DTI pre-processing

Diffusion Tensor Imaging depicts the anisotropy of tissue.

The acquisition protocol includes 6 or more diffusion weighted images (DWIs), one or more B null image (B0), all encoded into a 4D nifti file, its corresponding bval-bvec pair, a structural T1 image, an optional brain mask, and and optional field maps (FM) magnitude and phase that are used for susceptibility correction.

The nipype script to generate the DTI is perform_dti_processing.py and its help message is the following:

usage: perform_dti_processing.py [-h] -i dwis [dwis ...] -a bvals [bvals ...]
                                 -e bvecs [bvecs ...] -t t1 [-m fieldmapmag]
                                 [-p fieldmapphase] [-o output_dir] [-g]
                                 [--rot rot] [--etd etd] [--ped [ped]]
                                 [--rigid]

Perform Diffusion Model Fitting with pre-processing steps. Mandatory Inputs
are the Diffusion Weighted Images and the bval/bvec pair. as well as a T1
image are extracted for reference space. The Field maps are provided so
susceptibility correction is applied. Values to use for the susceptibility
parameters: ## DRC ## (--ped=-y --etd=2.46 --rot=34.56) and ## 1946 ##
(--ped=-y --etd=2.46 --rot=25.92). Note that these values are indicative.

optional arguments:
  -h, --help            show this help message and exit
  -i dwis [dwis ...], --dwis dwis [dwis ...]
                        Diffusion Weighted Images in a 4D nifti file
  -a bvals [bvals ...], --bvals bvals [bvals ...]
                        bval file to be associated with the DWIs
  -e bvecs [bvecs ...], --bvecs bvecs [bvecs ...]
                        bvec file to be associated with the DWIs
  -t t1, --t1 t1        T1 file to be associated with the DWIs
  -m fieldmapmag, --fieldmapmag fieldmapmag
                        Field Map Magnitude image file to be associated with
                        the DWIs
  -p fieldmapphase, --fieldmapphase fieldmapphase
                        Field Map Phase image file to be associated with the
                        DWIs
  -o output_dir, --output_dir output_dir
                        Output directory containing the registration result
                        Default is a directory called results
  -g, --graph           Print a graph describing the node connections
  --rot rot             Diffusion Read-Out time used for susceptibility
                        correction Default is 34.56
  --etd etd             Echo Time difference used for susceptibility
                        correction Default is 2.46
  --ped [ped]           Phase encoding direction used for susceptibility
                        correction (x, y or z) --ped=val form must be used for
                        -ve indicesDefault is the -y direction (-y)
  --rigid               Only use rigid registration for DWI (no eddy current
                        correction)

A 4D DWI image, corresponding to a single diffusion acquisition is necessarily associated with its corresponding set of bval/bvec. The script perform_dti_processing.py is designed to run for one subject only.

So, in most cases you have only one file per option, 1 4D-DWI, 1 T1, 1 bval, 1 bvec, etc, leading to the following command line:

perform_dti_processing.py -i DWI -a bval -e bvec -t T1 -m mag -p phase -o prep

In some cases, there are repeated (say 2) DWI acquisitions, in which case you have 2 sets of 4D-DWI, bval, bvec, but only one of the other acquisitions (T1, mag, phase). In this situation you can use:

perform_dti_processing.py -i DWI1 DWI2 -a bval1 bval2 -e bvec1 bvec2 -t T1 -m mag -p phase -o output_dir