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Comparative Study
. 2010 Mar;37(3):1225-36.
doi: 10.1118/1.3312435.

Radiation dose reduction using a CdZnTe-based computed tomography system: comparison to flat-panel detectors

Q Le Huy  1 , Justin L Ducote, Sabee Molloi
Affiliations
Comparative Study

Radiation dose reduction using a CdZnTe-based computed tomography system: comparison to flat-panel detectors

Q Le Huy et al. Med Phys. 2010 Mar.

Abstract

Purpose: Although x-ray projection mammography has been very effective in early detection of breast cancer, its utility is reduced in the detection of small lesions that are occult or in dense breasts. One drawback is that the inherent superposition of parenchymal structures makes visualization of small lesions difficult. Breast computed tomography using flat-panel detectors has been developed to address this limitation by producing three-dimensional data while at the same time providing more comfort to the patients by eliminating breast compression. Flat panels are charge integrating detectors and therefore lack energy resolution capability. Recent advances in solid state semiconductor x-ray detector materials and associated electronics allow the investigation of x-ray imaging systems that use a photon counting and energy discriminating detector, which is the subject of this article.

Methods: A small field-of-view computed tomography (CT) system that uses CdZnTe (CZT) photon counting detector was compared to one that uses a flat-panel detector for different imaging tasks in breast imaging. The benefits afforded by the CZT detector in the energy weighting modes were investigated. Two types of energy weighting methods were studied: Projection based and image based. Simulation and phantom studies were performed with a 2.5 cm polymethyl methacrylate (PMMA) cylinder filled with iodine and calcium contrast objects. Simulation was also performed on a 10 cm breast specimen.

Results: The contrast-to-noise ratio improvements as compared to flat-panel detectors were 1.30 and 1.28 (projection based) and 1.35 and 1.25 (image based) for iodine over PMMA and hydroxylapatite over PMMA, respectively. Corresponding simulation values were 1.81 and 1.48 (projection based) and 1.85 and 1.48 (image based). Dose reductions using the CZT detector were 52.05% and 49.45% for iodine and hydroxyapatite imaging, respectively. Image-based weighting was also found to have the least beam hardening effect.

Conclusions: The results showed that a CT system using an energy resolving detector reduces the dose to the patient while maintaining image quality for various breast imaging tasks.

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Figures

Figure 1
Figure 1
Schematic of the CZT CT setup.
Figure 2
Figure 2
Schematic of the 2.5 cm cylindrical PMMA phantom. Embedded in the center are different concentrations of iodine and calcium.
Figure 3
Figure 3
Tube output measurements and the corresponding spectral model (a). The total aluminum filtrations were 2.6 and 2.7 mm for the tube and the model, respectively. The 80 kV spectrum with divisions of energy bin is also shown (b).
Figure 4
Figure 4
The linear attenuation coefficient of iodine, hydroxyapatite, PMMA, and 50∕50 breast tissue. Also shown are the five energy bins used for CZT imaging.
Figure 5
Figure 5
Weight factors for the five energy bins are shown for HA (a) and Iodine (b). Projection-based and image-based values indicate their similarity in trend.
Figure 6
Figure 6
The reconstructed slice for the simulation experiments of the 10 cm breast (a) and the 2 cm PMMA cylinder (b). Iodine and HA contrast elements are visible. Window=400, level=400.
Figure 7
Figure 7
Reconstructed slice of the phantom for bin 1 (a), bin 2 (b), bin 3 (c), bin 4 (d), and bin 5 (e). Window=1000, level=400.
Figure 8
Figure 8
Reconstructed slice of the phantom for different detector types: Photon counting (a), projection-based weighting HA (b), image-based weighting HA (c), and charge integrating (d). Window=1000, level=400.
Figure 9
Figure 9
Contrast-to-noise ratio vs energy bin for HA (300 mg∕ml) and iodine (8 mg∕ml).
Figure 10
Figure 10
CNR as a function of air kerma of the experimental 2.5 cm PMMA cylinder for 300 mg∕ml HA (a) and 8 mg∕ml iodine (b).
Figure 11
Figure 11
CNR improvement as a function of the energy weighting methods for HA (a) and Iodine (b). Values from both simulations and experiments are shown. CI=charge integrating, PC=photon counting, PW=projection-based weighting, IW=image-based weighting.
Figure 12
Figure 12
Exposure reduction, compared to CNR value of the charge integrating∕flat-panel detector at 2.18 mGy, as a function of the energy weighting methods for HA (a) and iodine (b). Values from both simulations and experiments are shown. CI=charge integrating, PC=photon counting, PW=projection-based weighting, IW=image-based weighting.
Figure 13
Figure 13
Beam hardening quantification shows amount of change in μ for simulations (a) and measurements (b).
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