Using dominant eigenvalue analysis to predict formation of alternans in the heart

Virendra Kakade, Xiaopeng Zhao, Elena G. Tolkacheva

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Ventricular fibrillation at the whole heart level is often preceded by the alternation of action potential duration (APD), i.e., alternans, at the cellular level. As proven in many experiments, traditional approaches based on the slope of the restitution curve have not been successful in predicting alternans formation. Recently, a technique has been theoretically developed based on dominant eigenvalue analysis to predict alternans formation in isolated cardiac myocytes. Here, we aimed to demonstrate that this technique can be applied to predict alternans formation at the whole heart level. Optical mapping was performed in Langendorff-perfused hearts from New Zealand white rabbits (n = 4), which were paced at decreasing basic cycle lengths to introduce APD alternans. In each heart, the basic cycle length corresponding to the local onset of alternans, Bonset, was determined and two regions of the heart were identified at Bonset: one region which exhibited alternans (1:1alt) and one which did not (1:1). Corresponding two-dimensional eigenvalue (λ) maps were generated using principal component analysis by analyzing action potentials after short perturbations from the steady state, and mean eigenvalues (λ̄) were calculated separately for the 1:1 and 1:1alt regions. We demonstrated that λ̄ calculated at Bonset was significantly different (p<0.05) between the two regions. Our results suggest that this dominant eigenvalue technique can be used to successfully predict the local alternans formation in the heart.

Original languageEnglish (US)
Article number052716
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Issue number5
StatePublished - Nov 22 2013

Fingerprint Dive into the research topics of 'Using dominant eigenvalue analysis to predict formation of alternans in the heart'. Together they form a unique fingerprint.

Cite this