Radiofrequency ablation of hepatic tumors: simulation, planning, and contribution of virtual reality and haptics

A heuristic method for rapid and automatic radiofrequency ablation planning of liver tumors

PURPOSE

Preprocedural planning is a key step in radiofrequency ablation (RFA) treatment for liver tumors, which is a complex task with multiple constraints and relies heavily on the personal experience of interventional radiologists, and existing optimization-based automatic RFA planning methods are very time-consuming. In this paper, we aim to develop a heuristic RFA planning method to rapidly and automatically make a clinically acceptable RFA plan.

METHODS

First, the insertion direction is heuristically initialized based on tumor long axis. Then, the 3D RFA planning is divided into insertion path planning and ablation position planning, which are further simplified into 2D by projections along two orthogonal directions. Here, a heuristic algorithm based on regular arrangement and step-wise adjustment is proposed to implement the 2D planning tasks. Experiments are conducted on patients with liver tumors of different sizes and shapes from multicenter to evaluate the proposed method.

RESULTS

The proposed method automatically generated clinically acceptable RFA plans within 3 min for all cases in the test set and the clinical validation set. All RFA plans of our method achieve 100% treatment zone coverage without damaging the vital organs. Compared with the optimization-based method, the proposed method reduces the planning time by dozens of times while generating RFA plans with similar ablation efficiency.

CONCLUSION

The proposed method demonstrates a new way to rapidly and automatically generate clinically acceptable RFA plans with multiple clinical constraints. The plans of our method are consistent with the clinical actual plans on almost all cases, which demonstrates the effectiveness of the proposed method and can help reduce the burden on clinicians.

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.

Method for puncture trajectory planning in liver tumors thermal ablation based on NSGA-III

BACKGROUND

Thermal ablation of liver tumors is a conventional mode for treating liver tumors. In order to reduce the damage to normal tissue endangered by thermal ablation, the physician needs to plan the puncture path before surgery.

OBJECTIVE

In this paper, a puncture trajectory planning method for thermal ablation of liver tumor based on NSGA-III is proposed. This method takes the clinical hard constraints and soft constraints into account.

METHOD

The feasible puncture region is solved by the hard constraints, and after that the pareto front points are obtained under the soft constraints. When accessing the feasible puncture region, an adaptive morphological closing operation method based on K-means algorithm is adopted to process the spherical angle binary image of obstacles that might be encountered in the puncture process. RANSAC is performed to fit the tangent plane of liver surface when calculating the angle between the puncture trajectory and liver surface. In order to evaluate the puncture path obtained by this method, 6 tumors are selected as experimental subjects, and Hausdorff distance and Overlap Rate of Pareto front points with manually recommend points are calculated respectively.

RESULTS

The average value of Hausdorff distance is 24.91 mm, and the mean value of the overlap rate is 86.43%.

CONCLUSION

The proposed method can provide high safety and clinical practice of the puncture route.

Fast calculation of 3D radiofrequency ablation zone based on a closed-form solution of heat conduction equation fitted by ex vivo measurements

Fast calculation or simulation of the ablation zone induced by radiofrequency ablation (RFA) has a critical role in hepatic RFA planning and therapy. However, it remains challenging to approximate the ablation zone in real time, especially when more than one probe is involved in one ablation session. This paper presents a novel computational technique to calculate the 3D ablation zone of one probe RFA and two-probe switching RFA. The main idea is to get an approximate solution of the temperature distribution from a simplified Pennes bioheat equation, and further fit the solution to the coagulation measurements on ex vivo porcine liver. With a closed-form solution of temperature distribution, the calculation of the ablation zone is as simple as the commonly used ellipsoidal model, but it allows a more realistic prediction of combined ablation zones with different inter-probe spacing. The new approximation technique could potentially replace the original ellipsoidal model in the intervention planning step.

MRI guided procedure planning and 3D simulation for partial gland cryoablation of the prostate: a pilot study

PURPOSE

This study reports on the development of a novel 3D procedure planning technique to provide pre-ablation treatment planning for partial gland prostate cryoablation (cPGA).

METHODS

Twenty men scheduled for partial gland cryoablation (cPGA) underwent pre-operative image segmentation and 3D modeling of the prostatic capsule, index lesion, urethra, rectum, and neurovascular bundles based upon multi-parametric MRI data. Pre-treatment 3D planning models were designed including virtual 3D cryotherapy probes to predict and plan cryotherapy probe configuration needed to achieve confluent treatment volume. Treatment efficacy was measured with 6 month post-operative MRI, serum prostate specific antigen (PSA) at 3 and 6 months, and treatment zone biopsy results at 6 months. Outcomes from 3D planning were compared to outcomes from a series of 20 patients undergoing cPGA using traditional 2D planning techniques.

RESULTS

Forty men underwent cPGA. The median age of the cohort undergoing 3D treatment planning was 64.8 years with a median pretreatment PSA of 6.97 ng/mL. The Gleason grade group (GGG) of treated index lesions in this cohort included 1 (5%) GGG1, 11 (55%) GGG2, 7 (35%) GGG3, and 1 (5%) GGG4. Two (10%) of these treatments were post-radiation salvage therapies. The 2D treatment cohort included 20 men with a median age of 68.5 yrs., median pretreatment PSA of 6.76 ng/mL. The Gleason grade group (GGG) of treated index lesions in this cohort included 3 (15%) GGG1, 8 (40%) GGG2, 8 (40%) GGG3, 1 (5%) GGG4. Two (10%) of these treatments were post-radiation salvage therapies. 3D planning predicted the same number of cryoprobes for each group, however a greater number of cryoprobes was used in the procedure for the prospective 3D group as compared to that with 2D planning (4.10 ± 1.37 and 3.25 ± 0.44 respectively, p = 0.01). At 6 months post cPGA, the median PSA was 1.68 ng/mL and 2.38 ng/mL in the 3D and 2D cohorts respectively, with a larger decrease noted in the 3D cohort (75.9% reduction noted in 3D cohort and 64.8% reduction 2D cohort, p 0.48). In-field disease detection was 1/14 (7.1%) on surveillance biopsy in the 3D cohort and 3/14 (21.4%) in the 2D cohort, p = 0.056) In the 3D cohort, 6 month biopsy was not performed in 4 patients (20%) due to undetectable PSA, negative MRI, and negative MRI Axumin PET. For the group with traditional 2D planning, treatment zone biopsy was positive in 3/14 (21.4%) of the patients, p = 0.056.

CONCLUSIONS

3D prostate cancer models derived from mpMRI data provide novel guidance for planning confluent treatment volumes for cPGA and predicted a greater number of treatment probes than traditional 2D planning methods. This study prompts further investigation into the use of 3D treatment planning techniques as the increase of partial gland ablation treatment protocols develop.

Automatic Radiofrequency Ablation Planning for Liver Tumors With Multiple Constraints Based on Set Covering

Radiofrequency ablation (RFA) is now a widely used minimally invasive treatment method for hepatic tumors. Preoperative planning plays a vital role in RFA therapy. With increasing tumor size, multiple overlapping ablations are needed, which are challenging to optimize while considering clinical constraints. In this paper, we present a new automatic RFA planning method. First, a 2-steps set cover-based model is formulated, which can integrate multiple clinical constraints for optimization of overlapping ablations. To ensure that the planning model can be solved in a reasonable time, a search space reducing strategy is then proposed. We also developed an algorithm for automatic RFA electrode selection, which provides a proper electrode ablation zone for the planning model. The proposed method was evaluated with 20 tumors of varying sizes (0.92 cm³ to 28.4 cm³). Results showed that the proposed method can generate clinical feasible RFA plans with a minimum number of RFA electrodes and ablations, complete tumor coverage and minimized ablation of normal tissue.

SlicerVR for Medical Intervention Training and Planning in Immersive Virtual Reality

Virtual reality (VR) provides immersive visualization that has proved to be useful in a variety of medical applications. Currently, however, no free open-source software platform exists that would provide comprehensive support for translational clinical researchers in prototyping experimental VR scenarios in training, planning or guiding medical interventions. By integrating VR functions in 3D Slicer, an established medical image analysis and visualization platform, SlicerVR enables virtual reality experience by a single click. It provides functions to navigate and manipulate the virtual scene, as well as various settings to abate the feeling of motion sickness. SlicerVR allows for shared collaborative VR experience both locally and remotely. We present illustrative scenarios created with SlicerVR in a wide spectrum of applications, including echocardiography, neurosurgery, spine surgery, brachytherapy, intervention training and personalized patient education. SlicerVR is freely available under BSD type license as an extension to 3D Slicer and it has been downloaded over 7,800 times at the time of writing this article.

GPU-based 3D iceball modeling for fast cryoablation simulation and planning

PURPOSE

The elimination of abdominal tumors by percutaneous cryoablation has been shown to be an effective and less invasive alternative to open surgery. Cryoablation destroys malignant cells by freezing them with one or more cryoprobes inserted into the tumor through the skin. Alternating cycles of freezing and thawing produce an enveloping iceball that causes the tumor necrosis. Planning such a procedure is difficult and time-consuming, as it is necessary to plan the number and cryoprobe locations and predict the iceball shape which is also influenced by the presence of heating sources, e.g., major blood vessels and warm saline solution, injected to protect surrounding structures from the cold.

METHODS

This paper describes a method for fast GPU-based iceball modeling based on the simulation of thermal propagation in the tissue. Our algorithm solves the heat equation within a cube around the cryoprobes tips and accounts for the presence of heating sources around the iceball.

RESULTS

Experimental results of two studies have been obtained: an ex vivo warm gel setup and simulation on five retrospective patient cases of kidney tumors cryoablation with various levels of complexity of the vascular structure and warm saline solution around the tumor tissue. The experiments have been conducted in various conditions of cube size and algorithm implementations. Results show that it is possible to obtain an accurate result within seconds.

CONCLUSION

The promising results indicate that our method yields accurate iceball shape predictions in a short time and is suitable for surgical planning.

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.

Lesion modeling, characterization, and visualization for image-guided cardiac ablation therapy monitoring

In spite of significant efforts to improve image-guided ablation therapy, a large number of patients undergoing ablation therapy to treat cardiac arrhythmic conditions require repeat procedures. The delivery of insufficient thermal dose is a significant contributor to incomplete tissue ablation, in turn leading to the arrhythmia recurrence. Ongoing research efforts aim to better characterize and visualize RF delivery to monitor the induced tissue damage during therapy. Here, we propose a method that entails modeling and visualization of the lesions in real-time. The described image-based ablation model relies on classical heat transfer principles to estimate tissue temperature in response to the ablation parameters, tissue properties, and duration. The ablation lesion quality, geometry, and overall progression are quantified on a voxel-by-voxel basis according to each voxel's cumulative temperature and time exposure. The model was evaluated both numerically under different parameter conditions, as well as experimentally, using ex vivo bovine tissue samples undergoing ex vivo clinically relevant ablation protocols. The studies demonstrated less than 5°C difference between the model-predicted and experimentally measured end-ablation temperatures. The model predicted lesion patterns were within 0.5 to 1 mm from the observed lesion patterns, suggesting sufficiently accurate modeling of the ablation lesions. Lastly, our proposed method enables therapy delivery feedback with no significant workflow latency. This study suggests that the proposed technique provides reasonably accurate and sufficiently fast visualizations of the delivered ablation lesions.

Technical Note: On Cardiac Ablation Lesion Visualization for Image-guided Therapy Monitoring

The delivery of insufficient thermal dose is a significant contributor to incomplete tissue ablation and leads to arrhythmia recurrence and a large number of patients requiring repeat procedures. In concert with ongoing research efforts aimed at better characterizing the RF energy delivery, here we propose a method that entails modeling and visualization of the lesions in real time. The described image-based ablation model relies on classical heat transfer principles to estimate tissue temperature in response to the ablation parameters, tissue properties, and duration. The ablation lesion quality, geometry, and overall progression is quantified on a voxel-by-voxel basis according to each voxel's cumulative temperature and time exposure. The model was evaluated both numerically under different parameter conditions, as well as experimentally, using ex vivo bovine tissue samples. This study suggests that the proposed technique provides reasonably accurate and sufficiently fast visualizations of the delivered ablation lesions.

RFA Guardian: Comprehensive Simulation of Radiofrequency Ablation Treatment of Liver Tumors

The RFA Guardian is a comprehensive application for high-performance patient-specific simulation of radiofrequency ablation of liver tumors. We address a wide range of usage scenarios. These include pre-interventional planning, sampling of the parameter space for uncertainty estimation, treatment evaluation and, in the worst case, failure analysis. The RFA Guardian is the first of its kind that exhibits sufficient performance for simulating treatment outcomes during the intervention. We achieve this by combining a large number of high-performance image processing, biomechanical simulation and visualization techniques into a generalized technical workflow. Further, we wrap the feature set into a single, integrated application, which exploits all available resources of standard consumer hardware, including massively parallel computing on graphics processing units. This allows us to predict or reproduce treatment outcomes on a single personal computer with high computational performance and high accuracy. The resulting low demand for infrastructure enables easy and cost-efficient integration into the clinical routine. We present a number of evaluation cases from the clinical practice where users performed the whole technical workflow from patient-specific modeling to final validation and highlight the opportunities arising from our fast, accurate prediction techniques.

Active contour configuration model for estimating the posterior ablative margin in image fusion of real-time ultrasound and 3D ultrasound or magnetic resonance images for radiofrequency ablation: an experimental study

Purpose

The purpose of this study was to evaluate the accuracy of an active contour model for estimating the posterior ablative margin in images obtained by the fusion of real-time ultrasonography (US) and 3-dimensional (3D) US or magnetic resonance (MR) images of an experimental tumor model for radiofrequency ablation.

Methods

Chickpeas (n=12) and bovine rump meat (n=12) were used as an experimental tumor model. Grayscale 3D US and T1-weighted MR images were pre-acquired for use as reference datasets. US and MR/3D US fusion was performed for one group (n=4), and US and 3D US fusion only (n=8) was performed for the other group. Half of the models in each group were completely ablated, while the other half were incompletely ablated. Hyperechoic ablation areas were extracted using an active contour model from real-time US images, and the posterior margin of the ablation zone was estimated from the anterior margin. After the experiments, the ablated pieces of bovine rump meat were cut along the electrode path and the cut planes were photographed. The US images with the estimated posterior margin were compared with the photographs and post-ablation MR images. The extracted contours of the ablation zones from 12 US fusion videos and post-ablation MR images were also matched.

Results

In the four models fused under real-time US with MR/3D US, compression from the transducer and the insertion of an electrode resulted in misregistration between the real-time US and MR images, making the estimation of the ablation zones less accurate than was achieved through fusion between real-time US and 3D US. Eight of the 12 post-ablation 3D US images were graded as good when compared with the sectioned specimens, and 10 of the 12 were graded as good in a comparison with nicotinamide adenine dinucleotide staining and histopathologic results.

Conclusion

Estimating the posterior ablative margin using an active contour model is a feasible way of predicting the ablation area, and US/3D US fusion was more accurate than US/MR fusion.

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.

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.

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.

Automatic Multiple-Needle Surgical Planning of Robotic-Assisted Microwave Coagulation in Large Liver Tumor Therapy

The “robotic-assisted liver tumor coagulation therapy” (RALTCT) system is a promising candidate for large liver tumor treatment in terms of accuracy and speed. A prerequisite for effective therapy is accurate surgical planning. However, it is difficult for the surgeon to perform surgical planning manually due to the difficulties associated with robot-assisted large liver tumor therapy. These main difficulties include the following aspects: (1) multiple needles are needed to destroy the entire tumor, (2) the insertion trajectories of the needles should avoid the ribs, blood vessels, and other tissues and organs in the abdominal cavity, (3) the placement of multiple needles should avoid interference with each other, (4) an inserted needle will cause some deformation of liver, which will result in changes in subsequently inserted needles’ operating environment, and (5) the multiple needle-insertion trajectories should be consistent with the needle-driven robot’s movement characteristics. Thus, an effective multiple-needle surgical planning procedure is needed. To overcome these problems, we present an automatic multiple-needle surgical planning of optimal insertion trajectories to the targets, based on a mathematical description of all relevant structure surfaces. The method determines the analytical expression of boundaries of every needle “collision-free reachable workspace” (CFRW), which are the feasible insertion zones based on several constraints. Then, the optimal needle insertion trajectory within the optimization criteria will be chosen in the needle CFRW automatically. Also, the results can be visualized with our navigation system. In the simulation experiment, three needle-insertion trajectories were obtained successfully. In the in vitro experiment, the robot successfully achieved insertion of multiple needles. The proposed automatic multiple-needle surgical planning can improve the efficiency and safety of robot-assisted large liver tumor therapy, significantly reduce the surgeon’s workload, and is especially helpful for an inexperienced surgeon. The methodology should be easy to adapt in other body parts.

A simulator for percutaneous hepatic microwave thermal ablation under ultrasound guidance

The purpose of this study was to provide a simulation therapy environment for microwave thermal ablation (MWA) under the guidance of ultrasound, and to present an inexpensive and portable simulator built on real patient-based pre-operative computed tomography (CT) data. We established an experimental simulation system for teaching MWA and present the results of a preliminary evaluation of the simulator's realism and utility for training. The system comprises physical elements of an electromagnetic tracking device and an abdominal phantom, and software elements providing three-dimensional (3D) image processing tools, real-time navigation functions and objective evaluation function module. Details of the novel aspects of this system are presented, including a portable electromagnetic tracking device, adoption of real patient-based pre-operative CT data of liver, operation simulation of MWA, and recording and playback of the operation simulation. Patients with liver cancer were selected for evaluation of the clinical application value of the experimental simulation system. A total of 50 consultant interventional radiologists and 20 specialist registrars in radiology rated the simulator's hardware reality and overall ergonomics. Results show that the simulator system we describe can be used as a training tool for MWA. It enables training with real patient cases prior to surgery, and it can provide a realistic simulation of the actual procedure.

Rapid inverse planning for pressure-driven drug infusions in the brain

Infusing drugs directly into the brain is advantageous to oral or intravenous delivery for large molecules or drugs requiring high local concentrations with low off-target exposure. However, surgeons manually planning the cannula position for drug delivery in the brain face a challenging three-dimensional visualization task. This study presents an intuitive inverse-planning technique to identify the optimal placement that maximizes coverage of the target structure while minimizing the potential for leakage outside the target. The technique was retrospectively validated using intraoperative magnetic resonance imaging of infusions into the striatum of non-human primates and into a tumor in a canine model and applied prospectively to upcoming human clinical trials.

Toward online modeling for lesion visualization and monitoring in cardiac ablation therapy

Despite extensive efforts to enhance catheter navigation, limited research has been done to visualize and monitor the tissue lesions created during ablation in the attempt to provide feedback for effective therapy. We propose a technique to visualize the temperature distribution and extent of induced tissue injury via an image-based model that uses physiological tissue parameters and relies on heat transfer principles to characterize lesion progression in near real time. The model was evaluated both numerically and experimentally using ex vivo bovine muscle samples while emulating a clinically relevant ablation protocol. Results show agreement to within 5 degreeC between the model-predicted and experimentally measured end-ablation tissue temperatures, as well as comparable predicted and observed lesion characteristics. The model yields temperature and lesion updates in near real-time, thus providing reasonably accurate and sufficiently fast monitoring for effective therapy.

Emerging technologies for image guidance and device navigation in interventional radiology

Recent developments in image-guidance and device navigation, along with emerging robotic technologies, are rapidly transforming the landscape of interventional radiology (IR). Future state-of-the-art IR procedures may include real-time three-dimensional imaging that is capable of visualizing the target organ, interventional tools, and surrounding anatomy with high spatial and temporal resolution. Remote device actuation is becoming a reality with the introduction of novel magnetic-field enabled instruments and remote robotic steering systems. Robots offer several degrees of freedom and unprecedented accuracy, stability, and dexterity during device navigation, propulsion, and actuation. Optimization of tracking and navigation of interventional tools inside the human body will be critical in converting IR suites into the minimally invasive operating theaters of the future with increased safety and unsurpassed therapeutic efficacy. In the not too distant future, individual image guidance modalities and device tracking methods could merge into autonomous, multimodality, multiparametric platforms that offer real-time data of anatomy, morphology, function, and metabolism along with on-the-fly computational modeling and remote robotic actuation. The authors provide a concise overview of the latest developments in image guidance and device navigation, while critically envisioning what the future might hold for 2020 IR procedures.

Crepuscular rays for tumor accessibility planning

In modern clinical practice, planning access paths to volumetric target structures remains one of the most important and most complex tasks, and a physician's insufficient experience in this can lead to severe complications or even the death of the patient. In this paper, we present a method for safety evaluation and the visualization of access paths to assist physicians during preoperative planning. As a metaphor for our method, we employ a well-known, and thus intuitively perceivable, natural phenomenon that is usually called crepuscular rays. Using this metaphor, we propose several ways to compute the safety of paths from the region of interest to all tumor voxels and show how this information can be visualized in real-time using a multi-volume rendering system. Furthermore, we show how to estimate the extent of connected safe areas to improve common medical 2D multi-planar reconstruction (MPR) views. We evaluate our method by means of expert interviews, an online survey, and a retrospective evaluation of 19 real abdominal radio-frequency ablation (RFA) interventions, with expert decisions serving as a gold standard. The evaluation results show clear evidence that our method can be successfully applied in clinical practice without introducing substantial overhead work for the acting personnel. Finally, we show that our method is not limited to medical applications and that it can also be useful in other fields.

GPU-based real-time approximation of the ablation zone for radiofrequency ablation

Percutaneous radiofrequency ablation (RFA) is becoming a standard minimally invasive clinical procedure for the treatment of liver tumors. However, planning the applicator placement such that the malignant tissue is completely destroyed, is a demanding task that requires considerable experience. In this work, we present a fast GPU-based real-time approximation of the ablation zone incorporating the cooling effect of liver vessels. Weighted distance fields of varying RF applicator types are derived from complex numerical simulations to allow a fast estimation of the ablation zone. Furthermore, the heat-sink effect of the cooling blood flow close to the applicator's electrode is estimated by means of a preprocessed thermal equilibrium representation of the liver parenchyma and blood vessels. Utilizing the graphics card, the weighted distance field incorporating the cooling blood flow is calculated using a modular shader framework, which facilitates the real-time visualization of the ablation zone in projected slice views and in volume rendering. The proposed methods are integrated in our software assistant prototype for planning RFA therapy. The software allows the physician to interactively place virtual RF applicator models. The real-time visualization of the corresponding approximated ablation zone facilitates interactive evaluation of the tumor coverage in order to optimize the applicator's placement such that all cancer cells are destroyed by the ablation.

Optimal applicator placement in hepatic radiofrequency ablation on the basis of rare data

In this paper, a numerical procedure to determine an optimal applicator placement for hepatic radiofrequency ablation incorporating uncertain material parameters is presented. The main focus is set on the treatment of subjective and rare data-based information. For this purpose, we employ the theory of fuzzy sets and model uncertain parameters as fuzzy quantities. While fuzzy modelling has been established in structural engineering in the recent past, it is novel in biomedical engineering. Incorporating fuzzy quantities within an optimisation task is basically innovative. In our context, fuzzy modelling allows us to determine an optimal applicator placement that maximises the therapy success under the given uncertainty conditions. The applicability of our method is demonstrated by means of an example case.

Current Technology in Navigation and Robotics for Liver Tumours Ablation

Radiofrequecy ablation is the most widely used local ablative therapy for both primary and metastatic liver tumours. However, it has limited application in the treatment of large tumours (tumours >3cm) and multicentric tumours. In recent years, many strategies have been developed to extend the application of radiofrequency ablation to large tumours. A promising approach is to take advantage of the rapid advancement in imaging and robotic technologies to construct an integrated surgical navigation and medical robotic system. This paper presents a review of existing surgical navigation methods and medical robots. We also introduce our current developed model — Transcutaneous Robot-assisted Ablation-device Insertion Navigation System (TRAINS). The clinical viability of this prototyped integrated navigation and robotic system for large and multicentric umors is demonstrated using animal experiments. Keywords: Computer aided surgery, Liver, Radiofrequency ablation

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.

Imaging in interventional oncology

Medical imaging in interventional oncology is used differently than in diagnostic radiology and prioritizes different imaging features. Whereas diagnostic imaging prioritizes the highest-quality imaging, interventional imaging prioritizes real-time imaging with lower radiation dose in addition to high-quality imaging. In general, medical imaging plays five key roles in image-guided therapy, and interventional oncology, in particular. These roles are (a) preprocedure planning, (b) intraprocedural targeting, (c) intraprocedural monitoring, (d) intraprocedural control, and (e) postprocedure assessment. Although many of these roles are still relatively basic in interventional oncology, as research and development in medical imaging focuses on interventional needs, it is likely that the role of medical imaging in intervention will become even more integral and more widely applied. In this review, the current status of medical imaging for intervention in oncology will be described and directions for future development will be examined.

Effects of needle placement inaccuracies in hepatic radiofrequency tumor ablation

The correct needle placement is one of the crucial tasks in performing radiofrequency tumor ablation (RFA). In this work we evaluated the effects of imperfect needle placement for RFAs that are performed with an expandable needle array by using a finite-element simulation. We performed simulations for normal liver tissue with hypo- and hyperperfused metastasis as well as for cirrhotic liver tissue with hepatocellular carcinoma (HCC). We found that the shortest distance from tumor to the border of the ablated region is significantly smaller even for just 5mm deviation from the position recommended by the generator manufacturer. In case of hyperperfused metastasis even the tumor itself might stay unablated which means a very high probability of local tumor recurrence. These results provide valuable information on acceptability of inaccurate needle position to the radiologist performing RFA.

Navigation systems for ablation

Navigation systems, devices, and intraprocedural software are changing the way interventional oncology is practiced. Before the development of precision navigation tools integrated with imaging systems, thermal ablation of hard-to-image lesions was highly dependent on operator experience, spatial skills, and estimation of positron emission tomography-avid or arterial-phase targets. Numerous navigation systems for ablation bring the opportunity for standardization and accuracy that extends the operator's ability to use imaging feedback during procedures. In this report, existing systems and techniques are reviewed and specific clinical applications for ablation are discussed to better define how these novel technologies address specific clinical needs and fit into clinical practice.

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

We present a novel technique to predict the outcome of an RF ablation, including the vascular cooling effect. The main idea is to separate the problem into a patient independent part, which has to be performed only once for every applicator model and generator setting, and a patient dependent part, which can be performed very fast. The patient independent part fills a look-up table of the cooling effects of blood vessels, depending on the vessel radius and the distance of the RF applicator from the vessel, using a numerical simulation of the ablation process. The patient dependent part, on the other hand, only consists of a number of table look-up processes. The paper presents this main idea, along with the required steps for its implementation. First results of the computation and the related ex-vivo evaluation are presented and discussed. The paper concludes with future extensions and improvements of the approach.

Theoretical Modeling for Hepatic Microwave Ablation

Thermal tissue ablation is an interventional procedure increasingly being used for treatment of diverse medical conditions. Microwave ablation is emerging as an attractive modality for thermal therapy of large soft tissue targets in short periods of time, making it particularly suitable for ablation of hepatic and other tumors. Theoretical models of the ablation process are a powerful tool for predicting the temperature profile in tissue and resultant tissue damage created by ablation devices. These models play an important role in the design and optimization of devices for microwave tissue ablation. Furthermore, they are a useful tool for exploring and planning treatment delivery strategies. This review describes the status of theoretical models developed for microwave tissue ablation. It also reviews current challenges, research trends and progress towards development of accurate models for high temperature microwave tissue ablation.

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

We present a novel technique to predict the outcome of an RF ablation, including the vascular cooling effect. The main idea is to separate the problem into a patient independent part, which has to be performed only once for every applicator model and generator setting, and a patient dependent part, which can be performed very fast. The patient independent part fills a look-up table of the cooling effects of blood vessels, depending on the vessel radius and the distance of the RF applicator from the vessel, using a numerical simulation of the ablation process. The patient dependent part, on the other hand, only consists of a number of table look-up processes. The paper presents this main idea, along with the required steps for its implementation. First results of the computation and the related ex-vivo evaluation are presented and discussed. The paper concludes with future extensions and improvements of the approach.

Theoretical modeling for hepatic microwave ablation

Thermal tissue ablation is an interventional procedure increasingly being used for treatment of diverse medical conditions. Microwave ablation is emerging as an attractive modality for thermal therapy of large soft tissue targets in short periods of time, making it particularly suitable for ablation of hepatic and other tumors. Theoretical models of the ablation process are a powerful tool for predicting the temperature profile in tissue and resultant tissue damage created by ablation devices. These models play an important role in the design and optimization of devices for microwave tissue ablation. Furthermore, they are a useful tool for exploring and planning treatment delivery strategies. This review describes the status of theoretical models developed for microwave tissue ablation. It also reviews current challenges, research trends and progress towards development of accurate models for high temperature microwave tissue ablation.

Computer-assisted needle positioning for liver tumour radiofrequency ablation (RFA)

BACKGROUND

The RFA procedures rely on a precise positioning of the radiofrequency electrode and the complete destruction of the tumour. This article presents new optimization techniques to improve such surgical procedures.

METHODS

A method to optimize the coverage of the tumour by successive RFA destructions and an in vitro procedure with simulated tumours have been developed.

RESULTS

The guidance system and optimization coverage have been tested on 3D simulation and by the surgeon in vitro on a heifer liver. In this context, the RFA electrode is optically tracked and guided.

CONCLUSIONS

The optimization method provides needle placements that ensure a complete theoretical ablation of the tumour, and the guidance system helps the surgeon to reach each position of destruction.

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

Conventional radiofrequency ablation (RFA) planning methods for identifying suitable electrode placements typically use geometric shapes to model ablation outcomes. A method is presented for searching electrode placements that couples finite-element models (FEMs) of RFA together with a novel optimization strategy. The method was designed to reduce the need for model solutions per local search step. The optimization strategy was tested against scenarios requiring single and multiple ablations. In particular, for a scenario requiring multiple ablations, a domain decomposition strategy was described to minimize the complexity of simultaneously searching multiple electrode placements. The effects of nearby vasculature on optimal electrode placement were also studied. Compared with geometric planning approaches, FEMs could potentially deliver electrode placement plans that provide more physically meaningful predictions of therapeutic outcomes.

Preoperative surgery planning for percutaneous hepatic microwave ablation

A novel preoperative surgery planning method is proposed for percutaneous hepatic microwave ablation. An iterative framework for necrosis field simulation and 3D necrosis zone reconstruction is introduced here, and the necrosis model is further superimposed to patient anatomy structures using advanced GPU-accelerated visualization techniques. The full surgery planning is performed by the surgeon in an interactively way, until the optimal surgery plan is achieved. Experiments have been performed on realistic patient with hepatic cancer and the actual necrosis zone are measured in postoperative CT images for patient. Results show that this method is relative accurate for preoperative trajectory plan and could be used as an assistant to the clinical practice.

Characterization of tracked radiofrequency ablation in phantom

In radiofrequency ablation (RFA), successful therapy requires accurate, image-guided placement of the ablation device in a location selected by a predictive treatment plan. Current planning methods rely on geometric models of ablations that are not sensitive to underlying physical processes in RFA. Implementing plans based on computational models of RFA with image-guided techniques, however, has not been well characterized. To study the use of computational models of RFA in planning needle placement, this work compared ablations performed with an optically tracked RFA device with corresponding models of the ablations. The calibration of the tracked device allowed the positions of distal features of the device, particularly the tips of the needle electrodes, to be determined to within 1.4 +/- 0.6 mm of uncertainty. Ablations were then performed using the tracked device in a phantom system based on an agarose-albumin mixture. Images of the sliced phantom obtained from the ablation experiments were then compared with the predictions of a bioheat transfer model of RFA, which used the positional data of the tracked device obtained during ablation. The model was demonstrated to predict 90% of imaged pixels classified as being ablated. The discrepancies between model predictions and observations were analyzed and attributed to needle tracking inaccuracy as well as to uncertainties in model parameters. The results suggest the feasibility of using finite element modeling to plan ablations with predictable outcomes when implemented using tracked RFA.

Multiscale optimization of the probe placement for radiofrequency ablation

RATIONALE AND OBJECTIVES

We present a model for the optimal placement of mono- and bipolar probes in radiofrequency (RF) ablation. The model is based on a system of partial differential equations that describe the electric potential of the probe and the steady state of the induced heat distribution.

MATERIALS AND METHODS

To optimize the probe placement we minimize a temperature-based objective function under the constraining system of partial differential equations. Further, the extension of the resulting optimality system for the use of multiple coupled RF probes is discussed. We choose a multiscale gradient descent approach to solve the optimality system.

RESULTS

This article describes the discretization and implementation of the approach with finite elements on three-dimensional hexahedral grids.

CONCLUSION

Applications of the optimization to artificial test scenarios as well as a comparison to a real RF ablation show the usefulness of the approach.

Trajectory optimization for the planning of percutaneous radiofrequency ablation of hepatic tumors

Radiofrequency ablation is increasingly used in the treatment of hepatic tumors. Planning the percutaneous intervention is essential and particularly difficult. In this paper, we focus on an automated computation of optimal needle insertion in computer-assisted surgery with 3D visualization. First, we review our method which delineates on the skin of a virtual patient the candidate zones for needle insertion, i.e., those which allow safe access to the tumor. In each case, we look for the trajectory that minimizes the volume of burnt tissue. Secondly, we introduce a quasi-exhaustive method that allies sampling and certified minimization to form a strong argument for the accuracy of our results. We also compare results of applying both methods on 7 representative reconstructed patient cases.

Towards optimization of probe placement for radio-frequency ablation

We present a model for the optimal placement of mono- and bipolar probes in radio-frequency (RF) ablation. The model is based on a numerical computation of the probe's electric potential and of the steady state of the heat distribution during RF ablation. The optimization is performed by minimizing a temperature based objective functional under these constraining equations. The paper discusses the discretization and implementation of the approach. Finally, applications of the optimization to artificial data and a comparison to a real RF ablation are presented.

Toward the simulation of the strain of female pelvic organs

Surgical simulators have undergone a significant development, especially since the rise of mini-invasive surgery. The main simulators of digestive surgery have been developed for solid organs such as the liver and spleen. Studies relating to soft tissues like the pelvic organs are rare. The aim of this work was to create a model of female pelvis that will be used as a basis for the development of a patient specific pelvic simulator. A dynamic MRI acquisition is used to evaluate and to set the simulation model.

Theoretical modeling for radiofrequency ablation: state-of-the-art and challenges for the future

Radiofrequency ablation is an interventional technique that in recent years has come to be employed in very different medical fields, such as the elimination of cardiac arrhythmias or the destruction of tumors in different locations. In order to investigate and develop new techniques, and also to improve those currently employed, theoretical models and computer simulations are a powerful tool since they provide vital information on the electrical and thermal behavior of ablation rapidly and at low cost. In the future they could even help to plan individual treatment for each patient. This review analyzes the state-of-the-art in theoretical modeling as applied to the study of radiofrequency ablation techniques. Firstly, it describes the most important issues involved in this methodology, including the experimental validation. Secondly, it points out the present limitations, especially those related to the lack of an accurate characterization of the biological tissues. After analyzing the current and future benefits of this technique it finally suggests future lines and trends in the research of this area.