Clinical evaluation of in silico planning and real-time simulation of hepatic radiofrequency ablation (ClinicIMPPACT Trial).

Objectives: To evaluate the accuracy and clinical integrability of a comprehensive simulation tool to plan and predict radiofrequency ablation (RFA) zones in liver tumors.

Methods: Forty-five patients with 51 malignant hepatic lesions of different origins were included in a prospective multicenter trial. Prior to CT-guided RFA, all patients underwent multiphase CT which included acquisitions for the assessment of liver perfusion.

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.

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.

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.

RFA-cut: Semi-automatic segmentation of radiofrequency ablation zones with and without needles via optimal s-t-cuts.

In this contribution, we present a semi-automatic segmentation algorithm for radiofrequency ablation (RFA) zones via optimal s-t-cuts. Our interactive graph-based approach builds upon a polyhedron to construct the graph and was specifically designed for computed tomography (CT) acquisitions from patients that had RFA treatments of Hepatocellular Carcinomas (HCC). For evaluation, we used twelve post-interventional CT datasets from the clinical routine and as evaluation metric we utilized the Dice Similarity Coefficient (DSC), which is commonly accepted for judging computer aided medical segmentation tasks.

Interactive Volumetry Of Liver Ablation Zones.

Percutaneous radiofrequency ablation (RFA) is a minimally invasive technique that destroys cancer cells by heat. The heat results from focusing energy in the radiofrequency spectrum through a needle. Amongst others, this can enable the treatment of patients who are not eligible for an open surgery.