Applicability of the single equivalent moving dipole model in an infinite homogeneous medium to identify cardiac electrical sources: a computer simulation study in a realistic anatomic geometry torso model.

Contains fulltext : 50703.pdf (publisher's version ) (Closed access)We have previously proposed an inverse algorithm for fitting potentials due to an arbitrary bio-electrical source to a single equivalent moving dipole (SEMD) model. The algorithm achieves fast identification of the SEMD parameters by employing a SEMD model embedded in an infinite homogeneous volume conductor. However, this may lead to systematic error in the identification of the SEMD parameters. In this paper, we investigate the accuracy of the algorithm in a realistic anatomic geometry torso model (forward problem). Specifically, we investigate the effect of measurement noise, dipole position and electrode configuration in the accuracy of the algorithm. The boundary element method was used to calculate the forward potential distribution at multiple electrode positions on the body surface due to a point dipole in the heart. We have found that the position and not the number of electrodes as well as the site of the origin of the arrhythmia in the heart have a significant effect on the accuracy of the inverse algorithm, while the measurement noise does not. Finally, we have shown that the inverse algorithm preserves the topology of the source distribution in the heart, thus potentially allowing the cardiac electrophysiologist to efficiently and accurately guide the tip of the catheter to the ablation site

Mitochondrial networks in cardiac myocytes reveal dynamic coupling behavior

Oscillatory behavior of mitochondrial inner membrane potential (DeltaPsim) is commonly observed in cells subjected to oxidative or metabolic stress. In cardiac myocytes, the activation of inner membrane pores by reactive oxygen species (ROS) is a major factor mediating intermitochondrial coupling, and ROS-induced ROS release has been shown to underlie propagated waves of DeltaPsim depolarization as well as synchronized limit cycle oscillations of DeltaPsim in the network. The functional impact of DeltaPsim instability on cardiac electrophysiology, Ca(2+) handling, and even cell survival, is strongly affected by the extent of such intermitochondrial coupling. Here, we employ a recently developed wavelet-based analytical approach to examine how different substrates affect mitochondrial coupling in cardiac cells, and we also determine the oscillatory coupling properties of mitochondria in ventricular cells in intact perfused hearts. The results show that the frequency of DeltaPsim oscillations varies inversely with the size of the oscillating mitochondrial cluster, and depends on the strength of local intermitochondrial coupling. Time-varying coupling constants could be quantitatively determined by applying a stochastic phase model based on extension of the well-known Kuramoto model for networks of coupled oscillators. Cluster size-frequency relationships varied with different substrates, as did mitochondrial coupling constants, which were significantly larger for glucose (7.78 x 10(-2) +/- 0.98 x 10(-2) s(-1)) and pyruvate (7.49 x 10(-2) +/- 1.65 x 10(-2) s(-1)) than lactate (4.83 x 10(-2) +/- 1.25 x 10(-2) s(-1)) or beta-hydroxybutyrate (4.11 x 10(-2) +/- 0.62 x 10(-2) s(-1)). The findings indicate that mitochondrial spatiotemporal coupling and oscillatory behavior is influenced by substrate selection, perhaps through differing effects on ROS/redox balance. In particular, glucose-perfusion generates strong intermitochondrial coupling and temporal oscillatory stability. Pathological changes in specific catabolic pathways, which are known to occur during the progression of cardiovascular disease, could therefore contribute to altered sensitivity of the mitochondrial network to oxidative stress and emergent DeltaPsim instability, ultimately scaling to produce organ level dysfunction

A combined anatomic and electrophysiologic substrate based approach for sudden cardiac death risk stratification

BACKGROUND: Although left ventricular ejection fraction (LVEF) is the primary determinant for sudden cardiac death (SCD) risk stratification, in isolation, LVEF is a sub-optimal risk stratifier. We assessed whether a multi-marker strategy would provide more robust SCD risk stratification than LVEF alone. METHODS: We collected patient-level data (n = 3355) from 6 studies assessing the prognostic utility of microvolt T-wave alternans (MTWA) testing. Two thirds of the group was used for derivation (n = 2242) and one-third for validation (n = 1113). The discriminative capacity of the multivariable model was assessed using the area under the receiver-operating characteristic curve (c-index). The primary endpoint was SCD at 24 months. RESULTS: In the derivation cohort, 59 patients experienced SCD by 24 months. Stepwise selection suggested that a model based on 3 parameters (LVEF, coronary artery disease and MTWA status) provided optimal SCD risk prediction. In the derivation cohort, the c-index of the model was 0.817, which was significantly better than LVEF used as a single variable (0.637, P < .001). In the validation cohort, 36 patients experienced SCD by 24 months. The c-index of the model for predicting the primary endpoint was again significantly better than LVEF alone (0.774 vs 0.671, P = .020). CONCLUSIONS: A multivariable model based on presence of coronary artery disease, LVEF and MTWA status provides significantly more robust SCD risk prediction than LVEF as a single risk marker. These findings suggest that multi-marker strategies based on different aspects of the electro-anatomic substrate may be capable of improving primary prevention implantable cardioverter-defibrillator treatment algorithms