Evaluation of a numerical simulation for cryoablation - comparison with bench data, clinical kidney and lung cases.

PURPOSE: The accuracy of a numerical simulation of cryoablation ice balls was evaluated in gel phantom data as well as clinical kidney and lung cases. MATERIALS AND METHODS: To evaluate the accuracy, 64 experimental single-needle cryoablations and 12 multi-needle cryoablations in gel phantoms were re-simulated with the corresponding freeze-thaw-freeze cycles. The simulated temperatures were compared over time with the measurements of thermocouples. For single needles, temperature values were compared at each thermocouple location. For multiple needles, Euclidean distances between simulated and measured isotherms (10 °C, 0 °C, -20 °C, -40 °C) were computed. Furthermore, surface and volume of simulated 0 °C isotherms were compared to cryoablation-induced ice balls in 14 kidney and 13 lung patients. For this purpose, needle positions and relevant anatomical structures defining material parameters (kidney/lung, tumor) were reconstructed from pre-ablation CT images and fused with postablation CT images (from which ice balls were extracted by manual delineation). RESULTS: The single-needle gel phantom cases showed less than 5 °C prediction error on average. Over all multiple needle experiments in gel, the mean and maximum isotherm distance were less than 2.3 mm and 4.1 mm, respectively. Average Dice coefficients of 0.82/0.63 (kidney/lung) and mean surface distances of 2.59/3.12 mm quantify the prediction performance of the numerical simulation. However, maximum surface distances of 10.57/10.8 mm indicate that locally larger errors have to be expected. CONCLUSION: A very good agreement of the numerical simulations for gel experiments was measured and a satisfactory agreement of the numerical simulations with measured ice balls in patient data was shown.

Workflow and intervention times of MR-guided focused ultrasound - Predicting the impact of new techniques.

Magnetic resonance guided focused ultrasound surgery (MRgFUS) has become an attractive, non-invasive treatment for benign and malignant tumours, and offers specific benefits for poorly accessible locations in the liver. However, the presence of the ribcage and the occurrence of liver motion due to respiration limit the applicability MRgFUS. Several techniques are being developed to address these issues or to decrease treatment times in other ways. However, the potential benefit of such improvements has not been quantified. In this research, the detailed workflow of current MRgFUS procedures was determined qualitatively and quantitatively by using observation studies on uterine MRgFUS interventions, and the bottlenecks in MRgFUS were identified. A validated simulation model based on discrete events simulation was developed to quantitatively predict the effect of new technological developments on the intervention duration of MRgFUS on the liver. During the observation studies, the duration and occurrence frequencies of all actions and decisions in the MRgFUS workflow were registered, as were the occurrence frequencies of motion detections and intervention halts. The observation results show that current MRgFUS uterine interventions take on average 213min. Organ motion was detected on average 2.9 times per intervention, of which on average 1.0 actually caused a need for rework. Nevertheless, these motion occurrences and the actions required to continue after their detection consumed on average 11% and up to 29% of the total intervention duration. The simulation results suggest that, depending on the motion occurrence frequency, the addition of new technology to automate currently manual MRgFUS tasks and motion compensation could potentially reduce the intervention durations by 98.4% (from 256h 5min to 4h 4min) in the case of 90% motion occurrence, and with 24% (from 5h 19min to 4h 2min) in the case of no motion. In conclusion, new tools were developed to predict how intervention durations will be affected by future workflow changes and by the introduction of new technology.

An integrated model-based software for FUS in moving abdominal organs.

Focused ultrasound surgery (FUS) is a non-invasive method for tissue ablation that has the potential for complete and controlled local tumour destruction with minimal side effects. The treatment of abdominal organs such as the liver, however, requires particular technological support in order to enable a safe, efficient and effective treatment. As FUS is applied from outside the patient's body, suitable imaging methods, such as magnetic resonance imaging or diagnostic ultrasound, are needed to guide and track the procedure. To facilitate an efficient FUS procedure in the liver, the organ motion during breathing and the partial occlusion by the rib cage need to be taken into account in real time, demanding a continuous patient-specific adaptation of the treatment configuration. Modelling the patient's respiratory motion and combining this with tracking data improves the accuracy of motion predictions. Modelling and simulation of the FUS effects within the body allows the use of treatment planning and has the potential to be used within therapy to increase knowledge about the patient status. This article describes integrated model-based software for patient-specific modelling and prediction for FUS treatments of moving abdominal organs.

Data-Driven Discovery of Immune Contexture Biomarkers.

Background: Features characterizing the immune contexture (IC) in the tumor microenvironment can be prognostic and predictive biomarkers. Identifying novel biomarkers can be challenging due to complex interactions between immune and tumor cells and the abundance of possible features. Methods: We describe an approach for the data-driven identification of IC biomarkers. For this purpose, we provide mathematical definitions of different feature classes, based on cell densities, cell-to-cell distances, and spatial heterogeneity thereof. Candidate biomarkers are ranked according to their potential for the predictive stratification of patients. Results: We evaluated the approach on a dataset of colorectal cancer patients with variable amounts of microsatellite instability. The most promising features that can be explored as biomarkers were based on cell-to-cell distances and spatial heterogeneity. Both the tumor and non-tumor compartments yielded features that were potentially predictive for therapy response and point in direction of further exploration. Conclusion: The data-driven approach simplifies the identification of promising IC biomarker candidates. Researchers can take guidance from the described approach to accelerate their biomarker research.

Methodology on quantification of sonication duration for safe application of MR guided focused ultrasound for liver tumour ablation.

BACKGROUND AND OBJECTIVE: Magnetic Resonance Guided Focused Ultrasound (MRgFUS) for liver tumour ablation is a challenging task due to motion caused by breathing and occlusion due the ribcage between the transducer and the tumour. To overcome these challenges, a novel system for liver tumour ablation during free breathing has been designed. METHODS: The novel TRANS-FUSIMO Treatment System (TTS, EUFP7) interacts with a Magnetic Resonance (MR) scanner and a focused ultrasound transducer to sonicate to a moving target in liver. To meet the requirements of ISO 13485; a quality management system for medical device design, the system needs to be tested for certain process parameters. The duration of sonication and, the delay after the sonication button is activated, are among the parameters that need to be quantified for efficient and safe ablation of tumour tissue. A novel methodology is developed to quantify these process parameters. A computerised scope is programmed in LabVIEW to collect data via hydrophone; where the coordinates of fiber-optic sensor assembly was fed into the TRANS-FUSIMO treatment software via Magnetic Resonance Imaging (MRI) to sonicate to the tip of the sensor, which is synchronised with the clock of the scope, embedded in a degassed water tank via sensor assembly holder. The sonications were executed for 50 W, 100 W, 150 W for 10 s to quantify the actual sonication duration and the delay after the emergency stop by two independent operators for thirty times. The deviation of the system from the predefined specs was calculated. Student's-T test was used to investigate the user dependency. RESULTS: The duration of sonication and the delay after the sonication were quantified successfully with the developed method. TTS can sonicate with a maximum deviation of 0.16 s (Std 0.32) from the planned duration and with a delay of 14 ms (Std 0.14) for the emergency stop. Student's T tests indicate that the results do not depend on operators (p > .05). CONCLUSION: The evidence obtained via this protocol is crucial for translation- of-research into the clinics for safe application of MRgFUS. The developed protocol could be used for system maintenance in compliance with quality systems in clinics for daily quality assurance routines.

A focused ultrasound treatment system for moving targets (part I): generic system design and in-silico first-stage evaluation.

BACKGROUND: Focused ultrasound (FUS) is entering clinical routine as a treatment option. Currently, no clinically available FUS treatment system features automated respiratory motion compensation. The required quality standards make developing such a system challenging. METHODS: A novel FUS treatment system with motion compensation is described, developed with the goal of clinical use. The system comprises a clinically available MR device and FUS transducer system. The controller is very generic and could use any suitable MR or FUS device. MR image sequences (echo planar imaging) are acquired for both motion observation and thermometry. Based on anatomical feature tracking, motion predictions are estimated to compensate for processing delays. FUS control parameters are computed repeatedly and sent to the hardware to steer the focus to the (estimated) target position. All involved calculations produce individually known errors, yet their impact on therapy outcome is unclear. This is solved by defining an intuitive quality measure that compares the achieved temperature to the static scenario, resulting in an overall efficiency with respect to temperature rise. To allow for extensive testing of the system over wide ranges of parameters and algorithmic choices, we replace the actual MR and FUS devices by a virtual system. It emulates the hardware and, using numerical simulations of FUS during motion, predicts the local temperature rise in the tissue resulting from the controls it receives. RESULTS: With a clinically available monitoring image rate of 6.67 Hz and 20 FUS control updates per second, normal respiratory motion is estimated to be compensable with an estimated efficiency of 80%. This reduces to about 70% for motion scaled by 1.5. Extensive testing (6347 simulated sonications) over wide ranges of parameters shows that the main source of error is the temporal motion prediction. A history-based motion prediction method performs better than a simple linear extrapolator. CONCLUSIONS: The estimated efficiency of the new treatment system is already suited for clinical applications. The simulation-based in-silico testing as a first-stage validation reduces the efforts of real-world testing. Due to the extensible modular design, the described approach might lead to faster translations from research to clinical practice.

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.

Radiofrequency ablation planning beyond simulation.

It is a challenging task to plan a radiofrequency (RF) ablation therapy to achieve the best outcome of the treatment and avoid recurrences at the same time. A patient specific simulation in advance that takes the cooling effect of blood vessels into account is a helpful tool for radiologists, but this needs a very high accuracy and thus high computational costs. In this work, we present various methods, which improve and extend the planning of an RF ablation procedure. First, we discuss two extensions of the simulation model to obtain a higher accuracy, including the vaporization of the water in the tissue and identifying the model parameters and to analyze their uncertainty. Furthermore, we discuss an extension of the planning procedure namely the optimization of the probe placement, which optimizes the overlap of the tumor area with the estimated coagulation in order to avoid recurrences. Since the optimization is constrained by the model, we have to take into account the uncertainties in the model parameters for the optimization as well. Finally, applications of our methods to a real RF ablation case are presented.