Global sensitivity study for irreversible electroporation: Towards treatment planning under uncertainty.

BACKGROUND: Electroporation-based cancer treatments are minimally invasive, nonthermal interventional techniques that leverage cell permeabilization to ablate the target tumor. However, the amount of permeabilization is susceptible to the numerous uncertainties during treatment, such as patient-specific variations in the tissue, type of the tumor, and the resolution of imaging equipment. These uncertainties can reduce the extent of ablation in the tissue, thereby affecting the effectiveness of the treatment. PURPOSE: The aim of this work is to understand the effect of these treatment uncertainties on the treatment outcome for irreversible electroporation (IRE) in the case of colorectal liver metastasis (CRLM). Understanding the nature and extent of these effects can help us identify the influential treatment parameters and build better models for predicting the treatment outcome. METHODS: This is an in silico study using a static computational model with a custom applicator design, spherical tissue, and tumor geometry. A nonlinear electrical conductivity, dependent on the local electric field, is considered. Morris analysis is used to identify the influential treatment parameters on the treatment outcome. Seven treatment parameters pertaining to the relative tumor location with respect to the applicator, the tumor growth pattern, and the electrical conductivity of tissue are analyzed. The treatment outcome is measured in terms of the relative tumor ablation with respect to the target ablation volume and total ablation volume. RESULTS: The Morris analysis was performed with 800 model evaluations, sampled from the seven dimensional input parameter space. Electrical properties of the tissue, especially the electrical conductivity of the tumor before ablation, were found to be the most influential parameter for relative tumor ablation and total ablation volume. This parameter was found to be about 4-15 times more influential than the least influential parameter, depending on the tumor size. The tumor border configuration was identified as the least important parameter for treatment effectiveness. The most desired treatment outcome is obtained by a combination of high healthy liver conductivity and low tumor conductivity. This information can be used to tackle worst-case scenarios in treatment planning. Finally, when the safety margins used in the clinical applications are accounted for, the effects of uncertainties in the treatment parameters reduce drastically. CONCLUSIONS: The results of this work can be used to create an efficient surrogate estimator for uncertainty quantification in the treatment outcome, that can be utilized in optimal real-time treatment planning solutions.

Uncertainty quantification for basin-scale geothermal conduction models.

Geothermal energy plays an important role in the energy transition by providing a renewable energy source with a low CO2 footprint. For this reason, this paper uses state-of-the-art simulations for geothermal applications, enabling predictions for a responsible usage of this earth's resource. Especially in complex simulations, it is still common practice to provide a single deterministic outcome although it is widely recognized that the characterization of the subsurface is associated with partly high uncertainties. Therefore, often a probabilistic approach would be preferable, as a way to quantify and communicate uncertainties, but is infeasible due to long simulation times. We present here a method to generate full state predictions based on a reduced basis method that significantly reduces simulation time, thus enabling studies that require a large number of simulations, such as probabilistic simulations and inverse approaches. We implemented this approach in an existing simulation framework and showcase the application in a geothermal study, where we generate 2D and 3D predictive uncertainty maps. These maps allow a detailed model insight, identifying regions with both high temperatures and low uncertainties. Due to the flexible implementation, the methods are transferable to other geophysical simulations, where both the state and the uncertainty are important.

Tuning the Pennes Perfusion Rate to Model Large Vessel Cooling Effects in Hepatic Radiofrequency Ablation.

Radio frequency ablation (RFA) has become a popular method for the minimally invasive treatment of liver cancer. However, the success rate of these treatments depends heavily on the amount of experience the clinician possesses. Mathematical modeling can help mitigate this problem by providing an indication of the treatment outcome. Thermal lesions in RFA are affected by the cooling effect of both fine-scale and large-scale blood vessels. The exact model for large-scale blood vessels is advection-diffusion, i.e., a model capable of producing directional effects, which are known to occur in certain cases. In previous research, in situations where directional effects do not occur, the advection term in the blood vessel model has been typically replaced with the Pennes perfusion term, albeit with a higher-than-usual perfusion rate. Whether these values of the perfusion rate appearing in literature are optimal for the particular vessel radii in question, has not been investigated so far. This work aims to address this issue. An attempt has been made to determine, for values of vessel radius between 0.55 mm and 5 mm, best estimates for the perfusion rate which minimize the error in thermal lesion volumes between the perfusion-based model and the advection-based model. The results for the best estimate of the perfusion rate presented may be used in existing methods for fast estimation of RFA outcomes. Furthermore, the possible improvements to the presented methodology have been highlighted.

Study of flow effects on temperature-controlled radiofrequency ablation using phantom experiments and forward simulations.

PURPOSE: Blood flow is known to add variability to hepatic radiofrequency ablation (RFA) treatment outcomes. However, few studies exist on its impact on temperature-controlled RFA. Hence, we investigate large-scale blood flow effects on temperature-controlled RFA in flow channel experiments and numerical simulations. METHODS: Ablation zones were induced in tissue-mimicking, thermochromic phantoms with a single flow channel, using an RF generator with temperature-controlled power delivery and a monopolar needle electrode. Channels were generated by molding the phantom around a removable rod. Channel radius and saline flow rate were varied to study the impact of flow on (i) the ablated cross-sectional area, (ii) the delivered generator power, and (iii) the occurrence of directional effects on the thermal lesion. Finite volume simulations reproducing the experimental geometry, flow conditions, and generator power input were conducted and compared to the experimental ablation outcomes. RESULTS: Vessels of different channel radii r affected the ablation outcome in different ways. For r = 0.275  mm, the ablated area decreased with increasing flow rate while the energy input was hardly affected. For r = 0.9  mm and r = 2.3  mm, the energy input increased toward larger flow rates; for these radii, the ablated area decreased and increased toward larger flow rates, respectively, while still being reduced overall as compared to the reference experiment without flow. Directional effects, that is, local shrinking of the lesion upstream of the needle and an extension thereof downstream, were observed only for the smallest radius. The simulations qualitatively confirmed these observations. As compared to performing the simulations without flow, including flow effects in the simulations reduced the mean absolute error between experimental and simulated ablated areas from 0.23 to 0.12. CONCLUSION: While the temperature control mechanism did not detect the heat sink effect in the case of the smallest channel radius, it counteracted the heat sink effect in the case of the larger channel radii with an increased energy input; this explains the increase in ablated area toward high flow rates (for r = 2.3  mm). The experiments in a simple phantom setup, thus, contribute to a good understanding of the phenomenon and are suitable for model validation.

Simulation study of the cooling effect of blood vessels and blood coagulation in hepatic radio-frequency ablation.

PURPOSE: Computer simulations of hepatic radio-frequency ablation (RFA) were performed to: (i) determine the dependence of the vessel wall heat transfer coefficient on geometrical parameters; (ii) study the conditions required for the occurrence of the directional effect of blood; and (iii) classify blood vessels according to their effect on the thermal lesion while considering blood coagulation. The information thus obtained supports the development of a multi-scale bio-heat model tailored for more accurate prediction of hepatic RFA outcomes in the vicinity of blood vessels. MATERIALS AND METHODS: The simulation geometry consisted of healthy tissue, tumor tissue, a mono-polar RF-needle, and a single cylindrical blood vessel. The geometrical parameters of interest were the RF-needle active length and those describing blood vessel configuration. A simple, novel method to incorporate the effects of blood coagulation into the simulation was developed and tested. RESULTS: A closed form expression giving the dependence of the vessel wall heat transfer coefficient on geometrical parameters was obtained. Directional effects on the thermal lesion were found to occur for blood vessel radii between 0.4 mm and 0.5 mm. Below 0.4 mm blood coagulation blocked the flow. CONCLUSIONS: The closed form expression for the heat transfer coefficient can be used in models of RFA to speed up computation. The conditions on vessel radii required for the occurrence of directional effects on the thermal lesion were determined. These conditions allow the classification of blood vessels. Different approximations to the thermal equation can thus be used for these vessel classes.