Abstract
Purpose: MDCT beam‐shaping filters modulate X‐ray intensity across the fan beam, reducing patientsˈ skin dose while homogenizing detector statistics. A simple theoretical model for calculating beam‐shaping filter geometry has been developed; and for calculated attenuation profiles Monte‐ Carlo (MC) simulated transmission spectra have been compared to measured X‐ray spectra. Methods: Based on the assumption that X‐ray intensity after transmission through a given set of a beam‐shaping filter and a cylindrical object of homogeneous composition is equal for all fan angles, a theoretical beam‐shaping filter geometry has been calculated. For a set of fan angles (0°–21° relative to central ray of the fan), transmission spectra were simulated for calculated filter geometry using a Geant4 MC simulation. Simulated spectra have been compared to fan‐angle dependent measurements of MDCT X‐ray spectra (120kVp) acquired using a Compton spectrometer. Additionally, the initial assumption of equalized X‐ray intensity after beam transmission through a set of shaping filter and homogeneous cylindrical phantom was checked by simulating resulting detector signal. Results: Comparison of measured transmission spectra to those resulting from simulation of a beam‐shaping filter geometry estimated using the proposed theoretical model yields maximum differences below ±2.0% for all fan angles. K‐lines of simulated and measured spectra match well and are in agreement with theoretical values for tungsten anodes. Measured and simulated filter transmission and mean X‐ray energy after filter passage are also in good agreement. For the modeled filter geometry the initial assumption of signal homogenization could be validated through simulation. Conclusions: Comparison of measured transmission spectra to those simulated for a beam‐shaping filter geometry estimated using the proposed theoretical model reveals excellent qualitative and quantitative agreement. Thus the proposed method can be used for calculating reliable estimates of MDCT beam‐shaping filter geometry instead of having to rely on manufacturersˈ data or resort to time‐consuming measurements.This research project is in part funded by the German Federal Ministry of Education and Research (BMBF) within the collaboration project: “Innovative Methods for the Optimization of Radiological Applications in Biomedical Imaging”, grant number 02NUK008G.
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