Identification of Material Parameters from Temperature Measurements in Radio Frequency Ablation

The mathematical simulation of the method of radio frequency ablation (RFA) offers an opportunity to improve the success of the RFA. The results of the RFA depend highly on the experience of the radiologist. A simulation will offer a prediction of the results which can be used to adapt the setting and enable a complete destruction of the tumor, e.g. by adapting the probe's position. A good simulation needs as much information of the reality as possible. Especially the material properties pose a challenge since they vary from patient to patient, they can not be measured in vivo and they additionally change during the ablation. The aim of this thesis is to develop a mathematical model for the identification of the material parameters from temperature measurements and apply it to appropriate data sets. At first a minimization problem is formulated, where the difference between the measured temperature and the calculated temperature is minimized with respect to the material parameters. The temperature distribution is calculated with a coupled system of partial differential equations. Different approaches are considered which depend on the diverse modeling of the material parameters. The parameters are modeled as constant values as well as temperature dependent, tissue dependent and also spatially distributed. The advantages and disadvantages of the diverse models are illustrated by the numerical results for the identification with artificial temperature distributions as well as real temperature measurements

Identification of Material Parameters from Temperature Measurements in Radio Frequency Ablation

The mathematical simulation of the method of radio frequency ablation (RFA) offers an opportunity to improve the success of the RFA. The results of the RFA depend highly on the experience of the radiologist. A simulation will offer a prediction of the results which can be used to adapt the setting and enable a complete destruction of the tumor, e.g. by adapting the probe's position. A good simulation needs as much information of the reality as possible. Especially the material properties pose a challenge since they vary from patient to patient, they can not be measured in vivo and they additionally change during the ablation. The aim of this thesis is to develop a mathematical model for the identification of the material parameters from temperature measurements and apply it to appropriate data sets. At first a minimization problem is formulated, where the difference between the measured temperature and the calculated temperature is minimized with respect to the material parameters. The temperature distribution is calculated with a coupled system of partial differential equations. Different approaches are considered which depend on the diverse modeling of the material parameters. The parameters are modeled as constant values as well as temperature dependent, tissue dependent and also spatially distributed. The advantages and disadvantages of the diverse models are illustrated by the numerical results for the identification with artificial temperature distributions as well as real temperature measurements

A Theoretical and Experimental Analysis of Radiofrequency Ablation with a Multielectrode, Phased, Duty-Cycled System

Background:   The development of a unique radiofrequency (RF) cardiac ablation system, for the treatment of cardiac arrhythmias, is driven by the clinical need to safely create large uniform lesions while controlling lesion depth. Computational analysis of a finite element model of a three-dimensional, multielectrode, cardiac ablation catheter, powered by a temperature-controlled, multiphase, duty-cycled RF generator, is presented. Methods:   The computational model for each of the five operating modes offered by the generator is compared to independent tissue temperature measurements taken during in vitro ablation experiments performed on bovine myocardium. Results:   The results of the model agree with experimental temperature measurements very closely—the average values for mean error, root mean square difference, and correlation coefficient were 1.9°C, 13.3%, and 0.97, respectively. Lesions are shown to be contiguous and no significant edge effects are observed. Conclusions:   Both the in vitro and computational model results demonstrate that lesion depth decreases consistently as the bipolar-to-unipolar ratio increases—suggesting a clinical application to potentially control lesion depth with higher fidelity than is currently available. The effect of variable design parameters and clinical conditions on RF ablation can now be expeditiously studied with this validated model. (PACE 2010; 33:1089–1100)Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/79205/1/j.1540-8159.2010.02801.x.pd

Thermal ablation of biological tissues in disease treatment: A review of computational models and future directions

Percutaneous thermal ablation has proved to be an effective modality for treating both benign and malignant tumors in various tissues. Among these modalities, radiofrequency ablation (RFA) is the most promising and widely adopted approach that has been extensively studied in the past decades. Microwave ablation (MWA) is a newly emerging modality that is gaining rapid momentum due to its capability of inducing rapid heating and attaining larger ablation volumes, and its lesser susceptibility to the heat sink effects as compared to RFA. Although the goal of both these therapies is to attain cell death in the target tissue by virtue of heating above 50 oC, their underlying mechanism of action and principles greatly differs. Computational modelling is a powerful tool for studying the effect of electromagnetic interactions within the biological tissues and predicting the treatment outcomes during thermal ablative therapies. Such a priori estimation can assist the clinical practitioners during treatment planning with the goal of attaining successful tumor destruction and preservation of the surrounding healthy tissue and critical structures. This review provides current state-of- the-art developments and associated challenges in the computational modelling of thermal ablative techniques, viz., RFA and MWA, as well as touch upon several promising avenues in the modelling of laser ablation, nanoparticles assisted magnetic hyperthermia and non- invasive RFA. The application of RFA in pain relief has been extensively reviewed from modelling point of view. Additionally, future directions have also been provided to improve these models for their successful translation and integration into the hospital work flow

Computational simulation of the predicted dosimetric impact of adjuvant yttrium-90 PET/CT-guided percutaneous ablation following radioembolization

Background: 90Y PET/CT post-radioembolization imaging has demonstrated that the distribution of 90Y in a tumor can be non-uniform. Using computational modeling, we predicted the dosimetric impact of post-treatment 90Y PET/CT-guided percutaneous ablation of the portions of a tumor receiving the lowest absorbed dose. A cohort of fourteen patients with non-resectable liver cancer previously treated using 90Y radioembolization were included in this retrospective study. Each patient exhibited potentially under-treated areas of tumor following treatment based on quantitative 90Y PET/CT. 90Y PET/CT was used to guide electrode placement for simulated adjuvant radiofrequency ablation in areas of tumor receiving the lowest dose. The finite element method was used to solve Penne’s bioheat transport equation, coupled with the Arrhenius thermal cell-death model to determine 3D thermal ablation zones. Tumor and unablated tumor absorbed-dose metrics (average dose, D50, D70, D90, V100) following ablation were compared, where D70 is the minimum dose to 70% of tumor and V100 is the fractional tumor volume receiving more than 100 Gy. Results: Compared to radioembolization alone, 90Y radioembolization with adjuvant ablation was associated with predicted increases in all tumor dose metrics evaluated. The mean average absorbed dose increased by 11.2 ± 6.9 Gy. Increases in D50, D70, and D90 were 11.0 ± 6.9 Gy, 13.3 ± 10.9 Gy, and 11.8 ± 10.8 Gy, respectively. The mean increase in V100 was 7.2 ± 4.2%. All changes were statistically significant (P \u3c 0.01). A negative correlation between pre-ablation tumor volume and D50, average dose, and V100 was identified (ρ \u3c − 0.5, P \u3c 0.05) suggesting that adjuvant radiofrequency ablation may be less beneficial to patients with large tumor burdens. Conclusions: This study has demonstrated that adjuvant 90Y PET/CT-guided radiofrequency ablation may improve tumor absorbed-dose metrics. These data may justify a prospective clinical trial to further evaluate this hybrid approach

Highlighting the effect of heterogeneous blood perfusion on radio-frequency ablation of human brain tumors : An image-based numerical investigation

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