Probabilistic: Provides a probability distribution on the diffusion direction at each voxel (the broader the distribution, the higher the uncertainty of connections in that area) which is then used to draw thousands of streamlines to build up a connectivity distribution Advantages: - Allows to continue tracking in areas of high uncertainty (with very curvy tracts) - Provides a quantitative measure of the probability of a pathway being traced between two points Tractography Slide 17 Practice Deterministic Probabilistic Tractography Johansen-Berg & Rushworth, 2009 Slide 18 Practice Whole brain versus ROI based approach (Atlas generation) Tractography Slide 19 Practice Applications o Human Connectome generation of human white matter atlases o Comparing groups (personality traits, diseases, psychological disorders) o Longitudinal studies to investigate age or experience dependent white matter changes o Presurgical planning o etc. Tractography Johansen-Berg & Rushworth, 2009 Slide 16 Practice Deterministic: A point estimate of the principal diffusion direction at each voxel is used to draw a single line. Mohammadis ANI slides Slide 7 Diffusion Tensor Imaging Image acquisition You will need: 1) at least 6 diffusion weighted images (DWI) at a given b-value 2) b 0 image (a T2-weighted image) DWI z DWI x DWI y b0b0 Slide 8 Diffusion Tensor Imaging How do we describe diffusion? Diffusion in one dimension Ficks Law Diffusion in 3 dimensions The diffusion tensor (one value) A diffusion coefficient for every direction Slide 9 Diffusion Tensor Imaging Trace Diagonal terms Diffusivity along x, y, z Positive values Crossterms Diffusivity along/against crossterm Positive and negative values Slide 10 Diffusion Tensor Imaging Results Two types of images you can obtain: Mean diffusivity (MD) Average of diffusion (D) at every voxel across trace Independent of direction Fractional anisotropy (FA) Degree of diffusion anisotropy at every voxel estimated by tensor Scalar Direction independent Value from 0 (isotropy) to 1 (anisotropy) Slide 11 Diffusion Tensor Imaging Colour FA map Colour the map based on the principal diffusion direction Red = left / right Green = anterior / posterior Blue = superior / inferior Vector FA map Superimpose principal direction vector Tractography Following the vectors more on this later Slide 12 Diffusion Tensor Imaging Theory summary Water diffuses isotropically in water, anisotropically in oriented tissue DTI requires a diffusion-sensitizing gradient and at least 6 acquisitions (+ a B0 image) Anisotropic diffusion can be described by a mathematical tensor Diffusion can be summarised as MD or FA maps Slide 13 Overview Theory Basic physics Tensor Diffusion imaging Practice How do you do DTI? Tractography DTI in FSL and other programs Slide 14 Practice 1.Preprocessing: Realigning Coregistration Eddy current correction 2.Analysis: Fit the diffusion tensor model to the data Calculate maximum diffusion direction, MD & FA 3.Research Question ? How do you do DTI? Slide 15 Practice A technique that allows to identify fiber bundle tracts by connecting voxels based on the similiarities in maximal diffusion direction. Diffusion Tensor Imaging Slide 2 Overview Theory Basic physics Tensor Diffusion imaging Practice How do you do DTI? Tractography DTI in FSL and other programs Slide 3 Diffusion Tensor Imaging Brownian motion Random drifting of particles in a spatially homogeneous medium Ficks Law J = particle flux density C = particle concentration D = diffusion constant X = position Slide 4 Diffusion Tensor Imaging Isotropy and anisotropy In an unrestricted environment, water molecules move randomly When placed in a constrained environment, they diffuse more easily along the structure Isotropic voxelAnisotropic voxel Hagmann et al., 2006 Slide 5 Diffusion Tensor Imaging CSF Isotropic High diffusivity Grey matter Isotropic Low diffusivity White matter Anisotropic High diffusivity Slide 6 Diffusion Tensor Imaging Apply diffusion gradients S.
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