Simulations of Light Propagation and Thermal Response in Biological Tissues Accelerated by Graphics Processing Unit

In this paper we report on a prototype program for laser-tissue interaction simulation accelerated by graphics processing unit (GPU). We developed a Monte Carlo (MC) model for photon migration in arbitrary shaped turbid media which simulates the light flux inside biological tissues to solve the thermal source term in Pennes’ bioheat transfer equation (PBTE). Since both problems are highly parallelizable, we have transformed the underlying mathematical formalism into an OpenCL language code to reduce the computational time-costs. Comparing to sequential implementation, speedup of 210 was achieved in our simulation with GPU. Acceleration benefits are demonstrated separately for MC and PBTE and also for single simulation with both models. The simulation results were obtained in real-time allowing the effective usage in laser interstitial thermal therapy for thermal damage evaluation.

[1]  Chunping Zhang,et al.  Accuracy of the diffusion approximation for total time resolved reflectance from a semi-infinite turbid medium , 2003 .

[2]  Tomas Svensson,et al.  Parallel computing with graphics processing units for high-speed Monte Carlo simulation of photon migration. , 2008, Journal of biomedical optics.

[3]  Simon Brewster,et al.  Focal therapy for prostate cancer: possibilities and limitations. , 2010, European urology.

[4]  Jari P. Kaipio,et al.  Finite element model for the coupled radiative transfer equation and diffusion approximation , 2006 .

[5]  Anders Eklund,et al.  Medical image processing on the GPU - Past, present and future , 2013, Medical Image Anal..

[6]  Talieh Malekshahabi,et al.  Biological effects of low level laser therapy. , 2014, Journal of lasers in medical sciences.

[7]  Koushik Das,et al.  Numerical analysis for determination of the presence of a tumor and estimation of its size and location in a tissue. , 2013, Journal of thermal biology.

[8]  L Wang,et al.  MCML--Monte Carlo modeling of light transport in multi-layered tissues. , 1995, Computer methods and programs in biomedicine.

[9]  David A Boas,et al.  Monte Carlo simulation of photon migration in 3D turbid media accelerated by graphics processing units. , 2009, Optics express.

[10]  Carlos Rinaldi,et al.  Fundamental solutions to the bioheat equation and their application to magnetic fluid hyperthermia , 2010, International journal of hyperthermia : the official journal of European Society for Hyperthermic Oncology, North American Hyperthermia Group.

[11]  Pieter Verboven,et al.  Modeling the propagation of light in realistic tissue structures with MMC-fpf: a meshed Monte Carlo method with free phase function. , 2013, Optics express.

[12]  Antonio Fasano,et al.  On a mathematical model for laser-induced thermotherapy , 2009 .

[13]  Dragan Poljak,et al.  FETD computation of the temperature distribution induced into a human eye by a pulsed laser , 2011 .

[14]  V. Ntziachristos Going deeper than microscopy: the optical imaging frontier in biology , 2010, Nature Methods.

[15]  Ashleyj . Welch,et al.  Optical-Thermal Response of Laser-Irradiated Tissue , 1995 .

[16]  Quan Liu,et al.  Optimization in interstitial plasmonic photothermal therapy for treatment planning. , 2013, Medical physics.

[17]  J. K. Chen,et al.  Numerical Simulation of Thermal Damage to Living Biological Tissues Induced by Laser Irradiation Based on a Generalized Dual Phase Lag Model , 2012 .

[18]  Ruy Freitas Reis,et al.  3D numerical simulations on GPUs of hyperthermia with nanoparticles by a nonlinear bioheat model , 2016, J. Comput. Appl. Math..

[19]  J. D. Hazle,et al.  Computational Modeling and Real-Time Control of Patient-Specific Laser Treatment of Cancer , 2009, Annals of Biomedical Engineering.

[20]  X. X. Zhang,et al.  Effects of dynamic changes of tissue properties during laser-induced interstitial thermotherapy (LITT) , 2005, Lasers in Medical Science.