J. Bieberstein, C. Schumann, A. Weihusen, T. Boehler, S. Wirtz, P. Bruners, D. Schmidt, C. Trumm, M. Niethammer, G. Haras, R.-T. Hoffmann, A. Mahnken, P. Pereira, H.-O. Peitgen
Radiofrequency (RF) ablation is an image-guided minimally invasive therapy which destroys a tumor by locally
inducing electrical energy into the malignant tissue through a radiofrequency applicator. Treatment success is essentially
dependent on the accurate placement of the RF applicator. In the case of CT-guided RF ablation of liver tumors, a central
problem during monitoring is the reduced quality and information content in the peri-interventional images compared to
the images used for planning. Therefore, the question of how to effectively transfer information from the planning scan
into the peri-interventional scan in order to support the interventionalist is of high interest. Key to such an enhancement
of peri-interventional scans is an adequate registration of the pre- and peri-interventional image, which also needs to be
fast since intervention duration is still a challenge. We present an approach for the fast and automatic registration of a
high quality CT volume scan of the liver to a spiral CT scan of lower quality. Our method combines an approximate pre-registration
to compensate large displacements and a rigid registration of a liver subvolume for further refinement. The
method focuses on the position of the tumor to be ablated and the corresponding access path. Thereby, it achieves both
fast and precise results in the region of interest. A preliminary evaluation, on 37 data sets from 20 different patients,
shows that the registration is performed within a maximum of 18 seconds, while obtaining high accuracy in the relevant
region of the liver comprising tumor and the planned access path.
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.
Image guided radiofrequency (RF) ablation has taken a significant part in the clinical routine as a minimally
invasive method for the treatment of focal liver malignancies. Medical imaging is used in all parts of the clinical
workflow of an RF ablation, incorporating treatment planning, interventional targeting and result assessment.
This paper describes a software application, which has been designed to support the RF ablation workflow under
consideration of the requirements of clinical routine, such as easy user interaction and a high degree of robust and
fast automatic procedures, in order to keep the physician from spending too much time at the computer. The
application therefore provides a collection of specialized image processing and visualization methods for treatment
planning and result assessment. The algorithms are adapted to CT as well as to MR imaging. The planning
support contains semi-automatic methods for the segmentation of liver tumors and the surrounding vascular
system as well as an interactive virtual positioning of RF applicators and a concluding numerical estimation
of the achievable heat distribution. The assessment of the ablation result is supported by the segmentation
of the coagulative necrosis and an interactive registration of pre- and post-interventional image data for the
comparison of tumor and necrosis segmentation masks. An automatic quantification of surface distances is
performed to verify the embedding of the tumor area into the thermal lesion area. The visualization methods
support representations in the commonly used orthogonal 2D view as well as in 3D scenes.
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