Grants awarded

Making advanced characterisation of tissue microstructure clinically practical: a data-driven approach to efficient microstructural MRI


Chantal Tax

Cardiff University

United Kingdom

MRI provides information on the structure of the microscopic building blocks of living tissue. Combining different MRI techniques is crucial to achieve a comprehensive quantitative picture, but as the dimensionality of the MRI acquisition space increases, acquisition times and analysis-complexity become prohibitive. 

I will design methods to collect the most relevant MRI measurements in the shortest possible time to make quantitative microstructural MRI clinically-viable. I will employ a ‘top-down and bottom-up’ strategy. The top-down approach considers that it is known which tissue parameters are relevant and how they relate to measured signals; the acquisition can then be optimised to maximise precision per unit acquisition time. The bottom-up approach considers that it is unknown how many and which features are relevant; this may differ from assumptions in mathematical models. Starting with rich multicontrast data, I will develop data-driven approaches to characterise the measurement of information-content and use this to select the most relevant measurements.