Ali R. Khan, Scientist
My passion for science and knowledge began early on; my parents claim I was digging through encyclopedia sets just as I was learning my ABCs, but it was much later when I realized I wanted to become a scientist. Growing up, I was always near a computer, learning to script, code and hack from an early age. It was the enjoyment I got out of working and building these systems that finally led me to engineering school. Then, during a co-op term as an engineering student, I became exposed to medical imaging and began to work with magnetic resonance images of the brain. Once I realized I could apply my knowledge of computers towards medicine, potentially impacting patient lives, I was hooked. I went on to complete my PhD in this area, learning as much as I could about the brain along the way. I joined Robarts Research Institute to push my research in an even more translational direction, and realized my goal of becoming a scientist. At Robarts, I am working with a renowned team of clinicians and scientists, tackling the big problems faced in health, and training the next generation of researchers.
Medical images play a critical role in the diagnosis and monitoring of disease, and the planning and guidance of surgical therapies. My lab develops and applies sophisticated image processing and analysis techniques to extract, quantify, and distill information from medical images, ultimately leading to more accurate diagnoses and more precise surgical interventions.
Can ultra-high field 7T MRI help us better understand the structure and function of the hippocampus?
The hippocampus is a brain structure that has been implicated in many different neurological conditions including epilepsy and Alzheimer’s disease, where it plays a role in both diagnosis and treatment. Emerging evidence is revealing that the different sub-structures, or subfields, of the hippocampus are uniquely affected by disease, and that complete understanding of the disorder requires careful consideration of the complex hippocampal anatomy and circuitry. My lab is investigating novel imaging and image analysis techniques using 7T MRI to characterize and quantify structure and function of the hippocampus to improve clinical care of epilepsy patients.
Can we use advanced quantitative and diffusion MRI technologies to improve surgical treatment of neurological disorders?
Brain surgery 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. My lab is developing novel approaches to guide neurosurgeons towards more optimal therapies and is actively collaborating with Synaptive Medical to bring these technologies into the operating room.
Ph.D. Engineering Science, Simon Fraser University
B.ASc. Engineering Science, Simon Fraser University
Postdoctoral Fellow, Robarts Research Institute, Western University
Canadian Institutes of Health Research Fellowship, 2012-2014
Epilepsy Canada Postdoctoral Fellowship, 2011-2012
Goubran M, Bernhardt BC, Cantor-Rivera D, Lau JC, Blinston C, Hammond RH, de Ribaupierre S, Burneo JG, Mirsattari S, Steven DA, Parrent AG, Bernasconi A, Bernasconi N, Peters TM, Khan AR. In vivo MRI signatures of hippocampal subfield pathology in intractable epilepsy. Hum Brain Mapp. 2016 Mar;37(3):1103-19.
Goubran M, Currie C, de Ribaupierre S, Hammond RR, Burneo JG, Parrent AG, Peters TM, Khan AR. Registration of in-vivo to ex-vivo MRI of surgically resected specimens: a pipeline for histology to in-vivo registration. J Neurosci Methods. 2015 Feb 15;241:53-65.
Goubran M, Hammond RR, de Ribaupierre S, Burneo JG, Mirsattari S, Steven D, Parrent AG, Peters TM, Khan AR. Magnetic resonance imaging and histology correlation in the neocortex in temporal lobe epilepsy. Ann Neurol. 2015 Feb;77(2):237-50.
Khan AR, Wang L, Beg MF. Unified Voxel and Tensor-based Morphometry (UVTBM) using Registration Confidence. Neurobiol Aging. 2015 Jan;36 Suppl 1:S60-8.
Khan AR, Goubran M, de Ribaupierre S, Hammond RR, Burneo JG, Parrent AG, Peters TM. Quantitative relaxometry and diffusion MRI for lateralization in MTS and non-MTS temporal lobe epilepsy. Epilepsy Res. 2014 Mar;108(3):506-16.
Goubran M, Rudko D, Santyr B, Gati J, Szekeres T, Peters TM, Khan AR. In-vivo normative atlas of the hippocampal subfields using multi-echo susceptibility imaging at 7 Tesla. Hum Brain Mapp. 2014 Aug;35(8):3588-601.
Goubran M, Crukley C, de Ribaupierre S, Peters TM, Khan AR. Image registration of ex-vivo MRI to sparsely sectioned histology of hippocampal and neocortical temporal lobe specimens. Neuroimage. 2013 Dec;83:770-81.
Khan AR, Wang L, Beg MF. Multistructure large deformation diffeomorphic brain registration. IEEE Trans Biomed Eng. 2013 Feb;60(2):544-53.
Khan AR, Cherbuin N, Wen W, Anstey KJ, Sachdev P, Beg MF. Optimal weights for local multi-atlas fusion using supervised learning and dynamic information (SuperDyn): validation on hippocampus segmentation. Neuroimage. 2011 May 1;56(1):126-39.
Khan AR, Wang L, Beg MF. Freesurfer-initiated fully-automated subcortical brain segmentation in MRI using large deformation diffeomorphic metric mapping. Neuroimage. 2008 Jul 1;41(3):735-46.