@inproceedings{8bb3c2d217c24db28daac67cce67038d,
title = "Parameter estimation for personalization of liver tumor radiofrequency ablation",
abstract = "Mathematical modeling has the potential to assist radiofrequency ablation (RFA) of tumors as it enables prediction of the extent of ablation. However, the accuracy of the simulation is challenged by the material properties since they are patient-specific, temperature and space dependent. In this paper, we present a framework for patientspecific radiofrequency ablation modeling of multiple lesions in the case of metastatic diseases. The proposed forward model is based upon a computational model of heat diffusion, cellular necrosis and blood flow through vessels and liver which relies on patient images. We estimate the most sensitive material parameters, those need to be personalized from the available clinical imaging and data. The selected parameters are then estimated using inverse modeling such that the point-to-mesh distance between the computed necrotic area and observed lesions is minimized. Based on the personalized parameters, the ablation of the remaining lesions are predicted. The framework is applied to a dataset of seven lesions from three patients including pre- and post-operative CT images. In each case, the parameters were estimated on one tumor and RFA is simulated on the other tumor(s) using these personalized parameters, assuming the parameters to be spatially invariant within the same patient. Results showed significantly good correlation between predicted and actual ablation extent (average point-to-mesh errors of 4.03 mm).",
keywords = "Heat diffusion, Inverse modeling, Liver, Radiofrequency ablation",
author = "Chlo{\`e} Audigier and Tommaso Mansi and Herv{\`e} Delingette and Saikiran Rapaka and Viorel Mihalef and Daniel Carnegie and Emad Boctor and Michael Choti and Ali Kamen and Dorin Comaniciu and Nicholas Ayache",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2014.; 6th International Workshop on Abdominal Imaging: Computational and Clinical Applications, ABDI 2014 held in conjunction with 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 ; Conference date: 14-09-2014 Through 14-09-2014",
year = "2014",
doi = "10.1007/978-3-319-13692-9_1",
language = "English (US)",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "3--12",
editor = "Hiroyuki Yoshida and N{\"a}ppi, {Janne J.} and Sanjay Saini",
booktitle = "Abdominal Imaging",
}