Webinar Overview
MRI is a key modality to study animal models of stroke - from molecules to the whole brain. For example, fluorinated substances can be used for hypoxia mapping with fluorine-19 MRI while whole brain changes in structural networks can be mapped using the diffusion MRI connectome. However, there still is a translational gap between preclinical and clinical research. Preclinical researchers have mainly focused on brain tissue damage whereas improving functional outcome of the patient is the primary goal of clinicians.
Computational neuroscience applied to animal stroke models can help to close this gap by integrating MR neuroimaging and behavioral data. Philipp Boehm-Sturm’s group pooled 14 studies from their department to reach sample sizes that open the field for machine learning. With these tools at hand they asked important questions. Can they predict long term outcome after stroke in the mouse from an early MRI? Can they forecast the large differences in recovery? In his talk he addresses these questions as well as giving an insight into exciting community efforts on how we as preclinical MR researchers can collaborate better to enable more of such large scale studies.
On Demand Session
Speaker
Dr. Philipp Boehm-Sturm
Leader of the “Experimental MRI” group and scientific head of the Charité Core Facility „7 T experimental MRIs“ of the Charité University Medicine of Berlin, Germany
