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.
Proc. SPIE. 8518, Quantum Communications and Quantum Imaging X
KEYWORDS: Signal to noise ratio, Optical imaging, Diffraction, Super resolution, Imaging systems, Fourier transforms, Signal processing, Quantum physics, Reconstruction algorithms, Diode pumped solid state lasers
Sparsity constraint is a priori knowledge of the signal, which means that in some properly chosen basis only a small percentage of the signal components is nonzero. Sparsity constraint has been used in signal and image processing for a long time. Recent publications have shown that by taking advantage of the Sparsity constraint of the object, super-resolution beyond the diffraction limit could be realized. In this paper we present the quantum limits of super-resolution for the sparse objects. The key idea of our paper is to use the discrete prolate spheroidal sequences (DPSS) as the sensing basis. We demonstrate both analytically and numerically that this sensing basis gives superior performance over the Fourier basis conventionally used for sensing of sparse signals. The explanation of this phenomenon is in the fact that the DPSS are the eigenfunctions of the optical imaging system while the Fourier basis are not. We investigate the role of the quantum fluctuations of the light illuminating the object, in the performance of reconstruction algorithm. This analysis allows us to formulate the criteria for stable reconstruction of sparse objects with super-resolution.