# Microscopic anisotropy misestimation in spherical-mean single diffusion encoding MRI

## TL;DR

This study evaluates the accuracy of microscopic fractional anisotropy ({A}) estimation using spherical mean single diffusion encoding MRI, revealing significant misestimations due to model limitations and heterogeneity effects in ex vivo tissues.

## Contribution

The paper critically assesses the limitations of spherical mean techniques for {A} estimation, highlighting their inaccuracies and the need for improved models in microstructural MRI.

## Key findings

- {A} estimates from powder-averaged SDE signals deviate significantly from ground truth.
- Model assumptions and heterogeneity factors cause substantial misestimations.
- Current models are inadequate for accurate microstructural parameter estimation in tissues.

## Abstract

Purpose: Microscopic fractional anisotropy ({\mu}FA) can disentangle microstructural information from orientation dispersion. While double diffusion encoding (DDE) MRI methods are widely used to extract accurate {\mu}FA, it has only recently been proposed that powder-averaged single diffusion encoding (SDE) signals, when coupled with the diffusion standard model (SM) and a set of constraints, could be used for {\mu}FA estimation. This study aims to evaluate {\mu}FA as derived from the spherical mean technique (SMT) set of constraints, as well as more generally for powder-averaged SM signals. Methods: SDE experiments were performed at 16.4 T on an ex vivo mouse brain ({\Delta}/{\delta} = 12/1.5 ms). The {\mu}FA maps obtained from powder-averaged SDE signals were then compared to maps obtained from DDE-MRI experiments ({\Delta}/{\tau}/{\delta} = 12/12/1.5 ms), which allow a model-free estimation of {\mu}FA. Theory and simulations that consider different types of heterogeneity are presented for corroborating the experimental findings. Results: {\mu}FA, as well as other estimates derived from powder-averaged SDE signals produced large deviations from the ground truth in both gray and white matter. Simulations revealed that these misestimations are likely a consequence of factors not considered by the underlying microstructural models (such as intercomponent and intracompartmental kurtosis). Conclusion: Powder-averaged SMT and (2-component) SM are unable to accurately report {\mu}FA and other microstructural parameters in ex vivo tissues. Improper model assumptions and constraints can significantly compromise parameter specificity. Further developments and validations are required prior to implementation of these models in clinical or preclinical research.

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Source: https://tomesphere.com/paper/1903.08455