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RFA Guardian: Comprehensive Simulation of Radiofrequency Ablation Treatment of Liver Tumors
2018
Scientific Reports
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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
doi:10.1038/s41598-017-18899-2
pmid:29335429
pmcid:PMC5768804
fatcat:heftmcc42jhgbprnstzwvbb4ae
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... 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/
Validation of a Web-Based Planning Tool for Percutaneous Cryoablation of Renal Tumors
2020
Cardiovascular and Interventional Radiology
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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
doi:10.1007/s00270-020-02634-y
pmid:32935141
pmcid:PMC7591419
fatcat:eeimyej5tncgzpugfavagpu4g4
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... 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.
Go-Smart: Open-Ended, Web-Based Modelling of Minimally Invasive Cancer Treatments via a Clinical Domain Approach
[article]
2018
arXiv
pre-print
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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,
arXiv:1803.09166v1
fatcat:ezrpgz6kffgbvkivmukmhnzb2m
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... 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.
Go-Smart: Web-based Computational Modeling of Minimally Invasive Cancer Treatments
[article]
2015
arXiv
pre-print
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Other Versions
2015
2015 E-Health and Bioengineering Conference (EHB)
unpublished
doi:10.1109/ehb.2015.7391385 fatcat:t6xrugnhcrcn7lwsugb3nbhrza
doi:10.1109/ehb.2015.7391385 fatcat:t6xrugnhcrcn7lwsugb3nbhrza
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
arXiv:1511.03418v1
fatcat:jm34u6anjrcybchkcpvk4q4kqq
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... 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.
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)
2017
Contemporary Clinical Trials Communications
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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
doi:10.1016/j.conctc.2017.08.004
pmid:29696193
pmcid:PMC5898513
fatcat:lu2vepbrpjhhrdxhvcjioymjd4