Conventional Dual-energy Computed Tomography Research Articles

Sparse-view image reconstruction with total-variation minimization applied to sparsely sampled projection data from SiPM-based photon-counting CT

We constructed a sparse-view computed tomography (CT) system that combines a compressed sensing (CS)-based image-reconstruction algorithm and SiPM-based photon-counting (PC) CT. CS-based image-reconstruction algorithms have been extensively studied for X-ray CT image reconstruction using fewer projections because they are expected to reduce CT imaging time and radiation exposure while maintaining CT image quality. In most previous studies, CS-based image-reconstruction algorithms have been applied to data obtained through numerical simulations or conventional dual-energy CT. However, studies on PC-CT have been scarce. Therefore, we applied a CS-based image-reconstruction algorithm to the projection data obtained using our previously established SiPM-based PC-CT system and evaluated its image quality. We prepared static phantoms equivalent to iodine-containing contrast agents and a mouse model injected with iodine-containing contrast agents as subjects. Thereafter, CT scanning was performed. The obtained projection data were downsampled to simulate a sparse-view situation, and a CS-based image-reconstruction algorithm with total-variation minimization was applied. Consequently, sparse-view CT images were successfully reconstructed, and the image quality was maintained even after downsampling the projection data (downsampling ratios of 1/10 and 1/2 for the rod phantom and mouse model, respectively). Thus, the imaging time and exposure dose could be remarkably reduced (by a factor of 10 or 2), indicating that the CS-based image-reconstruction algorithm is effective for PC-CT.

A projection-based sparse-view virtual monochromatic computed tomography method based on a compressed-sensing algorithm

Computed tomography (CT) images obtained at different monochromatic X-ray beam energies can be synthesized from conventional dual-energy CT scans. This approach to synthesizing monochromatic CT images is based on basis material decomposition and the knowledge of attenuation of basis materials. The main benefits of virtual monochromatic CT (VMCT) images include reduction of beam-hardening artifacts and provision of accurate atteuation measurements. Despite the VMCT's benefits, main concerns in the use of VMCT in clinics may be high radiation dose the patient is exposed to. In this study, we investigated a projection-based sparse-view VMCT method in an attempt to overcome these difficulties. We performed a computational simulation and evaluated the feasibility of using the VMCT method in sparse-view CT. Two polychromatic data sets of 90 projections, far less than what is required by the Nyquist sampling theory, were simulated at 80 kVp and 140 kVp and used to synthesize VMCT images at a monochromatic energy range of 40–140 keV . VMCT image characteristics were quantitatively evaluated in terms of intensity profile, the contrast-to-noise ratio, and the signal-to-noise ratio. Our results indicate that the CS-based algorithm produced high-quality sparse-view CT images, and thereby the proposed VMCT method yielded CT image results of improved beam-hardening artifacts and quantitative measurements.

Effective atomic number estimation using kV-MV dual-energy source in LINAC

Dual-energy computed tomography (DECT) imaging can measure the effective atomic number (EAN) as well as the electron density, and thus its adoption may improve dose calculations in brachytherapy and external photon/particle therapy. An expanded energy gap in dual-energy sources is expected to yield more accurate EAN estimations than conventional DECT systems, which typically span less than 100kV. The aim of this paper is to assess a larger energy gap DECT by using a linear accelerator (LINAC) radiotherapy system with a kV X-ray imaging device, which are combined to provide X-rays in both the kV- and MV-energy ranges. Traditionally, the EAN is determined by parameterising the Hounsfield Unit; however, this is difficult in a kV-MV DECT due to different uncertainties in the reconstructed attenuation coefficient at each end of the energy spectrum. To overcome this problem, we included a new calibration step to produce the most likely linear attenuation coefficients, based upon the X-ray spectrum. To determine the X-ray spectrum, Monte Carlo calculations using GEANT4 were performed. Then the images were calibrated using information from eight inserts of known materials in a CIRS phantom (CIRS Inc., Norfolk, VA). Agreement between the estimated and empirical EANs in these inserts was within 11%. Validation was subsequently performed with the CatPhan500 phantom (The Phantom Laboratory, Salem). The estimated EAN for seven inserts agreed with the empirical values to within 3%. Accordingly, it can be concluded that, given properly reconstructed images based upon a well-determined X-ray spectrum, kV-MV DECT provides an excellent prediction for the EAN.

A Reconstruction Method for Dual High-Energy CT With MeV X-Rays

Dual-energy computed tomography (DECT) allows one to obtain both density and atomic number and thus can provide information about material composition of scanned objects. In this paper, we extend a basis material decomposition method for high energy X-ray DECT used in cargo inspection. It differs from conventional DECT reconstruction methods by pair-production effect coming into play in the reconstruction. The pair-production does not happen for DECT in low energy level (lower than 1 MeV). The decomposition error of the basis material model and its applicability in the high-energy level are analyzed in this paper. A reconstruction method based on this model is proposed to reconstruct both the atomic number <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Z</i> and the electron density ρ <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e</i> images for a high-energy DECT. The method is validated by a numerical simulation and a practical experiment on a cargo inspection system. Results show that the proposed reconstruction method is strongly grounded on physics and feasible for high-energy DECT in material discrimination, especially for cargo inspections. The advantages and limitations of the high-energy DECT, as well as possible improvements for future work are discussed in this paper.

Spectral optimization for measuring electron density by the dual-energy computed tomography coupled with balanced filter method

Dual-energy computed tomography (DECT) has the potential for measuring electron density distribution in a human body to predict the range of particle beams for treatment planning in proton or heavy-ion radiotherapy. However, thus far, a practical dual-energy method that can be used to precisely determine electron density for treatment planning in particle radiotherapy has not been developed. In this article, another DECT technique involving a balanced filter method using a conventional x-ray tube is described. For the spectral optimization of DECT using balanced filters, the author calculates beam-hardening error and air kerma required to achieve a desired noise level in electron density and effective atomic number images of a cylindrical water phantom with 50 cm diameter. The calculation enables the selection of beam parameters such as tube voltage, balanced filter material, and its thickness. The optimized parameters were applied to cases with different phantom diameters ranging from 5 to 50 cm for the calculations. The author predicts that the optimal combination of tube voltages would be 80 and 140 kV with Tb/Hf and Bi/Mo filter pairs for the 50-cm-diameter water phantom. When a single phantom calibration at a diameter of 25 cm was employed to cover all phantom sizes, maximum absolute beam-hardening errors were 0.3% and 0.03% for electron density and effective atomic number, respectively, over a range of diameters of the water phantom. The beam-hardening errors were 1/10 or less as compared to those obtained by conventional DECT, although the dose was twice that of the conventional DECT case. From the viewpoint of beam hardening and the tube-loading efficiency, the present DECT using balanced filters would be significantly more effective in measuring the electron density than the conventional DECT. Nevertheless, further developments of low-exposure imaging technology should be necessary as well as x-ray tubes with higher outputs to apply DECT coupled with the balanced filter method for clinical use.