Project ID NS-MH2024_49


Co Supervisor 1A Institute of Psychiatry, Psychology & Neuroscience, School of Academic Psychiatry, Department of Forensic and Neurodevelopmental ScienceWebsite

Co Supervisor 1B Faculty of Life Sciences & Medicine, School of Biomedical Engineering & Imaging Sciences, Department of Biomedical EngineeringWebsite

Additional Supervisor Dr Jon Cleary

Imaging Brain Microstructure in Childhood Focal Epilepsy using Magnetic Resonance Imaging

Epilepsy is a serious neurological disease, encompassing a spectrum of rare and uncommon disorders. It affects over 100,000 children in the UK, and approximately 30% will not respond to treatment. Seizures can occur at any age, characterised by a range of causes and clinical presentations, the combination of which may be unique. In children with treatment-resistant focal epilepsy, subtle malformations of cortical development and developmental tumours are more common. These can occur in any area of the brain and have variable presentation on conventional MRI. This heterogeneity means that epilepsies cannot easily be grouped for conventional case-control (group) cohort studies. This has constrained our ability to assess individual brain differences and understand how they underpin seizures.

In this project, the candidate will take advantage of state-of-the-art quantitative and diffusion MRI data collected at conventional (3 tesla) and ultra high-field (7T). They will use normative modelling approaches to discover neuroimaging-based phenotypes, brain fingerprints, that reflect neurobiological disruption in individual children. The candidate will next test whether this framework can identify networks associated with seizure propagation. These fingerprints will be used to uncover mechanisms of treatment resistance, independent of clinical phenotype or classification.

Year 1: Develop skills in MRI diffusion microstructure modelling and connectivity analysis with data already collected (n>120). Candidate will also assist with ongoing data collection.
Year 2: Using quantitative and diffusion MRI, develop normative charts of brain tissue development in childhood and contrast individual children with epilepsy against these charts.
Year 3: In children with known malformations that cause their epilepsy, use diffusion MRI to identify brain networks associated with pharmacological treatment resistance.

The supervisor team has a unique combination of engineering, radiology and brain development experts, giving the opportunity for broad interdisciplinary training.

Representative Publications

Wilson, Siân, Maximilian Pietsch, Lucilio Cordero-Grande… & Jonathan O’Muircheartaigh 2021. Development of human white matter pathways in utero over the second and third trimester. PNAS, 118(20).

Dimitrova, Ralica, Maximilian Pietsch, Daan Christiaens… A David Edwards and Jonathan O’Muircheartaigh 2020. ‘Heterogeneity in Brain Microstructural Development Following Preterm Birth.’ Cerebral Cortex 30 (9): 4800–4810.

O’Muircheartaigh, Jonathan, and Saad Jbabdi. 2018. ‘Concurrent White Matter Bundles and Grey Matter Networks Using Independent Component Analysis.’ NeuroImage 170 (April): 296–306.

M Barto?ová, JD Tournier, M Barto?, P ?íha, L Vojtíšek, R Mare?ek, … 2023. ‘White matter alterations in MR-negative temporal and frontal lobe epilepsy using fixel-based analysis.’ Scientific Reports 13 (1), 19

JD Tournier, R Smith, D Raffelt, R Tabbara, T Dhollander, M Pietsch, … 2019. ‘MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation.’ Neuroimage 202, 116137

M Pietsch, D Christiaens, J Hutter, L Cordero-Grande, AN Price, … and JD Tournier 2019. ‘A framework for multi-component analysis of diffusion MRI data over the neonatal period.’ Neuroimage 186, 321-337