Visualization of risk structures for interactive planning of image guided radiofrequency ablation of liver tumors

Image guided radiofrequency ablation (RFA) is becoming a standard procedure as a minimally invasive method for tumor treatment in the clinical routine. The visualization of pathological tissue and potential risk structures like vessels or important organs gives essential support in image guided pre-interventional RFA planning. In this work our aim is to present novel visualization techniques for interactive RFA planning to support the physician with spatial information of pathological structures as well as the finding of trajectories without harming vitally important tissue. Furthermore, we illustrate three-dimensional applicator models of different manufactures combined with corresponding ablation areas in homogenous tissue, as specified by the manufacturers, to enhance the estimated amount of cell destruction caused by ablation. The visualization techniques are embedded in a workflow oriented application, designed for the use in the clinical routine. To allow a high-quality volume rendering we integrated a visualization method using the fuzzy c-means algorithm. This method automatically defines a transfer function for volume visualization of vessels without the need of a segmentation mask. However, insufficient visualization results of the displayed vessels caused by low data quality can be improved using local vessel segmentation in the vicinity of the lesion. We also provide an interactive segmentation technique of liver tumors for the volumetric measurement and for the visualization of pathological tissue combined with anatomical structures. In order to support coagulation estimation with respect to the heat-sink effect of the cooling blood flow which decreases thermal ablation, a numerical simulation of the heat distribution is provided.

[1]  Luc Soler,et al.  Trajectory optimization for the planning of percutaneous radiofrequency ablation of hepatic tumors , 2007, Computer aided surgery : official journal of the International Society for Computer Aided Surgery.

[2]  Florian M Vogt,et al.  Value of CT volume imaging for optimal placement of radiofrequency ablation probes in liver lesions. , 2002, Journal of vascular and interventional radiology : JVIR.

[3]  Bradford J. Wood,et al.  Radio Frequency Ablation Registration, Segmentation, and Fusion Tool , 2006, IEEE Trans. Inf. Technol. Biomed..

[4]  Leonid Lobik,et al.  Geometry and temperature distribution during radiofrequency tissue ablation: an experimental ex vivo model. , 2005, Journal of endourology.

[5]  W. Helton,et al.  Radiofrequency ablation of primary and metastatic liver tumors: a critical review of the literature. , 2008, American journal of surgery.

[6]  Heinz-Otto Peitgen,et al.  Advanced Segmentation Techniques for Lung Nodules, Liver Metastases, and Enlarged Lymph Nodes in CT Scans , 2009, IEEE Journal of Selected Topics in Signal Processing.

[7]  Luc Soler,et al.  Radiofrequency ablation of hepatic tumors: simulation, planning, and contribution of virtual reality and haptics , 2005, Computer methods in biomechanics and biomedical engineering.

[8]  Mathew Chung,et al.  Radiofrequency ablation of 231 unresectable hepatic tumors: Indications, limitations, and complications , 2000, Annals of Surgical Oncology.

[9]  Rüdiger Westermann,et al.  Efficiently using graphics hardware in volume rendering applications , 1998, SIGGRAPH.

[10]  Guy Marchal,et al.  Experimental and Clinical Radiofrequency Ablation: Proposal for Standardized Description of Coagulation Size and Geometry , 2007, Annals of Surgical Oncology.

[11]  Markus Hadwiger,et al.  High-quality two-level volume rendering of segmented data sets on consumer graphics hardware , 2003, IEEE Visualization, 2003. VIS 2003..

[12]  Bernhard Preim,et al.  Visualization of anatomic tree structures with convolution surfaces , 2004, VISSYM'04.

[13]  Heinz-Otto Peitgen,et al.  Numerical Simulation of Radio Frequency Ablation with State Dependent Material Parameters in Three Space Dimensions , 2006, MICCAI.

[14]  Heinz-Otto Peitgen,et al.  Workflow oriented software support for image guided radiofrequency ablation of focal liver malignancies , 2007, SPIE Medical Imaging.