Anomalous Relaxation and Diffusion Study Group

A/Prof Viktor Vegh, The University of Queensland, Australia

Viktor started off in the field of Electrical Engineering, before realising that his wholesome passion lied in mathematics. As such, he switched to a degree in Applied Mathematics at the Queensland University of Technology and completed with Honours. The experience was so positive that soon after completing this degree he enrolled in a PhD in Computational and Applied Mathematics at the same University. During this time, he equipped himself with skills such as advanced computational mathematics techniques, i.e. solution of large linear systems, electromagnetics and simulation of electromagnetic waves. These competencies allowed him to pursue a post-PhD post-doctoral fellowship at the Centre for Magnetic Resonance, the University of Queensland. His synergistic background in Electrical Engineering and Mathematics underpinned his initial contributions on instrumentation design and development in NMR/MRI.

It seems that people equipped with strong analytical skills seek out other opportunities during their career. Like Matt, Viktor pursued opportunities in finance and, decided to complete a Master of Commerce degree with a major in Applied Finance. Interestingly, his roots in mathematics led to the choosing of final year electives such as stochastic modelling, Brownian motion in relation to stock price movements, Monte Carlo methods, martingales and more computational mathematics with primary focus on finance models (e.g. Black-Scholes equation). 

More recently, Viktor has focused on research and development of medical imaging methods for the direct in vivo mapping of biological effects, translatable to the diagnosis and monitoring of neurological diseases and disorders. As such, his research now focuses on understanding the underlying biological and physical processes influencing signal formation, specifically in MRI, via the use of mathematical models. Whilst his research focus has shifted over the years, it has always been, and continues to be, reinforced by his interests in the application of mathematics to real world problems. Applied finance remains a personal hobby for Viktor, in addition to cracking jokes with a straight face, offshore fishing and native Australian plants.

Prof Richard Magin, University of Chicago Illinois, USA

Professor Magin was trained as an engineer (Ga. Tech), retrained in biophysics (Rochester), and then educated in the deep waters of biomedicine at the National Cancer Institute (NIH). He found work in the flat lands of East Central Illinois (UIUC) in bioacoustics and bio-electromagnetics. Tried to teach what he had learned – gaining knowledge that informed his dive into the cresting wave of MRI. Swimming there, he was surprised to find that most of what he knew a little about (relaxation and diffusion) could be fashioned into a boat for exploring and extracting imaging information suitable for the detection of cancer.

Dr Matt Hall, National Physical Laboratory, UK

Matt used to describe his career as Brownian, but now feels that anomalous might  be a better description. He has a degree in Physics from the University of Sheffield, UK and a PhD in Mathematics from Imperial College London where  he studied statistical mechanics applied to evolutionary ecology. He then spent two years working as a consultant in a City of London firm specialising in complexity science for business, where he developed logistics software for firms including the Danish postal service. He then discovered diffusion MRI, moving first to St George’s, University of London, and then UCL.

He spent some time developing Monte-Carlo simulation  for diffusion MRI, and then went back to the City for a while, working at the Financial Services Authority – an experience which led him straight back to research. He moved back to UCL, firstly to CMIC and then to the UCL Great Ormond Street Institute of Child Health, where he worked on fractional approaches for diffusion in muscle tissue and Duchenne Muscular Dystrophy. His current incarnation is as a Principle Research Scientist at the UK’s National Physical Laboratory where he is developing MRI harmonisation and standardisation, including for clinical applications of fractional diffusion, advanced simulation-based methods and phantoms development.

Dr Qianqian Yang, Queensland University of Technology, Australia

Qianqian is a senior research fellow in the School of Mathematical Sciences at Queensland University of Technology. She has extensive experience in developing computationally efficient methods for solving fractional order partial differential equations. With this background, her recent research interest lies in the application of these fractional-order models to real-world problems, especially in the area of using anomalous diffusion MRI models to probe brain tissue microstructure.   

Prof Thomas Barrick (St George University London)

Tom has a degree in Mathematics from the University of Liverpool, UK (first class honours) and enjoyed the course sufficiently to do a Masters degree in Pure Mathematics (distinction) at the same university. After his Masters degree, while not knowing which direction to take his mathematical knowledge, he began a PhD in Medical Imaging at the Magnetic Resonance Image Analysis Research Centre (MARIARC), again at the University of Liverpool. This enabled him to begin his career in development of MRI techniques for image analysis and brain mapping.

He then moved to London to work on diffusion MRI and its application to patient diagnosis and disease progression at the Clinical Neuroscience Department at St George’s, University of London, UK. Eventually, after working with Matt Hall and meeting Richard Magin his interest in mathematics was rekindled in the form of fractional diffusion models and their applications in MRI. He currently works as an Associate Professor at St George’s, University of London and is developing Quasi-Diffusion Imaging, an advanced diffusion MRI technique based on fractional diffusion models that can be rapidly acquired in clinically feasible time.

Dr David Reiter (Emory University)

David began his training in the field of mechanical engineering at North Carolina State University (USA). He completed a M.S. and PhD at the University of California at Davis as part of the Biomedical Research Group where his work focused on non-destructive measurements of mechanical strain in soft tissue using MRI. Inspired in graduate school by the versatility of MRI as a quantitative tool, he then completed a post-doctoral fellowship at the National Institute on Aging (NIA) in the National Institutes of Health (NIH), focusing on quantitative MRI and MRS towards improved non-invasive cartilage matrix characterization. He soon transitioned into clinical MRI research as a staff scientist and head of the clinical MRI facility at NIA. His work there supported aging studies using imaging and spectroscopy of multiple organ systems while his independent research examined modeling and analysis of multicompartment and anomalous relaxation and diffusion in musculoskeletal tissues like cartilage and muscle.

Now at Emory University in the Department of Radiology and Imaging Sciences and the Department of Orthopedics, his lab continues to develop quantitative MRI and MRS approaches for addressing basic and applied research questions primarily in the musculoskeletal system. These approaches aim to improve the measurement of biomechanical, metabolic, and functional tissue properties in healthy and diseased conditions with the goal of obtaining detailed characterization of tissue status and disease progression, and enhanced diagnostic accuracy.

Dr Muge Karaman (University of Illinois, Chicago)

Muge received her first degree in Applied Mathematics from Istanbul Technical University in Istanbul (yes, that’s where Istanbul Technical University is located), Turkey (yes, that’s where Istanbul is located). She then pursued a Master’s degree in Computational Sciences and Engineering, where she worked on developing computational optimization models for disaster preparedness and response logistics; hoping to alleviate the impact of the expected powerful earthquakes in the region.

She found herself in the MRI field in 2009. She received her Ph.D. in Computational Sciences from Marquette University in Milwaukee, Wisconsin, where she had a lot of time to learn a lot about functional MRI (fMRI). Her research focused on developing complex-valued statistical models for fMRI and functional connectivity MRI in contrast to conventional techniques that use magnitude-only MRI data. As a reflection of her background in unconventional methods and models, she developed interest in anomalous diffusion after she joined the University of Illinois at Chicago (UIC) in 2014.

She is now a Research Assistant Professor at the Department of Bioengineering and the Center for MR Research of UIC. The overall goal of her research is developing and validating quantitative diffusion-weighted MRI techniques for the characterization of complex biological tissue in vivo, and integrating these techniques into computational models to address current and future medical challenges. She is particularly interested in investigating their feasibility in probing the underlying tissue characteristics in different disease conditions and organs, including adult and pediatric brain tumors, gastric cancer, and breast cancer. She is confident these advanced MRI techniques will facilitate critical clinical decisions in cancer diagnosis, early prediction of response to therapy, monitoring disease recurrence; and ultimately will help save lives.