Imaging Biomarkers in Neurological Conditions
Alzheimer’s disease is a neurodegenerative disease and the most common form of dementia. In Alzheimer’s disease, there are progressive changes in brain metabolism and structure that lead to symptoms of cognitive decline. Detecting these metabolic and structural changes may one day allow us to determine who is at risk of developing Alzheimer’s disease and who could benefit from early treatment.
In our lab, we are interested in using advanced imaging techniques in both animal models and humans to to identify imaging biomarkers for Alzheimer’s disease and to better understand how the brain is affected. These techniques include magnetic resonance spectroscopy and magnetic resonance imaging (DTI, rs-fMRI) at high and ultra-high field strengths (3T, 7T, and 9.4T).
Spinal Cord Compression
Brain MRI scan of healthy controls and CSM patients. (Yellow showing high activation)
Spinal cord compression is a debilitating disease with a wide range of symptoms. Bio markers of recovery and surgical success are currently unclear. With the use of advanced imaging techniques such as functional MRI, magnetic resonance imaging and diffusion tensor imaging, we are currently investigating the cortical adaptations that occur after spinal compression and decompression and how they relate to recovery. In addition to examining potential bio markers of recovery, our group is examining potential rehabilitation protocols to enhance recovery after spinal cord injury.
Our group is currently using a rat model of reversible spinal cord compression to investigate bio markers of recovery. By inducing spinal cord injury and subsequently removing the source of compression, we are able to detect metabolic changes that occur in the brain after compression and subsequent decompression of the spine.
Capitalizing on Concussions
The concussion research in our lab has been an ongoing collaborative study since 2011 focused around sports-related concussion. We have had the opportunity to collect high quality MRI data including diffusion tensor imaging, resting state functional MRI, and proton spectroscopy from a female varsity rugby team over the course of 5 seasons. This research is in collaboration with many other labs and scientists to allow additional data collection including hematology, clinical scores and head impacts.
Within the Bartha lab we are focused on analyzing and interpreting the proton spectroscopy data, as well as reverse translating our ongoing results into an animal model. With all of this data together we are working on building a better picture of the brain after concussion to identify potential biomarkers that can aid in diagnosis and prognosis to keep athletes as safe as possible.
Epilepsy is one of the most common neurological conditions; roughly 1 in 100 people will be diagnosed with the condition as some point during their lifetime. A majority of people diagnosed with epilepsy can effectively manage their condition with anti-epileptic drugs, however a sizeable minority can not; patients in this group represent the majority of healthcare costs associated with epilepsy. These 'Drug-Resistant' patients are often considered for more invasive procedures, such as neurosurgery, to remove or stabilize epileptic tissue. Magnetic Resonance Imaging a key tool for treatment planning for drug-resistant epilepsy patients; clear findings on MRI have been linked with much better clinical outcomes for patients.
In collaboration with neurologists with the London Health Sciences Center Epilepsy Program, our lab is using the advanced MRI systems at Robarts to answer to main research questions;
1) Can we use alternative MR techniques, such as Magnetic Resonance Spectroscopy (MRS), to better locate epileptic tissue, especially in patients who do not have obvious epileptic abnormalities in typical MRI scans?
2) Using ultra-high field MRI, can we observe changes over time in patients at risk of developing epilepsy to predict both who will develop epilepsy, and how well the patient will respond to drug treatments? Can this information be used to better guide treatment?