Neurosurgery to treat drug-resistant epilepsy or brain cancer is very challenging, as the surgeon needs to trade-off completely removing the disease, with sparing healthy functional tissue. Planning how much of the brain to treat requires knowledge of the neurological pathways and abnormal regions, however this can be difficult as the boundaries are not always well defined. Incorrectly defining the region to treat can carry a great deal of risk; if too small, the surgery will not be effective, and if too large, function may be altered negatively.

We are working on computational tools to guide neurosurgeons towards more optimal resections, biopsies, and electrode implantations by extracting and exploiting the information present in medical images.

Histology provides a microscopic view into tissue and, when possible, is an invaluable way to validate what we are observing with medical imaging. We have the opportunity to access tissue obtained from surgical procedures, however, correcting for the tissue deformations that occur from resection and histological processing remains a major challenge.

We are developing semi-automated pipelines for performing this image registration in applications that include temporal lobe resections, and carotid plaque endartarectomies, and are employing these tools to investigate the correlation between imaging and histological markers.

Epilepsy is a debilitating neurological disorder, and many patients do not have control of seizures with anti-epileptic medications. In these cases, it becomes imperative to map out where the seizures are originating from in order to perform focal surgical treatment.

We are using advanced imaging techniques, such as quantitative multi-parametric MRI and ultra-high-field MRI in order to detect lesions which may be otherwise hidden, and to better understand how the brain and it’s networks are affected by epilepsy.

Alterations in brain structure can be seen in many neurological disorders, both at the macro and the micro scale. We have been investigating sensitive techniques for quantifying brain structure using anatomical MRI morphometry techniques that are sensitive to the size and shape of the cortical and subcortical structures, and diffusion MRI to investigate microstructure.