Day 1 Basic understanding of
the diffusion tensor
09.00-10.00 Basic linear algebra
10.00-10.15
Strong coffee break
10.15-11.00 Ficks law, probability
distribution, iso-surfaces (the diffusion ellipsoid), the diffusion tensor
matrix
11.00-11.45 Rotated tensors,
diagonalising the tensor, eigenvalues and eigenvectors
11.45-12.45
Lunch
12.45-13.30 Calculating the tensor
from diffusion MR data
b-values, ADC, diffusion schemes with 6 or more directions
13.30-14.00 Scalar invariants
(gray scale images) of DT data
Mean ADC, Anisotropy, Skewness
14.00-14.20
Strong coffee break
14.20-16:30 Practical session – A single voxel DTI experience
Calculate and visualise your own tensor based on diffusion weighted data
for diffusion schemes with 6 and more than 6 directions. Calculation of the
scalar invariants of the tensor. MATLAB is used for this purpose.
The purpose of this session is also to have time to discuss and ask questions
that may have arised during the lectures so far
Day 2 Optimisation & correction
of artefacts in DTI data
09.00-09.30 Ways of using DTI data
Clinical use, group analyses, colour mapping, fibre tracking
09.30-10.00 Optimal b-value,
avoiding cross-terms, the b-matrix
10.00-10.15 Strong coffee break
10.15-10.30 Diffusion schemes
10.30-11.00 Problems with single shot pulse
sequences
Image blurring, SNR, Chemical shift, Maxwell terms, Susceptibility
artefacts
11.00-11.45 Diffusion gradient related image artefacts
Ghosting (multi-shot pulse sequences), Stimulated echoes (SS-FSE),
Signal dropout (brain motion), Eddy currents,Mismatch between DW component
images (patient motion)
