15:00 - Multiparametric quantitative imaging of the brain: interpreting tissue (micro)structure
Ana-Maria Oros-Peusquens, Principal Investigator - Forschungszentrum Jülich, Germany
Quantitative MRI enables the comparison of brain imaging data in terms of numerical parameters rather than scanner- and protocol-dependent image contrast. More importantly, many qMRI parameters have interpretable physical or physiological origins, including water content, relaxation rates, magnetic susceptibility, electrical conductivity, and oxygen extraction fraction. In large in vivo datasets such as 1000BRAINS, these parameters can be analysed jointly to characterise brain tissue beyond single-contrast imaging.
This presentation will discuss how multiparametric qMRI can be used to describe anatomical regions and tissue classes by their quantitative profiles, and how clustering approaches can segment tissue based on combinations of measured properties. A central focus will be the interpretation of relationships between parameters. Examples include correlations between T2* and magnetic susceptibility, which can reflect shared sensitivity to iron, myelin, and venous oxygenation, and relationships between water content and R1, which inform the interpretation of hydration and macromolecular contributions to relaxation.
Multiparametric qMRI also allows tissue properties to be followed across development, ageing, or disease as trajectories in a multidimensional parameter space. Finally, quantitative modelling can move beyond one value per voxel, using multicomponent T2, T2*, or diffusion analyses to estimate intra-voxel tissue heterogeneity.
15:30 - AI-powered multiplexed magnetic resonance imaging for brain mapping
Yudu Li, Assistant Professor - University of Illinois - USA
Understanding the brain —how it works and what goes wrong when it is injured or diseased — is considered one of the last frontiers in science, driving scientists and engineers to meet this objective.
In this exciting scientific endeavor, magnetic resonance imaging (MRI) techniques have played an indispensable role, providing a range of noninvasive tools to acquire anatomical, physiological, and metabolic information about the brain. And yet, new imaging capabilities continue to emerge every few years. This talk will discuss a new MRI technique known as MRx (multiplexed magnetic resonance imaging) for brain mapping. MRx synergistically integrates ultrafast data acquisition with physics-based machine learning. Experimental results show an unprecedented capability to simultaneously obtain a large set of quantitative structural, physiological and molecular biomarkers of the whole brain in standard clinical settings. In this talk, I’ll give an overview of MRx and also show some exciting brain imaging experimental results we have obtained to demonstrate its unique capability and potential.
16:00 - Advancing microstructure imaging via diffusion MRI: harnessing modern machine learning and advanced computational models
Marco Palombo, Associate Professor - University of Cardiff, United Kingdom
Diffusion MRI has emerged as one of the most powerful non-invasive tools for probing tissue microstructure, offering unprecedented opportunities to characterize the cellular architecture of the brain and other organs in health and disease. In this talk, I will present recent advances in microstructure imaging that combine cutting-edge diffusion MRI, computational biophysical modelling, and modern machine learning to push beyond the limits of conventional imaging. Drawing on pioneering work on generative models of brain tissue microstructure, the presentation will illustrate how advanced computational frameworks can reveal cellular features such as soma size, neurite density, membrane permeability, and water exchange processes in vivo. The talk will further highlight how Monte Carlo simulations, deep learning, and uncertainty-aware inference methods are enabling more robust and biologically meaningful biomarkers from diffusion MRI data.
16:30 - Q&A/ panel discussion