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

Phosphoglycerate dehydrogenase diverts glycolytic flux and contributes to oncogenesis

Most tumors exhibit increased glucose metabolism to lactate, however, the extent to which glucose-derived metabolic fluxes are used for alternative processes is poorly understood [1, 2]. Using a metabolomics approach with isotope labeling, we found that in some cancer cells a relatively large amount of glycolytic carbon is diverted into serine and glycine metabolism through phosphoglycerate dehydrogenase (PHGDH). An analysis of human cancers showed that PHGDH is recurrently amplified in a genomic region of focal copy number gain most commonly found in melanoma. Decreasing PHGDH expression impaired proliferation in amplified cell lines. Increased expression was also associated with breast cancer subtypes, and ectopic expression of PHGDH in mammary epithelial cells disrupted acinar morphogenesis and induced other phenotypic alterations that may predispose cells to transformation. Our findings show that the diversion of glycolytic flux into a specific alternate pathway can be selected during tumor development and may contribute to the pathogenesis of human cancer.National Institutes of Health (U.S.)National Cancer Institute (U.S.)Smith Family FoundationDamon Runyon Cancer Research FoundationBurroughs Wellcome Fun

Evaluation of cardiac PET-MRI registration methods using a numerical breathing phantom

The thorax structure movements (breathing, heart motion and patient motion) during the positron emission tomography (PET) scanning cause deformations and blurring to PET scans. These artifacts are important reasons, for the mis-registration of PET volumes. In this paper, a breathing simulated PET phantom was constructed by deforming simulated (static) PET volume according to breathing model. The constructed volume was used as a ground truth in the assessment of a non-rigid registration method for cardiac MR and PET volumes. Results showed that the assessed non-rigid registration method was more accurate than a rigid registration method which was used as a reference

RFA Guardian

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.Peer reviewe

Software-based planning of ultrasound and CT-guided percutaneous radiofrequency ablation in hepatic tumors

Publisher Copyright: © 2021, The Author(s). Copyright: Copyright 2021 Elsevier B.V., All rights reserved.Objectives: Radiofrequency ablation (RFA) can be associated with local recurrences in the treatment of liver tumors. Data obtained at our center for an earlier multinational multicenter trial regarding an in-house developed simulation software were re-evaluated in order to analyze whether the software was able to predict local recurrences. Methods: Twenty-seven RFA ablations for either primary or secondary hepatic tumors were included. Colorectal liver metastases were shown in 14 patients and hepatocellular carcinoma in 13 patients. Overlap of the simulated volume and the tumor volume was automatically generated and defined as positive predictive value (PPV) and additionally visually assessed. Local recurrence during follow-up was defined as gold standard. Sensitivity and specificity were calculated using the visual assessment and gold standard. Results: Mean tumor size was 18 mm (95% CI 15–21 mm). Local recurrence occurred in 5 patients. The PPV of the simulation showed a mean of 0.89 (0.84–0.93 95% CI). After visual assessment, 9 incomplete ablations were observed, of which 4 true positives and 5 false positives for the detection of an incomplete ablation. The sensitivity and specificity were, respectively, 80% and 77% with a correct prediction in 78% of cases. No significant correlation was found between size of the tumor and PPV (Pearson Correlation 0.10; p = 0.62) or between PPV and recurrence rates (Pearson Correlation 0.28; p = 0.16). Conclusions: The simulation software shows promise in estimating the completeness of liver RFA treatment and predicting local recurrence rates, but could not be performed real-time. Future improvements in the field of registration could improve results and provide a possibility for real-time implementation.Peer reviewe