Hardware acceleration of a Monte Carlo simulation for photodynamic treatment planning

William C. Y. Lo; Keith Redmond; Jason Luu; Paul Chow; Jonathan Rose; Lothar D. Lilge

doi:10.1117/1.3080134

1 January 2009 Hardware acceleration of a Monte Carlo simulation for photodynamic treatment planning

William C. Y. Lo, Keith Redmond, Jason Luu, Paul Chow, Jonathan Rose, Lothar D. Lilge

Author Affiliations +

Journal of Biomedical Optics, Vol. 14, Issue 1, 014019 (January 2009). https://doi.org/10.1117/1.3080134

Abstract

Monte Carlo (MC) simulations are being used extensively in the field of medical biophysics, particularly for modeling light propagation in tissues. The high computation time for MC limits its use to solving only the forward solutions for a given source geometry, emission profile, and optical interaction coefficients of the tissue. However, applications such as photodynamic therapy treatment planning or image reconstruction in diffuse optical tomography require solving the inverse problem given a desired dose distribution or absorber distribution, respectively. A faster means for performing MC simulations would enable the use of MC-based models for accomplishing such tasks. To explore this possibility, a digital hardware implementation of a MC simulation based on the Monte Carlo for Multi-Layered media (MCML) software was implemented on a development platform with multiple field-programmable gate arrays (FPGAs). The hardware performed the MC simulation on average 80 times faster and was 45 times more energy efficient than the MCML software executed on a 3-GHz Intel Xeon processor. The resulting isofluence lines closely matched those produced by MCML in software, diverging by only less than 0.1 mm for fluence levels as low as 0.00001 cm^-2 in a skin model.

©(2009) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

William C. Y. Lo, Keith Redmond, Jason Luu, Paul Chow, Jonathan Rose, and Lothar D. Lilge "Hardware acceleration of a Monte Carlo simulation for photodynamic treatment planning," Journal of Biomedical Optics 14(1), 014019 (1 January 2009). https://doi.org/10.1117/1.3080134

Published: 1 January 2009

ACCESS THE FULL ARTICLE

JOURNAL ARTICLE
11 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY