Enhancing subtle cortical lesion detection through multi-dimensional MRI modelling and optimization

Motivation: Many cortical pathologies are invisible via conventional MRI, making it difficult for clinicians to correctly diagnose and treat patients. Goal(s): Our aim was to optimize advanced MRI acquisitions, making them sensitive to subtle cortical pathologies while at the same time reducing acquisition times to clinically-feasible durations. Approach: We calculated the combined relaxation-diffusion signal to encompass surface relaxivity and T2 effects. We used Monte-Carlo simulations to model the signal from healthy and pathological cortical neurons for different PGSE schemes. Results: Our optimized sequences can distinguish pathology associated with focal cortical dysplasia from healthy tissue, and differentiate between focal cortical dysplasia subcategories. Impact: We calculate the combined relaxation-diffusion signal encompassing surface relaxivity and T2 effects, and use it in Monte-Carlo simulations to optimize MRI sequences for subtle cortical lesion detection. Our methodology can be used by researchers to investigate other cortical pathologies.