Monte Carlo Modeling of Shortwave-Infrared Fluorescence Photon Migration in Voxelized Media for the Detection of Breast Cancer

Abstract

Recent progress regarding shortwave-infrared (SWIR) molecular imaging technology has inspired another modality of noninvasive diagnosis for early breast cancer detection in which previous mammography or sonography would be compensated. Although a SWIR fluorescence image of a small breast cancer of several millimeters was obtained from experiments with small animals, detailed numerical analyses before clinical application were required, since various parameters such as size as well as body hair differed between humans and small experimental animals. In this study, the feasibility of SWIR was compared against visible (VIS) and near-infrared (NIR) region, using the Monte Carlo simulation in voxelized media. In this model, due to the implementation of the excitation gradient, fluorescence is based on rational mechanisms, whereas fluorescence within breast cancer is spatially proportional to excitation intensity. The fluence map of SWIR simulation with excitation gradient indicated signals near the upper surface of the cancer, and stronger than those of the NIR. Furthermore, there was a dependency on the fluence signal distribution on the contour of the breast tissue, as well as the internal structure, due to the implementation of digital anatomical data for the Visible Human Project. The fluorescence signal was observed to become weaker in all regions including the VIS, the NIR, and the SWIR region, when fluorescence-labeled cancer either became smaller or was embedded in a deeper area. However, fluorescence in SWIR alone from a cancer of 4 mm diameter was judged to be detectable at a depth of 1.4 cm.