PD Dr. med. Roza Umarova

Attending

Inselspital, Bern University Hospital, Department of Neurology

Brain reserve as predictor of stroke outcome

The concept of brain reserve is well established in neurodegeneration. In this project, we aim to adapt the concept of brain reserve for stroke to improve prediction of post-stroke outcome. Brain reserve is represented by quantitative brain characteristics at the time stroke occurs (e.g. brain volume, hippocampus volume), it is reduced by brain pathology (e.g. white matter hyperintensities, brain atrophy). We investigate the impact of proxies of brain reserve and its pathology on post-stroke cognition and outcome.

Impact of cognitive reserve on stroke outcome

The concept of cognitive reserve has been developed to explain the inter-individual variability in response to neurodegenerative pathology. We suggested that this concept might be a valuable framework to predict post-stroke cognitive deficits and functional outcome. ‘Cognitive reserve’ (CR) is defined as the function of lifetime intellectual activities, which serve to shape network efficiency, processing capacity and flexibility (Barulli & Stern, 2013). We propose that post-stroke cognition and stroke outcome can be defined as a result of an interaction between brain reserve (e.g. brain volume), cognitive reserve (e.g. level of education) and lesion load. The project is supported by Synapsis-Foundation and Heidi Seiler-Foundation.

Post-stroke cognitive trajectories

Post-stroke cognitive deficits demonstrate high inter-individual variability, which is expected to increase further due to the increasing life expectancy and number of patients with pre-stroke brain pathology and cognitive deficits.

There exist different types and patterns of post-stroke cognitive decline:

  • the deficits in one or several cognitive domains meaning the variability in neuropsychological profiles;
  • the decline might vary from mild to manifested dementia comprising a wide spectrum in severity;
  • with occurrence immediately after stroke or with delayed manifestation several months later without obvious reasons.

Patients at risk for post-stroke cognitive decline cannot be reliably identified now. In the project, we track the cognitive functioning in stroke patients. Our aim is to understand the inter-individual variability in post-stroke cognitive trajectories and to improve its prediction.

Neuroimaging of post-stroke cognition

In this project, we aim to apply the methods of advanced neuroimaging (e.g. functional MRI, diffusion q-imaging) to understand the underlying mechanisms of inter-individual variability in post-stroke cognitive trajectories.

Research fields

  • Stroke and Cognition

Team

Collabortions

 Overview    
Doctoral Thesis (PhD-analogue in Russia) 2003-2006 Institute of Neurology, Russian Academy of Medical Science, Moscow (RU)
Residency and post-doctorate 2007-2014 University of Freiburg (DE)
Certified neurologist 2014
Venia legendi 2017 University of Freiburg (DE)
Attending since 2017  University Hospital Bern (CH)