Publication:
Quantitative examination of a novel clustering method using magnetic resonance diffusion tensor tractography

Thumbnail Image

Date

2009

Journal Title

Journal ISSN

Volume Title

Publisher

Elsevier BV
The Harvard community has made this article openly available. Please share how this access benefits you.

Research Projects

Organizational Units

Journal Issue

Citation

Voineskos AN, O'Donnell LJ, Lobaugh NJ, Markant D, Ameis SH, Niethammer M, Mulsant BH, Pollock BG, Kennedy JL, Westin CF, Shenton ME. 2009. Quantitative examination of a novel clustering method using magnetic resonance diffusion tensor tractography. Neuroimage 45, no. 2:370-6. doi:10.1016/j.neuroimage.2008.12.028

Research Data

Abstract

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 Tesla 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.

Description

Keywords

diffusion tensor imaging, tractography, streamline, clustering, region of interest, schizophrenia

Terms of Use

This article is made available under the terms and conditions applicable to Other Posted Material (LAA), as set forth at Terms of Service

Endorsement

Review

Supplemented By

Referenced By

Related Stories