AUTHOR=Pinto Maíra Siqueira , Paolella Roberto , Billiet Thibo , Van Dyck Pieter , Guns Pieter-Jan , Jeurissen Ben , Ribbens Annemie , den Dekker Arnold J. , Sijbers Jan 

TITLE=Harmonization of Brain Diffusion MRI: Concepts and Methods

JOURNAL=Frontiers in Neuroscience

VOLUME=Volume 14 - 2020

YEAR=2020

URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2020.00396

DOI=10.3389/fnins.2020.00396

ISSN=1662-453X

ABSTRACT=MRI diffusion data suffers from significant inter- and intra-site variability, which hinders multi-site and/or longitudinal diffusion studies. This variability may arise from a range of factors, such as hardware, reconstruction algorithms and acquisition settings. To allow a reliable comparison and joint analysis of diffusion data across sites and over time, there is a clear need for robust data harmonisation methods. This review article provides a comprehensive overview of diffusion data harmonisation concepts and methods, and their limitations. Overall, the methods for the harmonisation of multi-site diffusion images can be categorized in two main groups: diffusion parametric map harmonisation (DPMH) and diffusion weighted image harmonisation (DWIH). Whereas DPMH harmonises the diffusion parametric maps (e.g., FA, MD, MK), DWIH harmonises the diffusion-weighted images. Defining a gold standard harmonisation technique for dMRI data is still an ongoing challenge. Nevertheless, in this paper we provide two classification tools, namely a feature table and a flowchart, which aim to guide the readers in selecting an appropriate harmonisation method for their study.