Cardiac alternans, or changes in action potential duration (APD), are thought to be a precursor to lethal tachyarrhythmias like ventricular tachycardia or ventricular fibrillation, which can lead to sudden cardiac death. Linear methods for detecting alternans onset and suppression have had limited success, owing primarily to the presence of cardiac memory, in which APD prediction at any instant allegedly requires knowledge of multiple previous APDs and diastolic intervals (DIs) to successfully characterize the current cardiac state. Considering the non-linear relationship The transition from steady state to alternans has been successfully captured using non-linear analytical methods such as bifurcation theory, principal component analysis, and chaos control techniques between the APDs and preceding DIs. This chapter provides an overview of non-linear analytical approaches used to predict the onset of alternans, which have the potential to translate into preclinical modalities capable of alternans detection and control, preventing fatal tachyarrhythmias and the transition to sudden cardiac death. We present a preclinical evaluation that makes use of high resolution optical imaging. mapping of two novel techniques for predicting the onset of alternans based on bifurcation analysis and eigenvalue decomposition Furthermore, we find a link between alternans' spatial evolution and bifurcation parameters and dominant eigenvalues, suggesting a potential marker for alternans estimation.
Author (S) Details
Kanchan Kulkarni
Department of Biomedical Engineering, University of Minnesota-Twin Cities, Minneapolis, MN 55455, USA.
Elena G. Tolkacheva
Department of Biomedical Engineering, University of Minnesota-Twin Cities, Minneapolis, MN 55455, USA.
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