Based Regional Gray Matter Tissue Segmentation Using the International Consortium for Brain Mapping Atlases

被引:16
作者
Hasan, Khader M. [1 ]
Frye, Richard E. [2 ]
机构
[1] Univ Texas Houston, Sch Med, Dept Diagnost & Intervent Imaging, Houston, TX 77030 USA
[2] Univ Texas Hlth Sci Ctr Houston, Sch Med, Dept Pediat, Houston, TX USA
关键词
DTI; segmentation; Icosa21; ICBM; MNI; FreeSurfer; atlas; basal ganglia; putamen; lifespan; MAGNETIC-RESONANCE IMAGES; MIDSAGITTAL CORPUS-CALLOSUM; HUMAN BASAL GANGLIA; WHITE-MATTER; LIFE-SPAN; PROBABILISTIC ATLAS; NEUROANATOMICAL STRUCTURES; AUTOMATIC SEGMENTATION; VOLUMETRIC-ANALYSIS; CEREBRAL-CORTEX;
D O I
10.1002/hbm.21004
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
In this communication, we extended a previously described and validated diffusion tensor imaging (DTI) method for segmenting whole brain cerebrospinal fluid (CSF) and gray and white matter (WM) tissue to provide regional volume and DTI metrics of WM tract and cortical and subcortical gray matter. This DTI-based regional segmentation was implemented using the statistical parametric mapping (SPM) toolbox and used the international consortium for brain mapping atlases and Montreal Neurological Institute brain templates. We used our DTI-based segmentation approach to calculate the left putamen volume in a cohort of 136 healthy right-handed males and females aged 15.8-62.8 years. We validated our approach by demonstrating its sensitivity to age-related changes of the putamen. Indeed, our method found that the putamen volume decreased with age (r = 0.30; P < 0.001) while the corresponding fractional anisotropy (FA) increased with advancing age (r = 0.5; P < 0.00001). It is then demonstrated, on a subset of our cohort (n = 31), that the putamen volume obtained by our method correlated with measurements obtained from FreeSurfer (r = 0.396, P < 0.05). Our novel approach increases the information obtained with a DTI examination by providing routine volumetry measure, thereby eliminating separate scans to obtain volumetry data. In addition, the labeled volumes obtained with our method have the potential to increase the accuracy of fiber tracking. In the future, this new approach can be automated to analyze large data sets to help discover noninvasive neuroimaging markers for clinical trials and brain-function studies in both health and disease. Hum Brain Mapp 32: 107-117, 2011. (C) 2010 Wiley-Liss, Inc.
引用
收藏
页码:107 / 117
页数:11
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