Lattice Boltzmann Method for Fast Patient-Specific Simulation of Liver Tumor Ablation from CT Images

Abstract

Abstract. Radio-frequency ablation (RFA), the most widely used minimally invasive ablative therapy of liver cancer, is challenged by a lack of patient-specific planning. In particular, the presence of blood vessels and time-varying thermal diffusivity makes the prediction of the extent of the ablated tissue difficult. This may result in incomplete treatments and increased risk of recurrence. We propose a new model of the physical mechanisms involved in RFA of abdominal tumors based on Lattice Boltzmann Method to predict the extent of ablation given the probe location and the biological parameters. Our method relies on patient images, from which level set representations of liver geometry, tumor shape and vessels are extracted. Then a computational model of heat diffusion, cellular necrosis and blood flow through vessels and liver is solved to estimate the extent of ablated tissue. After quantitative verifications against an analytical solution, we apply our framework to 5 patients datasets which include pre-and post-operative CT images, yielding promising correlation between predicted and actual ablation extent (mean point to mesh errors of 8.7 mm). Implemented on graphics processing units, our method may enable RFA planning in clinical settings as it leads to near real-time computation: 1 minute of ablation is simulated in 1.14 minutes, which is almost 60× faster than standard finite element method.

Parameter Estimation for Personalization of Liver Tumor Radiofrequency Ablation

“…Model Description The blood in the main vessels and in the parenchyma are combined in the generalized 3D incompressible Navier-Stokes equation for fluid flow in porous media, thus considerably easing the definition of boundary conditions between vessels and parenchyma, improving on [8]. More precisely, writing v as the blood velocity and p the pressure inside the liver, we solve:…”

“…LBM has been developed for CFD and is now a well-established discretization method. In RFA, it has been validated in [8] through a comparison with an analytical solution, for a similar accuracy as FEM. An isotropic Cartesian grid with 19-connectivity topology and Neumann boundary conditions is employed.…”

“…Most of the parameters are defined as constant whereas the heat capacity c t and conductivity dt =dt * (1+0.00161) * (T −310)W (mK) −1 are temperature dependent and therefore spatially distributed [8]. Using DAKOTA 1 , we first perform a sensitivity analysis to know which parameters mostly influence the volume and the point-to-mesh error [15] of the computed necrosis area.…”

“…Studies [3][4][5] have investigated the finite element method (FEM) to simulate the heat transfer on generic human anatomies and eventually optimize the placement of the probes [6]. Simulations with animal-specific [7] or patient-specific anatomies were also recently considered [8] with the inclusion of cooling effects computed from simulated hepatic venous flow and hepatic parenchymal flow. However, nominal tissue parameters were employed in these studies with values often based on ex vivo experiments on animal tissue sometimes with a large varying range between published studies.…”

“…Our framework is adapted to situation where no temperature map is available. We rely on the Lattice-Boltzmann Method (LBM) to compute not only heat diffusion, cellular necrosis as in [8] but also blood and parenchyma flow in the liver tissue. This latter method is based on a computational fluid Dynamics (CFD) solver which incorporates a porous part to deal with the liver parenchyma.…”