5 research outputs found
Effects of Tissue Material Properties on X-Ray Image, Scatter and Patient Dose Determined using Monte Carlo Simulations
With increasing patient and staff X-ray radiation awareness, many efforts
have been made to develop accurate patient dose estimation methods. To date,
Monte Carlo (MC) simulations are considered golden standard to simulate the
interaction of X-ray radiation with matter. However, sensitivity of MC
simulation results to variations in the experimental or clinical setup of image
guided interventional procedures are only limited studied. In particular, the
impact of patient material compositions is poorly investigated. This is mainly
due to the fact, that these methods are commonly validated in phantom studies
utilizing a single anthropomorphic phantom. In this study, we therefore
investigate the impact of patient material parameters mapping on the outcome of
MC X-ray dose simulations. A computation phantom geometry is constructed and
three different commonly used material composition mappings are applied. We
used the MC toolkit Geant4 to simulate X-ray radiation in an interventional
setup and compared the differences in dose deposition, scatter distributions
and resulting X-ray images. The evaluation shows a discrepancy between
different material composition mapping up to 20 % concerning directly
irradiated organs. These results highlight the need for standardization of
material composition mapping for MC simulations in a clinical setup.Comment: 6 pages, 4 figures, Bildverarbeitung f\"ur die Medizin 201
XDose: toward online cross-validation of experimental and computational X-ray dose estimation
Purpose!#!As the spectrum of X-ray procedures has increased both for diagnostic and for interventional cases, more attention is paid to X-ray dose management. While the medical benefit to the patient outweighs the risk of radiation injuries in almost all cases, reproducible studies on organ dose values help to plan preventive measures helping both patient as well as staff. Dose studies are either carried out retrospectively, experimentally using anthropomorphic phantoms, or computationally. When performed experimentally, it is helpful to combine them with simulations validating the measurements. In this paper, we show how such a dose simulation method, carried out together with actual X-ray experiments, can be realized to obtain reliable organ dose values efficiently.!##!Methods!#!A Monte Carlo simulation technique was developed combining down-sampling and super-resolution techniques for accelerated processing accompanying X-ray dose measurements. The target volume is down-sampled using the statistical mode first. The estimated dose distribution is then up-sampled using guided filtering and the high-resolution target volume as guidance image. Second, we present a comparison of dose estimates calculated with our Monte Carlo code experimentally obtained values for an anthropomorphic phantom using metal oxide semiconductor field effect transistor dosimeters.!##!Results!#!We reconstructed high-resolution dose distributions from coarse ones (down-sampling factor 2 to 16) with error rates ranging from 1.62 % to 4.91 %. Using down-sampled target volumes further reduced the computation time by 30 % to 60 %. Comparison of measured results to simulated dose values demonstrated high agreement with an average percentage error of under [Formula: see text] for all measurement points.!##!Conclusions!#!Our results indicate that Monte Carlo methods can be accelerated hardware-independently and still yield reliable results. This facilitates empirical dose studies that make use of online Monte Carlo simulations to easily cross-validate dose estimates on-site
Geometric misalignment and calibration in cone-beam tomography
© 2004 American Association of Physicists in MedicineLorenz von Smekal, Marc Kachelrieß, Elizaveta Stepina, and Willi A. Kalende