Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI.
Quantitative-diffusion-tensor MRI consists of deriving and displaying parameters that resemble histological or physiological stains, i.e., that characterize intrinsic features of tissue microstructure and microdynamics. Specifically, these parameters are objective, and insensitive to the choice of laboratory coordinate system. Here, these two properties are used to derive intravoxel measures of diffusion isotropy and the degree of diffusion anisotropy, as well as intervoxel measures of structural similarity, and fiber-tract organization from the effective diffusion tensor, D, which is estimated in each voxel. First, D is decomposed into its isotropic and anisotropic parts, [D] I and D - [D] I, respectively (where [D] = Trace(D)/3 is the mean diffusivity, and I is the identity tensor). Then, the tensor (dot) product operator is used to generate a family of new rotationally and translationally invariant quantities. Finally, maps of these quantitative parameters are produced from high-resolution diffusion tensor images (in which D is estimated in each voxel from a series of 2D-FT spin-echo diffusion-weighted images) in living cat brain. Due to the high inherent sensitivity of these parameters to changes in tissue architecture (i.e., macromolecular, cellular, tissue, and organ structure) and in its physiologic state, their potential applications include monitoring structural changes in development, aging, and disease.
Basser
P J
PJ
Biomedical Engineering and Instrumentation Program, NCRR, NINDS, Bethesda, Maryland 20892-5766, USA.
Pierpaoli
C
C
D000818:Animals; D001921:Brain / Q000033:anatomy & histology*; D002415:Cats; D004058:Diffusion; D004578:Electron Spin Resonance Spectroscopy; D005583:Fourier Analysis; D007089:Image Enhancement / Q000295:instrumentation*; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation*; D008279:Magnetic Resonance Imaging / Q000295:instrumentation*; D012680:Sensitivity and Specificity