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In-depth Multicenter Workflow Analysis of Liver Tumor Ablations for the Development of a Novel Computer-aided Software Tool

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Radiofrequency ablation (RFA) is a percutaneous procedure for cancer treatment, which belongs to the minimally invasive and image-guided techniques. Cancer cells are heated up and destroyed by focusing energy in the RF spectrum through a needle. Thus, needle placement and the right amount of energy play the crucial roles for a therapeutic success. However, there is no standardized practice for needle guidance, which can depend on the equipment, or personal preferences (like 2D/3D Ultrasound (US) or CT-guidance). The aim was to assess the clinical feasibility of a common multicenter workflow of thermally induced liver lesions for the development of a novel computer-aided RFA software tool.
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In-depth Multicenter Workflow Analysis of Liver Tumor Ablations for
the Development of a Novel Computer-aided Software Tool
J. Egger a,b, P. Voglreiter a, M. Dokter a. M. Hofmann a, H. F. Busse c, D. Seider c, P. Brandmaier c
R. Rautio d, G. Zettel e, B. Schmerböck e, M. van Amerongen f, S. Jenniskens f, M. Kolesnik g
B. Kainz h, R. B. Sequeiros i, H. Portugaller j, P. Stiegler e, J. Futterer f, D. Schmalstieg a
M. Moche c
a Institute for Computer Graphics and Vision, Graz University of Technology, Austria.
b BioTechMed-Graz, Austria.
c Department of Diagnostic and Interventional Radiology, Leipzig University Hospital, Germany.
d Department of Radiology, Turku University Hospital, Turku, Finland.
e Department of Surgery, Division of Transplantation Surgery, Medical University of Graz, Austria.
f Department of Radiology, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands.
g Institute for Applied Information Technology, Fraunhofer Ges., Schloss Birlinghoven, Sankt Augustin, Germany.
h Division of Imaging Sciences and Biomedical Engineering, King's College, London, UK.
i South Western Finland Imaging Centre, Turku University Hospital, Turku, Finland.
j Department of Radiology, Medical University of Graz, Austria.
BACKGROUND
Radiofrequency ablation (RFA) is a percutaneous procedure for cancer treatment, which belongs to the
minimally invasive and image-guided techniques. Cancer cells are heated up and destroyed by focusing
energy in the RF spectrum through a needle. Thus, needle placement and the right amount of energy
play the crucial roles for a therapeutic success. However, there is no standardized practice for needle
guidance, which can depend on the equipment, or personal preferences (like 2D/3D Ultrasound (US) or
CT-guidance). The aim was to assess the clinical feasibility of a common multicenter workflow of
thermally induced liver lesions for the development of a novel computer-aided RFA software tool.
EVALUATION
RFAs of primary liver tumors where observed at four different clinical centers around Europe and
discussed between medical and technical partners. As primary imaging modalities, CT scanners from the
major manufactures (GE, Philips, Siemens and Toshiba) have been used. For needle placement, several
navigation techniques were applied: CT-guidance, 2D US guidance, CT-US fusion; although the final
needle position was always confirmed by a CT scan. Thus, a heat simulation can be used to prepare
patient-specific ablation protocols, especially for cases where other organs like the diaphragm are close
by. In addition, a study among 269 patients showed that the safety margin around the ablated tumor is
the only independent factor that influenced tumor recurrence. Thus, we developed a bivariate
visualization and a levels-of-detail-based distance algorithm supporting radiologists in both: RFA planning
and monitoring. The algorithm has been evaluated by 13 interventional radiologists within multiple tasks
of an official approved Visual Saliency study, showing a significant improvement of 42% (3.8±0.8 vs
5.4±0.4).
DISCUSSION
Needle placement and RF simulation are crucial factors for a complete and successful ablation of liver
tumors, which can be assisted by a software tool that results from studying the interventions of several
experts.
CONCLUSION
Reliable computer-aided support of the complex procedure of liver RFAs by study multicenter workflows
to lay the foundation for a novel software tool.
REFERENCES
[1] H. F. Busse, et al. Novel Semiautomatic Real-time CT Segmentation Tool and Preliminary Clinical
Evaluation on Thermally Induced Lesions in the Liver, 100th Annual Meeting of The Radiological
Society of North America (RSNA), PHS 171, December 2014.
[2] J. Egger, et al. RFA-Cut: Semi-automatic Segmentation of Radiofrequency Ablation Zones with and
without Needles via Optimal s-t-Cuts. 37th Annual International Conference of the IEEE Engineering
in Medicine and Biology Society, Milan, Italy, IEEE Press, Aug. 2015.
[3] J. Egger, et al. Semi-automatic Segmentation of Ablation zones in post-interventional CT Data.
Proceedings of Bildverarbeitung für die Medizin (BVM), Springer Press, pp. 281-286, 2015.
[4] J. Egger, et al. Interactive Volumetry of Liver Ablation Zones. Sci. Rep. 5, 15373, October 2015.
[5] J. Egger. Refinement-Cut: User-Guided Segmentation Algorithm for Translational Science. Sci. Rep.
4, 5164, June 2014.
[6] J. Egger, et al. Nugget-Cut: A Segmentation Scheme for Spherically- and Elliptically-Shaped 3D
Objects. 32nd Annual Symposium of the German Association for Pattern Recognition (DAGM), LNCS
6376, pp. 383-392, Springer Press, Darmstadt, Germany, Sep. 2010.
[7] J. Egger, et al. Template-Cut: A Pattern-Based Segmentation Paradigm. Sci. Rep., 2, 420, May 2012.
[8] J. Egger, et al. Interactive-Cut: Real-Time Feedback Segmentation for Translational Research.
Comput Med Imaging Graph. 38(4):285-95, June 2014.
[9] J. Egger, et al. A medical software system for volumetric analysis of cerebral pathologies in
magnetic resonance imaging (MRI) data. J Med Syst. 2012 Aug; 36(4):2097-109.
[10] J. Egger, et al. A Software System for Stent Planning, Stent Simulation and Follow-Up Examinations
in the Vascular Domain. 22nd IEEE International Symposium on Computer-Based Medical Systems,
Albuquerque, New Mexico, USA, IEEE Press, ACM/SIGAPP, pp. 1-7, Aug. 2009.
ACKNOWLEDGMENTS
This work received funding from two European Union projects in FP7:
Clinical Intervention Modelling, Planning and Proof for Ablation Cancer Treatment (ClinicIMPPACT)
Grant agreement no. 610886
http://www.clinicimppact.eu
Generic Open-end Simulation Environment for Minimally Invasive Cancer Treatment (GoSmart)
Grant agreement no. 600641
http://www.gosmart-project.eu
Dr. Dr. Jan Egger receives funding from BioTechMed-Graz (“Hardware accelerated intelligent medical
imaging”).
CITE THIS ABSTRACT
Egger,J, Voglreiter,P, Dokter,M, Hofmann,M, Busse,H, Seider,D, Brandmaier,P, Rautio,R, Zettel,G, Schmerböck,B, van
Amerongen,M, Jenniskens,S, Kolesnik,M, Kainz,B, Sequeiros,R, Portugaller,H, Stiegler,P, Futterer,J, Schmalstieg,D, Moche,M, In-
depth Multicenter Workflow Analysis of Liver Tumor Ablations for the Development of a Novel Computer-aided Software Tool.
Radiological Society of North America 2015 Scientific Assembly and Annual Meeting, November 29 - December 4, 2015, IN243-
SD-WEA4, Chicago IL.
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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.
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Jan Egger receives funding from BioTechMed-Graz ( " Hardware accelerated intelligent medical imaging " )
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Dr. Dr. Jan Egger receives funding from BioTechMed-Graz ( " Hardware accelerated intelligent medical imaging " ).