Parameter Estimation for Personalization of Liver Tumor Radiofrequency Ablation

Abstract

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).

Optimization of tissue physical parameters for accurate temperature estimation from finite-element simulation of radiofrequency ablation

“…Sample-specific tissue properties can be estimated using iterative inverse techniques (Fuentes et al, 2013; Audigier et al, 2014), which typically require a large number of computations before convergence. As a typical 3D FEM simulation of RFA requires about 1 h to complete, these methods can be computationally expensive (dos Santos et al, 2009).…”

Challenges to Validate Multi-Physics Model of Liver Tumor Radiofrequency Ablation from Pre-clinical Data

“…Future work will attempt to optimize the computation time to estimate on the fly key parameters from readily available probe measurements, to include additional cases and observations quantities (MR thermometry, for instance) in order to further improve the personalization and to reliably estimate the deformation between preand post-operative imaging for a precise validation of the necrosis extent prediction. Further refinements in the model can be added such as the advection effect of the porous circulation in the parenchyma [6].…”

“…Few authors [2,4,5] have proposed to simulate RFA on realistic subject-specific geometries extracted from images and only [6] has personalized biophysical parameters on patient data in order to minimize the discrepancy between simulated and measured necrotic (ablated) regions.…”

“…Up to now, the comparison between simulated and measured necrotic regions has been used by several authors [2,[4][5][6] as the main criteria of success in predicting the effect of RFA on abdominal tumors, for either model validation or personalization. However, the necrosis of tissue is the resultant of several combined physical phenomena, mainly the heat transfer and cell death mechanisms, meaning that a given ablated region may be explained by several combinations of parameters.…”

Progress in Fully Automated Abdominal CT Interpretation

“…Hepatic vessel analysis has been used for treatment planning, including surgery and radiofrequency ablation [27–29]. Liver volumetrics and vessel analysis are useful for liver transplantation [30].…”