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Quantitative examination of a novel clustering method using magnetic resonance diffusion tensor tractography
Institution:
 1Geriatric Mental Health Program, Centre for Addiction and Mental Health, Department of Psychiatry, University of Toronto, Canada; Department of Neuroscience, Centre for Addiction and Mental Health, Department of Psychiatry, University of Toronto, Canada.
2Department of Neuroscience, Centre for Addiction and Mental Health, Department of Psychiatry, University of Toronto, Canada
3Golby Laboratory, Department of Neurosurgery, Brigham and Women's Hospital, Harvard University, USA
4Cognitive Neurology, Sunnybrook Health Sciences Centre, Department of Medicine, University of Toronto, Canada
5Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard University, USA
6Department of Computer Science and Biomedical Imaging Research Center, University of North Carolina, Chapel Hill, USA
7Laboratory for Mathematics in Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard University, USA
8VA Boston Healthcare System, Brockton Division, Brockton MA, Harvard University, USA
Publisher:
 Neuroimage
Publication Date:
 Apr-2009
Citation:
 Neuroimage. 2009 Apr 1;45(2):370-6.
PubMed ID:
 19159690
PMCID:
 PMC2646811
Keywords:
 Diffusion tensor imaging, Clustering, Tractography, Region of interest, Streamline, Schizophrenia
Appears in Collections:
PNL, LMI, NAC, NCIGT
Sponsors:
 Canadian Institutes of Health Research Clinician Scientist Award
NIH U41 RR019703
Brain Science Foundation
NIH R01 MH074794
NIH P41 RR13218
NIH R01 MH50740
NIH 1P50 MH08272
NIH U54 GM072977-01
Schizophrenia Center Grant
Sandra A. Rotman Research Institute
Generated Citation:
 Voineskos A, O'Donnell L, Lobaugh N, Markant D, Ameis S, Niethammer M, Mulsant B, Pollock B, Kennedy J, Westin C, Shenton M. Quantitative examination of a novel clustering method using magnetic resonance diffusion tensor tractography. Neuroimage. 2009 Apr 1;45(2):370-6. PMID: 19159690. PMCID: PMC2646811.
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MR diffusion tensor imaging (DTI) can measure and visualize organization of white matter fibre tracts in vivo. DTI is a relatively new imaging technique, and new tools developed for quantifying fibre tracts require evaluation. The purpose of this study was to compare the reliability of a novel clustering approach with a multiple region of interest (MROI) approach in both healthy and disease (schizophrenia) populations. DTI images were acquired in 20 participants (n=10 patients with schizophrenia: 56±15 years; n=10 controls: 51±20 years) (1.5 T GE system) with diffusion gradients applied in 23 non-collinear directions, repeated three times. Whole brain seeding and creation of fibre tracts were then performed. Interrater reliability of the clustering approach, and the MROI approach, were each evaluated and the methods compared. There was high spatial (voxel-based) agreement within and between the clustering and MROI methods. Fractional anisotropy, trace, and radial and axial diffusivity values showed high intraclass correlation (p<0.001 for all tracts) for each approach. Differences in scalar indices of diffusion between the clustering and MROI approach were minimal. The excellent interrater reliability of the clustering method and high agreement with the MROI method, quantitatively and spatially, indicates that the clustering method can be used with confidence. The clustering method avoids biases of ROI drawing and placement, and, not limited by a priori predictions, may be a more robust and efficient way to identify and measure white matter tracts of interest.

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