Novel MRI Techniques to Image Hippocampal Internal Architecture

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DESCRIPTION (provided by applicant): Dr. Lawrence Ver Hoef is an epileptologist and Assistant Professor of Neurology at the University of Alabama at Birmingham. With an undergraduate background in engineering and post-doctoral graduate studies in biomedical engineering, Dr. Ver Hoef seeks to establish himself as a technical translational neuroimaging researcher that bridges the gap between the unapplied cutting-edge abilities of the MRI engineering community and the disease-specific imaging needs of the clinical neuroscience community to facilitate cooperative endeavors. These two highly specialized arenas would benefit greatly from a researcher who is fluent in both languages who could connect engineering abilities in need of application with clinical investigations in need of better tools. To accomplish this goal Dr Ver Hoef will develop his research abilities through a mentored project and educational curriculum that will complete his engineering credentials, equip him with skills in biostatistics and study design, and provide hands-on experience managing a project with engineering and clinical components. The project will optimize a novel MRI technique ("3D Cones") to generate high-resolution thin-sliced images of the human hippocampus that will clearly demonstrate the normal layered hippocampal internal architecture (HIA). A loss of differentiation of HIA on coronal MRI has been suggested to be an imaging halmark of hippocampal sclerosis (HS) in epilepsy patients. HS is a common cause of medically refractory epilepsy, but is also highly remediable with resective surgery. Current MRI techniques are inconsistent and poorly able to demonstrate HIA. Therefore, an imaging technique that consistently demonstrates HIA, or abnormalities thereof, may identify certain patients with disabling, intractible epilepsy as surgical candidates with an excellent prognosis for seizure freedom. The project will utilize the 3D cones imaging technique in conjunction with multiple-image averaging (to improve signal to noise ratio) and inter-scan co-registration (to minimize movement effects). Several specific parameters will be optimized to generate the best possible differentiation of HIA. The new technique will then be compared to standard MRI techniques to demonstrate superiority. Dr. Ver Hoef will have close mentorship under experts in both biomedical engineering and clinical neuroimaging.