  Purpose: Free water elimination diffusion tensor imaging (FWE-DTI) has been
widely used to distinguish increases of free water (FW) partial volume effects
from tissue's diffusion in healthy ageing and degenerative diseases. Since the
FWE-DTI fitting is only well posed for multi-shell acquisitions, a regularized
gradient descent (RGD) method was proposed to enable application to
single-shell data, more common in the clinic. However, the validity of the RGD
method has been poorly assessed. This study aims to quantify the specificity of
FWE-DTI procedures on single- and multi-shell data. Methods: Different FWE-DTI
fitting procedures were tested on an open-source in vivo diffusion dataset and
single- and multi-shell synthetic signals, including the RGD and standard
non-linear least squares (NLS) methods. Single-voxel simulations were carried
out to compare initialization approaches. A multi-voxel phantom simulation was
performed to evaluate the impact of spatial regularization when comparing
between methods. To test the algorithms' specificity, phantoms with two
different types of lesions were simulated: with increased mean diffusivity (MD)
or with increased FW. Result: Plausible parameter maps were obtained with RGD
from single-shell in vivo data. The plausibility of these maps was shown to be
determined by the initialization. Tests with simulated lesions inserted into
the in vivo data revealed that the RGD approach cannot distinguish FW from
tissue MD alterations, contrarily to the NLS algorithm. Conclusion: RGD FWE-DTI
has limited specificity and, thus, its results from single-shell data should be
carefully interpreted. When possible, multi-shell acquisitions and the NLS
approach should be preferred instead.
