Work Package Leader: Nadia Smith (NPL)

The aims of this WP are: to develop simulated models of the phantoms (digital phantoms) manufactured in WP1; to develop data analysis and uncertainty quantification tools for standardised qMRI measurement chains; to perform a comparison of the measurand maps derived from the analysis of qMRI scans to the fundamental characterisation measurements performed in WP1; and to curate the data generated in a standardised and FAIR-compliant manner.

This WP will focus on:

• Developing and using digital phantoms to improve the characterisation of the phantoms produced in WP1 and the image acquisition process developed in WP3. By modelling the phantom itself and simulating the complete image acquisition process, the impact of each independent step in the MRI measurement chain, such as varying contrast agent properties or pulse sequence parameters on resultant image artefacts, noise levels, and analysis model chosen can be quantified. Generating a greater understanding of how parameters interact will lead to an optimised and robust experimental acquisition design.

• Using the results from Task 2.1 to determine a sensitivity analysis, that will highlight the most important factors that contribute to the uncertainty budget of the image acquisition chain. This is a fundamentally new approach to MR imaging. Uncertainty quantification tools will be developed for propagating measurement uncertainties through the entire image formation chain.

• Comparing the measurand maps of relevant MR parameters (such as relaxation times, fat fraction, etc.) derived from the analysis of qMRI scans to the characterisation measurements performed in WP1 using measuring instruments independent of the MR scanner itself. This comparison will serve as a quality control and calibration tool for the scanners involved in WP3.

• Managing and curating in a standardised way that is FAIR-compliant the significant amount of data produced throughout the project’s duration from the development and characterisation of test materials, the findings of simulation work, and measurements and protocols from the multi-site study. This Task will construct an appropriate data framework and make it available to all project partners.