X-ray Computed Tomography (CT) is an indispensable imaging modality in the diagnosis of traumatic brain injury and brain hemorrhage. While the technology and the associated system components have been refined over the last several decades, all modern CT systems still rely on the principle of rotating sources and detectors. The rotating gantry adds a high degree of complexity to the overall system design, and could be eliminated in favor of a configuration of stationary x-ray sources and detectors. Such a change could potentially enable CT systems to be better suited for austere environments. Furthermore, the image acquisition speed would no longer be limited by the maximum rotating speed of the gantry. Unfortunately, due to the size and bulk of existing commercial x-ray sources, such a configuration is impossible to build with a sufficient number of focal spots. Recently, carbon nanotube (CNT) x-ray source arrays have been used in various stationary imaging configurations to generate diagnostic quality tomosynthesis images in the fields of mammography, dentistry, and orthopedics. In this study, we present a potential stationary head CT (s-HCT) design which combines projection data from 3 separate but parallel imaging planes for a complete CT fan-beam reconstruction. The proposed scanner consists of 3 CNT x-ray source arrays with a large number distributed focal spots each, and an Electronic Control System (ECS) for high speed control of the x-ray exposure from each focal spot. The projection data was collected by an array of multi-row detectors. For this unique imaging configuration, a customized geometry calibration procedure was developed. A linear collimator was designed and constructed for the reduction of cone-angle scatter. Finally, volumetric CT slice data was acquired through z-axis translation of the imaging object.
Purpose: Carbon nanotube (CNT) based field-emission x-ray source arrays allow the development of robust stationary computed tomography (CT) imaging systems with no gantry movement. There are many technical considerations that constrain the optimal system design. The aim of this work is to assess the image quality of a proposed Stationary Head CT (sHCT) system through simulation. Methods: In our previous work, we defined a system design consisting of three parallel imaging planes. Each plane consists of a CNT x-ray source array with a large number of linearly distributed focal spots and three strip detector modules. Each imaging plane is rotated 120° with respect to the adjacent plane to provide maximum projection view coverage of the region of interest (ROI). An iterative reconstruction algorithm based on the ASTRA toolbox was developed for the specific sHCT system. The ACR 464 phantom and a set of clinical head CT data were used to assess the system design and image quality. Imaging performance was evaluated both quantitatively and qualitatively. Results: The simulation results suggest that the proposed sHCT design is feasible and high-fidelity CT images can be obtained. The reconstructed image of the ACR 464 phantom reproduces accurate CT numbers. The reconstructed CT images for the human head confirm the capability of this prototype for identifying low contrast pathologies. Conclusion: A three-plane sHCT system is evaluated in this work. The iterative reconstruction algorithm produces high image quality in terms of uniformity, signal-to-noise ratio, signal-to-contrast ratio and structural information. Further work on the optimization of the current sHCT system will focus on speed up of volumetric image data collection in system hardware and further improvement of the reconstruction image quality through regularization and incorporating of machine leaning techniques.
Purpose: Today’s state-of-the-art CT systems rely on a rotating gantry to acquire projections spanning up to 360 degrees around the head and/or body. By replacing the rotating source and detector with a stationary array of x-ray sources and line detectors, a head CT scanner could be potentially constructed with a small footprint and fast scanning speed. The purpose of this project is to design and construct a stationary head CT (s-HCT) scanner capable of diagnosis of stroke and head trauma patients in limited resource areas such as forward operating bases. Here we present preliminary imaging results which demonstrate the feasibility of such a system using carbon nanotube (CNT) x-ray source arrays.
Methods: The feasibility study was performed using a benchtop setup consisting of an x-ray source array with 45 distributed focal spots, each operating at 120kVp, and an Electronic Control System (ECS) for high speed control of the x-ray output from individual focal spots. The projection data was collected by an array of detectors configured specifically for head imaging. The basic performance of the CNT x-ray source array was characterized. By rotating the object in discrete angular steps, a potential s-HCT configuration was emulated. The collected projection images were reconstructed using an iterative reconstruction algorithm developed specifically for this configuration. Evaluation of the image quality was completed by comparing this image of the ACR CT phantom obtained with the s-HCT to that obtained by a clinical CT scanner.
Results: The CNT x-ray source array was found to have a consistent focal spot size of 1.3×1.1 mm2 for all beams (IEC 1.0). At 120 kVp the HVL was measured to be 5.8 mm Al. Axial images have been acquired with slice thickness 2.5 mm to evaluate the imaging performance of the s-HCT system. Contrast-noise-ratio was measured for the acrylic (120 HU) and water (0 HU) materials in the ACR CT 464 phantom Module 01. A value of 5.2 is reported for the benchtop setup with an entrance dose of 2.9 mGy, compared to the clinical measurement of 30.5 found at 74.5 mGy. These images demonstrate that the s-HCT system based on CNT x-ray source arrays is feasible.
Conclusion: Customized CNT x-ray sources were developed specifically for head CT imaging. The feasibility of using this source array to construct a s-HCT scanner has been demonstrated by emulating a potential CT configuration. It is shown that diagnostic quality CT images can be obtained using the proposed system geometry. These preliminary images provide confidence that a s-HCT system can be constructed for clinical evaluation.
Purpose: The invention of carbon nanotube (CNT) x-ray source array has allowed development of many novel imaging systems including stationary tomosynthesis devices for breast, chest and dental imaging. This technology enables stationary computed tomography with potentially a fast data acquisition rate and a mechanically robust structure by eliminating the rotating gantry. It reduces the image blur caused by the mechanical motion. The purpose of this work is to explore possible system configurations of stationary head CT (s-HCT) using fixed-position linear CNT x-ray source arrays and detector arrays. Methods: Sinogram coverage is used for qualitative evaluation on the CT projection data collection efficiency for a given configuration. Accordingly, the configuration is optimized based on the coverage in sinogram space. To evaluate the system feasibility on imaging low-contrast brain tissues, a modified low-contrast Shepp-Logan phantom is implemented for quality assessment using quantitative metrics. Different Iterative Reconstruction methods are compared for both qualitative and quantitative assessment as well. Results: The sinogram coverage of s-HCT configurations changes significantly with different number of CNT source arrays used, as well as the layout of the geometry. Preliminary results suggest that a s-HCT configuration with three planes gives a nearly completed sinogram coverage which provides enough information to reconstruct image with good quality. Different reconstruction techniques are used for such configuration with a low-contrast head phantom. High-quality images are reconstructed for the proposed configuration. Conclusion: An optimized s-HCT system configuration can be built with few linear CNT x-ray source arrays. Given such configuration, Iterative Reconstruction algorithms in conjunction with Total-Variation Regularization provides highquality images even for low-contrast objects.