Conference proceedings. International Conference on Image Formation in X-Ray Computed Tomography最新文献

Despite the evident benefits of spectral computed tomography (CT) in delivering qualitative imaging superior to that of conventional CT in adults, its application in pediatric diagnostic imaging is still relatively limited due to various reasons, including design limitations and radiation dose considerations. The use of specialized K-edge filters, in conjunction with other spectral technologies, has been demonstrated to improve spectral quantification accuracy. X-ray flux limitations generally pose challenges in these concepts when applied to adults. However, such limitations are not present in pediatric imaging, allowing the full exploitation of K-edge filters to improve performance. To facilitate the adoption of spectral CT's benefits, as seen in the adult population, into pediatric settings, we introduce an innovative double bowtie filter design. This design incorporates a K-edge material coupled with Teflon and is integrated with rapid kVp-switching technology. A Python simulation was built to model a rapid kVp-switching x-ray tube and to estimate Cramer-Rao lower bound (CRLB) noise in photoelectric and Compton scatter basis domains. We estimate a conventional bowtie filter and corresponding reference patient dose before optimizing double bowtie configurations to contain the highest obtainable spectral signal-to-noise content for the specified phantom. Our findings indicate that an optimal combination of holmium and Teflon in the filter geometry can increase spectral SNR up to twofold the conventional estimates, while still maintaining low radiation dose exposure. This study broadens the scope for pediatric patients to fully benefit from the capabilities of spectral CT.

Cone-beam CT imaging using non-circular orbits has been demonstrated to be effective in reducing artifacts around metal. With the increasing interest in spectral imaging in the interventional suite, there are potential advantages to combine both technologies to yield further image quality benefits. We simulated a neuro-interventional application where imaging around the embolization is challenged by metal artifacts and the differentiation of bleeds and contrast extravasation is difficult with single-energy imaging. The imaging system was simulated with a dual-layer detector and different sinusoidal orbits. Material decomposition used a projection-domain approach followed by a model-based reconstruction of the density line integrals of each basis. The spectral non-circular orbits acquisitions were compared with single-energy circular, single-energy non-circular, and spectral circular orbits. Results using spectral non-circular orbit contain minimal metal artifacts and allow the differentiation of bleeds and contrast extravasation, demonstrating the potential of the combined technologies.

Spectral CT has great potential for a variety of clinical applications due to the improved material discrimination with respect to conventional CT. Many clinical and preclinical spectral CT systems have two spectral channels for dual-energy CT using strategies such as split-filtration, dual-layer detectors, or kVp-switching. However, there are emerging clinical imaging applications which would require three or more spectral sensitivity channels, for example, multiple exogenous contrast agents in a single scan. Spatial-spectral filters are a new spectral CT technology which use x-ray beam modulation to offer greater spectral diversity. The device consists of an array of k-edge filters which divide the x-ray beam into spectrally varied beamlets. This design allows for an arbitrary number of spectral channels; however, traditional two-step reconstruction-decomposition schemes are typically not effective because the measured data for any individual spectral channel is sparse in the projection domain. Instead, we use a one-step model-based material decomposition algorithm to iteratively estimate material density images directly from spectral CT data. In this work, we present a prototype spatial-spectral filter integrated with an x-ray CT test-bench. The filter is composed of an array of tin, erbium, tantalum, and lead filter tiles which spatially modulate the system spectral sensitivity pattern. After the system was characterized and modeled, we conducted a spectral CT scan of a multi-contrast-enhanced phantom containing water, iodine, and gadolinium solutions. We present the resulting spectral CT data as well as the material density images estimated by model-based material decomposition. The calibrated system model is in close agreement with the measured data, and the reconstructed material density images match the ground truth concentrations for the multi-contrast phantom. These preliminary results demonstrate the potential of spatial-spectral filters to enable multi-contrast imaging and other new clinical applications of spectral CT.

Metal artifacts are a major confounding factor for image quality in CT, especially in image-guided surgery scenarios where surgical tools and implants frequently occur in the field-of-view. Traditional metal artifact correction methods typically use algorithmic solutions to interpolate over the highly attenuated projection measurements where metal is present but cannot recover the missing information obstructed by the metal. In this work, we treat metal artifacts as a missing data problem and employ noncircular orbits to maximize data completeness in the presence of metal. We first implement a local data completeness metric based on Tuy's condition as the percentage of great circles sampled by a particular orbit and accounted for the presence of metal by discounting any rays that pass through metal. We then compute the metric over many locations and many possible metal locations to reflect data completeness for arbitrary metal placements within a volume of interest. We used this metric to evaluate the effectiveness of sinusoidal orbits of different magnitudes and frequencies in metal artifact reduction. We also evaluated noncircular orbits in two imaging systems for phantoms with different metal objects and metal arrangements. Among a circular, tilted circular, and a sinusoidal orbit of two cycles per rotation, the latter is shown to most effectively remove metal artifacts. The noncircular orbit not only reduce the extent of streaks, but allows better visualization of spatial frequencies that cannot be recovered by metal artifact correction algorithms. These results illustrate the potential of relatively simple noncircular orbits to be robust against metal implants which ordinarily present significant challenges in interventional imaging.

In this work we compare a novel model-based material decomposition (MBMD) approach against a standard approach in high-resolution spectral CT using multi-layer flat-panel detectors. Physical experiments were conducted using a prototype dual-layer detector and a custom high-resolution iodine-enhanced line-pair phantom. Reconstructions were performed using three methods: traditional filtered back-projection (FBP) followed by image-domain decomposition, idealized MBMD with no blur modeling (iMBMD), and MBMD with system blur modeling (bMBMD). We find that both MBMD methods yielded higher resolution decompositions with lower noise than the FBP method, and that bMBMD further improves spatial resolution over iMBMD due to the additional blur modeling. These results demonstrate the advantages of MBMD in resolution performance and noise control over traditional methods for spectral CT. Model-based material decomposition hence has great potential in high-resolution spectral CT applications.

Spectral CT permits material discrimination beyond the structural information in conventional single-energy CT. Model-based material decomposition facilitates direct estimation of material density from spectral measurements, incorporating a general forward model for arbitrary spectral CT system, a statistical model of spectral CT measurements, and flexible regularization schemes. Such one-step approaches are promising for superior image quality, but the relationship between regularization parameters, imaging conditions, and reconstructed image properties is complicated. More specifically, the estimator is inherently nonlinear and may include additional nonlinearities like edge-preserving regularization, making image quality metrics intended for linear system evaluation difficult to apply. In this work, we seek approaches to quantify the image properties of this inherently nonlinear process through an investigation of perturbation response - the generalized system response to a local perturbation of arbitrary shape, location, and contrast. Such responses include cross-talk between material density channels, and we investigate the application of this metric in a sample spectral CT system. Inspired by the prior work under assumptions of local linearity and shift-invariant we also propose a prediction framework for perturbation response using a perceptron neural network. The proposed prediction framework offers an alternative to exhaustive evaluation and is a potential tool that can be used to prospectively choose optimal regularization parameters based on imaging conditions and diagnostic task.

Interest in spectral CT for diagnostics and therapy evaluation has been growing. Acquisitions of data from distinct energy spectra provide, among other advantages, quantitative density estimations for multiple materials. We introduce a novel spectral CT concept that includes a fine-pitch grating for prefiltration of the x-ray beam. The attenuation behavior of this grating changes significantly if x-rays are slightly angled in relation to the grating structures. To apply such an angle (i.e. switch between the different filtrations) we propose a fast, controllable, and precise solution by moving the focal spot of the x-ray tube. In this work, we performed preliminary evaluations with a grating prototype on a CT test bench. Our results include x-ray spectrometer measurements that reveal diverse and controllable spectral shaping between 4° and 6° for a specific grating design. Additional experiments with a contrast agent phantom illustrated the capability to decompose clinically relevant iodine concentrations (5, 10, 20, and 50mg/mL) - demonstrating the feasibility of the grating-based approach. Ongoing and future studies will investigate the potential of this novel concept as a relatively simple upgrade to standard energy-integrating CT.

Detector lag and gantry motion during x-ray exposure and integration both result in azimuthal blurring in CT reconstructions. These effects can degrade image quality both for high-resolution features as well as low-contrast details. In this work we consider a forward model for model-based iterative reconstruction (MBIR) that is sufficiently general to accommodate both of these physical effects. We integrate this forward model in a penalized, weighted, nonlinear least-square style objective function for joint reconstruction and correction of these blur effects. We show that modeling detector lag can reduce/remove the characteristic lag artifacts in head imaging in both a simulation study and physical experiments. Similarly, we show that azimuthal blur ordinarily introduced by gantry motion can be mitigated with proper reconstruction models. In particular, we find the largest image quality improvement at the periphery of the field-of-view where gantry motion artifacts are most pronounced. These experiments illustrate the generality of the underlying forward model, suggesting the potential application in modeling a number of physical effects that are traditionally ignored or mitigated through pre-corrections to measurement data.

This work reports experimental results of dynamic fluence field modulation (FFM) using a dual multiple aperture devices (MAD) system. MAD filters use Moiré patterns produced by relative motions between two sets of thin, highly attenuating tungsten bars of varying widths and spacings. Each MAD was affixed to a linear actuator and installed on an experimental cone-beam CT bench. Phantom-specific FFM profiles were designed based on a flatness and minimum mean variance objectives and realized through a combination of MAD translations and pulse width modulation at a constant tube current. To properly correct for gains associated with the MAD filters, a correction algorithm was designed to account for focal spot shifts during scanning, as well as spectral effects from incomplete blockage of x-rays by the tungsten bars. The FFM designs were demonstrated in an elliptical phantom (25.8×14.1 cm). Variance and noise power spectrum (NPS) analysis was performed on the resulting reconstructions. While conventionalgain correction produced reconstructions with high frequency ring artifacts in axial slices, the proposed correction algorithm effectively removed such artifacts while preserving phantom details. Fluence field designs for the elliptical phantom were achievedusing relative MAD motions over a 0.44 mm range, and measured beam profiles closely approximated the theoretically computed target profiles. The noise properties of the resulting reconstructions behave as expected: a flat detected fluence criterion yields nearly isotropic NPS and more homogeneous variance across the reconstruction as compared to an unmodulated scan; the minimum mean variance FFM results in lower mean variance compared to both the unmodulated and flat-field patterns at approximately matched total bare-beam fluence. These results suggest that a dual-MAD CT is an effective approach to provide fluence and image quality control and that can potentially accommodate a wide range of phantoms and design objectives.

Interior tomography is promising approach for retaining high quality CT images within a volume-of-interest (VOI) while reducing the total patient dose. A static collimating filter can only image a centered symmetric VOI, which requires careful patient positioning and may be suboptimal for many clinical applications. Multiple aperture devices (MADs) are an emerging technology based on sequential binary filters that can provide a wide range of fluence patterns that may be adjusted dynamically with relatively small motions. In this work, we introduce a general approach for VOI imaging using MAD-based fluence field modulation (FFM). Physical experiments using a CT test bench are conducted illustrating off-center x-ray beam control for imaging the spine in an abdominal phantom. Image quality and dose metrics are computed for both standard full-field CT and VOI CT. We find that the image quality within the VOI can be preserved for VOI CT with a significant drop in integral dose as compared with a standard full-field protocol.