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

Details

Serval ID
serval:BIB_2202C51D02B1
Type
Article: article from journal or magazin.
Publication sub-type
Review (review): journal as complete as possible of one specific subject, written based on exhaustive analyses from published work.
Collection
Publications
Institution
Title
hMRI - A toolbox for quantitative MRI in neuroscience and clinical research.
Journal
NeuroImage
Author(s)
Tabelow K., Balteau E., Ashburner J., Callaghan M.F., Draganski B., Helms G., Kherif F., Leutritz T., Lutti A., Phillips C., Reimer E., Ruthotto L., Seif M., Weiskopf N., Ziegler G., Mohammadi S.
ISSN
1095-9572 (Electronic)
ISSN-L
1053-8119
Publication state
Published
Issued date
01/07/2019
Peer-reviewed
Oui
Volume
194
Pages
191-210
Language
english
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't
Publication Status: ppublish
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 open-source, easy-to-use tool 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 R <sub>1</sub> and R <sub>2</sub> <sup>⋆</sup> , proton density PD and magnetisation transfer MT saturation) that can be used for quantitative parameter analysis and accurate delineation of subcortical brain structures. The qMRI maps generated by the toolbox are key input parameters for biophysical models designed to estimate tissue microstructure properties such as the MR g-ratio and to derive standard and novel MRI biomarkers. Thus, the current version of the toolbox is a first step towards in vivo histology using MRI (hMRI) and is being extended further in this direction. Embedded in the Statistical Parametric Mapping (SPM) framework, it benefits from the extensive range of established SPM tools for high-accuracy spatial registration and statistical inferences and can be readily combined with existing SPM toolboxes for estimating diffusion MRI parameter maps. From a user's perspective, the hMRI-toolbox is an efficient, robust and simple framework for investigating qMRI data in neuroscience and clinical research.
Keywords
Brain Mapping/methods, Datasets as Topic, Humans, Image Processing, Computer-Assisted/methods, Magnetic Resonance Imaging/methods, Neurosciences/methods, In vivo histology, Microstructure, Multi-parameter mapping, Quantitative MRI, Relaxometry, SPM toolbox
Pubmed
Web of science
Open Access
Yes
Create date
01/03/2019 13:26
Last modification date
04/01/2020 7:17
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