Efficient Lattice Boltzmann Solver for Patient-Specific Radiofrequency Ablation of Hepatic Tumors

Abstract

Radiofrequency ablation (RFA) is an established treatment for liver cancer when resection is not possible. Yet, its optimal delivery is challenged by the presence of large blood vessels and the time-varying thermal conductivity of biological tissue. Incomplete treatment and an increased risk of recurrence are therefore common. A tool that would enable the accurate planning of RFA is hence necessary. This manuscript describes a new method to compute the extent of ablation required based on the Lattice Boltzmann Method (LBM) and patient-specific, pre-operative images. A detailed anatomical model of the liver is obtained from volumetric images. Then a computational model of heat diffusion, cellular necrosis, and blood flow through the vessels and liver is employed to compute the extent of ablated tissue given the probe location, ablation duration and biological parameters. The model was verified against an analytical solution, showing good fidelity. We also evaluated the predictive power of the proposed framework on ten patients who underwent RFA, for whom pre- and post-operative images were available. Comparisons between the computed ablation extent and ground truth, as observed in postoperative images, were promising (DICE index: 42%, sensitivity: 67%, positive predictive value: 38%). The importance of considering liver perfusion while simulating electrical-heating ablation was also highlighted. Implemented on graphics processing units (GPU), our method simulates 1 minute of ablation in 1.14 minutes, allowing near real-time computation.

Ultrasound thermal monitoring with an external ultrasound source for customized bipolar RF ablation shapes

“…Indeed, the RFA biophysical model supports the temperature estimation for complex structures. For instance, it has been used to simulate RFA close to blood vessels [9]. Information from prior or intra-operative medical image can be used as inputs, and heterogeneous tissue structures can be taken into account in order to reconstruct SOS images more accurately.…”

“…In in vivo scenario, the reaction coefficient can be chosen to match target tissues [12,13]. This physics-based RFA simulation models the heat propagation in biological tissue using a reaction–diffusion equation, implemented using the lattice Boltzmann method (LBM) [9]. In the case of bipolar RFA, we assume the RF electrodes to be two independent sources and their temperatures are imposed as Dirichlet boundary conditions.…”

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

“…LBM has been developed for CFD and is now a well-established discretization method. Verification of the implementation has been performed through a comparison with an analytical solution and it has the advantage over FEM to be easily parallelized in GPU [4]. An isotropic Cartesian grid with 7-connectivity topology and Neumann boundary conditions at the boundaries of the liver is employed.…”

“…considered in [4,5]. 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.…”