Computer simulation of cardiac cryoablation: comparison with in vivo data.

Simulation of cardiac cryoablation by the finite element method can contribute to optimizing ablation results and understanding the effects of modifications prior to time-consuming and expensive experiments. In this work an intervention scenario using a 9 Fr 8 mm tip applicator applied to ventricular tissue was simulated using the effective heat capacity model based on Pennes' bioheat equation. Using experimentally obtained refrigerant flow rates and temperature profiles recorded by a thermocouple located at the tip of the applicator the cooling performance of the refrigerant was estimated and integrated by time and temperature dependent boundary conditions based on distinct phases of a freeze-thaw cycle. Our simulations exhibited a mean difference of approximately 6°C at the applicator tip compared to temperature profiles obtained during in vivo experiments. The presented model is a useful tool for simulation and validation of new developments in clinical cardiac cryoablation.

Prediction of countershock success: a comparison of autoregressive and fast fourier transformed spectral estimators.

OBJECTIVES: Spectral analysis of the ventricular fibrillation (VF) ECG has been used for predicting countershock success, where the Fast Fourier Transformation (FFT) is the standard spectral estimator. Autoregressive (AR) spectral estimation should compute the spectrum with less computation time. This study compares the predictive power and computational performance of features obtained by the FFT and AR methods. METHODS: In an animal model of VF cardiac arrest, 41 shocks were delivered in 25 swine. For feature parameter analysis, 2.5 s signal intervals directly before the shock and directly before the hands-off interval were used, respectively. Invasive recordings of the arterial pressure were used for assessing the outcome of each shock. For a proof of concept, a micro-controller program was implemented. RESULTS: Calculating the area under the receiver operating characteristic (ROC) curve (AUC), the results of the AR-based features called spectral pole power (SPP) and spectral pole power with dominant frequency (DF) weighing (SPPDF) yield better outcome prediction results (85%; 89%) than common parameters based on FFT calculation method (centroid frequency (CF), amplitude spectrum area (AMSA)) (72%; 78%) during hands-off interval. Moreover, the predictive power of the feature parameters during ongoing CPR was not invalidated by closed-chest compressions. The calculation time of the AR-based parameters was nearly 2.5 times faster than the FFT-based features. CONCLUSION: Summing up, AR spectral estimators are an attractive option compared to FFT due to the reduced computational speed and the better outcome prediction. This might be of benefit when implementing AR prediction features on the microprocessor of a semi-automatic defibrillator.

Frequency distribution effects of anchored mother rotors--a computer model study.

Recent findings indicate that major organized centers (mother rotors) can maintain ventricular fibrillation (VF). In computer models the mother rotors can be induced by local shortening of the action potential duration (APD) in the cardiac tissue. Because of the fact that these rotors tend to drift away towards regions with longer APD, an additional heterogeneity (e.g. bundle) has to be included in the model for stabilizing the activation. Thus, the rotor anchors on this bundle and yields to interesting frequency distribution effects. In the dominant frequency (DF) map of a simplified computer model of the left ventricle it can be observed that the anchoring site of the rotor produces a slightly lower DF than in the surrounding cardiac tissue. That means that due to the load effect of the bundle the frequency is decreased. Furthermore the meandering of the mother rotor around this anchor site is reflected in the spectra of signals taken randomly in the organized region. These effects are both detected with two different independent spectral estimators with different resolutions.