Diffusion tensor‐based regional gray matter tissue segmentation using the international consortium for brain mapping atlases

Abstract

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.

Multimodal Quantitative Magnetic Resonance Imaging of Thalamic Development and Aging across the Human Lifespan: Implications to Neurodegeneration in Multiple Sclerosis

“…The age-expected volume of regional WM tracts, subcortical GM, and whole brain tissue have been reported previously on ~ 60% of all healthy children and adults included in this Communication (Hasan et al, 2007; Hasan et al, 2010a,b; Hasan and Frye 2011). The age-expected global or regional volumetry and their corresponding microstructural attributes obtained on healthy children, adults and across the lifespan were consistent with data published by others (Courchesne et al, 2000; Sowell et al, 2003; Lebel et al, 2008; Saito et al, 2009; Leppert et al, 2009; Ostby et al, 2009; Kochunov et al, 2010; Walhovd et al, 2011).…”

“…The MRI data used in this Communication were collected over ~ 5 year span during which scanner stability, intrascan and interscan reliability and reproducibility were monitored closely using a database of water phantom relaxation time and DTI measurements (Hasan, 2007) and brain data acquired serially on healthy children (Hasan et al, 2011b), healthy adults (Hasan et al, 2007; Hasan and Frye 2011) and MS patients (Hasan et al, 2009). The age-expected volume of regional WM tracts, subcortical GM, and whole brain tissue have been reported previously on ~ 60% of all healthy children and adults included in this Communication (Hasan et al, 2007; Hasan et al, 2010a,b; Hasan and Frye 2011).…”

Human brain atlas-based multimodal MRI analysis of volumetry, diffusimetry, relaxometry and lesion distribution in multiple sclerosis patients and healthy adult controls: Implications for understanding the pathogenesis of multiple sclerosis and consolidation of quantitative MRI results in MS

“…It is well-documented that whole brain gray matter [29, 37, 47, 48], cortical [47] and subcortical [20, 30, 37, 49] undergo age-related volume loss. Therefore, it is important to attempt to decouple natural age-related changes from MS pathology effects [20, 30].…”

Serial Atlas-Based Diffusion Tensor Imaging Study of Uncomplicated Mild Traumatic Brain Injury in Adults

“…Regional cerebrospinal fluid, gray matter, and white matter segmentation using diffusion tensor imaging DTI scalar maps were used to facilitate regional tissue segmentation and parcellation, using statistical parametric mapping (SPM) unified and multi-modal segmentation 37 implemented in SPM (http://www.fil.ion.ucl.ac.uk/spm/), as previously described 38 and applied elsewhere. 39,40 In brief, the segmentation of GM, WM, and CSF utilized the high contrast offered by DTI between brain parenchyma and CSF in the FA versus MD space.…”