Jordan A. Chad^{1,2}, Ofer Pasternak^{3}, and J. Jean Chen^{1,2}

Free water eliminated diffusion tensor imaging (fwDTI) and neurite orientation dispersion and density imaging (NODDI) are two increasingly established techniques that measure free water (FW) in diffusion MRI. Yet, despite the utility of each approach, their corresponding FW estimates have yet to be compared. In this work, we find that FW measurements near cerebrospinal fluid are highly similar between the two approaches, but within tissue, NODDI tends to compute slightly higher FW values in the white matter and lower FW values in gray matter than fwDTI. Potential sources of this discrepancy are discussed.

Extracellular free water content, as measured by diffusion MRI, has recently gained attention as a sensitive biomarker of brain aging and pathology, and its elimination from the diffusion MRI signal can increase specificity of other diffusion-derived biomarkers to processes within the tissue. One method of free water mapping is to extend the conventional diffusion tensor model to incorporate a free water compartment via free water DTI (fwDTI)^{1}. This model can be used to estimate free water from standard single-shell acquisitions^{1}.

Alternatively, rather than modeling the tissue compartment as a single tensor, multiple compartments attributed to different tissue types can be modeled using multi-shell data. A popular tissue-modeling approach is NODDI, which includes a free-water compartment^{2}.

While fwDTI is commonly used on single-shell data and NODDI is commonly used on multi-shell data, cross-validation between free water measurements in each of these approaches has yet to be shown. This is the motivation for the current study.

In all three subjects, FW values computed by fwDTI and NODDI are correlated throughout the brain, with correlation coefficient r ranging between 0.8 and 0.9 within slices. Correlations in a central slice is shown in Figure 1. The variance in free water values between the two approaches is smaller at higher FW values, i.e., the approaches are more strongly correlated in regions of partial-voluming with cerebrospinal fluid. Within tissue, NODDI tends to compute lower FW values in the gray matter and higher FW values in the white matter relative to fwDTI (Figure 2), a trend consistent across all three subjects (Figure 3).

Figure 4 shows that the frequency of FW values in the brain peaks between 0.1 and 0.2 when computed from both methods. NODDI detects a significant amount of voxels with zero FW content, particularly in the gray matter, whereas the lowest FW values computed by fwDTI tend to be nonzero.

1. Pasternak O, Sochen N, Gur Y, et al. Free water elimination and mapping from diffusion MRI. Magn Reson Med. 2009;62(3):717-730.

2. Zhang H, Schneider T, Wheeler-Kingshott CA, Alexander DC. NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain. Neuroimage 2012;61:1000-1016.

3. Lampinen B, Szczepankiewicz F, Mårtensson J, van Westen D, Sundgren PC, Nilsson M. Neurite density imaging versus imaging of microscopic anisotropy in diffusion MRI: a model comparison using spherical tensor encoding. Neuroimage 2017;147:517-531.

4. Pasternak O, Shenton ME, Westin CF. Estimation of extracellular volume from regularized multi-shell diffusion MRI. Med Image Comput Comput Assist Interv 2012;15:305-312.

5. Chad JA, Chen JJ, Pasternak O. Regularization stabilizes the fit of the two-compartment free water diffusion MRI model. Submitted to ISMRM 2019