Vasculature segmentation for radio frequency ablation of non-resectable hepatic tumors

15 March 2006 Vasculature segmentation for radio frequency ablation of non-resectable hepatic tumors

Paul F. Hemler, Evan S. McCreedy, Ruida Cheng, Brad Wood, Matthew J. McAuliffe

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Proceedings Volume 6144, Medical Imaging 2006: Image Processing; 61443K (2006) https://doi.org/10.1117/12.649990
Event: Medical Imaging, 2006, San Diego, California, United States

Abstract

In Radio Frequency Ablation (RFA) procedures, hepatic tumor tissue is heated to a temperature where necrosis is insured. Unfortunately, recent results suggest that heating tumor tissue to necrosis is complicated because nearby major blood vessels provide a cooling effect. Therefore, it is fundamentally important for physicians to perform a careful analysis of the spatial relationship of diseased tissue to larger liver blood vessels. The liver contains many of these large vessels, which affect the RFA ablation shape and size. There are many sophisticated vasculature detection and segmentation techniques reported in the literature that identify continuous vessels as the diameter changes size and it transgresses through many bifurcation levels. However, the larger blood vessels near the treatment area are the only vessels required for proper RFA treatment plan formulation and analysis. With physician guidance and interaction, our system can segment those vessels which are most likely to affect the RFA ablations. We have found that our system provides the physician with therapeutic, geometric and spatial information necessary to accurately plan treatment of tumors near large blood vessels. The segmented liver vessels near the treatment region are also necessary for computing isolevel heating profiles used to evaluate different proposed treatment configurations.

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Paul F. Hemler, Evan S. McCreedy, Ruida Cheng, Brad Wood, and Matthew J. McAuliffe "Vasculature segmentation for radio frequency ablation of non-resectable hepatic tumors", Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61443K (15 March 2006); https://doi.org/10.1117/12.649990

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KEYWORDS

Image segmentation

Liver

Blood vessels

Tumors

Digital filtering

Radiofrequency ablation

Image filtering

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