hMRI - A toolbox for using quantitative MRI in neuroscience and clinical research

Abstract

Neuroscience and clinical researchers are increasingly interested in quantitative magnetic resonance imaging (qMRI) due to its sensitivity to micro-structural properties of brain tissue such as axon, myelin, iron and water concentration.We introduce the hMRI-toolbox, an easy-to-use tool openly available on GitHub, for qMRI data handling and processing, presented together with a tutorial and example dataset. This toolbox allows the estimation of high-quality multi-parameter qMRI maps (longitudinal and effective transverse relaxation rates R1 and R? 2, proton density PD and magnetisation transfer MT saturation) that can be used for accurate delineation of subcortical brain structures and calculation of standard and novel MRI biomarkers of tissue microstructure. Embedded in the Statistical Parametric Mapping (SPM) framework, it can be readily combined with existing SPM toolboxes for estimating diffusion MRI parameter maps, and it benefits from the extensive range of established SPM tools for high-accuracy spatial registration and statistical inferences. The hMRI-toolbox is an efficient, robust and simple framework for investigating qMRI data in neuroscience and clinical research.