Free‐water DTI estimates from single b‐value data might seem plausible but must be interpreted with care

Abstract

Free-water elimination DTI (FWE-DTI) has been used widely to distinguish increases of free-water partial-volume effects from tissue's diffusion in healthy aging and degenerative diseases. Because the FWE-DTI fitting is only wellposed for multishell 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-shell and multishell data. Methods: Different FWE-DTI fitting procedures were tested on an open-source in vivo diffusion data set and single-shell and multishell synthetic signals, including the RGD and standard nonlinear least-squares methods. Single-voxel simulations were carried out to compare initialization approaches. A multivoxel phantom simulation was performed to evaluate the effect of spatial regularization when comparing between methods. To test the algorithms' specificity, phantoms with two different types of lesions were simulated: with altered mean diffusivity or with modified free water. Results: 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 free water from tissue mean-diffusivity alterations, contrarily to the nonlinear least-squares algorithm. Conclusion: The RGD FWE-DTI method has limited specificity; thus, its results from single-shell data should be carefully interpreted. When possible, multishell acquisitions and the nonlinear least-squares approach should be preferred instead.

Characterization of Age-Related Differences in the Human Choroid Plexus Volume, Microstructural Integrity, and Blood Perfusion Using Multiparameter Magnetic Resonance Imaging

“…Indeed, given the large fraction of free water in the CP, this could have introduced bias in derived parameter values. Although the free-water elimination DTI (FWE-DTI) approach has been used widely to distinguish free-water partial-volume effects from tissue's diffusion in healthy aging and degenerative diseases (Pasternak et al, 2009), it has recently been shown that this method is unstable when applied to single-shell DTI data, requiring careful implementation (Golub et al, 2021). Further, we note that our derived DTI parameters values could change depending on the choice of the b-values.…”

Single‐shell NODDI using dictionary‐learner‐estimated isotropic volume fraction

“…The generated coefficient vector contributes to a fully connected feed-forward network to estimate the f ISO . The network incorporates important determinants of f ISO priors, 26 ie MD and T2w signal S 0 , which facilitates single-shell estimation of f ISO with NODDI-based data-driven learning.…”

Longitudinal Changes in Brain Diffusion MRI Indices during and after Proton Beam Therapy in a Child with Pilocytic Astrocytoma: A Case Report

“…We found that: (i) a cumulative PBT dose causes different sequential hyperacute processes during treatment, (ii) quantifying the fluid tumor content can be helpful as an additional strategy for monitoring and interpreting tissue reactions to irradiation. Larger studies with multi-shell dMRI acquisitions [ 14 ] may further investigate these metrics as predictors of a treatment’s outcome.…”