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ComputeDKI brick

Reconstruction of the diffusion signal with the kurtosis tensor model

The diffusion kurtosis imaging (DKI) model is an expansion of the diffusion tensor imaging (DTI) model that allows quantification of the degree to which water diffusion in biological tissues is non-Gaussian.

This brick used functions proposed by Dipy to reconstruct the diffusion signal with the kurtosis tensor model.

Since the diffusion kurtosis model estimates the diffusion tensor, all standard diffusion tensor statistics can be computed: the fractional anisotropy (FA), the mean diffusivity (MD), the axial diffusivity (AD) and the radial diffusivity (RD).

In addition to the standard diffusion statistics, this brick can be used to estimate the non-Gaussian measures of mean kurtosis (MK), the axial kurtosis (AK) and the radial kurtosis (RK).

The mean of the kurtosis tensor (mKT) and the kurtosis fractional anisotropy (kFA) are also computed. These measures only depend on the kurtosis tensor.


Mandatory inputs parameters:

  • in_dwi (a string representing an existing file)

    Diffusion file (valid extensions: [.nii, .nii.gz]). It should be multi-shell data, i.e. data acquired from more than one non-zero b-value.

    ex. '/home/username/data/raw_data/dwi.nii'
    

    Optional inputs parameters:

  • dwi_bvec (a string representing an existing file)

    Bvec file (valid extensions: [.bvec]). If no file is supplied, the file with the same name as “in_dwi” but with “.bvec” extension will automatically be used.

    ex. '/home/username/data/raw_data/dwi.bvec'
    
  • dwi_bval (a string representing an existing file)

    Bval file (valid extensions: [.bval]). If no file is supplied, the file with the same name as “in_dwi” but with “.bval” extension will automatically be used.

    ex. '/home/username/data/raw_data/dwi.bval'
    
  • in_mask (a string representing an existing file)

    Brain mask file (valid extensions: [.nii, .nii.gz]). If you want to fit the model within a mask.

    ex. '/home/username/data/derived_data/dwi_brainmask.nii'
    

Outputs parameters:

  • out_FA (a strings representing a file)

    The fractional anisotropy (FA) image

    ex. '/home/username/data/derived_data/dwi_dki_FA.nii'
    
  • out_MD (a strings representing a file)

    The mean diffusivity (MD) image

    ex. '/home/username/data/derived_data/dwi_dki_MD.nii'
    
  • out_RD (a strings representing a file)

    The radial diffusivity (RD) image

    ex. '/home/username/data/derived_data/dwi_dki_RD.nii'
    
  • out_AD (a strings representing a file)

    The axial diffusivity (AD) image

    ex. '/home/username/data/derived_data/dwi_dki_AD.nii'
    
  • out_MK (a strings representing a file)

    The mean kurtosis (MK) image

    ex. '/home/username/data/derived_data/dwi_dki_MK.nii'
    
  • out_RK (a strings representing a file)

    The radial kurtosis (RK) image

    ex. '/home/username/data/derived_data/dwi_dki_RK.nii'
    
  • out_AK (a strings representing a file)

    The axial kurtosis (AK) image

    ex. '/home/username/data/derived_data/dwi_dki_AK.nii'
    
  • out_mKT (a strings representing a file)

    The mean of the kurtosis tensor (mKT) image

    ex. '/home/username/data/derived_data/dwi_dki_mKT.nii'
    
  • out_kFA (a strings representing a file)

    The kurtosis fractional anisotropy (kFA) image

    ex. '/home/username/data/derived_data/dwi_dki_kFA.nii'
    

Useful links:

Dipy Reconstruction of the diffusion signal with the kurtosis tensor model

Jensen JH 2005