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.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
El-Serag, H.B., Davila, J.A., Petersen, N.J., McGlynn, K.A.: The continuing increase in the incidence of hepatocellular carcinoma in the united states: An update. Ann. Intern. Med. 139, 817–823 (2003)
Chen, X., Saidel, G.M.: Mathematical modeling of thermal ablation in tissue surrounding a large vessel. J. Biomech. 131 (2009)
Jiang, Y., Mulier, S., Chong, W., Diel Rambo, M., Chen, F., Marchal, G., Ni, Y.: Formulation of 3D finite elements for hepatic radiofrequency ablation. IJMIC 9, 225–235 (2010)
Kröger, T., Pätz, T., Altrogge, I., Schenk, A., Lehmann, K., Frericks, B., Ritz, J., Peitgen, H., Preusser, T.: Fast estimation of the vascular cooling in RFA based on numerical simulation. Open Biomed. Eng. J. 4, 16–26 (2010)
O’Neill, D., Peng, T., Stiegler, P., Mayrhauser, U., Koestenbauer, S., Tscheliessnigg, K., Payne, S.: A three-state mathematical model of hyperthermic cell death. Ann. Biomed. Eng. 39, 570–579 (2011)
Rapaka, S., Mansi, T., Georgescu, B., Pop, M., Wright, G.A., Kamen, A., Comaniciu, D.: LBM-EP: Lattice-boltzmann method for fast cardiac electrophysiology simulation from 3D images. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds.) MICCAI 2012, Part II. LNCS, vol. 7511, pp. 33–40. Springer, Heidelberg (2012)
Pennes, H.H.: Analysis of tissue and arterial blood temperatures in the resting human forearm. J. Appl. Physiol. 85, 5–34 (1998)
Klinger, H.: Heat transfer in perfused biological tissue I: General theory. B. Math. Biol. 36, 403–415 (1974)
Payne, S., Flanagan, R., Pollari, M., Alhonnoro, T., Bost, C., O’Neill, D., Peng, T., Stiegler, P.: Image-based multi-scale modelling and validation of radio-frequency ablation in liver tumours. Philos. T. Roy. Soc. A. 369, 4233–4254 (2011)
Grady, L.: Random walks for image segmentation. IEEE T. Pattern Anal. Mach. Intell. 28, 1768–1783 (2006)
Ralovich, K., et al.: Hemodynamic assessment of pre- and post-operative aortic coarctation from MRI. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds.) MICCAI 2012, Part II. LNCS, vol. 7511, pp. 486–493. Springer, Heidelberg (2012)
Schenk Jr., W.G., McDonald, J.C., McDonald, K., Drapanas, T.: Direct measurement of hepatic blood flow in surgical patients: with related observations on hepatic flow dynamics in experimental animals. Ann. Surg. 156, 463–469 (1962)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Audigier, C. et al. (2013). Lattice Boltzmann Method for Fast Patient-Specific Simulation of Liver Tumor Ablation from CT Images. In: Mori, K., Sakuma, I., Sato, Y., Barillot, C., Navab, N. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013. MICCAI 2013. Lecture Notes in Computer Science, vol 8151. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40760-4_41
Download citation
DOI: https://doi.org/10.1007/978-3-642-40760-4_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40759-8
Online ISBN: 978-3-642-40760-4
eBook Packages: Computer ScienceComputer Science (R0)