Fast Estimation of the Vascular Cooling in RFA Based on Numerical Simulation

An analytical solution for temperature distributions in hepatic radiofrequency ablation incorporating the heat-sink effect of large vessels

Fast prediction of the local thermal field induced by radiofrequency ablation (RFA) plays a critical role in hepatic RFA therapy. At present, it is still a challenging task to calculate and visualize the temperature distribution of RFA in real-time, especially when the heat-sink effect of adjacent large vessels is taken into account. To achieve this, the current investigation presented an analytical solution to calculate the temperature in RFA with an execution time of 0.05 s for three dimensional thermal field reconstruction. The presented temperature distribution is a combination of temperatures in homogeneous tissue and a quantification of the heat-sink effect of adjacent blood vessels. Temperatures in homogeneous tissue is calculated from a simplified Pennes bioheat equation, where several weighting parameters in the temperature expression are determined based on some reference point temperatures from the numerical simulation. The heat-sink effect is quantified based on a temperature factor, which measures the temperature difference between the vessel and the heated tissue, and a distance factor, which measures the distance to the vessel. The proposed method is validated to be able to gain similar temperature distributions to the numerical simulation but with its computational time being orders of magnitude smaller than that of numerical simulation, which improves the efficiency of interactive planning of RFA.

Intermittent Pringle maneuver may be beneficial for radiofrequency ablations in situations with tumor-vessel proximity

Background

Radiofrequency ablation (RFA) represents a treatment option for non-resectable liver malignancies. Larger ablations can be achieved with a temporary hepatic inflow occlusion (Pringle maneuver - PM). However, a PM can induce dehydration and carbonization of the target tissue. The objective of this study was to evaluate the impact of an intermittent PM on the ablation size.

Methods

Twenty-five multipolar RFAs were performed in porcine livers ex vivo. A perfused glass tube was used to simulate a natural vessel. The following five test series (each n=5) were conducted: (1) continuous PM, (2-4) intermittent PM, and (5) no PM. Ablations were cut into half. Ablation area, minimal radius, and maximal radius were compared.

Results

No change in complete ablation size could be measured between the test series (p>0.05). A small rim of native liver tissue was observed around the glass tube in the test series without PM. A significant increase of ablation area could be measured on the margin of the ablations with an intermittent PM, starting without hepatic inflow occlusion (p<0.05).

Conclusion

An intermittent PM did not lead to smaller ablations compared to a continuous or no PM ex vivo. Furthermore, an intermittent PM can increase the ablation area when initial hepatic inflow is succeeded by a PM.

A prospective development study of software-guided radio-frequency ablation of primary and secondary liver tumors: Clinical intervention modelling, planning and proof for ablation cancer treatment (ClinicIMPPACT)

Introduction

Radio-frequency ablation (RFA) is a promising minimal-invasive treatment option for early liver cancer, however monitoring or predicting the size of the resulting tissue necrosis during the RFA-procedure is a challenging task, potentially resulting in a significant rate of under- or over treatments. Currently there is no reliable lesion size prediction method commercially available.

Objectives

ClinicIMPPACT is designed as multicenter-, prospective-, non-randomized clinical trial to evaluate the accuracy and efficiency of innovative planning and simulation software. 60 patients with early liver cancer will be included at four European clinical institutions and treated with the same RFA system. The preinterventional imaging datasets will be used for computational planning of the RFA treatment. All ablations will be simulated simultaneously to the actual RFA procedure, using the software environment developed in this project. The primary outcome measure is the comparison of the simulated ablation zones with the true lesions shown in follow-up imaging after one month, to assess accuracy of the lesion prediction.

Discussion

This unique multicenter clinical trial aims at the clinical integration of a dedicated software solution to accurately predict lesion size and shape after radiofrequency ablation of liver tumors. Accelerated and optimized workflow integration, and real-time intraoperative image processing, as well as inclusion of patient specific information, e.g. organ perfusion and registration of the real RFA needle position might make the introduced software a powerful tool for interventional radiologists to optimize patient outcomes.

Finding Optimal Ablation Parameters for Multipolar Radiofrequency Ablation

PURPOSE

Radiofrequency ablation (RFA) for primary liver tumors and liver metastases is restricted by a limited ablation size. Multipolar RFA is a technical advancement of RFA, which is able to achieve larger ablations. The aim of this ex vivo study was to determine optimal ablation parameters for multipolar RFA depending on applicator distance and energy input.

METHODS

RFA was carried out ex vivo in porcine livers with three internally cooled, bipolar applicators in multipolar ablation mode. Three different applicator distances were used and five different energy inputs were examined. Ablation zones were sliced along the cross-sectional area at the largest ablation diameter, orthogonally to the applicators. These slices were digitally measured and analyzed.

RESULTS

Sixty RFA were carried out. A limited growth of ablation area was seen in all test series. This increase was dependent on ablation time, but not on applicator distance. A steady state between energy input and energy loss was not observed. A saturation of the minimum radius of the ablation zone was reached. Differences in ablation radius between the three test series were seen for lowest and highest energy input ( P < .05). No differences were seen for medium amounts of energy ( P > .05).

CONCLUSIONS

The ablation parameters applicator distance and energy input can be chosen in such a way, that minor deviations of the preplanned ablation parameters have no influence on the size of the ablation area.

GPU-based RFA simulation for minimally invasive cancer treatment of liver tumours

PURPOSE

Radiofrequency ablation (RFA) is one of the most popular and well-standardized minimally invasive cancer treatments (MICT) for liver tumours, employed where surgical resection has been contraindicated. Less-experienced interventional radiologists (IRs) require an appropriate planning tool for the treatment to help avoid incomplete treatment and so reduce the tumour recurrence risk. Although a few tools are available to predict the ablation lesion geometry, the process is computationally expensive. Also, in our implementation, a few patient-specific parameters are used to improve the accuracy of the lesion prediction.

METHODS

Advanced heterogeneous computing using personal computers, incorporating the graphics processing unit (GPU) and the central processing unit (CPU), is proposed to predict the ablation lesion geometry. The most recent GPU technology is used to accelerate the finite element approximation of Penne's bioheat equation and a three state cell model. Patient-specific input parameters are used in the bioheat model to improve accuracy of the predicted lesion.

RESULTS

A fast GPU-based RFA solver is developed to predict the lesion by doing most of the computational tasks in the GPU, while reserving the CPU for concurrent tasks such as lesion extraction based on the heat deposition at each finite element node. The solver takes less than 3 min for a treatment duration of 26 min. When the model receives patient-specific input parameters, the deviation between real and predicted lesion is below 3 mm.

CONCLUSION

A multi-centre retrospective study indicates that the fast RFA solver is capable of providing the IR with the predicted lesion in the short time period before the intervention begins when the patient has been clinically prepared for the treatment.

Interactive multi-criteria planning for radiofrequency ablation

PURPOSE

Image-guided radiofrequency ablation (RFA) is a broadly used minimally invasive method for the thermal destruction of focal liver malignancies using needle-shaped instruments. The established planning workflow is based on examination of 2D slices and manual definition of the access path. During that process, multiple criteria for all possible trajectories have to be taken into account. Hence, it demands considerable experience and constitutes a significant mental task.

METHODS

An access path determination method based on image processing and numerical optimization is proposed. Fast GPU-based simulation approximation is utilized to incorporate the heat distribution including realistic cooling effects from nearby blood vessels. A user interface for intuitive exploration of the optimization results is introduced.

RESULTS

The proposed methods are integrated into a clinical software assistant. To evaluate the suitability of the interactive optimization approach for the identification of meaningful therapy strategies, a retrospective study has been carried out. The system is able to propose clinically relevant trajectories to the target by incorporating multiple criteria.

CONCLUSIONS

A novel method for planning of image-guided radiofrequency ablation by means of interactive access path determination based on optimization is presented. A first retrospective study indicates that the method is suited to improve the classical planning of RFA.

Dynamics of tissue shrinkage during ablative temperature exposures

There is a lack of studies that examine the dynamics of heat-induced shrinkage of organ tissues. Clinical procedures such as radiofrequency ablation, microwave ablation or high-intensity focused ultrasound, use heat to treat diseases such as cancer and cardiac arrhythmia. When heat is applied to tissues, shrinkage occurs due to protein denaturation, dehydration and contraction of collagen at temperatures greater 50 °C. This is particularly relevant for image-guided procedures such as tumor ablation, where pre- and post-treatment images are compared and any changes in dimensions must be considered to avoid misinterpretations of the treatment outcome. We present data from ex vivo, isothermal shrinkage tests in porcine liver tissue, where axial changes in tissue length were recorded during 15 min of heating to temperatures between 60 and 95 °C. A mathematical model was developed to accurately describe the time and temperature-dependent shrinkage behavior. The shrinkage dynamics had the same characteristics independent of temperature; the estimated relative shrinkage, adjusted for time since death, after 15 min heating to temperatures of 60, 65, 75, 85 and 95 °C, was 12.3, 13.8, 16.6, 19.2 and 21.7%, respectively. Our results demonstrate the shrinkage dynamics of organ tissues, and suggest the importance of considering tissue shrinkage for thermal ablative treatments.

Computational modelling of microwave tumour ablations

Microwave tissue heating is being increasingly utilised in several medical applications, including focal tumour ablation, cardiac ablation, haemostasis and resection assistance. Computational modelling of microwave ablations is a precise and repeatable technique that can assist with microwave system design, treatment planning and procedural analysis. Advances in coupling temperature and water content to electrical and thermal properties, along with tissue contraction, have led to increasingly accurate computational models. Developments in experimental validation have led to broader acceptability and applicability of these newer models. This review will discuss the basic theory, current trends and future direction of computational modelling of microwave ablations.

Patient-Specific Planning for Radio-Frequency Ablation of Tumors in the Presence of Uncertainty

The radio frequency (RF) ablation is a promising minimally invasive form of treatment for hepatic metastases and primary tumors. Thereby a needle like applicator, which is interstitially placed into the lesion, induces an electric current that causes heating and consequent destruction of the tissue due to its Ohmic resistance. In order to be a true alternative to the standard surgical resection, RF ablation must lead to a result similar to R0 resections. Here, patient specific mathematical modeling and numerical simulation of the bio-physical processes lead to a valuable support of the therapy planning, because they allow for an a priori estimation of the success as well as an optimization of the therapy parameters. In this article we discuss a mathematical model of partial differential equations (PDEs) for the patient specific numerical simulation of RF ablation. A particular focus lies on the consideration of uncertainties in the material properties, the underlying image data as well as the computational results. We discuss a stochastic PDE model, which allows for a sensitivity analysis of the computational results with respect to perturbations in the material properties. Furthermore a method for the fast estimation of the thermal necrosis is shown, which bases on the separation of non patient specific pre-calculations and patient specific computations, leading to an interactive real-time simulation tool.