Epilepsy affects approximately 50 million people worldwide. Up to 30 per cent of patients with focal epilepsy have persistent, disabling seizures that are resistant to conventional treatment. Uncontrolled epilepsy is harmful to the brain, has devastating socio-economic consequences, and is associated with increased risk of injury and sudden death. Surgery is the most effective treatment for drug-resistant focal childhood epilepsy.

Magnetic resonance imaging (MRI) has revolutionized the evaluation and management of drug-resistant epilepsy by allowing the reliable detection of the structural lesion associated with certain focal epilepsies, thus leading to increased rates of successful resective surgery. Multiple studies have shown that the most important predictor for favorable post-surgical outcome is the complete resection of the abnormality detected on pre-operative MRI. However, despite technical improvements in MR hardware and sequences, in up to 50 percent of patients with drug-resistant focal epilepsy have a best-practice MRI that is unremarkable and thus unable to show the potential surgical target.

Our research focuses on the use of advanced MRI techniques to improve the understanding and treatment epilepsy due to focal lesions.


Multiscale Structure–Function Gradients in the Neonatal Connectome
Cerebral Cortex
Sara Larivière and Reinder Vos de Wael and Seok-Jun Hong and Casey Paquola and Shahin Tavakol and Alexander J Lowe and Dewi V Schrader and Boris C Bernhardt
DOI: 10.1093/cercor/bhz069

Targeting Age-Related Differences in Brain and Cognition with Multimodal Imaging and Connectome Topography Profiling
Lowe AJ and Paquola C and Vos de Wael R and Girn M and Lariviere S and Tavakol S and Caldairou B and Royer J and Schrader DV and Bernasconi A and Bernasconi N and Spreng RN and Bernhardt BC
DOI: 10.1101/601146

Brain Morphometry: Epilepsy
Dewi S. Schrader and Neda Bernasconi and Andrea Bernasconi
DOI: 10.1007/978-1-4939-7647-8_18

Multimodal MRI profiling of focal cortical dysplasia type II
Seok-Jun Hong and Boris C. Bernhardt and Benoit Caldairou and Jeffery A. Hall and Marie C. Guiot and Dewi Schrader and Neda Bernasconi and Andrea Bernasconi
DOI: 10.1212/wnl.0000000000003632

Whole-brain MRI phenotyping in dysplasia-related frontal lobe epilepsy
Seok-Jun Hong and Boris C. Bernhardt and Dewi S. Schrader and Neda Bernasconi and Andrea Bernasconi
DOI: 10.1212/wnl.0000000000002374

Urgent, resective surgery for medically refractory, convulsive status epilepticus
European Journal of Paediatric Neurology
Dewi V. Schrader and Paul Steinbok and Mary Connolly
DOI: 10.1016/j.ejpn.2008.01.011


Connectome-informed simulations of pediatric epilepsy surgery

Surgery is the most effective treatment for drug-resistant childhood epilepsy. Yet, ~30 per cent of patients show post-surgical seizure recurrence and many suffer from cognitive side effects. So far, an outcome cannot be reliably predicted for a given patient prior to intervention.


1) Integrate preoperative MRI markers and data on the actual surgery for more effective prediction;

2) analyze brain change from pre- to postoperative time points, mapping alterations of non-resected areas; 3) simulate network reorganization using connectome models.
Hypothesis. Combining preoperative markers of patient anatomy with with models that simulate consequences of surgery will yield high accuracy in predicting clinical and cognitive outcomes.


In children that will undergo epilepsy surgery, we will obtain MRI and neurocognitive data shortly before surgery, 6 months after surgery (and 12 months after surgery. We will overlay resection extent (from postoperative MRI) with preoperative MRI features (atrophy, gliosis, myelin), testing whether anomalies outside the resection margin predict seizure relapse. In addition, fMRI pattern analysis will localize regions critical for language/memory function, testing whether their resection relates to postoperative cognitive decline. Mixed-effects models will map MRI feature change, assessing surgical consequences. Connectome-based models will be devised to predict downstream degeneration and functional reorganization after surgery in non-resected areas. Supervised learners will predict outcomes based on preoperative data and simulations.

Expected Results

Empirical studies on surgical consequences will help build effective in silico models that optimize outcome prediction, improving clinical decision-making in >10,000 children with drug-resistant seizures in Canada.
Improved detection of Focal Cortical Dysplasia.
Focal cortical dysplasia (FCD) is the most common cause of surgically-treatable, extra-temporal epilepsy. Unfortunately, the findings of FCD on MRI are often subtle and can be easily overlooked. We are using advanced MRI techniques to improve the detection of focal cortical dysplasia, allowing us to offer the life changing benefits of epilepsy surgery to more patients.


SickKids Foundation - New Investigator Grant 2016 "Connectome informed simulations of pediatric epilepsy surgery"

Research Group Members

Katerina Pezarro