Magnetic Resonance Imaging (MRI) is a commonly used medical scanning technique; more than 30 million scans are performed per year in EURAMET countries. Standard MRI scans are typically qualitative, requiring visual inspection to identify diseased tissue. Variation in subjective interpretations of images means diagnostic accuracy could be improved using quantitative analysis. MRI imaging techniques Electric Properties Tomography (EPT) and Magnetic Resonance Fingerprinting (MRF), for instances, could herald a ‘quantitative revolution’ in MRI. However, these technologies require validation before use in clinical diagnosis.

This project has evaluated emerging and complementary EPT and MR techniques, to develop quantitative MRI analysis for more accurate disease diagnostics. Algorithms for analysing EPT and MRF output signals have been developed and improved, with performance validated using fully characterised, SI-traceable, ‘phantom’ reference artefacts and monitored components. Diagnosis of high impact clinical conditions with these new techniques (such as cerebrovascular diseases) will be assessed, and results disseminated to end-users such as MRI manufacturers and the medical community.