< Back to previous page

Project

Automated and advance imaging analysis in acute stroke patients to evaluate early ischemic changes, diagnose vessel occlusions, and predict infarct growth and functional outcome

Stroke is a devastating disease and a leading cause of mortality and
handicap over the world. In patients with ischemic stroke the
obstruction of a blood vessel will result in neurological symptoms
which can be temporarily if blood flow is restored in time, or
persistent if this will not occur in time, resulting in brain ischemia.
Identifying early ischemic changes and vessel occlusions is critical to
select patients for endovascular therapy. Automated analyses of
neuroimaging can assist physicians in the diagnostic pathway. The
development of brain ischemia is time dependent with large
individual variation in infarct growth. The size of the baseline infarct
and the growth rate are predictors of the final infarct volume and
clinical outcomes. To increase the number of patients eligible for
endovascular stroke therapy and to improve the outcomes of patients
undergoing this therapy, it is critical to develop treatments that slow
infarct growth before blood flow can be restored. Individual prediction
of baseline infarct and growth rate as proposed in this project will
enable precision-based management of stroke patients for both
reperfusion therapy and neuroprotective drugs. In addition,
development of models beyond prediction of infarct growth, but
focusing on functional outcome is needed. We aim to establish both
tissue- and functional outcome clocks which can be implemented in
clinical practice.

Date:1 Oct 2022 →  Today
Keywords:Stroke, Automated neuroimaging analysis, Deep learning models, Prediction of infarct growth, Prediction of outcome
Disciplines:Computational biomodelling and machine learning, Diagnostic radiology, Neurological and neuromuscular diseases