Table 1.

Summary of method characteristics

Model	Method	Estimated metrics	Advantages	Disadvantages
Mathematical models	DTI	FA, MD, AxD, RD	Short acquisition time; relatively high reproducibility;	The estimation of voxels containing multidirectional nerve fibers or free water may not be accurate.
			easy data acquisition	Does not reflect specific pathological changes (e.g., demyelination, axonal degeneration)
	DKI	MK, AK, RK	It is not restricted to evaluate the voxels of single fiber populations. Voxels containing multidirectional nerve fibers or gray matter can also be evaluated	Relatively long acquisition time; difficulty in the interpretation of the changes in DKI measures
Biophysical models	NODDI	ICVF, OD, ISOVF	A biological interpretation such as neurite density, neurite orientation dispersion can be provided (needs to be verified)	Long acquisition times to acquire 2 b-shells; relatively low reproducibility: because of the pre-fixed intracellular and extracellular diffusivity, deviations from the fixed value can bias the NODDI measures.
Hybrid models	FWI	FAT, MDT, ADT, RDT, FW	Can eliminate the effect of partial volume of free water contained in voxels	The voxels containing multidirectional nerve fibers might be considered as FW

AD_T: Free water-corrected AxD; AK: axial kurtosis; AxD: axial diffusivity; DKI: diffusional kurtosis imaging; DTI: diffusion tensor imaging; FA: fractional anisotropy; FA_T: free water-corrected FA; FW: free water; FWI: free-water imaging; ICVF: intracellular volume fraction; ISOVF: isotropic volume fraction; MD: mean diffusivity; MD_T: free water-corrected MD; MK: mean kurtosis; OD: orientation dispersion index; RD: radial diffusivity; RD_T: free water-corrected RD; RK: radial kurtosis.