Bowtie filters for dedicated breast CT: theory and computational implementation.
OBJECTIVE
To design bowtie filters with improved properties for dedicated breast CT to improve image quality and reduce dose to the patient.


METHODS
The authors present three different bowtie filters designed for a cylindrical 14-cm diameter phantom with a uniform composition of 40/60 breast tissue, which vary in their design objectives and performance improvements. Bowtie design #1 is based on single material spectral matching and produces nearly uniform spectral shape for radiation incident upon the detector. Bowtie design #2 uses the idea of basis material decomposition to produce the same spectral shape and intensity at the detector, using two different materials. Bowtie design #3 eliminates the beam hardening effect in the reconstructed image by adjusting the bowtie filter thickness so that the effective attenuation coefficient for every ray is the same. All three designs are obtained using analytical computational methods and linear attenuation coefficients. Thus, the designs do not take into account the effects of scatter. The authors considered this to be a reasonable approach to the filter design problem since the use of Monte Carlo methods would have been computationally intensive. The filter profiles for a cone-angle of 0° were used for the entire length of each filter because the differences between those profiles and the correct cone-beam profiles for the cone angles in our system are very small, and the constant profiles allowed construction of the filters with the facilities available to us. For evaluation of the filters, we used Monte Carlo simulation techniques and the full cone-beam geometry. Images were generated with and without each bowtie filter to analyze the effect on dose distribution, noise uniformity, and contrast-to-noise ratio (CNR) homogeneity. Line profiles through the reconstructed images generated from the simulated projection images were also used as validation for the filter designs.


RESULTS
Examples of the three designs are presented. Initial verification of performance of the designs was done using analytical computations of HVL, intensity, and effective attenuation coefficient behind the phantom as a function of fan-angle with a cone-angle of 0°. The performance of the designs depends only weakly on incident spectrum and tissue composition. For all designs, the dynamic range requirement on the detector was reduced compared to the no-bowtie-filter case. Further verification of the filter designs was achieved through analysis of reconstructed images from simulations. Simulation data also showed that the use of our bowtie filters can reduce peripheral dose to the breast by 61% and provide uniform noise and CNR distributions. The bowtie filter design concepts validated in this work were then used to create a computational realization of a 3D anthropomorphic bowtie filter capable of achieving a constant effective attenuation coefficient behind the entire field-of-view of an anthropomorphic breast phantom.


CONCLUSIONS
Three different bowtie filter designs that vary in performance improvements were described and evaluated using computational and simulation techniques. Results indicate that the designs are robust against variations in breast diameter, breast composition, and tube voltage, and that the use of these filters can reduce patient dose and improve image quality compared to the no-bowtie-filter case.
Department of Bioengineering, University of Maryland, College Park, Maryland 20742 and U.S. Food and Drug Administration, Center for Devices and Radiological Health, Office of Science and Engineering Laboratories, Division of Imaging and Applied Mathematics, 10903 New Hampshire Avenue, Silver Spring, Maryland 20993.
Kimberly
K
Kontson
Department of Bioengineering, University of Maryland, College Park, Maryland 20742 and U.S. Food and Drug Administration, Center for Devices and Radiological Health, Office of Science and Engineering Laboratories, Division of Imaging and Applied Mathematics, 10903 New Hampshire Avenue, Silver Spring, Maryland 20993.
Robert J
RJ
Jennings
D001940:Breast; D006801:Humans; D008327:Mammography; D008962:Models, Theoretical; D009010:Monte Carlo Method; D019047:Phantoms, Imaging; D011856:Radiographic Image Enhancement / Q000379:methods*; D059629:Signal-To-Noise Ratio