Patient-specific radiation dose and cancer risk estimation in CT: part I. development and validation of a Monte Carlo program.

PURPOSE

Radiation-dose awareness and optimization in CT can greatly benefit from a dose-reporting system that provides dose and risk estimates specific to each patient and each CT examination. As the first step toward patient-specific dose and risk estimation, this article aimed to develop a method for accurately assessing radiation dose from CT examinations.

METHODS

A Monte Carlo program was developed to model a CT system (LightSpeed VCT, GE Healthcare). The geometry of the system, the energy spectra of the x-ray source, the three-dimensional geometry of the bowtie filters, and the trajectories of source motions during axial and helical scans were explicitly modeled. To validate the accuracy of the program, a cylindrical phantom was built to enable dose measurements at seven different radial distances from its central axis. Simulated radial dose distributions in the cylindrical phantom were validated against ion chamber measurements for single axial scans at all combinations of tube potential and bowtie filter settings. The accuracy of the program was further validated using two anthropomorphic phantoms (a pediatric one-year-old phantom and an adult female phantom). Computer models of the two phantoms were created based on their CT data and were voxelized for input into the Monte Carlo program. Simulated dose at various organ locations was compared against measurements made with thermoluminescent dosimetry chips for both single axial and helical scans.

RESULTS

For the cylindrical phantom, simulations differed from measurements by -4.8% to 2.2%. For the two anthropomorphic phantoms, the discrepancies between simulations and measurements ranged between (-8.1%, 8.1%) and (-17.2%, 13.0%) for the single axial scans and the helical scans, respectively.

CONCLUSIONS

The authors developed an accurate Monte Carlo program for assessing radiation dose from CT examinations. When combined with computer models of actual patients, the program can provide accurate dose estimates for specific patients.