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. However, the possibility of recurrent liver cancer due to incomplete ablation of the tumor makes post-interventional monitoring via regular follow-up scans mandatory. These scans have to be carefully inspected for any conspicuousness. Within this study, the RF ablation zones from twelve post-interventional CT acquisitions have been segmented semi-automatically to support the visual inspection. An interactive, graph-based contouring approach, which prefers spherically shaped regions, has been applied. For the quantitative and qualitative analysis of the algorithm's results, manual slice-by-slice segmentations produced by clinical experts have been used as the gold standard (which have also been compared among each other). As evaluation metric for the statistical validation, the Dice Similarity Coefficient (DSC) has been calculated. The results show that the proposed tool provides lesion segmentation with sufficient accuracy much faster than manual segmentation. The visual feedback and interactivity make the proposed tool well suitable for the clinical workflow.
Department of Neuroscience and Biomedical Engineering, Aalto University, Rakentajanaukio 2 C, 02150 Espoo, Finland.|Institute for Computer Graphics and Vision, Faculty of Computer Science and Biomedical Engineering, Graz University of Technology, Inffeldgasse 16, 8010 Graz, Austria.|BioTechMed-Graz, Austria.
Jan
J
Egger
Department of Diagnostic and Interventional Radiology, Leipzig University Hospital, Liebigstraße 20, 04103 Leipzig, Germany.
Harald
H
Busse
Department of Diagnostic and Interventional Radiology, Leipzig University Hospital, Liebigstraße 20, 04103 Leipzig, Germany.
Philipp
P
Brandmaier
Department of Diagnostic and Interventional Radiology, Leipzig University Hospital, Liebigstraße 20, 04103 Leipzig, Germany.
Daniel
D
Seider
Department of Diagnostic and Interventional Radiology, Leipzig University Hospital, Liebigstraße 20, 04103 Leipzig, Germany.
Matthias
M
Gawlitza
Department of Diagnostic and Interventional Radiology, Leipzig University Hospital, Liebigstraße 20, 04103 Leipzig, Germany.
Steffen
S
Strocka
Institute for Computer Graphics and Vision, Faculty of Computer Science and Biomedical Engineering, Graz University of Technology, Inffeldgasse 16, 8010 Graz, Austria.
Philip
P
Voglreiter
Institute for Computer Graphics and Vision, Faculty of Computer Science and Biomedical Engineering, Graz University of Technology, Inffeldgasse 16, 8010 Graz, Austria.
Mark
M
Dokter
Institute for Computer Graphics and Vision, Faculty of Computer Science and Biomedical Engineering, Graz University of Technology, Inffeldgasse 16, 8010 Graz, Austria.
Michael
M
Hofmann
Department of Computing, Imperial College London, Huxley Building, 180 Queen's Gate, London SW7 2AZ, UK.
Bernhard
B
Kainz
Department of Internal Medicine and Gastroenterology, Katharinenhospital, Kriegsbergstraße 60, 70174 Stuttgart, Germany.
Alexander
A
Hann
Institute of Biomedical Manufacturing and Life Quality Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, Dong Chuan Road 800, Shanghai Post Code: 200240, China.
Xiaojun
X
Chen
Department of Neuroscience and Biomedical Engineering, Aalto University, Rakentajanaukio 2 C, 02150 Espoo, Finland.
Tuomas
T
Alhonnoro
Department of Neuroscience and Biomedical Engineering, Aalto University, Rakentajanaukio 2 C, 02150 Espoo, Finland.
Mika
M
Pollari
Institute for Computer Graphics and Vision, Faculty of Computer Science and Biomedical Engineering, Graz University of Technology, Inffeldgasse 16, 8010 Graz, Austria.
Dieter
D
Schmalstieg
Department of Diagnostic and Interventional Radiology, Leipzig University Hospital, Liebigstraße 20, 04103 Leipzig, Germany.
Michael
M
Moche
D000465:Algorithms; D006528:Carcinoma, Hepatocellular / Q000175:diagnosis* / Q000628:therapy*; D017115:Catheter Ablation / Q000379:methods; D006801:Humans; D007089:Image Enhancement; D008113:Liver Neoplasms / Q000175:diagnosis* / Q000628:therapy*; D012189:Retrospective Studies; D060388:Support Vector Machine; D014057:Tomography, X-Ray Computed / Q000379:methods; D016896:Treatment Outcome