Extensive research has helped identify risk factors for acute stroke, but information about what the brains of stroke patients look like at a population level is still lacking, according to the study.
The results of the first large-scale assessment of radiographic brain health in stroke patients in the community will be presented by University of Cincinnati researchers at the European Stroke Organization Conference (ESOC) 2023, May 24-26 in Munich, Germany.
“The imaging can be an objective manifestation of the presence and severity of clinical factors such as diabetes, hypertension, high cholesterol and renal failure,” said Achala Vagal, MD, professor of neuroradiology at UC. “However, most large epidemiologic studies of brain health have been conducted in subjects without stroke.”
Vagal was a co-investigator of the Assessing Population-based Radiological brain health in Stroke Epidemiology (APRISE) study, which obtained new information from neuroimaging results of stroke patients.
The research team analyzed all available clinical imaging data from nearly 3,500 patients who had a stroke in the Greater Cincinnati/Northern Kentucky area in 2015 and assessed imaging markers of small vessel disease in the brain in the form of prior injury, microbleeds, white matter disease ( tissue wear and tear) or brain atrophy, among other observations.
Vagal said the team identified three distinct clusters of observable imaging characteristics, each associated with a specific set of clinical variables.
“This can help us understand the biology of pre-existing brain health in stroke patients and help guide future interventions,” she said. “We expected all imaging parameters of brain health due to small vessel disease to be closely clustered, but we found a lack of clustering of microbleeds with white matter disease.”
With knowledge gained from the study, Vagal said the team is now using imaging data on brain health to create a predictive model of recurrent stroke. “Such large-scale characterization of pre-existing brain health is useful to identify new observable characteristics that can lead to further studies,” she said.
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