Diffusion Tensor Imaging Analysis of Regional Whiter
Matter Changes along the Cingulum in Mild Cognitive Impairment

Xuwei Liang, Ning Kang, Jun Zhang
Laboratory for Computational Medical Imaging & Data Analysis
Department of Computer Science
University of Kentucky
773 Anderson Tower
Lexington, KY 40506-0046, USA

and
Stephen E. Rose, and Jonathan B. Chalk
Centre for Magnetic Resonance
University of Queensland
Brisbane, QLD, 4072, Australia

Abstract

Diffusion tensor imaging (DTI) based tractography enables selective reconstruction of specific white matter (WM) pathways. The cingulum tracts, connecting hippocampal, thalamic and association cortices, are suspected to be involved in the episodic memory impairment in mild cognitive impairment (MCI). We investigate the local micro structural WM changes along the cingulum paths that could not be studied effectively due to its curvilinear feature in the posterior and anterior regions, which causes significant difficulty in defining the regions of interest and in comparing diffusion properties across individual subjects in three dimensional (3D) brain images. We develop a new analysis technique to define the complex 3D regions of interest, reconstruct the entire cingulum tracts, and measure the regional micro structural WM alternations along the major fiber bundles. Our approach is based on DTI tractography and geodesic path mapping, which allows cross-subject evaluation of diffusion properties along the cingulum by parameterizing the space of reconstructed pathways as a function of geodesic distance. Assessment of the technique by comparing 17 MCI participants and 17 controls reveals specific anatomical locations along the left cingulum paths with significantly reduced fractional anisotropy value in the MCI subjects. The results show that this analysis technique is promising and may provide a sensitive approach to determining the integrity of WM tracts for complex regions of interest in the brain.


Key words: Mild cognitive impairment, cingulum, diffusion tensor imaging, tractography, geodesic distance.

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Download the PDF file liang1.pdf.
Technical Report No. 489-07, Department of Computer Science, University of Kentucky, Lexington, KY, 2007.


The authors would like to thank Greig de Zubicaray and Brona O'Dowd for their work on the MCI project. The research work of J. Zhang was supported in part by the US National Science Foundation under grant CCF-0527967 and CCF-0727600, in part by the National Institutes of Health under grant 1R01HL086644-01, in part by the Kentucky Science and Engineering Foundation under grant KSEF-148-502-06-186, and in part by the Alzheimer's Association under grant NIRG-06-25460.