The purpose of this study is to define a simplified method to accurately predict and characterize kV cone beam computed tomography (kV CBCT) and computed tomography (CT) image contrast enhancement from gold nanoparticles (GNPs). Parameters of the kV CBCT of a Varian Novalis Tx linear accelerator and of a GE LightSpeed 4 Big Bore CT machine were modeled using the MCNP 6.2 Monte Carlo code. A 0.25 × 0.25 cm2 source, defined with a 100 kVp energy spectrum with appropriate filtration, was implemented in the MCNP6.2 model for kV CBCT, which also contained x- A nd y-blades and a full bowtie filter. A 1 cm3 cube of GNP solution (modeled as a mass percentage of gold in water) was placed 100 cm below the source. For the CT-simulator model, a source was defined with energy spectra for 80 and 140 kVp X-rays with appropriate filtration and angular spectrum. A 1 cm3 GNP solution was modeled as before and a detector was placed 40 cm below that. Attenuation coefficients of four GNP solutions were computed and Hounsfield unit (HU) values were calculated. The computed HU values were compared against experimentally measured values obtained by scanning batches of GNPs of various sizes and concentrations using a GE LightSpeed 4 Big Bore CT scanner at 80 kVp and 140 kVp energies, as well as the kV CBCT capability of a Varian Novalis Tx linear accelerator. HU analysis was carried out using Velocity Medical Solutions clinical CT image analysis software. The MCNP calculated HU values matched the measured values to within ± 5%. Image contrast enhancement analysis showed a total increase in HU of up to 223. The sample having the highest gold mass percentage tested showed the greatest increase in HU number compared to water.
ASJC Scopus subject areas