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Introduction to Diffusion Tensor Imaging – Susumu Mori – Google Books
MR diffusion kurtosis imaging for neural tissue characterization. Unlike the diffusion 1 in a glass of pure water, which would be the same in all directions isotropicthe diffusion measured in tissue varies with direction is anisotropic.
Twenty-five pitfalls in the analysis of diffusion MRI data.
The most common approach is streamline tractography Figure 6 [ 52535455 ], which is closely related to an earlier method for visualization of tensor fields known as hyperstreamlines [ 56 ].
Virtual in vivo interactive dissection of white matter fasciculi in the human brain. Anatomical investigations have been undertaken regarding for example the structure of the language network [ 2324 ], the asymmetry of the white matter in twins and siblings [ 25 ], and the location, asymmetry, and variability of the fiber tracts [ 26 ]. High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity.
An introduction to diffusion tensor image analysis
FA is basically a normalized variance of the eigenvalues:. For the original paper that measured and compared several scalar measures, as well as suxumu eigenvalues, in different regions of the human brain see [ 11 ].
The parallel diffusivity measure, also called the axial diffusivity, is equal to the largest eigenvalue. A unified framework for clustering and quantitative analysis of white matter fiber tracts.
An introduction to diffusion tensor image analysis
The measured diffusion effects are averaged over a voxel three-dimensional pixelcomplicating the biophysical interpretation of the diffusion tensor [ 8384 ]. The motor-evoked potential threshold evaluated by tractography and electrical stimulation. Several computational methods can be used to perform basic streamline tractography. It has been applied to a tremendous variety of neuroscientific studies see reviews in [ 141516 ] including schizophrenia [ 17 ], traumatic brain injury [ 18 ], multiple sclerosis [ 1920 ], autism [ 21 ], and aging [ 22 ].
However, to date there is no perfect method, and it is unlikely that perfect tractography is possible. Orthogonal tensor invariants and the analysis of diffusion tensor magnetic resonance images. By repeating this process of diffusion weighting in multiple directions, a three-dimensional diffusion model the tensor can be estimated.
Another type of multiple b-value acquisition is diffusion spectrum imaging DSI [ 89 ]. The diffusion tensor was originally proposed for use in magnetic resonance imaging MRI by Peter Basser in [ 56 ]. The application of the Euler and Runge-Kutta methods to white matter tractography was explored in [ 5253 ].
A diffusion tensor imaging tractography atlas for virtual in vivo dissections. The introduction of the diffusion tensor model allowed, for the first time, a rotationally invariant description of the shape of water diffusion.
The scale of DTI and the brain: Visualization and Processing of Tensor Fields. DTI has also been applied for neurosurgical planning and navigation. To enhance visualization of the white matter and suppress information outside of it, the brightness of the color is usually controlled by tensor anisotropy FA.
Overall, this difficulty in interpretation of DTI is due to the fact that the scale at which diffusion is measured with DTI is very different from the size scale of individual axons.
A DTI study of introduciton and siblings. The trace is clinically useful in early stroke detection because it is sensitive to the initial cellular swelling cytotoxic edema which restricts diffusion [ 41 ]. Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention-Volume Part I; Springer-Verlag; Support Center Support Center.
Note that in clinical imaging ADC maps may be measured using fewer diffusion gradients than needed for the tensor. The cingulum can be seen in blue, and the posterior limb of the internal capsule in green. Resolving crossings in the corticospinal tract by two-tensor streamline tractography: Wherever possible, pointers will be provided to more in-depth technical articles or books for further reading.
Quantification of measurement error in DTI: The b-factor is near s m m 2 for the image S 0 which is Ddiffusion, and the b-factor is near 1, s m m 2 for the diffusion-weighted images S k in DTI.
These measures are interpreted as diffusivity parallel to and perpendicular to a white matter fiber tract, so they make the sjsumu sense in regions of coherently oriented axons with no fiber crossings. Proceedings of the National Introeuction of Sciences.
Diffusion tensor magnetic resonance imaging DTI difffusion a relatively new technology that is popular for imaging the white matter of the brain. For reviews of tractography techniques including explanations of common tractography tl and a comparison of methods see [ 5051 ].
Probabilistic diffusion tractography with multiple fibre orientations: High angular resolution diffusion imaging HARDI includes methods that acquire diffusion data using many more than 6 diffusion directions such as 32 or higher [ 86 ].
Three example diffusion tensors, selected from a DTI scan of the human brain to illustrate differences in tensor anisotropy and orientation. Multi-shell acquisitions enable description of the full diffusion function using measures such as displacement, zero-probability and kurtosis that are highly sensitive to myelin [ 8788 ].
Studying connections in the living human brain with diffusion MRI. Traumatic brain injury, major depression, and diffusion tensor imaging: For a comparison of diffusion calculation methods including least tensof and weighted least squares in the presence of noise see [ 38 ].
Example false negative streamline tractography error. We have tried to include equations for completeness but they are not necessary for understanding the paper. Colors were assigned automatically according to an atlas-based tractography segmentation method [ 60 ].