Meet The Researcher

Samuel Klistoner

Mr Samuel Klistorner

The University of Sydney, NSW

Let’s get started! Tell us an interesting fact about yourself..
In my spare time I enjoy hiking. For my honeymoon I hiked to Everest Base Camp, it sure is a great way to cement the marriage.
What inspired you to get involved in MS research?
Coming from an engineering background I was drawn to MS research due to the influence engineering capabilities can provide to the understanding of MS and how it can contribute to treatment. Some of the biggest breakthroughs have come from technical challenges being solved such as data analysis using ai tools. I thoroughly enjoy collaborating with the neurologists, researchers, clinicians and AI developers to have an impact in the MS community.
What do you think has been the most exciting development in MS research?
For me, the most exciting development is the recent discovery of the role that expansion of chronic lesions plays in disease progression. This is the area that I will be involved in for my PHD. Another fascinating area is the use of AI in image analysis.
Tell us about your current research project... 
My research is aimed at using the latest techniques of MRI imaging to understand the progression of MS and be able to predict how the disease will progress. I will use this as a biomarker to measure the efficacy of drug treatments, such as remyelination drugs.. Specifically I will be using Diffusion Weighted Imaging (DWI) alongside traditional imaging techniques, such as T1 and FLAIR, to track the evolution of lesions and other pathological structures such as the Choroid Plexus. This will allow me to measure and evaluate slow-burning inflammation at the rim of chronic MS lesions; and, as such, this can be used as a biomarker of chronic slow-burning inflammation and associated progressive brain tissue damage.
Why is your research important and how will it influence the understanding and treatment of MS?
This research project aims at better understanding of disease progression. Furthermore, it is likely to result in development of specific biomarkers, which can be used in clinical trials of remyelination therapies. This is exciting as currently there are no, or very few, methods that are able to measure a successful remyelinating drug.
What do you enjoy most about working in the lab and what are some of the challenges you face?
I enjoy working with state of the art MRI imaging techniques and using a variety of tools, such as AI to analyse the data. Some of the challenges I have been facing is the difficulties of sharing MRI data between labs and also to be able to integrate various AI tools on our own datasets.
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Samuel Klistoner