Feasibility of X-ray Fluorescence Computed Tomography (XFCT) Imaging of Human Lung Tumors loaded with Gold Nanoparticles: A Monte Carlo Study

We present a novel Monte Carlo model of x-ray fluorescence (XRF) computed tomography (XFCT) imaging of human lung tumors loaded with gold nanoparticles (GNPs). In this model, the lung phantom derived from CT images was excited using a fan/cone beam of x-rays and the XRF/Scatter photons were detected using linear array detectors coupled with parallel-hole collimators. Whereas 1 wt. % GNP regions located at ~4-5 centimeter depths within the phantom could be detected reliably under the current conditions, it became challenging to detect such GNP regions present at deeper depths. Nevertheless, this study opened up the possibility to apply XFCT techniques for human lung cancer detection in conjunction with GNPs.