Intracellular Ca dynamics in ventricular fibrillation

Abstract

In the heart, membrane voltage (Vm) and intracellular Ca (Cai) are bidirectionally coupled, so that ionic membrane currents regulate Cai cycling and Cai affects ionic currents regulating action potential duration (APD). Although Cai reliably and consistently tracks Vm at normal heart rates, it is possible that at very rapid rates, sarcoplasmic reticulum Cai cycling may exhibit intrinsic dynamics. Non-voltage-gated Cai release might cause local alternations in APD and refractoriness that influence wavebreak during ventricular fibrillation (VF). In this study, we tested this hypothesis by examining the extent to which Cai is associated with Vm during VF. Cai transients were mapped optically in isolated arterially perfused swine right ventricles using the fluorescent dye rhod 2 AM while intracellular membrane potential was simultaneously recorded either locally with a microelectrode (5 preparations) or globally with the voltage-sensitive dye RH-237 (5 preparations). Mutual information (MI) is a quantitative statistical measure of the extent to which knowledge of one variable (Vm) predicts the value of a second variable (Cai). MI was high during pacing and ventricular tachycardia (VT; 1.13 +/- 0.21 and 1.69 +/- 0.18, respectively) but fell dramatically during VF (0.28 +/- 0.06, P < 0.001). Cai at sites 4-6 mm apart also showed decreased MI during VF (0.63 +/- 0.13) compared with pacing (1.59 +/- 0.34, P < 0.001) or VT (2.05 +/- 0.67, P < 0.001). Spatially, Cai waves usually bore no relationship to membrane depolarization waves during nonreentrant fractionated waves typical of VF, whereas they tracked each other closely during pacing and VT. The dominant frequencies of Vm and Cai signals analyzed by fast Fourier transform were similar during VT but differed significantly during VF. Cai is closely associated with Vm closely during pacing and VT but not during VF. These findings suggest that during VF, non-voltage-gated Cai release events occur and may influence wavebreak by altering Vm and APD locally.

β-Adrenergic modulation of arrhythmogenesis and identification of targeted sites of antiarrhythmic therapy in Timothy (LQT8) syndrome: a theoretical study

“…Under normal physiological conditions, V m and [Ca 2ϩ ] i are bidirectionally coupled (12,16,27). V m regulates ionic current activities, thereby influencing [Ca 2ϩ ] i cycling of Ca 2ϩ release and removal, and [Ca 2ϩ ] i , in turn, affects various Ca 2ϩ -sensitive ionic current activities, primarily I Ca,L , I NaCa , and I nsCa , thereby determining the shape and duration of the action potential.…”

“…V m regulates ionic current activities, thereby influencing [Ca 2ϩ ] i cycling of Ca 2ϩ release and removal, and [Ca 2ϩ ] i , in turn, affects various Ca 2ϩ -sensitive ionic current activities, primarily I Ca,L , I NaCa , and I nsCa , thereby determining the shape and duration of the action potential. However, under abnormal conditions favoring "Ca 2ϩ overload," such as rapid pacing, ischemia, BAS, and digitalis intoxication, SR may exhibit I rel,SOICR , which is initiated locally but may propagate throughout the cell as a Ca 2ϩ wave (11,12,16,27). I rel,SOICR may then activate the forward-mode I NaCa and I nsCa , either alone or in combination, to generate I Ti , thereby producing DADs and DAD-mediated triggered activity (Fig.…”

A technical review of optical mapping of intracellular calcium within myocardial tissue

“…During PVCs, the chirality of the phase plot was reversed (Fig. 5E) distinct relationships between fluorescence maps and each process having significantly different fundamental rates (73). Later, excised blood-perfused swine hearts were studied using simultaneous imaging to determine the relationship between conduction block and Ca i 2ϩ cycling during fibrillation (112).…”

The Photodiode Array: A Critical Cornerstone in Cardiac Optical Mapping

“…This data is challenging to analyze and interpret, since recordings of fibrillation often have a chaotic appearance when viewed with time as the horizontal axis. Thus a variety of alternate methods have been used to gain insight into the nature of fibrillation, including dominant frequency analysis (Caldwell et al, 2007;Choi et al, 2003;Choi et al, 2006;Joel & Hsia, 2005;Moreno et al, 2005;Wu et al, 2004;Wu et al, 2006;Zaitsev et al, 2003) and mutual information (Omichi et al, 2004, Wu et al, 2005. More recently the use of a metric known as spatiotemporal entropy has been used to analyze oscillatory dynamics in cardiac and neural systems Jung et al, 2000;Himel et al, 2009).…”