Workshop Talk Abstracts

Session 1 – Introduction to the hMRI toolbox: computation and pre-processing of MRI relaxometry data

MRI relaxometry – motivations and introduction

This talk will begin with an introduction to the MRI relaxometry data generated by the hMRI toolbox. We will then highlight the potential of these data as biomarkers of the histological properties of brain tissue and review studies investigating microscopic brain changes using these data. We will also discuss the complementarity of relaxometry data and conventional measures of brain morphology.

Computing relaxometry maps with the hMRI toolbox

This talk will describe how MRI relaxometry data are computed from raw MR images using the hMRI toolbox. We will present the general principles underlying these computations and provide a practical guide to the toolbox implementation.

Specific consideration for the spatial processing of quantitative MRI maps

This talk will present how to spatially process the quantitative maps, after their creation and before feeding them into some statistical analysis. Given their quantitative nature, these maps require careful consideration for the usual segmentation, spatial normalization, and smoothing steps. Some of these operations rely on SPM’s functionalities but others, e.g. tissue-weighted smoothing, are specific to the hMRI toolbox.

Session 2 – Making sense of quantitative maps: statistical inference and neuroscientific applications

Specific consideration for the statistical analysis of quantitative MRI maps

to-be-added

Neuroscientific applications of qMRI in ageing

This talk will provide a concise overview of applying qMRI to track microstructural brain changes in aging. We will highlight how multi-contrast relaxometry maps capture subtle tissue alterations, such as changes in myelin and iron content, that conventional morphology metrics miss.

Session 3 – Advanced functionalities

Advanced tools for the computation of MRI relaxometry maps

This talk will present the advanced capabilities provided by the toolbox, including the fitting methods available for computing MRI relaxometry maps and the quantitative metrics used to assess data quality. We will also introduce the parameters that can be adjusted by users and discuss their effects on the resulting relaxometry maps.

Addressing motion degradation in analyses of MRI relaxometry data

Degradation of image quality due to head motion is a notorious challenge in MRI data analysis. Here, we will introduce the quantitative tools available in the hMRI toolbox that enable the mitigation of motion artefacts during the computation and analysis of MRI relaxometry data.

Advanced computational tools: denoising module

Noise commonly degrades image quality in general image processing and, specifically, in quantitative MRI. In this talk, we present the advanced, built‑in denoising features of the hMRI toolbox.