Date of Award


Degree Type


Degree Name

Doctor of Philosophy (PhD)


Health Sciences

First Advisor

Keith Stantz

Committee Chair

Keith Stantz

Committee Member 1

Ulrike Dydak

Committee Member 2

David Hofeldt

Committee Member 3

Shuang Liu

Committee Member 4

James Schweitzer


Purpose: The long-term goal of this research is to determine the feasibility of using near infra-red light to stimulate drug release in metastatic lesions within the brain. In this work, we focused on developing the tools needed to quantify and verify photon fluence distribution in biological tissue. To accomplish this task, an optical dosimetry probe and Monte Carlo based simulation code were fabricated, calibrated and developed to predict light transport in heterogeneous tissue phantoms of the skull and brain. Empirical model (EM) of photon transport using CT images as input were devised to provide real-time calculations capable of being translated to preclinical and clinical applications.

Methods and Materials: A GPU based 3D Monte Carlo code was customized to simulate the photon transport within head phantoms consisting of skull bone, white and gray matter with differing laser beam properties, including flat, Gaussian, and super-Gaussian profiles that are converging, parallel, or diverging. From these simulations, the local photon fluence and tissue dosimetric distribution was simulated and validated through the implementation of a novel titanium-based optical dosimetry probe with an isotropic acceptance and 1.5mm diameter. Empirical models (EM) of photon transport were devised and calibrated to MC simulated data to provide 3D fluence and optical dosimetric maps in real-time developed around on a voxel-based convolution technique. Optical transmission studies were performed using human skull bone samples to determine the optical transmission characteristics of heterogeneous bone structures and the effectiveness of the Monte Carlo in simulating this heterogeneity. These tools provide the capability to develop and optimize treatment plans for optimal release of pharmaceuticals to metastatic breast cancer in the brain.

Results: At the time of these experiments, the voxel-based CUDA MC code implemented and further developed in this study had not been validated by measurement. A novel optical dosimetry probe was fabricated and calibrated to measure the absolute photon fluence (mW/mm2) in phantoms resembling white matter, gray matter and skull bone and compared to 3D Monte Carlo simulated data. The TiO2-based dosimetry probe was shown to have superior linearity and isotropicity of response to previous Nylon based probes, and was better suited to validate the Monte Carlo using localized 3D measurement (< 25% systematic error for white matter, gray matter and skull bone phantoms along illumination beam axis up to a depth of 2cm in homogeneous tissue and 3.8cm in heterogeneous head phantom). Next, the transport parameters of the empirical algorithm was calibrated using the 3D Monte Carlo and EMs and validated by optical dosimetry probe measurements (with error of 10.1% for White Matter, 45.1% for Gray Matter and 22.1% for Skull Bone phantoms) along illumination beam axis.

Conclusions: The design and validation of the Monte Carlo, the optical dosimetry probe and the Empirical algorithm increases the clinical feasibility of optical therapeutic planning to narrow down the complex possibilities of illumination conditions, further compounded by the heterogeneous structure of the brain, such as varying skull thicknesses and densities. Our ultimate goal is to design a fast Monte Carlo based optical therapeutic protocol to treat brain metastasis. The voxelated nature of the MC and EM provides the necessary 3D photon distribution to within 25% error to guide future clinical studies involving optically triggered drug release.