Analysis of partial volume effects in diffusion-tensor MRI.
The diffusion tensor is currently the accepted model of diffusion in biological tissues. The measured diffusion behavior may be more complex when two or more distinct tissues with different diffusion tensors occupy the same voxel. In this study, a partial volume model of MRI signal behavior for two diffusion-tensor compartments is presented. Simulations using this model demonstrate that the conventional single diffusion tensor model could lead to highly variable and inaccurate measurements of diffusion behavior. The differences between the single and two-tensor models depend on the orientations, fractions, and exchange between the two diffusion tensor compartments, as well as the diffusion-tensor encoding technique and diffusion-weighting that is used in the measurements. The current single compartment model's inaccuracies could cause diffusion-based characterization of cerebral ischemia and white matter connectivity to be incorrect. A diffusion-tensor MRI imaging experiment on a normal human brain revealed significant partial volume effects between oblique white matter regions when using very large voxels and large diffusion-weighting (b approximately 2.69 x 10(3) sec/mm(2)). However, the apparent partial volume effects in white matter decreased significantly when smaller voxel dimensions were used. For diffusion tensor studies obtained using typical diffusion-weighting values (b approximately 1 x 10(3) sec/mm(2)) partial volume effects are much more difficult to detect and resolve. More accurate measurements of multiple diffusion compartments may lead to improved confidence in diffusion measurements for clinical applications.
Alexander
A L
AL
Department of Medical Physics, University of Wisconsin, Madison 53705-2280, USA. alalexander2@facstaff.wisc.edu
Hasan
K M
KM
Lazar
M
M
Tsuruda
J S
JS
Parker
D L
DL
D016880:Anisotropy; D001921:Brain / Q000033:anatomy & histology*; D003198:Computer Simulation; D004058:Diffusion; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*