An empirical approach to estimate near-infra-red photon propagation and optically induced drug release in brain tissues

Akshay Prabhu Verleker; Qianqian Fang; Mi-Ran Choi; Susan Clare; Keith M. Stantz

doi:10.1117/12.2079991

2 March 2015 An empirical approach to estimate near-infra-red photon propagation and optically induced drug release in brain tissues

Akshay Prabhu Verleker, Qianqian Fang, Mi-Ran Choi, Susan Clare, Keith M. Stantz

Author Affiliations +

Proceedings Volume 9308, Optical Methods for Tumor Treatment and Detection: Mechanisms and Techniques in Photodynamic Therapy XXIV; 93080T (2015) https://doi.org/10.1117/12.2079991
Event: SPIE BiOS, 2015, San Francisco, California, United States

Abstract

The purpose of this study is to develop an alternate empirical approach to estimate near-infra-red (NIR) photon propagation and quantify optically induced drug release in brain metastasis, without relying on computationally expensive Monte Carlo techniques (gold standard). Targeted drug delivery with optically induced drug release is a noninvasive means to treat cancers and metastasis. This study is part of a larger project to treat brain metastasis by delivering lapatinib-drug-nanocomplexes and activating NIR-induced drug release. The empirical model was developed using a weighted approach to estimate photon scattering in tissues and calibrated using a GPU based 3D Monte Carlo. The empirical model was developed and tested against Monte Carlo in optical brain phantoms for pencil beams (width 1mm) and broad beams (width 10mm). The empirical algorithm was tested against the Monte Carlo for different albedos along with diffusion equation and in simulated brain phantoms resembling white-matter (μ_s’=8.25mm^-1, μ_a=0.005mm^-1) and gray-matter (μ_s’=2.45mm^-1, μ_a=0.035mm^-1) at wavelength 800nm. The goodness of fit between the two models was determined using coefficient of determination (R-squared analysis). Preliminary results show the Empirical algorithm matches Monte Carlo simulated fluence over a wide range of albedo (0.7 to 0.99), while the diffusion equation fails for lower albedo. The photon fluence generated by empirical code matched the Monte Carlo in homogeneous phantoms (R²=0.99). While GPU based Monte Carlo achieved 300X acceleration compared to earlier CPU based models, the empirical code is 700X faster than the Monte Carlo for a typical super-Gaussian laser beam.

Citation Download Citation

Akshay Prabhu Verleker, Qianqian Fang, Mi-Ran Choi, Susan Clare, and Keith M. Stantz "An empirical approach to estimate near-infra-red photon propagation and optically induced drug release in brain tissues", Proc. SPIE 9308, Optical Methods for Tumor Treatment and Detection: Mechanisms and Techniques in Photodynamic Therapy XXIV, 93080T (2 March 2015); https://doi.org/10.1117/12.2079991

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available