Optimizing electrode placement using finite-element models in radiofrequency ablation treatment planning

Optimization of three-dimensional esophageal tumor ablation by simultaneous functioning of multiple electrodes

Radiofrequency ablation is a widely accepted minimal-invasive and effective local treatment for tumors. However, its current application in esophageal cancer treatment is limited to targeting thin and superficial lesions, such as Barrett's Esophagus. This study proposes an optimization method using multiple electrodes simultaneously to regulate the temperature field and achieve conformal ablation of tumors. A particle swarm optimization algorithm, coupled with a three-dimensional thermal ablation model, was developed to optimize the status of the functioning electrodes, the optimal voltage (Vopt), and treatment duration (ttre) for targeted esophageal tumors. This approach takes into account both the electrical and thermal interactions of the electrodes. The results indicate that for esophageal cancers at various stages, with thickness (c) ranging from 4.5 mm to 10.0 mm, major axis (a) ranging from 7.3 mm to 27.3 mm, and minor axis (b) equaling 7.3 mm or 27.3 mm, as well as non-symmetrical geometries, complete tumor coverage (over 99.5%) close to conformal can be achieved. This method illustrates possible precise conformal ablation of esophageal cancers and it may also be used for conformal treatments of other intraluminal lesions.

Development and validation of a radiofrequency ablation treatment planning system for vertebral metastases

PURPOSE

Bone-targeted radiofrequency ablation (RFA) is widely used in the treatment of vertebral metastases. While radiation therapy utilizes established treatment planning systems (TPS) based on multimodal imaging to optimize treatment volumes, current RFA of vertebral metastases has been limited to qualitative image-based assessment of tumour location to direct probe selection and access. This study aimed to design, develop and evaluate a computational patient-specific RFA TPS for vertebral metastases.

METHODS

A TPS was developed on the open-source 3D slicer platform, including procedural setup, dose calculation (based on finite element modelling), and analysis/visualization modules. Usability testing was carried out by 7 clinicians involved in the treatment of vertebral metastases on retrospective clinical imaging data using a simplified dose calculation engine. In vivo evaluation was performed in a preclinical porcine model (n = 6 vertebrae).

RESULTS

Dose analysis was successfully performed, with generation and display of thermal dose volumes, thermal damage, dose volume histograms and isodose contours. Usability testing showed an overall positive response to the TPS as beneficial to safe and effective RFA. The in vivo porcine study showed good agreement between the manually segmented thermally damaged volumes vs. the damage volumes identified from the TPS (Dice Similarity Coefficient = 0.71 ± 0.03, Hausdorff distance = 1.2 ± 0.1 mm).

CONCLUSION

A TPS specifically dedicated to RFA in the bony spine could help account for tissue heterogeneities in both thermal and electrical properties. A TPS would enable visualization of damage volumes in 2D and 3D, assisting clinicians in decisions about potential safety and effectiveness prior to performing RFA in the metastatic spine.

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 modelling 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. The present 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.

Computer-assisted planning for a concentric tube robotic system in neurosurgery

PURPOSE

Laser-induced thermotherapy in the brain is a minimally invasive procedure to denature tumor tissue. However, irregularly shaped brain tumors cannot be treated using existing commercial systems. Thus, we present a new concept for laser-induced thermotherapy using a concentric tube robotic system. The planning procedure is complex and consists of the optimal distribution of thermal laser ablations within a volume as well as design and configuration parameter optimization of the concentric tube robot.

METHODS

We propose a novel computer-assisted planning procedure that decomposes the problem into task- and robot-specific planning and uses a multi-objective particle swarm optimization algorithm with variable length.

RESULTS

The algorithm determines a Pareto-front of optimal ablation distributions for three patient datasets. It considers multiple objectives and determines optimal robot parameters for multiple trajectories to access the tumor volume.

CONCLUSIONS

We prove the effectiveness of our planning procedure to enable the treatment of irregularly shaped brain tumors. Multiple trajectories further increase the applicability of the procedure.

Overlapping radiofrequency ablation planning and robot-assisted needle insertion for large liver tumors

BACKGROUND

We aimed at facilitating percutaneous radiofrequency ablation (RFA) for large tumors with accurate overlapping ablation planning and robot-assisted needle insertion from a single incision port (SIP).

METHODS

We developed a personalized and quantitative RFA planning method to obtain multiple needle overlapping ablation planning through a single incision. A robot with a remote center of motion mechanism was designed to perform needle insertions through a SIP according to the planning.

RESULTS

Numerical and visual evaluation showed that the planning could yield nearly full coverage over large tumors and greatly reduce both ablation times and the ablations of normal tissues. Ex vivo and in vivo experiments showed that our robot-assisted needle insertion system was capable of conducting the RFA procedure in large liver tumors from a SIP.

CONCLUSIONS

Robot-assisted RFA needle insertions from a SIP makes RFA treatment for large tumors more minimally invasive, predictable, and repeatable.

Automatic planning of needle placement for robot-assisted percutaneous procedures

PURPOSE

Percutaneous procedures allow interventional radiologists to perform diagnoses or treatments guided by an imaging device, typically a computed tomography (CT) scanner with a high spatial resolution. To reduce exposure to radiations and improve accuracy, robotic assistance to needle insertion is considered in the case of X-ray guided procedures. We introduce a planning algorithm that computes a needle placement compatible with both the patient's anatomy and the accessibility of the robot within the scanner gantry.

METHODS

Our preoperative planning approach is based on inverse kinematics, fast collision detection, and bidirectional rapidly exploring random trees coupled with an efficient strategy of node addition. The algorithm computes the allowed needle entry zones over the patient's skin (accessibility map) from 3D models of the patient's anatomy, the environment (CT, bed), and the robot. The result includes the admissible robot joint path to target the prescribed internal point, through the entry point. A retrospective study was performed on 16 patients datasets in different conditions: without robot (WR) and with the robot on the left or the right side of the bed (RL/RR).

RESULTS

We provide an accessibility map ensuring a collision-free path of the robot and allowing for a needle placement compatible with the patient's anatomy. The result is obtained in an average time of about 1 min, even in difficult cases. The accessibility maps of RL and RR covered about a half of the surface of WR map in average, which offers a variety of options to insert the needle with the robot. We also measured the average distance between the needle and major obstacles such as the vessels and found that RL and RR produced needle placements almost as safe as WR.

CONCLUSION

The introduced planning method helped us prove that it is possible to use such a "general purpose" redundant manipulator equipped with a dedicated tool to perform percutaneous interventions in cluttered spaces like a CT gantry.

Dielectric Properties of Ex Vivo Porcine Liver Tissue Characterized at Frequencies Between 5 and 500 kHz When Heated at Different Rates

OBJECTIVE

The released energy during radio frequency thermal ablation therapy changes the dielectric properties of biological tissues. Understanding changes of dielectric properties of biological tissues during heating is fundamental to suitably model the medical procedure. The aim of this work is to obtain the thermal dependences of conductivity and permittivity of ex vivo porcine liver tissue at six frequencies from 5 to 500 kHz, during heating from 37 °C to 100 °C at three heating rates of approximately 0.1, 3, and 10 °C/min.

METHODS

Two experimental setups using different heating sources and a four-needle electrode connected to an impedance analyzer were developed to evaluate the thermal dependencies.

RESULTS

The results at a body temperature of 37 °C show a good agreement with the data reported in the literature. The conductivity initially shows an increase followed by a decrease, whereas the permittivity increases before a subsequent sharp decrease. Above 60 °C, different trends are observed for the three heating rates studied.

CONCLUSION

The electric conductivity and permittivity show a similar behavior at all evaluated frequencies and heating rates. The observed abrupt change of the slope near 45 °C at a slow heating rate may be used to identify the region of reversible changes in the tissue.

SIGNIFICANCE

These results confirm the connection among tissue dielectric properties, working frequency, and exposure time with thermal damage during heating.

Model-based optimal planning of hepatic radiofrequency ablation

This article presents a model-based pre-treatment optimal planning framework for hepatic tumour radiofrequency (RF) ablation. Conventional hepatic radiofrequency (RF) ablation methods rely on pre-specified input voltage and treatment length based on the tumour size. Using these experimentally obtained pre-specified treatment parameters in RF ablation is not optimal to achieve the expected level of cell death and usually results in more healthy tissue damage than desired. In this study we present a pre-treatment planning framework that provides tools to control the levels of both the healthy tissue preservation and tumour cell death. Over the geometry of tumour and surrounding tissue, we formulate the RF ablation planning as a constrained optimization problem. With specific constraints over the temperature profile (TP) in pre-determined areas of the target geometry, we consider two different cost functions based on the history of the TP and Arrhenius index (AI) of the target location, respectively. We optimally compute the input voltage variation to minimize the damage to the healthy tissue while ensuring a complete cell death in the tumour and immediate area covering the tumour. As an example, we use a simulation of a 1D symmetric target geometry mimicking the application of single electrode RF probe. Results demonstrate that compared to the conventional methods both cost functions improve the healthy tissue preservation.

Role of mathematical medicine in gastrointestinal carcinoma: Current status and perspectives

Mathematical medicine has already played an important role in clinical and basic research as a major interdisciplinary branch of medicine. Mathematical medicine has an important role not only in imaging diagnosis, image storage and transmission in gastrointestinal (GI) cancer, but also in tumor precision therapy. Specifically, in the field of minimally invasive treatment such as precise ablation, 3-dimension modeling, navigation, and surgical simulation significantly improve the therapeutic safety and efficiency in GI cancer. In addition, in the era of big data, data analysis and individualized therapy using mathematical medicine will become a trend in the future, offering an effective method for diagnosing and treating GI cancer and promoting clinical and scientific research.

Augmenting Surgery via Multi-scale Modeling and Translational Systems Biology in the Era of Precision Medicine: A Multidisciplinary Perspective

In this era of tremendous technological capabilities and increased focus on improving clinical outcomes, decreasing costs, and increasing precision, there is a need for a more quantitative approach to the field of surgery. Multiscale computational modeling has the potential to bridge the gap to the emerging paradigms of Precision Medicine and Translational Systems Biology, in which quantitative metrics and data guide patient care through improved stratification, diagnosis, and therapy. Achievements by multiple groups have demonstrated the potential for (1) multiscale computational modeling, at a biological level, of diseases treated with surgery and the surgical procedure process at the level of the individual and the population; along with (2) patient-specific, computationally-enabled surgical planning, delivery, and guidance and robotically-augmented manipulation. In this perspective article, we discuss these concepts, and cite emerging examples from the fields of trauma, wound healing, and cardiac surgery.

Simulation of thermal ablation by high-intensity focused ultrasound with temperature-dependent properties

An integrated computational framework was developed in this study for modeling high-intensity focused ultrasound (HIFU) thermal ablation. The temperature field was obtained by solving the bioheat transfer equation (BHTE) through the finite element method; while, the thermal lesion was considered as a denatured material experiencing phase transformation and modeled with the latent heat. An equivalent attenuation coefficient, which considers the temperature-dependent properties of the target material and the ultrasound diffraction due to bubbles, was proposed in the nonlinear thermal transient analysis. Finally, a modified thermal dose formulation was proposed to predict the lesion size, shape and location. In-vitro thermal ablation experiments on transparent tissue phantoms at different energy levels were carried out to validate this computational framework. The temperature histories and lesion areas from the proposed model show good correlation with those from the in-vitro experiments.

Optimization of tissue physical parameters for accurate temperature estimation from finite-element simulation of radiofrequency ablation

Computational finite element models are commonly used for the simulation of radiofrequency ablation (RFA) treatments. However, the accuracy of these simulations is limited by the lack of precise knowledge of tissue parameters. In this technical note, an inverse solver based on the unscented Kalman filter (UKF) is proposed to optimize values for specific heat, thermal conductivity, and electrical conductivity resulting in accurately simulated temperature elevations. A total of 15 RFA treatments were performed on ex vivo bovine liver tissue. For each RFA treatment, 15 finite-element simulations were performed using a set of deterministically chosen tissue parameters to estimate the mean and variance of the resulting tissue ablation. The UKF was implemented as an inverse solver to recover the specific heat, thermal conductivity, and electrical conductivity corresponding to the measured area of the ablated tissue region, as determined from gross tissue histology. These tissue parameters were then employed in the finite element model to simulate the position- and time-dependent tissue temperature. Results show good agreement between simulated and measured temperature.

Computational Modeling for Enhancing Soft Tissue Image Guided Surgery: An Application in Neurosurgery

With the recent advances in computing, the opportunities to translate computational models to more integrated roles in patient treatment are expanding at an exciting rate. One area of considerable development has been directed towards correcting soft tissue deformation within image guided neurosurgery applications. This review captures the efforts that have been undertaken towards enhancing neuronavigation by the integration of soft tissue biomechanical models, imaging and sensing technologies, and algorithmic developments. In addition, the review speaks to the evolving role of modeling frameworks within surgery and concludes with some future directions beyond neurosurgical applications.

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.

Geometric optimization of a mathematical model of radiofrequency ablation in hepatic carcinoma

Radio frequency ablation (RFA) is an effective means of achieving local control of liver cancer. It is a particularly suitable mode of therapy for small and favorably located tumors. However, local progression rates are substantially higher for large tumors (>3.0 cm). In the current study, we report on a mathematical model based on geometric optimization to treat large liver tumors. A database of mathematical models relevant to the configuration of liver cancer was also established. The specific placement of electrodes and the frequency of ablation were also optimized. In addition, three types of liver cancer lesion were simulated by computer guidance incorporating mathematical models. This approach can be expected to provide a more effective and rationale mechanism for employing RFA in the therapy of hepatic carcinoma.

Radiofrequency ablation technique in the treatment of liver tumours: review and future issues

Thermal ablation is increasingly being used for treatment of liver tumours. Among the techniques of thermal ablation, radiofrequency ablation (RF) is undoubtedly being used most frequently because of its advantages, such as morbidity and mortality rates, effective tumour ablation, as well as being less time-consuming. This paper presents the state of the art of RF ablation technique. This includes the theoretical development, experimental study and clinical application of the radiofrequency ablation technique. First, it introduces the principle of this technique. Second, it shows the development of this technique and valuable achievements. These achievements include the device, strategy of operation and extension to other diseases. Third, it concludes future issues to be addressed in order to further advance this technique.

Generalised polynomial chaos-based uncertainty quantification for planning MRgLITT procedures

PURPOSE

A generalised polynomial chaos (gPC) method is used to incorporate constitutive parameter uncertainties within the Pennes representation of bioheat transfer phenomena. The stochastic temperature predictions of the mathematical model are critically evaluated against MR thermometry data for planning MR-guided laser-induced thermal therapies (MRgLITT).

METHODS

The Pennes bioheat transfer model coupled with a diffusion theory approximation of laser tissue interaction was implemented as the underlying deterministic kernel. A probabilistic sensitivity study was used to identify parameters that provide the most variance in temperature output. Confidence intervals of the temperature predictions are compared to MR temperature imaging (MRTI) obtained during phantom and in vivo canine (n = 4) MRgLITT experiments. The gPC predictions were quantitatively compared to MRTI data using probabilistic linear and temporal profiles as well as 2-D 60 °C isotherms.

RESULTS

Optical parameters provided the highest variance in the model output (peak standard deviation: anisotropy 3.51 °C, absorption 2.94 °C, scattering 1.84 °C, conductivity 1.43 °C, and perfusion 0.94 °C). Further, within the statistical sense considered, a non-linear model of the temperature and damage-dependent perfusion, absorption, and scattering is captured within the confidence intervals of the linear gPC method. Multivariate stochastic model predictions using parameters with the dominant sensitivities show good agreement with experimental MRTI data.

CONCLUSIONS

Given parameter uncertainties and mathematical modelling approximations of the Pennes bioheat model, the statistical framework demonstrates conservative estimates of the therapeutic heating and has potential for use as a computational prediction tool for thermal therapy planning.

Grand challenge: applying regulatory science and big data to improve medical device innovation

Understanding how proposed medical devices will interface with humans is a major challenge that impacts both the design of innovative new devices and approval and regulation of existing devices. Today, designing and manufacturing medical devices requires extensive and expensive product cycles. Bench tests and other preliminary analyses are used to understand the range of anatomical conditions, and animal and clinical trials are used to understand the impact of design decisions upon actual device success. Unfortunately, some scenarios are impossible to replicate on the bench, and competitive pressures often accelerate initiation of animal trials without sufficient understanding of parameter selections. We believe that these limitations can be overcome through advancements in data-driven and simulation-based medical device design and manufacturing, a research topic that draws upon and combines emerging work in the areas of Regulatory Science and Big Data. We propose a cross-disciplinary grand challenge to develop and holistically apply new thinking and techniques in these areas to medical devices in order to improve and accelerate medical device innovation.

Considerations for theoretical modelling of thermal ablation with catheter-based ultrasonic sources: implications for treatment planning, monitoring and control

PURPOSE

To determine the impact of including dynamic changes in tissue physical properties during heating on feedback controlled thermal ablation with catheter-based ultrasound. Additionally, we compared the impact of several indicators of thermal damage on predicted extents of ablation zones for planning and monitoring ablations with this modality.

METHODS

A 3D model of ultrasound ablation with interstitial and transurethral applicators incorporating temperature-based feedback control was used to simulate thermal ablations in prostate and liver tissue. We investigated five coupled models of heat dependent changes in tissue acoustic attenuation/absorption and blood perfusion of varying degrees of complexity. Dimensions of the ablation zone were computed using temperature, thermal dose, and Arrhenius thermal damage indicators of coagulative necrosis. A comparison of the predictions by each of these models was illustrated on a patient-specific anatomy in the treatment planning setting.

RESULTS

Models including dynamic changes in blood perfusion and acoustic attenuation as a function of thermal dose/damage predicted near-identical ablation zone volumes (maximum variation < 2.5%). Accounting for dynamic acoustic attenuation appeared to play a critical role in estimating ablation zone size, as models using constant values for acoustic attenuation predicted ablation zone volumes up to 50% larger or 47% smaller in liver and prostate tissue, respectively. Thermal dose (t(43) ≥ 240 min) and thermal damage (Ω ≥ 4.6) thresholds for coagulative necrosis are in good agreement for all heating durations, temperature thresholds in the range of 54°C for short (<5 min) duration ablations and 50°C for long (15 min) ablations may serve as surrogates for determination of the outer treatment boundary.

CONCLUSIONS

Accounting for dynamic changes in acoustic attenuation/absorption appeared to play a critical role in predicted extents of ablation zones. For typical 5-15 min ablations with this modality, thermal dose and Arrhenius damage measures of ablation zone dimensions are in good agreement, while appropriately selected temperature thresholds provide a computationally cheaper surrogate.

Kalman filtered MR temperature imaging for laser induced thermal therapies

The feasibility of using a stochastic form of Pennes bioheat model within a 3-D finite element based Kalman filter (KF) algorithm is critically evaluated for the ability to provide temperature field estimates in the event of magnetic resonance temperature imaging (MRTI) data loss during laser induced thermal therapy (LITT). The ability to recover missing MRTI data was analyzed by systematically removing spatiotemporal information from a clinical MR-guided LITT procedure in human brain and comparing predictions in these regions to the original measurements. Performance was quantitatively evaluated in terms of a dimensionless L(2) (RMS) norm of the temperature error weighted by acquisition uncertainty. During periods of no data corruption, observed error histories demonstrate that the Kalman algorithm does not alter the high quality temperature measurement provided by MR thermal imaging. The KF-MRTI implementation considered is seen to predict the bioheat transfer with RMS error < 4 for a short period of time, ∆t < 10 s, until the data corruption subsides. In its present form, the KF-MRTI method currently fails to compensate for consecutive for consecutive time periods of data loss ∆t > 10 sec.

Electrical-thermal-structural coupling simulation for electrosurgery simulators

An electrosurgery is a fundamental operation that utilizes Joule heat generated by the passage of a radiofrequency current. Surgical simulators are demanded for training of the electrosurgical skill with fewer complications. However, foregoing simulators have never implemented a series of physics phenomena in electrosurgery. The aim of this study is to construct a surgical simulator with a unified physics-based modeling of whole processes of electrosurgery. In this paper, we developed an electrosurgical cutting simulation system with consideration of a series of physical phases: electrical, thermal, and structural phases. Especially, the structural change based on the vaporization and mechanical rupture is modeled. The experiments using porcine livers compared the simulated temperature change with the measured one in electrosurgical cutting, and the effectiveness of the proposed model was found. In addition, the rate-controlling step for real-time electrosurgery simulation was examined.

Mathematical modeling of impedance controlled radiofrequency tumor ablation and ex-vivo validation

Radiofrequency (RF) ablation uses RF current to heat and kill cancer applied via an electrode inserted under image-guidance, and is in clinical use for tumors in liver, lung kidney, and bone. Mathematical models are frequently used to determine tissue temperature during RF ablation, but most prior models do not include accurate implementation of power control algorithms as are used in clinical devices. We created a computer model employing the Finite Element Method, and implemented a clinically used impedance control algorithm. We assumed a rapid increase in tissue electrical conductivity upon vaporization to approximate tissue vapor formation and allow impedance control. We performed ex vivo tissue experiments where we measured the tissue temperature and impedance to validate the computer models. Impedance and temperature time course were comparable between model and experiments, and deviations are likely due to inaccurate data on temperature dependence of tissue properties. Ablation zone diameter was 33 mm in the computer model, and 29 ± 3 mm in the experiments. Our computer model may more accurately allow tissue temperature calculation via including power control algorithms as used in clinical devices.

High-fidelity computer models for prospective treatment planning of radiofrequency ablation with in vitro experimental correlation

PURPOSE

To evaluate the accuracy of computer simulation in predicting the thermal damage region produced by a radiofrequency (RF) ablation procedure in an in vitro perfused bovine liver model. The thermal dose end point in the liver model is used to assess quantitatively computer prediction for use in prospective treatment planning of RF ablation procedures.

MATERIALS AND METHODS

Geometric details of the tri-cooled tip electrode were modeled. The resistive heating of a pulsed voltage delivery was simulated in four dimensions using finite element models (FEM) implemented on high-performance parallel computing architectures. A range of physically realistic blood perfusion parameters, 3.6-53.6 kg/sec/m(3), was considered in the computer model. An Arrhenius damage model was used to predict the thermal dose. Dice similarity coefficients (DSC) were the metric of comparison between computational predictions and T1-weighted contrast-enhanced images of the damage obtained from a RF procedure performed on an in vitro perfused bovine liver model.

RESULTS

For a perfusion parameter greater than 16.3 kg/sec/m(3), simulations predict the temporal evolution of the damaged volume is perfusion limited and will reach a maximum value. Over a range of physically meaningful perfusion values, 16.3-33.1 kg/sec/m(3), the predicted thermal dose reaches the maximum damage volume within 2 minutes of the delivery and is in good agreement (DSC > 0.7) with experimental measurements obtained from the perfused liver model.

CONCLUSIONS

As measured by the computed volumetric DSC, computer prediction accuracy of the thermal dose shows good correlation with ablation lesions measured in vitro in perfused bovine liver models over a range of physically realistic perfusion values.

Model-based planning and real-time predictive control for laser-induced thermal therapy

In this article, the major idea and mathematical aspects of model-based planning and real-time predictive control for laser-induced thermal therapy (LITT) are presented. In particular, a computational framework and its major components developed by authors in recent years are reviewed. The framework provides the backbone for not only treatment planning but also real-time surgical monitoring and control with a focus on MR thermometry enabled predictive control and applications to image-guided LITT, or MRgLITT. Although this computational framework is designed for LITT in treating prostate cancer, it is further applicable to other thermal therapies in focal lesions induced by radio-frequency (RF), microwave and high-intensity-focused ultrasound (HIFU). Moreover, the model-based dynamic closed-loop predictive control algorithms in the framework, facilitated by the coupling of mathematical modelling and computer simulation with real-time imaging feedback, has great potential to enable a novel methodology in thermal medicine. Such technology could dramatically increase treatment efficacy and reduce morbidity.

RF ablation at low frequencies for targeted tumor heating: in vitro and computational modeling results

RF ablation uses RF current to heat and kill cancer applied via an electrode inserted under image guidance. Tumor has about half the electrical resistivity of normal tissue below 20 kHz, but similar resistivity above 500 kHz. We placed normal porcine liver tissue in contact with agar gel having similar resistivity as tumor within 20-450 kHz. A needle electrode was placed with half of the electrically active tip in each layer. We performed ablation with electric current applied for 12 min at 30 W, either at 20 or 450 kHz (n = 7 each), while measuring temperature via thermocouples 4 and 8 mm from the electrode. Mathematical heat-transfer models were created of an equivalent configuration and temperature profile determined at both frequencies. At 8-mm distance, at 450 kHz, tumor gel phantom and normal tissue obtained similar temperatures (57.5 ± 1.4 versus 58.7 ± 2.5 (°)C); at 20 kHz, tumor phantom obtained significantly higher temperatures than normal tissue (65.6 ± 2.0 versus 57.2 ± 5.6 (°)C, p < 0.01). Computer models confirm these results, and show the ablation zone diameter to be larger within the tumor phantom at 20 kHz compared to 450 kHz. Heating at low RFs may thus allow targeted heating of tumor tissue and reduced heating of normal tissue.

Interstitial microwave transition from hyperthermia to ablation: historical perspectives and current trends in thermal therapy

This work reviews the transition from hyperthermia to ablation for cancer treatment with interstitial microwave (MW) antennas. Early work utilising MW energy for thermal treatment of cancer tissue began in the late 1970s using single antennas applied interstitially or the use of multiple interstitial antennas driven with the same phase and equal power at 915 or 2450 MHz. The original antenna designs utilised monopole or dipole configurations. Early work in thermal therapy in the hyperthermia field eventually led to utilisation of these antennas and methods for MW ablation of tumours. Efforts to boost the radiated MW power levels while decreasing antenna shaft temperatures led to incorporation of internally cooled antennas for ablation. To address larger tumours, MW treatment utilised arrays that were simultaneously activated by either non-synchronous or synchronous phase operation, benefiting both hyperthermia and ablation strategies. Numerical modelling was used to provide treatment planning guidance for hyperthermia treatments and is expected to provide a similar benefit for ablation therapy. Although this is primarily a review paper, some new data are included. These new data show that three antennas with 2.5 cm spacing at 45 W/channel and 10 min resulted in a volume of 89.8 cm(3) when operated synchronously, but only 53.4 cm(3) non-synchronously. Efficiency was 1.1 (synchronous) versus 0.7 (non-synchronous). MW systems, treatment planning, and image guidance continue to evolve to provide better tools and options for clinicians and patients in order to provide better approach and targeting optimisation with the goal of improved treatment for the patient.

Mathematical spatio-temporal model of drug delivery from low temperature sensitive liposomes during radiofrequency tumour ablation

PURPOSE

Studies have demonstrated a synergistic effect between hyperthermia and chemotherapy, and clinical trials in image-guided drug delivery combine high-temperature thermal therapy (ablation) with chemotherapy agents released in the heating zone via low temperature sensitive liposomes (LTSL). The complex interplay between heat-based cancer treatments such as thermal ablation and chemotherapy may require computational models to identify the relationship between heat exposure and pharmacokinetics in order to optimise drug delivery.

MATERIALS AND METHODS

Spatio-temporal data on tissue temperature and perfusion from heat-transfer models of radiofrequency ablation were used as input data. A spatio-temporal multi-compartmental pharmacokinetic model was built to describe the release of doxorubicin (DOX) from LTSL into the tumour plasma space, and subsequent transport into the extracellular space, and the cells. Systemic plasma and tissue compartments were also included. We compared standard chemotherapy (free-DOX) to LTSL-DOX administered as bolus at a dose of 0.7 mg/kg body weight.

RESULTS

Modelling LTSL-DOX treatment resulted in tumour tissue drug concentration of approximately 9.3 microg/g with highest values within 1 cm outside the ablation zone boundary. Free-DOX treatment produced comparably uniform tissue drug concentrations of approximately 3.0 microg/g. Administration of free-DOX resulted in a considerably higher peak level of drug concentration in the systemic plasma compartment (16.1 microg/g) compared to LTSL-DOX (4.4 microg/g). These results correlate well with a prior in vivo study.

CONCLUSIONS

Combination of LTSL-DOX with thermal ablation allows localised drug delivery with higher tumour tissue concentrations than conventional chemotherapy. Our model may facilitate drug delivery optimisation via investigation of the interplays among liposome properties, tumour perfusion, and heating regimen.