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

Philip Voglreiter, Panchatcharam Mariappan, Mika Pollari, Ronan Flanagan, Roberto Blanco Sequeiros, Rupert Horst Portugaller, Jurgen Fütterer, Dieter Schmalstieg, Marina Kolesnik, Michael Moche
2018 Scientific Reports  
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
more » ... 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. Radiofrequency ablation (RFA) of liver malignancies has become an important alternative therapy for patients who disqualify for standard surgical treatment or are in an early tumor stage 1,2 . When surgical resection is not feasible, RFA is the preferred treatment option for small liver tumors 1,2 . Moreover, patient recovery after surgical resection takes longer and post-procedural quality of life is lower than after RFA 2 . While many more options for local cancer treatment exist (e.g. Cryo Ablation 3 , Irreversible Electroporation 4 or hyperthermia in conjunction with other treatment methods 5,6 ), the clincial routine prefers RFA (or, occasionally, microwave ablation) treatment for smaller liver tumors. Although microwave ablation has become more prevalent in the past years, no statistically significant difference in survival rates compared to RFA of smaller lesions (diameter below 3.5 cm) in the liver could be found 7,8 . In RFA, interventional radiologists (IR) destroy malignant cells using percutaneous probes that induce heating in a locally delimited region around a tumor. Successful treatment is defined as complete ablation of the tumor with a safety margin of destroyed healthy tissue in its immediate vicinity. However, clinical experience with RFA indicates a significant mismatch between expected and observed lesion size, leading to reduced survival rates due to over-treatment with severe injuries (up to 9%) or under-treatment with tumor recurrence 9 (up to 40%). Further, Hildebrand et al. 10 have shown that the survival rates after 1 and 2 years significantly depend on the experience of the IR: Operating experience of 0-2 years resulted in 69%/46% (1/2 years) survival, while rates of 3-4 years experience corresponded to 92%/89%, respectively. Further, Published: xx xx xxxx OPEN www.nature.com/scientificreports/
doi:10.1038/s41598-017-18899-2 pmid:29335429 pmcid:PMC5768804 fatcat:heftmcc42jhgbprnstzwvbb4ae

Validation of a Web-Based Planning Tool for Percutaneous Cryoablation of Renal Tumors

Tim J van Oostenbrugge, Jan Heidkamp, Michael Moche, Phil Weir, Panchatcharam Mariappan, Ronan Flanigan, Mika Pollari, Stephen Payne, Marina Kolesnik, Sjoerd F M Jenniskens, Jurgen J Fütterer
2020 Cardiovascular and Interventional Radiology  
To validate a simulation environment for virtual planning of percutaneous cryoablation of renal tumors. Prospectively collected data from 19 MR-guided procedures were used for validation of the simulation model. Volumetric overlap of the simulated ablation zone volume (Σ) and the segmented ablation zone volume (S; assessed on 1-month follow-up scan) was quantified. Validation metrics were DICE Similarity Coefficient (DSC; the ratio between twice the overlapping volume of both ablation zones
more » ... ded by the sum of both ablation zone volumes), target overlap (the ratio between the overlapping volume of both ablation zones to the volume of S; low ratio means S is underestimated), and positive predictive value (the ratio between the overlapping volume of both ablation zones to the volume of Σ; low ratio means S is overestimated). Values were between 0 (no alignment) and 1 (perfect alignment), a value > 0.7 is considered good. Mean volumes of S and Σ were 14.8 cm3 (± 9.9) and 26.7 cm3 (± 15.0), respectively. Mean DSC value was 0.63 (± 0.2), and ≥ 0.7 in 9 cases (47%). Mean target overlap and positive predictive value were 0.88 (± 0.11) and 0.53 (± 0.24), respectively. In 17 cases (89%), target overlap was ≥ 0.7; positive predictive value was ≥ 0.7 in 4 cases (21%) and < 0.6 in 13 cases (68%). This indicates S is overestimated in the majority of cases. The validation results showed a tendency of the simulation model to overestimate the ablation effect. Model adjustments are necessary to make it suitable for clinical use.
doi:10.1007/s00270-020-02634-y pmid:32935141 pmcid:PMC7591419 fatcat:eeimyej5tncgzpugfavagpu4g4

Go-Smart: Open-Ended, Web-Based Modelling of Minimally Invasive Cancer Treatments via a Clinical Domain Approach [article]

Phil Weir, Roland Ellerweg, Stephen Payne, Dominic Reuter, Tuomas Alhonnoro, Philip Voglreiter, Panchatcharam Mariappan, Mika Pollari, Chang Sub Park, Peter Voigt, Tim van Oostenbrugge, Sebastian Fischer (+6 others)
2018 arXiv   pre-print
Clinicians benefit from online treatment planning systems, through off-site accessibility, data sharing and professional interaction. As well as enhancing clinical value, incorporation of simulation tools affords innovative avenues for open-ended, multi-disciplinary research collaboration. An extensible system for clinicians, technicians, manufacturers and researchers to build on a simulation framework is presented. This is achieved using a domain model that relates entities from theoretical,
more » ... gineering and clinical domains, allowing algorithmic generation of simulation configuration for several open source solvers. The platform is applied to Minimally Invasive Cancer Treatments (MICTs), allowing interventional radiologists to upload patient data, segment patient images and validate simulated treatments of radiofrequency ablation, cryoablation, microwave ablation and irreversible electroporation. A traditional radiology software layout is provided in-browser for clinical use, with simple, guided simulation, primarily for training and research. Developers and manufacturers access a web-based system to manage their own simulation components (equipment, numerical models and clinical protocols) and related parameters. This system is tested by interventional radiologists at four centres, using pseudonymized patient data, as part of the Go-Smart Project (http://gosmart-project.eu). The simulation technology is released as a set of open source components http://github.com/go-smart.
arXiv:1803.09166v1 fatcat:ezrpgz6kffgbvkivmukmhnzb2m

Go-Smart: Web-based Computational Modeling of Minimally Invasive Cancer Treatments [article]

Phil Weir, Dominic Reuter, Roland Ellerweg, Tuomas Alhonnoro, Mika Pollari, Philip Voglreiter, Panchatcharam Mariappan, Ronan Flanagan, Chang Sub Park, Stephen Payne, Elmar Staerk, Peter Voigt (+2 others)
2015 arXiv   pre-print
The web-based Go-Smart environment is a scalable system that allows the prediction of minimally invasive cancer treatment. Interventional radiologists create a patient-specific 3D model by semi-automatic segmentation and registration of pre-interventional CT (Computed Tomography) and/or MRI (Magnetic Resonance Imaging) images in a 2D/3D browser environment. This model is used to compare patient-specific treatment plans and device performance via built-in simulation tools. Go-Smart includes
more » ... ation techniques for comparing simulated treatment with real ablation lesions segmented from follow-up scans. The framework is highly extensible, allowing manufacturers and researchers to incorporate new ablation devices, mathematical models and physical parameters.
arXiv:1511.03418v1 fatcat:jm34u6anjrcybchkcpvk4q4kqq

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)

Martin Reinhardt, Philipp Brandmaier, Daniel Seider, Marina Kolesnik, Sjoerd Jenniskens, Roberto Blanco Sequeiros, Martin Eibisberger, Philip Voglreiter, Ronan Flanagan, Panchatcharam Mariappan, Harald Busse, Michael Moche
2017 Contemporary Clinical Trials Communications  
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
more » ... 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. (resection or transplant) can be curative, but is not always suitable especially for older patients with existing comorbid conditions, e.g. liver cirrhosis [2] . Therefore adequate patient selection is of paramount importance [3, 4] . Radiofrequency ablation (RFA) has become the first treatment choice for early-stage HCC in cirrhotic livers [5] . Also, for http://dx.
doi:10.1016/j.conctc.2017.08.004 pmid:29696193 pmcid:PMC5898513 fatcat:lu2vepbrpjhhrdxhvcjioymjd4