Data Acquisition for Radiofrequency Ablation Simulation

One approach to treat liver tumors is local destruction of the tumor for example by radiofrequency ablation. In this intervention an electrode is placed into the tumor and dissipates radiofrequency waves, thereby heating up the surrounding area. The heated tissue coagulates and cells in this region die. The treatment is successful if all tumor cells are destroyed. A computational description for this procedure would allow a better planning, safer performance and a lower rate in local recurrence of tumors. It would therefore be highly desired, but is hard to achieve as it is both difficult to model and open research in many related areas. For building a computational model the first step is to take a close look at the procedure to understand in detail what the model has to predict. At the same time, a good understanding of the information gained from patients during the procedure is necessary to see what is available for an experimental validation of a created model. Existing gaps in verification then have to be filled with phantom or animal experimental studies. The paper gives an overview over the procedure with an emphasis on the gathered data and a conceptual evaluation of the data’s suitability for automatic processing and computational modeling.