Document Detail


Diffusion tensor-based regional gray matter tissue segmentation using the international consortium for brain mapping atlases.
MedLine Citation:
PMID:  20799340     Owner:  NLM     Status:  In-Process    
Abstract/OtherAbstract:
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.
Authors:
Khader M Hasan; Richard E Frye
Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural    
Journal Detail:
Title:  Human brain mapping     Volume:  32     ISSN:  1097-0193     ISO Abbreviation:  Hum Brain Mapp     Publication Date:  2011 Jan 
Date Detail:
Created Date:  2010-12-15     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9419065     Medline TA:  Hum Brain Mapp     Country:  United States    
Other Details:
Languages:  eng     Pagination:  107-17     Citation Subset:  IM    
Copyright Information:
Hum Brain Mapp, 2010. © 2010 Wiley-Liss, Inc.
Affiliation:
Department of Diagnostic and Interventional Imaging, University of Texas Medical School at Houston, Houston, Texas, USA. Khader.M.Hasan@uth.tmc.edu
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MeSH Terms
Descriptor/Qualifier:
Grant Support
ID/Acronym/Agency:
NS046565/NS/NINDS NIH HHS; R01 NS052505-04/NS/NINDS NIH HHS

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