Technology development in Computed Tomography (CT) is driven by clinical needs, for example the need for image
quality sufficient for the clinical task, and the need to obtain the required image quality using the lowest possible
radiation dose to the patient. One approach to manage dose without compromising image quality is to spatially vary the
X-ray flux such that regions of high interest receive more radiation while regions of low interest or regions sensitive to
radiation receive less dose. If the region of interest (ROI) is centered at the CT system’s axis of rotation, a simple
stationary bowtie mounted between the X-ray tube and the patient is sufficient to reduce the X-ray flux outside the
central region. If the ROI is off center, then a dynamic bowtie that can track the ROI as the gantry rotates is preferred.
We experimentally demonstrated the dynamic bowtie using a design that is relatively simple, low cost, requires no
auxiliary power supply, and can be retrofitted to an existing clinical CT scanner. We installed our prototype dynamic
bowtie on a clinical CT scanner, and we scanned a phantom with a pre-selected off-center ROI. The dynamic bowtie
reduced the X-ray intensity outside the targeted ROI tenfold. As a result, the reconstructed image shows significantly
lower noise within the dynamic bowtie ROI compared to regions outside it. Our preliminary results suggest that a
dynamic bowtie could be an effective solution for further reducing CT radiation dose.
In this study, we propose to use patient-specific x-ray fluence control to reduce the radiation dose to sensitive organs
while still achieving the desired image quality (IQ) in the region of interest (ROI). The mA modulation profile is
optimized view by view, based on the sensitive organs and the ROI, which are obtained from an ultra-low-dose
volumetric CT scout scan . We use a clinical chest CT scan to demonstrate the feasibility of the proposed concept: the
breast region is selected as the sensitive organ region while the cardiac region is selected as IQ ROI. Two groups of
simulations are performed based on the clinical CT dataset: (1) a constant mA scan adjusted based on the patient
attenuation (120 kVp, 300 mA), which serves as baseline; (2) an optimized scan with aggressive bowtie and ROI
centering combined with patient-specific mA modulation. The results shows that the combination of the aggressive
bowtie and the optimized mA modulation can result in 40% dose reduction in the breast region, while the IQ in the
cardiac region is maintained. More generally, this paper demonstrates the general concept of using a 3D scout scan for
optimal scan planning.
Radiation exposure during CT imaging has drawn growing concern from academia, industry as well as the general public. Sinusoidal tube current modulation has been available in most commercial products and used routinely in clinical practice. To further exploit the potential of tube current modulation, Sperl et al. proposed a Computer-Assisted Scan Protocol and Reconstruction (CASPAR) scheme  that modulates the tube current based on the clinical applications and patient specific information. The purpose of this study is to accelerate the CASPAR scheme to make it more practical for clinical use and investigate its dose benefit for different clinical applications. The Monte Carlo simulation in the original CASPAR scheme was substituted by the dose reconstruction to accelerate the optimization process. To demonstrate the dose benefit, we used the CATSIM package generate the projection data and perform standard FDK reconstruction. The NCAT phantom at thorax position was used in the simulation. We chose three clinical cases (routine chest scan, coronary CT angiography with and without breast avoidance) and compared the dose level with different mA modulation schemes (patient specific, sinusoidal and constant mA) with matched image quality. The simulation study of three clinical cases demonstrated that the patient specific mA modulation could significantly reduce the radiation dose compared to sinusoidal modulation. The dose benefits depend on the clinical application and object shape. With matched image quality, for chest scan the patient specific mA profile reduced the dose by about 15% compared to the sinusoid mA modulation; for the organ avoidance scan the dose reduction to the breast was over 50% compared to the constant mA baseline.
Computerized Tomography (CT) is a powerful radiographic imaging technology but the health risk due to the exposure of x-ray radiation has drawn wide concern. In this study, we propose to use kVp modulation to reduce the radiation dose and achieve the personalized low dose CT. Two sets of simulation are performed to demonstrate the effectiveness of kVp modulation and the corresponding calibration. The first simulation used the helical body phantom (HBP) that is an elliptical water cylinder with high density bone inserts. The second simulation uses the NCAT phantom to emulate the practical use of kVp modulation approach with region of interest (ROI) selected in the cardiac region. The kVp modulation profile could be optimized view by view based on the knowledge of patient attenuation. A second order correction is applied to eliminate the beam hardening artifacts. To simplify the calibration process, we first generate the calibration vectors for a few representative spectra and then acquire other calibration vectors with interpolation. The simulation results demonstrate the beam hardening artifacts in the images with kVp modulation can be eliminated with proper beam hardening correction. The results also show that the simplification of calibration did not impair the image quality: the calibration with the simplified and the complete vectors both eliminate the artifacts effectively and the results are comparable. In summary, this study demonstrates the feasibility of kVp modulation and gives a practical way to calibrate the high order beam hardening artifacts.
Computer simulation tools for X-ray CT are important for research efforts in developing reconstructionmethods, designing
new CT architectures, and improving X-ray source and detector technologies. In this paper, we propose a physics-based
modeling method for X-ray CT measurements with energy-integrating detectors. It accurately accounts for the dependence
characteristics on energy, depth and spatial location of the X-ray detection process, which is either ignored or over
simplified in most existing CT simulation methods. Compared with methods based on Monte Carlo simulations, it is
computationally much more efficient due to the use of a look-up table for optical collection efficiency. To model the CT
measurments, the proposed model considers five separate effects: energy- and location-dependent absorption of the incident
X-rays, conversion of the absorbed X-rays into the optical photons emitted by the scintillator, location-dependent
collection of the emitted optical photons, quantumefficiency of converting fromoptical photons to electrons, and electronic
noise. We evaluated the proposed method by comparing the noise levels in the reconstructed images from measured data
and simulations of a GE LightSpeed VCT system. Using the results of a 20 cm water phantom and a 35 cm polyethylene
(PE) disk at various X-ray tube voltages (kVp) and currents (mA), we demonstrated that the proposed method produces realistic CT simulations. The difference in noise standard deviation between measurements and simulations is approximately
2% for the water phantom and 10% for the PE phantom.
Ray-tracing based simulation methods are widely used in modeling X-ray propagation, detection and imaging. While
most of the existing simulation methods rely on analytical modeling, a novel hybrid approach comprising of statistical
modeling and analytical approaches, is proposed here.
Our hybrid simulator is a unique combination of analytical modeling for evoking the fundamentals of X-ray transport
through ray-tracing, and a look-up-table (LUT) based approach for integrating it with the Monte Carlo simulations that
model optical photon-transport within scintillator. The LUT approach for scintillation-based X-ray detection invokes
depth-dependent gain factors to account for intra-pixel absorption and light-transport, together with incident-angle
dependent effects for inter-pixel X-ray absorption (parallax effect). The model simulates the post-patient collimator for
scatter-rejection, as an X-ray shadow on scintillator, while handling its position with respect to the pixel boundary, by a
smart over-sampling strategy for high efficiency.
We have validated this simulator for computed tomography system-simulations, by using real data from GE Brivo
CT385. The level of accuracy of image noise and spatial resolution is better than 98%. We have used the simulator for
designing the post-patient collimator, and measured modulation transfer function (MTF) for different widths of the
Validation and simulation study clearly demonstrates that the hybrid simulator is an accurate, reliable, efficient tool for
realistic system-level simulations. It could be deployed for research, design and development purposes to model any
scintillator-based X-ray imaging-system (2-dimensional and 3-dimensional), while being equally applicable for medical
and industrial imaging.