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The main limitation of radiofrequency (RF) ablation numerical simulations reported in the literature is their failure to provide statistical results based on the statistical variability of tissue thermalelectrical parameters. This work developed an efficient probabilistic approach to hepatic RF ablation in order to statistically evaluate the effect of four thermal-electrical properties of liver tissue on the uncertainty of the ablation zone dimensions: thermal conductivity, specific heat, blood perfusion and electrical conductivity. A deterministic thermal-electrical finite element model of a monopolar electrode inserted in the liver was coupled with the unscented transform method in order to obtain coagulation zone confidence intervals, probability and cumulative density functions. The coagulation zone volume, diameter and length were 10.96 cm 3 , 2.17 cm and 4.08 cm, respectively (P < 0.01). Furthermore, a probabilistic sensitivity analysis showed that perfusion and thermal conductivity account for >95% of the variability in coagulation zone volume, diameter and length.

Background: One of the current shortcomings of radiofrequency (RF) tumor ablation is its limited performance in regions close to large blood vessels, resulting in high recurrence rates at these locations. Computer models have been used to determine tissue temperatures during tumor ablation procedures. To simulate large vessels, either constant wall temperature or constant convective heat transfer coefficient (h) have been assumed at the vessel surface to simulate convection. However, the actual distribution of the temperature on the vessel wall is non-uniform and time-varying, and this feature makes the convective coefficient variable.

We measured specific heat directly by heating a sample uniformly between two electrodes by an electric generator. We minimized heat loss by styrofoam insulation. We measured temperature from multiple thermocouples at temperatures from 25 • C to 80 • C while heating the sample, and corrected for heat loss. We confirm method accuracy with a 2.5% agar-0.4% saline physical model and obtain specific heat of 4121 ± 89 J (kg K) −1 , with an average error of 3.1%.

Ablative therapies such as radio-frequency (RF) ablation are increasingly used for treatment of tumours in liver and other organs. Often large vessels limit the extent of the thermal lesion, and cancer cells close to the vessel survive resulting in local tumour recurrence. Accurate estimates of the heat convection coefficient h for large vessels will help improve ablation techniques, and are required for estimation of thermal lesion dimensions in simulations. Previous estimates of h did not consider that only part of the vessel is heated, and assumed uniform temperature distribution at the vessel wall. An analytical relationship between the heat convection coefficient, blood velocity and temperature is formulated. The heat convection coefficient evaluated will assist both simulations and design of proper protocols for in vivo measurements. The mathematical model developed in this work describes the exchange of heat between a solid surface and a moving fluid and it is based on energy and motion equations for Navier-Stokes fluids. A particular case of a laminar blood flow in the portal vein is studied when a portion of its surface is heated. The results show that heating a larger portion of the vessels reduces convective heat loss, which may result in more effective ablation strategies.

Abstruct-The analysis of heart rate variability (HRV) signals is an important tool for studying the autonomic nervous system, as it allows the evaluation of the balance between the sympathetic and parasympathetic influences on heart rhythm. Time-frequency analysis of HRV makes it easier to evaluate how this balance varies with time. This work presents a tool for time-frequency analysis of heart rate variability (HRV) developed in Matlab 6.5 Three techniques are available: Short-Time Fourier Transform, Continuous Wavelet Transform Scalogram and Time-Variant Auto-Regressive Modeling.

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