Evaluation of carbon nanotube x-ray source array for stationary head computed tomography

A carbon nanotube x-ray source array designed for a new multisource cone beam computed tomography scanner

Cone beam computed tomography (CBCT) is known to suffer from strong scatter and cone beam artifacts. The purpose of this study is to develop and characterize a rapidly scanning carbon nanotube (CNT) field emission x-ray source array to enable a multisource CBCT (ms-CBCT) image acquisition scheme which has been demonstrated to overcome these limitations. A CNT x-ray source array with eight evenly spaced focal spots was designed and fabricated for a medium field of view ms-CBCT for maxillofacial imaging. An external multisource collimator was used to confine the radiation from each focal spot to a narrow cone angle. For ms-CBCT imaging, the array was placed in the axial direction and rapidly scanned while rotating continuously around the object with a flat panel detector. The x-ray beam profile, temporal and spatial resolutions, energy and dose rate were characterized and evaluated for maxillofacial imaging. The CNT x-ray source array achieved a consistent focal spot size of 1.10 ± 0.04 mm × 0.84 ± 0.03 mm and individual beam cone angle of 2.4°±0.08 after collimation. The x-ray beams were rapidly switched with a rising and damping times of 0.21 ms and 0.19 ms, respectively. Under the designed operating condition of 110 kVp and 15 mA, a dose rate of 8245μGy s-1was obtained at the detector surface with the inherent Al filtration and 2312μGy s-1with an additional 0.3 mm Cu filter. There was negligible change of the x-ray dose rate over many operating cycles. A ms-CBCT scan of an adult head phantom was completed in 14.4 s total exposure time for the imaging dose in the range of that of a clinical CBCT scanner. A spatially distributed CNT x-ray source array was designed and fabricated. It has enabled a new multisource CBCT to overcome some of the main inherent limitations of the conventional CBCT.

A streak artifact reduction algorithm in sparse-view CT using a self-supervised neural representation

PURPOSE

Sparse-view computed tomography (CT) has been attracting attention for its reduced radiation dose and scanning time. However, analytical image reconstruction methods suffer from streak artifacts due to insufficient projection views. Recently, various deep learning-based methods have been developed to solve this ill-posed inverse problem. Despite their promising results, they are easily overfitted to the training data, showing limited generalizability to unseen systems and patients. In this work, we propose a novel streak artifact reduction algorithm that provides a system- and patient-specific solution.

METHODS

Motivated by the fact that streak artifacts are deterministic errors, we regenerate the same artifacts from a prior CT image under the same system geometry. This prior image need not be perfect but should contain patient-specific information and be consistent with full-view projection data for accurate regeneration of the artifacts. To this end, we use a coordinate-based neural representation that often causes image blur but can greatly suppress the streak artifacts while having multiview consistency. By employing techniques in neural radiance fields originally proposed for scene representations, the neural representation is optimized to the measured sparse-view projection data via self-supervised learning. Then, we subtract the regenerated artifacts from the analytically reconstructed original image to obtain the final corrected image.

RESULTS

To validate the proposed method, we used simulated data of extended cardiac-torso phantoms and the 2016 NIH-AAPM-Mayo Clinic Low-Dose CT Grand Challenge and experimental data of physical pediatric and head phantoms. The performance of the proposed method was compared with a total variation-based iterative reconstruction method, naive application of the neural representation, and a convolutional neural network-based method. In visual inspection, it was observed that the small anatomical features were best preserved by the proposed method. The proposed method also achieved the best scores in the visual information fidelity, modulation transfer function, and lung nodule segmentation.

CONCLUSIONS

The results on both simulated and experimental data suggest that the proposed method can effectively reduce the streak artifacts while preserving small anatomical structures that are easily blurred or replaced with misleading features by the existing methods. Since the proposed method does not require any additional training datasets, it would be useful in clinical practice where the large datasets cannot be collected.

Design and optimization of thin-film tungsten (W)-diamond target for multi-pixel X-ray sources

BACKGROUND

Emerging multi-pixel X-ray source technology enables new designs for X-ray imaging systems. The power of multi-pixel X-ray sources with a fixed anode is limited by focal spot power density.

PURPOSE

The purpose of this study is to optimize the W-diamond target and predict its performance in multi-pixel X-ray sources.

METHODS

X-ray intensity and energy deposition in the W-diamond target with different thicknesses of tungsten film and incident electron energies was calculated with the Geant4 Monte Carlo toolkit. COMSOL Multiphysics software was used to analyze the transient and stationary heat transfer in the thin-film W-diamond target. The maximum tube power and X-ray output intensity were predicted for both transmission and reflection target configurations.

RESULTS

The maximum focal spot power density was limited by either the graphitization of the diamond substrate or the melting point of the W target. With optimal W-target thickness, the maximum transmission X-ray intensities are about 40%-50% higher than the maximum reflection intensities. Thin-film W-diamond targets allow four to five times more maximum power input and produce six to seven times higher transmission X-ray intensity in continuous mode compared with conventional reflection W thick targets. Depending on the focal spot size, reducing the X-ray pulse duration can further enhance the tube power.

CONCLUSIONS

Multi-pixel X-ray sources using this W-diamond target design can produce significantly higher X-ray output than traditional thick tungsten targets without major modification of the tube design.

High-Performance Cold Cathode X-ray Tubes Using a Carbon Nanotube Field Electron Emitter

A cold cathode X-ray tube was fabricated using a carbon nanotube (CNT) field electron emitter made by a free-standing CNT film which is composed of a highly packed CNT network. A lot of CNT bundles with a sharp tip are vertically aligned at the edge of the thin CNT film with a length of 10 mm and a thickness of 7 μm. The cold cathode X-ray tube using the CNT field emitter presents an extremely high tube current density of 152 A/cm² (corresponding to tube current of 106.4 mA), the electron beam transmittance of 95.2% and a small focal spot size (FSS) of 0.5 mm. In addition, the cold cathode X-ray tube also shows stable lifetime during 100 000 shots. High emission current density of the cold cathode X-ray tube is mainly attributed to a lot of electron emission sites at an edge of the CNT film. The small FSS is caused by an ensemble of the CNT field electron emitter made by a free-standing thin CNT film and the optimized curve-shape elliptical focusing lens. Based on obtained results, the cold cathode X-ray tube can be widely used for various X-ray applications such as medical diagnosis systems and security check systems in the future.

Feasibility of dual-energy CBCT by spectral filtration of a dual-focus CNT x-ray source

Cone beam computed tomography (CBCT) is now widely used in dentistry and growing areas of medical imaging. The presence of strong metal artifacts is however a major concern of using CBCT especially in dentistry due to the presence of highly attenuating dental restorations, fixed appliances, and implants. Virtual monoenergetic images (VMIs) synthesized from dual energy CT (DECT) datasets are known to reduce metal artifacts. Although several techniques exist for DECT imaging, they in general come with significantly increased equipment cost and not available in dental clinics. The objectives of this study were to investigate the feasibility of developing a low-cost dual energy CBCT (DE-CBCT) by retrofitting a regular CBCT scanner with a carbon nanotube (CNT) x-ray source with dual focal spots and corresponding low-energy (LE) and high-energy (HE) spectral filters. A testbed with a CNT field emission x-ray source (NuRay Technology, Chang Zhou, China), a flat panel detector (Teledyne, Waterloo, Canada), and a rotating object stage was used for this feasibility study. Two distinct polychromatic x-ray spectra with the mean photon energies of 66.7keV and 86.3keV were produced at a fixed 120kVp x-ray tube voltage by using Al+Au and Al+Sn foils as the respective LE and HE filters attached to the exist window of the x-ray source. The HE filter attenuated the x-ray photons more than the LE filter. The calculated post-object air kerma rate of the HE beam was 31.7% of the LE beam. An anthropomorphic head phantom (RANDO, Nuclear Associates, Hicksville, NY) with metal beads was imaged using the testbed and the images were reconstructed using an iterative volumetric CT reconstruction algorithm. The VMIs were synthesized using an image-domain basis materials decomposition method with energy ranging from 30 to 150keV. The results were compared to the reconstructed images from a single energy clinical dental CBCT scanner (CS9300, Carestream Dental, Atlanta, GA). A significant reduction of the metal artifacts was observed in the VMI images synthesized at high energies compared to those from the same object imaged by the clinical dental CBCT scanner. The ability of the CNT x-ray source to generate the output needed to compensate the reduction of photon flux due to attenuation from the spectral filters and to maintain the CT imaging time was evaluated. The results demonstrated the feasibility of DE-CBCT imaging using the proposed approach. Metal artifact reduction was achieved in VMIs synthesized. The x-ray output needed for the proposed DE-CBCT can be generated by a fixed-anode CNT x-ray source.

Interventional Treatment of Bronchiectasis Macrosomia Based on Multirow CT Tomography Monitoring

We present in this paper an in-depth study and analysis of bronchiectasis haemoptysis by multirow CT tomography and a multifaceted treatment and analysis of the interventions monitored by the scan. Although coronary CT is of great clinical value in the diagnosis and monitoring of coronary artery disease, the potential radiation damage caused by coronary CT should not be underestimated because CT imaging is based on X-rays and the actual effective dose is 5-30 mSv, which is reported in the literature to be high when using conventional imaging modalities for coronary CT. Although there is no direct evidence of a definite causal relationship between X-ray exposure during CT examinations and tumorigenesis, theoretically, even small doses of radiation exposure may pose some potential health risk. Therefore, in clinical practice, coronary CT examinations should be performed in strict compliance with the radiation protection rule "as low as reasonably achievable" (ALARA) recognized by the radiation industry. For longitudinal openings in the range of 0° to 59° and transverse openings in the range of 0° to 44°, the CB2 catheter is significantly more stable than the MIK catheter, and for longitudinal openings in the range of 60° to 119° and transverse openings in the range of 0° to 44°, the CB2 catheter is more stable than the MIK catheter. For longitudinal openings from 0° to 120° and lateral openings from 45° to 90°, there was no significant difference in cannulation stability between the CB2 and MIK catheters. There was a potential tendency for MIK cannulation stability to be higher than CB2 for longitudinal openings in the range of 120° to 180° and lateral openings in the range of 45° to 90°, but there was no significant difference.

Generalized deep iterative reconstruction for sparse-view CT imaging

Sparse-view CT is a promising approach in reducing the X-ray radiation dose in clinical CT imaging. However, the CT images reconstructed from the conventional filtered backprojection (FBP) algorithm suffer from severe streaking artifacts. Iterative reconstruction (IR) algorithms have been widely adopted to mitigate these streaking artifacts, but they may prolong the CT imaging time due to the intense data-specific computations. Recently, model-driven deep learning (DL) CT image reconstruction method, which unrolls the iterative optimization procedures into the deep neural network, has shown exciting prospect in improving the image quality and shortening the reconstruction time. In this work, we explore the generalized unrolling scheme for such iterative model to further enhance its performance on sparse-view CT imaging. By using it, the iteration parameters, regularizer term, data-fidelity term and even the mathematical operations are all assumed to be learned and optimized via the network training. Results from the numerical and experimental sparse-view CT imaging demonstrate that the newly proposed network with the maximum generalization provides the best reconstruction performance.

Simulation on system configuration for stationary head CT using linear carbon nanotube x-ray source arrays

Purpose: The invention of carbon nanotube (CNT) x-ray source arrays has enabled the development of novel imaging systems, including stationary tomosynthesis and stationary computed tomography (CT) with fast data acquisition, mechanically robust structures, and reduced image blur from source-detector motion. In this work, we report the results of simulation studies of potential system configurations for a stationary head CT (s-HCT) using linear CNT x-ray sources and detector arrays. Approach: We explored s-HCT configurations that utilize one, two, and three linear CNT source arrays. Simulations were implemented using three digital phantoms with both CPU and GPU computing. Sinogram coverage was used for qualitative evaluation of the CT projection collection efficiency for each configuration. A modified low-contrast Shepp-Logan (SL) phantom was implemented for image quality assessment using quantitative metrics. Different iterative reconstruction (IR) methods were compared with both qualitative and quantitative assessments. Results: Sinogram coverage of s-HCT configurations was sensitive to the number of CNT source arrays and geometry. The simulations suggest that a s-HCT configuration with three planes gives near complete sinogram coverage. Such a configuration enables accurate reconstruction of the low-contrast SL phantom and considerably diminished artifacts caused by the system geometry. Conclusions: An optimized s-HCT system configuration with three linear CNT x-ray source arrays is feasible. IR algorithms can diminish artifacts caused by sparse and asymmetrical scans. The proposed s-HCT system configuration is currently under construction.

Geometry calibration and image reconstruction for carbon-nanotube-based multisource and multidetector CT

Conventional intraoperative computed tomography (CT) has a long scan time, degrading the image quality. Its large size limits the position of a surgeon during surgery. Therefore, this study proposes a CT system comprising of eight carbon-nanotube (CNT)-based x-ray sources and 16 detector modules to solve these limitations. Gantry only requires 45° of rotation to acquire the whole projection, reducing the scan time to 1/8 compared to the full rotation. Moreover, the volume and scan time of the system can be significantly reduced using CNT sources with a small volume and short pulse width and placing a heavy and large high-voltage generator outside the gantry. We divided the proposed system into eight subsystems and sequentially devised a geometry calibration method for each subsystem. Accordingly, a calibration phantom consisting of four polytetrafluoroethylene beads, each with 15 mm diameter, was designed. The geometry calibration parameters were estimated by minimizing the difference between the measured bead projection and the forward projection of the formulated subsystem. By reflecting the estimated geometry calibration parameters, the projection data were obtained via rebinning to be used in the filtered-backprojection reconstruction. The proposed calibration and reconstruction methods were validated by computer simulations and real experiments. Additionally, the accuracy of the geometry calibration method was examined by computer simulation. Furthermore, we validated the improved quality of the reconstructed image through the mean-squared error (MSE), structure similarity (SSIM), and visual inspections for both the simulated and experimental data. The results show that the calibrated images, reconstructed by reflecting the calibration results, have smaller MSE and higher SSIM values than the uncalibrated images. The calibrated images were observed to have fewer artifacts than the uncalibrated images in visual inspection, demonstrating that the proposed calibration and reconstruction methods effectively reduce artifacts caused by geometry misalignments.