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Proceedings Paper

Automated RFA planning for complete coverage of large tumors
Author(s): Karen Trovato; Sandeep Dalal; Jochen Krücker; Aradhana Venkatesan; Bradford J. Wood
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Paper Abstract

Radiofrequency ablation (RFA) is a minimally invasive procedure used for the treatment of small-to-moderate sized tumors most commonly in the liver, kidney and lung. An RFA procedure for successfully treating large or complex shape tumors may require many ablations, in a non-obvious pattern. Tumor size > 3cm predisposes to incomplete treatment [1] and potential recurrence, therefore RFA is less often successful and less often used for treating large tumors. A mental solution is the current clinical practice standard, but is a daunting task for defining the complete 3D geometrical coverage of a tumor and margin (planned target volume, PTV) with the fewest ellipsoidal ablation volumes, while also minimizing collateral damage to healthy tissue. In order to generate a repeatable and reliable result, a solution must quantify precise locations. A new interactive planning system with an automated coverage algorithm is described. The planning system allows the interventional radiologist to segment the potentially complex PTV, select an RFA needle (which determines the specific 3D ablation shape), and identify the skin entry location that defines the shape's orientation. The algorithm generates a cluster of overlapping ablations from the periphery of the PTV, filling toward the center. The cluster is first tightened toward the center to reduce the overall number of ablations and collateral damage, and then pulled toward optimal attractors to further reduce the number of ablations. For most clinical applications, computation requires less than 15 seconds. This fast ablation planning enables rapid scenario assessment, including proper probe selection, skin entry location, collateral damage and procedure duration. The plan can be executed by transferring target locations to a navigation system.

Paper Details

Date Published: 13 March 2009
PDF: 7 pages
Proc. SPIE 7261, Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling, 72610D (13 March 2009); doi: 10.1117/12.811593
Show Author Affiliations
Karen Trovato, Philips Research North America (United States)
Sandeep Dalal, Philips Research North America (United States)
Jochen Krücker, Philips Research North America (United States)
Aradhana Venkatesan, National Institutes of Health (United States)
Bradford J. Wood, National Institutes of Health (United States)


Published in SPIE Proceedings Vol. 7261:
Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling
Michael I. Miga; Kenneth H. Wong, Editor(s)

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