Region-of-interest cone beam computed tomography (ROI CBCT) with a high resolution CMOS detector

A C-arm photon counting CT prototype with volumetric coverage using multi-sweep step-and-shoot acquisitions

Objective.Existing clinical C-arm interventional systems use scintillator-based energy-integrating flat panel detectors (FPDs) to generate cone-beam CT (CBCT) images. Despite its volumetric coverage, FPD-CBCT does not provide sufficient low-contrast detectability desired for certain interventional procedures. The purpose of this work was to develop a C-arm photon counting detector (PCD) CT system with a step-and-shoot data acquisition method to further improve the tomographic imaging performance of interventional systems.Approach.As a proof-of-concept, a cadmium telluride-based 51 cm × 0.6 cm PCD was mounted in front of a FPD in an Artis Zee biplane system. A total of 10 C-arm sweeps (5 forward and 5 backward) were prescribed. A motorized patient table prototype was synchronized with the C-arm system such that it translates the object by a designated distance during the sub-second rest time in between gantry sweeps. To evaluate whether this multi-sweep step-and-shoot acquisition strategy can generate high-quality and volumetric PCD-CT images without geometric distortion artifacts, experiments were performed using physical phantoms, a human cadaver head, and anin vivoswine subject. Comparison with FPD-CT was made under matched narrow beam collimation and radiation dose conditions.Main results.Compared with FPD-CT images, PCD-CT images had lower noise and improved visualization of low-contrast lesion models, as well as improved visibility of small iodinated blood vessels. Fine structures were visualized more clearly by the PCD-CT than the highest-available resolution provided by FPD-CBCT and MDCT. No perceivable geometric distortion artifacts were observed in the multi-planar PCD-CT images.Significance.This work is the first demonstration of the feasibility of high-quality and multi-planar (volumetric) PCD-CT imaging with a rotating C-arm gantry.

Clinical Micro-CT Empowered by Interior Tomography, Robotic Scanning, and Deep Learning

While micro-CT systems are instrumental in preclinical research, clinical micro-CT imaging has long been desired with cochlear implantation as a primary application. The structural details of the cochlear implant and the temporal bone require a significantly higher image resolution than that (about 0.2 mm) provided by current medical CT scanners. In this paper, we propose a clinical micro-CT (CMCT) system design integrating conventional spiral cone-beam CT, contemporary interior tomography, deep learning techniques, and the technologies of a micro-focus X-ray source, a photon-counting detector (PCD), and robotic arms for ultrahigh-resolution localized tomography of a freely-selected volume of interest (VOI) at a minimized radiation dose level. The whole system consists of a standard CT scanner for a clinical CT exam and VOI specification, and a robotic micro-CT scanner for a local scan of high spatial and spectral resolution at minimized radiation dose. The prior information from the global scan is also fully utilized for background compensation of the local scan data for accurate and stable VOI reconstruction. Our results and analysis show that the proposed hybrid reconstruction algorithm delivers accurate high-resolution local reconstruction, and is insensitive to the misalignment of the isocenter position, initial view angle and scale mismatch in the data/image registration. These findings demonstrate the feasibility of our system design. We envision that deep learning techniques can be leveraged for optimized imaging performance. With high-resolution imaging, high dose efficiency and low system cost synergistically, our proposed CMCT system has great promise in temporal bone imaging as well as various other clinical applications.

A Prototype Intraoral Periapical Sensor with High Frame Rates for a 2.5D Periapical Radiography System

X-ray radiography is currently used in dentistry and can be divided into two categories: two-dimensional (2D) radiographic images (e.g., using periapical film, cephalometric film, and panoramic X-ray) and three-dimensional (3D) radiographic images (e.g., using dental cone-beam computed tomography (CBCT)). Among them, 2D periapical film images are most commonly used. However, 2D periapical film compresses 3D image information into a 2D image, which means that depth cannot be identified from the image. Such compressed images lose a considerable amount of information, reducing their clinical applicability. A 2.5D periapical radiography system prototype was developed by our research team. Our previous study indicated that this prototype could be used to capture images at different depths of an object. However, the prototype was limited by its commercially available intraoral periapical sensor, which had a low temporal resolution and could not capture multiple images in a short period of time. Therefore, the total time required for image capture was too long for practical clinical application. The present study developed a high-frame-rate intraoral periapical sensor with a sensor imaging speed of up to 15 Hz. The primary components of the developed intraoral periapical sensor include a scintillator, complementary metal oxide semiconductor chip, component circuit board, and video processing board. The external dimensions of the sensor are 41 × 26 × 6.6 mm³. The performance of the developed high-frame-rate intraoral periapical sensor was verified through qualified and quantified analyses using line pairs. The results showed that the resolution of the developed intraoral periapical sensor could reach 18 lp/mm. The sensor was further installed in our 2.5D periapical radiography system to conduct image capturing. The results indicated that the developed sensor could be used for high-frame-rate imaging to incorporate tomosynthesis to obtain reconstructed slice images of different depths. The developed sensor has the potential for clinical dentistry applications in the future.

Volumetric CT with sparse detector arrays (and application to Si-strip photon counters)

Novel x-ray medical imaging sensors, such as photon counting detectors (PCDs) and large area CCD and CMOS cameras can involve irregular and/or sparse sampling of the detector plane. Application of such detectors to CT involves undersampling that is markedly different from the commonly considered case of sparse angular sampling. This work investigates volumetric sampling in CT systems incorporating sparsely sampled detectors with axial and helical scan orbits and evaluates performance of model-based image reconstruction (MBIR) with spatially varying regularization in mitigating artifacts due to sparse detector sampling. Volumetric metrics of sampling density and uniformity were introduced. Penalized-likelihood MBIR with a spatially varying penalty that homogenized resolution by accounting for variations in local sampling density (i.e. detector gaps) was evaluated. The proposed methodology was tested in simulations and on an imaging bench based on a Si-strip PCD (total area 5 cm  ×  25 cm) consisting of an arrangement of line sensors separated by gaps of up to 2.5 mm. The bench was equipped with translation/rotation stages allowing a variety of scanning trajectories, ranging from a simple axial acquisition to helical scans with variable pitch. Statistical (spherical clutter) and anthropomorphic (hand) phantoms were considered. Image quality was compared to that obtained with a conventional uniform penalty in terms of structural similarity index (SSIM), image uniformity, spatial resolution, contrast, and noise. Scan trajectories with intermediate helical width (~10 mm longitudinal distance per 360° rotation) demonstrated optimal tradeoff between the average sampling density and the homogeneity of sampling throughout the volume. For a scan trajectory with 10.8 mm helical width, the spatially varying penalty resulted in significant visual reduction of sampling artifacts, confirmed by a 10% reduction in minimum SSIM (from 0.88 to 0.8) and a 40% reduction in the dispersion of SSIM in the volume compared to the constant penalty (both penalties applied at optimal regularization strength). Images of the spherical clutter and wrist phantoms confirmed the advantages of the spatially varying penalty, showing a 25% improvement in image uniformity and 1.8  ×  higher CNR (at matched spatial resolution) compared to the constant penalty. The studies elucidate the relationship between sampling in the detector plane, acquisition orbit, sampling of the reconstructed volume, and the resulting image quality. They also demonstrate the benefit of spatially varying regularization in MBIR for scenarios with irregular sampling patterns. Such findings are important and integral to the incorporation of a sparsely sampled Si-strip PCD in CT imaging.