Research Papers

Hardware acceleration of a Monte Carlo simulation for photodynamic therapy treatment planning

[+] Author Affiliations
William Chun Yip Lo

University of Toronto, Department of Medical Biophysics, Rm. 8-324,610 University Avenue, Toronto, Ontario M5G 2M9 Canada

Keith Redmond, Jason Luu, Paul Chow, Jonathan Rose

University of Toronto, The Edward S. Rogers Sr. Department of Electrical and Computer Engineering, 10 King’s College Road, Toronto, Ontario M5S 3G4

Lothar Lilge

Princess Margaret Hospital, Ontario Cancer Institute, University of Toronto, Department of Medical Biophysics, Rm. 7-416,610 University Avenue, Toronto, Ontario M5G 2M9 Canada

J. Biomed. Opt. 14(1), 014019 (February 27, 2009). doi:10.1117/1.3080134
History: Received September 12, 2008; Revised December 02, 2008; Accepted December 17, 2008; Published February 27, 2009; March 17, 2009
Text Size: A A A

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 0.00001cm2 in a skin model.

Figures in this Article
© 2009 Society of Photo-Optical Instrumentation Engineers

Citation

William Chun Yip Lo ; Keith Redmond ; Jason Luu ; Paul Chow ; Jonathan Rose, et al.
"Hardware acceleration of a Monte Carlo simulation for photodynamic therapy treatment planning", J. Biomed. Opt. 14(1), 014019 (February 27, 2009). ; http://dx.doi.org/10.1117/1.3080134


Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.