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Diffusion models and metrics

There are currently four diffusion models that are supported by the ElikoPy pipeline. These models are listed below with their accessible parameters.

  • Diffusion Tensor Imaging (DTI)
  • Neurite Orientation Dispersion and Density Imaging (NODDI)
    • lambda_iso_diff - isotropic diffusivity for the CSF model
    • lambda_par_diff - axial diffusivity of the intra-neurite space
  • DIstribution of 3D Anisotropic MicrOstructural eNvironment in Diffusion compartment imaging (DIAMOND)
  • Microstructure Fingerprinting (MF)
    • dictionary_path - Path to the dictionary of fingerprints (mandatory)
    • CSD_bvalue - If the DIAMOND outputs are not available, the fascicles directions are estimated using a CSD with the images at the b-values specified in this argument.
study.dti()
study.noddi(lambda_iso_diff=3.e-9, lambda_par_diff=1.7e-9)
study.diamond()
study.fingerprinting(dictionary_path="my_dictionary", CSD_bvalue=None)

The metrics outputted by the functions are listed below.

Diffusion Tensor Imaging (DTI)

  • Fractional anisotropy (FA).
  • Axial diffusivity (AD).
  • Radial diffusivity (RD).
  • Mean diffusivity (MD).
  • Colored FA i.e. RGB map, a color is attributed to each voxel depending on the direction of the first eigenvalue and the intensity of the color depends on the FA value (fargb).
  • Residual (residual).
  • Eigenvectors of the diffusion tensor (evecs).
  • Eigenvalues of the diffusion tensor (evals).
  • Diffusion Tensor (dtensor).

Neurite Orientation Dispersion and Density Imaging (NODDI)

  • Thresholded intra-cellular volume fraction $nu{ic}$ (icvf).
  • Fiber orientation dispersion index (odi).
  • Mean of the watson distribution of the Intra-cellular model (mu).
  • Fiber bundles volume fraction (fbundle).
  • Extra-cellular volume fraction (fextra).
  • Intra-cellular volume fraction (fintra).
  • Free water volume fraction (fiso).
  • Mean squared error (mse).
  • R squared (R2).

DIstribution of 3D Anisotropic MicrOstructural eNvironment in Diffusion compartment imaging (DIAMOND)

  • Tensor orientations of the fiber population 0 (t0).
  • Tensor orientations of the fiber population 1 (t1).
  • Residuals (residuals).
  • Intermediary step of the t0 output (mtm_t0).
  • Intermediary step of the t1 output (mtm_t1).
  • Intermediary step of the fractions output (mtm_fractions).
  • Volume with a null b-value (b0).
  • DTI estimate (dti).
  • Automose model selection map. Gray and white matter correspond to positive values and CSF to negative values (aicu).
  • Fraction of voxel attributed to each compartment (fractions).
  • Shape parameters of the mv-$Gamma$ distribution, Homogeneity index (kappa).
  • Log of kappa (logkappa).
  • The heterogeneity indexes defined as $H E I=frac{2}{pi} arctan left(frac{1}{kappa}right)$ (hei).
  • Number of fascicles by voxel (mosemap).

Microstructure Fingerprinting (MF)

  • Extra-axonal diffusivity of fascicle 0 (DIFF_ex_f0).
  • Extra-axonal diffusivity of fascicle 1 (DIFF_ex_f1).
  • Total extra-axonal diffusivity (DIFF_ex_tot).
  • Volume fraction of cerebrospinal fluid (frac_csf).
  • Volume fractions of fascicle 0 (frac_f0).
  • Volume fractions of fascicle 1 (frac_f1).
  • Fiber volume fractions of the fascicle 0 (fvf_f0).
  • Fiber volume fractions of the fascicle 1 (fvf_f1).
  • Total fiber volume fraction of all fascicles (fvf_tot).
  • Mask (M0).
  • Mean squared error (MSE).
  • Peak map fascicle 0 (peak_f0).
  • Peak map fascicle 1 (peak_f1).
  • R squared (coefficient of determination, square of Pearson) (R2).