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Updated: Jun 22, 2026

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
Direct quantitative comparison between cross-relaxation imaging and diffusion tensor imaging of the human brain at
Hunter R Underhill1, Chun Yuan, Vasily L Yarnykh
1Department of Radiology, University of Washington, Seattle, WA 98109, USA. hunterru@u.washington.edu
Abstract:
Cross-relaxation imaging (CRI) describes the magnetization transfer within tissues between mobile water protons and macromolecular protons. Whole-brain parametric maps of the principle kinetic components of magnetization transfer, the fraction of macromolecular protons (f) and the rate constant (k), revealed detailed anatomy of white matter (WM) fiber tracts at 1.5 T. In this study, CRI was first adapted to 3.0 T, and constraints for transverse relaxation times of water and macromolecular protons were identified to enable unbiased f and k estimation. Subsequently, whole-brain CRI and diffusion tensor imaging (DTI) were performed in five healthy subjects. The parameters f and k were compared to DTI indices (fractional anisotropy (FA), apparent diffusion coefficient (ADC), radial diffusivity (RD), and axial diffusivity (AD)) across a range of anatomic regions. In WM, neither f nor k was significantly correlated to FA, RD, and AD. In contrast, both f (r=0.90 and r=-0.80) and k (r=0.92 and r=-0.89) in gray matter (GM) were strongly correlated to FA and RD, respectively. A moderate correlation between ADC and k (r=0.48) was identified in WM, while an inverse correlation was identified in GM (r=-0.72). The lack of association between CRI and FA in WM is consistent with differences in the underlying physical principles between techniques - fiber density vs. directionality, respectively. The association in GM may be attributable to variable axonal density unique to each structure. Our findings suggest that whole-brain CRI provides distinct quantitative information compared to DTI, and CRI parameters may prove constructive as biomarkers in neurological diseases.
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