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Laboratory of Unconventional Electrophysiology

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Personalized Risk Prediction of Stroke and Silent Brain Infarction Using Computational Fluid Dynamics

Our objective is to establish the feasibility of a computational fluid dynamics (CFD)-based, left atrial (LA) regional blood flow analysis technology to predict stroke and abnormal brain MRI findings in patients with and without a history of atrial fibrillation (Afib). The proposed research will 1) identify novel biomarkers to predict stroke and silent brain infarction (SBI) in patients with and without a history of Afib, whereas the current guidelines allow risk stratification only in individuals with Afib; and 2) provide evidence for studies to evaluate prophylactic oral anticoagulation or LAA closure to reduce the risk of stroke, SBI, and cognitive decline.

Media Coverage:

  • MRI may help gauge stroke risk in those with irregular heartbeat (April 2015)
  • Motion-tracking MRI gives new insight into stroke risk (April 2015)
  • 'Corkscrew' shape of blood flow in heart's upper chamber my signal low stroke risk (November 2016)
  • Video: This visualization of a human heart could help doctors predict stroke risk (November 2016)
  • Biomarker Predicts Success of Afib Treatment (February 2018)

 

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