Abstract
Cryoablation, a minimally invasive technique for treating cancer, could benefit from computer support in planning, intervention and follow-up. For employing such treatment planning in daily clinical routine, individualized simulation of cryoablation needs to be sufficiently accurate and fast. This paper describes a simulation of cryoablation of human kidney permitting high-performance simulations on graphics hardware. The simulation involves partial differential equations modeling temperature evolution and phase changes in the tissue, as well as equations describing the dependence of tissue parameters on tissue temperature. A mushy region approach and a predictor-corrector time stepping scheme are utilized for discretization to achieve an efficient numerical scheme implemented on graphics hardware. The simulation is planned to be integrated in an approved medical device.
J. Georgii and T. Pätz have contributed equally to this work.
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Notes
- 1.
Note that in cryoablation, blood vessels act as “warming devices”. Nevertheless, we employ the widely used “heat sink effect” notion seen in the literature.
References
H.D. Baehr, K. Stephan, Wärme- und Stoffübertragung (Springer, Heidelberg, 2010)
R. Baissalov, G.A. Sandison, B.J. Donnelly, J.C. Saliken, J.G. McKinnon, K. Muldrew, J. C. Rewcastle, A semi-empirical treatment planning model for optimization of multiprobe cryosurgery. Phys. Med. Biol. 45(5), 1085–1098 (2000)
H.M. Cheng, D.B. Plewes, Tissue thermal conductivity by magnetic resonance thermometry and focused ultrasound heating. J. Magn. Reson. Imaging 16, 598–609 (2002)
J.H. Choi, J.C. Bischof, Review of biomaterial thermal property measurements in the cryogenic regime and their use for prediction of equilibrium and non-equilibrium freezing applications in cryobiology. Cryobiology 60(1), 52–70 (2010)
R. Courant, K.O. Friedrichs, H. Lewy, On the partial difference equations of mathematical physics. IBM J. 11(2), 215–234 (1967). https://doi.org/10.1147/rd.112.0215
G. Deshazer, D. Merck, M. Hagmann, D. Dupuy, P. Prakash, Physical modeling of microwave ablation zone clinical margin variance. Med. Phys. 43(4), 1764–1776 (2016)
G. Deshazer, P. Prakash, D. Merck, D. Haemmerich, Experimental measurement of microwave ablation heating pattern and comparison to computer simulations. Int. J. Hyperthermia 33(1), 74–82 (2017)
D.K. Filippiadis, S. Tutton, A. Mazioti, A. Kelekis, Percutaneous image-guided ablation of bone and soft tissue tumours: a review of available techniques and protective measures. Insights Imaging 5(3), 339–346 (2014)
A.A. Gage, J. Baust, Mechanisms of tissue injury in cryosurgery. Cryobiology 37(3), 171–186 (1998)
L. Gavrilă, A. Fînaru, L. Istrati, A.I. Simion, M.E. Ciocan, Influence of temperature, fat and water content on the thermal conductivity of some dairy products. Sci. Res. J. Agroaliment. Processes Technol. 11(1), 205–210 (2005)
P.A. Hasgall, F. Di Gennaro, C. Baumgartner, E. Neufeld, B. Lloyd, M.C. Gosselin, D. Payne, A. Klingenboeck, N. Kuster, IT’IS database for thermal and electromagnetic parameters of biological tissues, version 4.0 (2018)
L.J. Hayes, K.R. Diller, Implementation of phase change in numerical models of heat transfer. J. Energy Resour. Technol. 105(4), 431–435 (1983)
International Organization for Standardization, Medical devices – quality management systems – requirements for regulatory purposes (ISO Norm 13485:2016) (2016)
R. Keelan, H. Zhang, K. Shimada, Y. Rabin, Graphics processing unit-based bioheat simulation to facilitate rapid decision making associated with cryosurgery training. Technol. Cancer Res. Treat. 15(2), 377–386 (2016)
F. Liu, P. Liang, X. Yu, T. Lu, Z. Cheng, C. Lei, Z. Han, A three-dimensional visualisation preoperative treatment planning system in microwave ablation for liver cancer: a preliminary clinical application. Int. J. Hyperthermia 29(7), 671–677 (2013)
H.H. Mitchell, T.S. Hamilton, F.R. Steggerda, H.W. Bean, The chemical composition of the adult human body and its bearing on the biochemistry of growth. J. Biol. Chem. 158, 625–637 (1945)
H.H. Pennes, Analysis of tissue and arterial blood temperatures in the resting human forearm. J. Appl. Physiol. 1(2), 93–122 (1948)
Q.T. Pham, J. Willix, Thermal conductivity of fresh lamb meat, offals and fat in the range −40 to + 30∘C: measurements and correlations. J. Food Sci. 54(3), 508–515 (1989)
Y. Rabin, K. Shimada, P. Joshi, A. Sehrawat, R. Keelan, D.M. Wilfong, J.T. McCormick, A computerized tutor prototype for prostate cryotherapy: key building blocks and system evaluation. Proc. SPIE Int. Soc. Opt. Eng. 10066 (2017)
Y. Rabin, A. Shitzer, Numerical solution of the multidimensional freezing problem during cryosurgery. J. Biomech. Eng. 120(1), 32–37 (2007)
K.F. Ross, R.E. Gordon, Water in malignant tissue, measured by cell refractometry and nuclear magnetic resonance. J. Microsc. 128(1), 7–21 (1982)
M.R. Rossi, Y. Rabin, Experimental verification of numerical simulations of cryosurgery with application to computerized planning. Phys. Med. Biol. 52(15), 4553–4567 (2007)
M.R. Rossi, D. Tanaka, K. Shimada, Y. Rabin, An efficient numerical technique for bioheat simulations and its application to computerized cryosurgery planning. Comput. Methods Programs Biomed. 1(85), 41–50 (2007)
C. Rossmann, D. Haemmerich, Review of temperature dependence of thermal properties, dielectric properties, and perfusion of biological tissues at hyperthermic and ablation temperatures. Crit. Rev. Biomed. Eng. 42(6), 467–492 (2014)
Rotes Kreuz Austria, Die Zusammensetzung unseres Blutes, call: 2018/09/19. https://www.roteskreuz.at/blutspende/blut-im-detail/wissenswertes-ueber-blut/blutbestandteile/
R. Schmidt, G. Thews, Physiologie des Menschen (Springer, Berlin/Heidelberg, 1995)
C. Schumann, C. Rieder, J. Bieberstein, A. Weihusen, S. Zidowitz, J.H. Moltz, T. Preusser, State of the art in computer-assisted planning, intervention, and assessment of liver-tumor ablation. Crit. Rev. Biomed. Eng. 38(1), 31–52 (2010)
A. Sehrawat, R. Keelan, K. Shimada, D.M. Wilfong, J.T. McCormick, Y. Rabin, Simulation-based cryosurgery training: variable insertion depth planning in prostate cryosurgery. Technol. Cancer Res. Treat. 15(6), 805–814, 12 (2016)
T.-C. Shih, H.-S. Kou, W.-L. Lin, Effect of effective tissue conductivity on thermal dose distributions of living tissue with directional blood flow during thermal therapy. Int. Commun. Heat Mass Transf. 29(1), 115–126 (2002)
T. Stein, Untersuchungen zur Dosimetrie der hochfrequenzstrominduzierten interstitiellen Thermotherapie in bipolarer Technik, vol. 22 of Fortschritte in der Lasermedizin (Ecomed Verlagsgesellschaft AG & Co. KG, 2000)
J.W. Valvano, J.R. Cochran, K.R. Diller, Thermal conductivity and diffusivity of biomaterials measured with self-heated thermistors. Int. J. Thermophys. 6(3), 301–311 (1985)
A. Weihusen, F. Ritter, T. Kröger, T. Preusser, S. Zidowitz, H.-O. Peitgen, in Workflow Oriented Software Support for Image Guided Radiofrequency Ablation of Focal Liver Malignancies, ed. by K.R. Cleary, M.I. Miga, Proceedings SPIE (2007), pp. 650919–650919–9
S. Weinbaum, L.M. Jiji, A new simplified bioheat equation for the effect of blood flow on local average tissue temperature. J. Biomech. Eng. 107(2), 131–139 (1985)
S. Yılmaz, M. Özdoğan, M. Cevener, A. Ozluk, A. Kargi, F. Kendiroglu, I. Ogretmen, A. Yildiz, Use of cryoablation beyond the prostate. Insights Imaging 7(2), 223–232 (2016)
J. Zhang, G.A. Sandison, J.Y. Murthy, L.X. Xu, Numerical simulation for heat transfer in prostate cancer cryosurgery. J. Biomech. Eng. 127(2), 279–294, 09 (2004)
Acknowledgements
We acknowledge Prof. A. Mahnken for providing the dataset shown in Fig. 6. Furthermore, we thank our colleague D. Black for proofreading the manuscript. This work was partly supported by the FhG Internal Programs under Grant No. MEF 142-600369.
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Georgii, J. et al. (2020). Efficient GPU-Based Numerical Simulation of Cryoablation of the Kidney. In: Miller, K., Wittek, A., Joldes, G., Nash, M., Nielsen, P. (eds) Computational Biomechanics for Medicine. MICCAI MICCAI 2019 2018. Springer, Cham. https://doi.org/10.1007/978-3-030-42428-2_11
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