Monte Carlo Modeling of Near-infrared Fluorescence Photon Migration in Breast Tissue for Tumor Prediction

Monte Carlo Modeling of Near-infrared Fluorescence Photon Migration in Breast Tissue for Tumor Prediction

Tatsuto Iida, Takashi Jin, Yasutomo Nomura
Vol. 9 (2020) p.100-105

Breast cancer is one of the most common types of cancer in Japanese women. To address the low spatial resolution challenges associated with mammography and ultrasonography, we focused on the potential of using fluorescence to observe cellular and subcellular structures. Light scattering in living tissue causes a decrease in resolution in in vivo imaging. However, scattering in near-infrared region is weaker than that in the visible region. Therefore, it is essential to investigate the behavior of excitation and emission photons in near-infrared fluorescence within tissues, which could be applied in the detection of breast cancer. We modified our previous multi-layered fluorescence Monte Carlo model of in vivo neuroimaging using quantum dots as the first step for the detection of early-stage breast tumor using both visible and near-infrared light, and developed a model containing skin, breast tissue, and tumor. In the present study, fluorophore concentration and quantum yield parameters were set appropriately based on the mechanism of fluorescence onset. When the depths and sizes of a fluorescent tumor embedded in the breast tissue model were varied, excitation and emission fluence, in addition to intensity were examined from the breast surface. In contrast to visible fluorescence (Ex 488/Em 520), Monte Carlo simulation for breast cancer using near-infrared fluorescence (Ex 780/Em 820) could be used to detect a tumor 1.0 cm in diameter at a depth of 1.0 cm.

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