Diffusion Models and Metrics

Before practicum on Friday, please complete following:

During practicum on Friday:


Review: Diffusion MRI Preprocessing (10 min)

Diffusion MRI models (10 min)

Model/Method Full Name Tool Publications B-table requirements Handle Free Water Quantify Restricted Diffusion Resolve Multiple Fibers Metrics
DTI (Basser, 1994) Diffusion tensor imaging   353,000 B0, >= 1 b-value(s) No (except for DTI-FWE) No No (except for Multi-Tensor) fa, ad, rd, md
DKI (Jensen, 2005) Diffusion kurtosis imaging DKE 6,400 B0, >= 2 b-values No Yes No (except for Multi-Tensor) ak, rk, mk
NODDI (Zhang, 2012) Neurite Orientation Dispersion and Density Imaging NODDI Matlab Toolbox 4,680 B0, >= 2 b-values Yes Yes No (except for Multi-Fiber NODDI ) iso, odi, ndi (icvf)
BSM (Behrens,2003) Ball & Stick Model BEDPOSTX,FSL 1,830 B0, >= 1 b-value(s) Yes Yes Yes qa, iso, rdi
Model-Free (Q-Space Imaging)                
DSI (Wedeen, 2005) Diffusion Spectrum Imaging TrackVis 5,480 B0, >10 b-values on grid No No Yes -
QBI (Tuch,2004) Q-ball Imaging TrackVis 3,460 B0, 1 b-value No No Yes gfa
GQI (Yeh, 2010),QSDR (Yeh,2011) Generalized Q-sampling Imaging,
Q-Space Diffeomorphic Reconstruction
DSI Studio 860,
B0, >= 1 b-value(s) Yes Yes Yes qa, iso, rdi
Spherical Deconvolution                
CSD (Tournier,2007) Constrained Spherical Deconvolution MRtrix3, DIPY 4,010 1 b-value No No Yes afd
MSMT-CSD (Jeurissen,2014) Multi-Shell, Multi-Tissue CSD MRtrix3, DIPY 229 >= 2 b-values Yes Yes Yes afd

Personal recommendation:

for deriving voxel-wise metrics

for mapping white matter tracts

Hands-on: DTI, GQI, and QSDR Reconstruction (10 min)

Metrics (10 min)

P. Mukherjee, J.I. Berman, S.W. Chung, C.P. Hess and R.G. Henry American Journal of Neuroradiology April 2008, 29 (4) 632-641; DOI: https://doi.org/10.3174/ajnr.A1051


Hands-on: dMRI analysis (15 min)

Practicum assignment: ROI-based and Track-based analysis comparing SCA2 with controls

  1. Download SCA2 eddy-processed SRC Files. Ignore those in the follow-up folder.
  2. Reconstruct data at [Step T2 Reconstruction] using QSDR
  3. Create connectometry databases using [Step C1: Create a connectometry Database] and select dti_fa as the metric. The created database can be checked using [Step C2].
  4. Open the database at [Step T3: Fiber Tracking]
  5. Use region-based analysis to get fa at pons and compare between patients and controls.
  6. Use tract-based analysis to get fa at CST and compare between patients and controls.
  7. Cut CST into multiple segments and compare them between patients and controls.