Technical note: comparing coherent and incoherent scatter effects for cone-beam CT

Dual-source photon-counting CT: impact of residual cross-scatter on quantitative spectral results

Dual-source photon-counting CT combines the high temporal resolution and high pitch of dual-source CT with the material quantification capabilities of photon-counting CT. It, however, results in cross-scatter that increases in severity with increased patient size and collimation. This cross-scatter must be corrected to ensure the removal of scatter artifacts and improve quantitative accuracy. To evaluate residual cross-scatter of a first-generation dual-source photon-counting CT and the effect of phantom size, collimation, and radiation dose, a phantom was scanned in single- and dual-source modes with and without its extension ring at three collimations and three radiation doses. Virtual monoenergetic images (VMI) at 50 keV, VMI 150 keV, and iodine density maps were reconstructed to determine variation between acquisition parameters in single- and dual-source modes. Additionally, differences relative to single-source acquisitions and to single-source and small collimation acquisitions were calculated to reflect residual cross-scatter with and without matched collimation. At VMI 50 keV, inserts exhibited accuracy and similar variation between single- and dual-source modes, averaging 5.4 ± 2.6 and 6.2 ± 2.5 HU, respectively, across phantom size, collimation, and radiation dose. Differences relative to single-source measured 5.1 ± 8.5 and 0.4 ± 4.2 HU while differences relative to single-source and small collimation acquisitions were 6.4 ± 10.8 HU and -0.5 ± 3.9 HU for VMI 50 and 150 keV, respectively. This minimal residual cross-scatter increases confidence in the quantitative accuracy of spectral results necessary for clinical applications of dual-source photon-counting CT with motion, such as cardiac imaging.

Scatter-to-primary ratio in dentomaxillofacial cone-beam CT: effect of field of view and beam energy

OBJECTIVE

The aim of this study was to evaluate the effect of field of view (FOV) and beam energy on the scatter-to-primary ratio (SPR) in dental cone-beam CT (CBCT).

METHODS

An anthropomorphic phantom representing an adult male (ATOM Max 711-HN, Norfolk, VA, USA) was scanned using the 3D Accuitomo 170 CBCT (J. Morita, Kyoto, Japan) using 11 FOVs. During each scan, half of the X-ray beam was blocked. Each scan was performed at three exposure settings with varying beam energy and equal radiation dose: 90 kV 5 mA, 77 kV 7.5 mA and 69 kV 10 mA. The SPR was estimated by measuring the grey values in the blocked and non-blocked regions of the RAW data. The effect of FOV on SPR was evaluated using Dunn's multiple comparison test, and the effect of the exposure settings was compared using a Wilcoxon signed rank test.

RESULTS

Larger FOVs showed increased scatter. FOVs with a shorter isocenter-detector distance showed a particularly high SPR. Most intercomparisons between FOVs were statistically significant. The largest difference was found between 17 × 12 cm and 6 × 6 cm (lower jaw), with the former showing a 4.9-fold higher SPR. The effect of beam energy was relatively small and varied between FOV sizes and positions.

CONCLUSION

While the choice of FOV size and position is determined by the diagnostic region of interest, the image quality deterioration for large FOVs due to scatter provides another incentive to limit the FOV size as much as possible.

Impact of bowtie filter and detector collimation on multislice CT scatter profiles: A simulation study

PURPOSE

To investigate via Monte Carlo simulations, the impact of scan subject size, antiscatter grid (ASG), collimator size, and bowtie filter on the distribution of scatter radiation in a typical realistically modeled third generation 16 slice diagnostic computed tomography (CT) scanner.

METHODS

Full radiation transport was simulated with Geant4 in a realistic CT scanner geometric model, including the imaging phantom, bowtie filter (BTF), collimators and detector assembly, except for the ASGs. An analytical method was employed to quantify the probable transmission through the ASG of each photon intersecting the detector array. Normalized scatter profiles (NSP) and scatter-to-primary-ratio (SPR) profiles were simulated for 90 and 140 kVp beams for different size phantoms and slice thicknesses. The impact of CT scatter on the reconstructed attenuation coefficient factor was also studied as were the modulating effects of phantom- and patient-tissue heterogeneities on scatter profiles. A method to characterize the relative spatial frequency content of sinogram signals was developed to assess the latter.

RESULTS

For the 21.4-cm diameter phantom, NSP and SPR increase linearly with collimator opening for both tube potentials, with the 90 kVp scan exhibiting slightly larger NSP and SPR. The BTF modestly modulates scatter under the phantom center, reducing the prominent off-axis lobes by factors of 1.1-1.3. The ASG reduces scatter on the central axis NSP threefold, and reduces scatter at the detectors outside the phantom shadow by factors of 25 to 500. For the phantoms with diameters of 27 and 32 cm, the scatter increases roughly three- and fourfold, respectively, demonstrating that scatter monotonically increases with phantom size, despite deployment of the ASG and BTF. In the absence of a scan subject, the ASG reduces the signal profile arising photons scattered by the BTF. Without ASG, the in-air scatter profile is relatively flat compared to the scatter profile when the ASG is present. For both 90 and 140 kVp photon spectra, the calculated attenuation coefficient decreases linearly with increasing collimation size. For both homogeneous and heterogeneous objects, NSPs are dominated by low spatial frequency content compared to the primary signal. However, the SPR, which quantifies the local magnitude of nonlinear detector response and is dominated by the high frequency content of the primary profile, can contribute strongly to high-spatial frequency streaking artifacts near high-density structures in reconstructed image artifacts.

CONCLUSION

Public-domain Monte Carlo codes, Geant-4 in particular, is a feasible method for characterizing CT detector response to scattered- and off-focal radiation. Our study demonstrates that the ASG substantially reduces the scatter radiation and reshapes scatter-radiation profiles and affects the accuracy with which the detector array can measure narrow-beam attenuation due its inability to distinguish between true uncollided primary and narrow-angle coherently scattered photons. Hence, incorporating the impact of detector array collimation into the forward-projection signal formation models used by iterative reconstruction algorithms is necessary to use CT for accurately characterizing material properties. While tissue heterogeneities exercise a modest influence on local NPS shape and magnitude, they do not add significant high spatial frequency content.

A weighted rebinned backprojection-filtration algorithm from partially beam-blocked data for a single-scan cone-beam CT with hybrid type scatter correction

PURPOSE

Scatter contamination constitutes a dominant source of degradation of image quality in cone-beam computed tomography (CBCT). We have recently developed an analytic image reconstruction method with a scatter correction capability from the partially blocked cone-beam data out of a single scan. Despite its easy implementation and its computational efficiency, the developed method may result in additional image artifacts for a large cone angle geometry due to data inconsistency. To improve the image quality at a large cone angle, we propose a weighted rebinned backprojection-filtration (wrBPF) algorithm in conjunction with a hybrid type scatter correction approach.

METHODS

The proposed method uses a beam-blocker array that provides partial data for scatter correction and image reconstruction and that only blocks the beam within a limited cone angle. This design allows a chance to keep the image quality at larger cone angles by use of data redundancy since the projection data corresponding to larger cone angles are not blocked. However, the scatter correction would not be straightforward. In order to correct for the scatter in the projections at larger cone angles, we propose a novel scatter correction method combining a measurement-based and a convolution-based method. We first estimated the scatter signal using a measurement-based method in the partially beam-blocked regions, and then optimized the fitting parameters of a convolution-kernel that can be used for scatter correction in the projections at larger cone angles. For image reconstruction, we developed a wrBPF with butterfly filtering. We have conducted an experimental study to validate the proposed algorithm for image reconstruction and scatter correction.

RESULTS

The experimental results revealed that the developed reconstruction method makes full use of the benefits of partial beam-blocking for scatter correction and image reconstruction and at the same time enhances image quality at larger cone angles by use of an optimized convolution-based scatter correction.

CONCLUSIONS

The proposed method that enjoys the advantages of both measurement-based and convolution-based methods for scatter correction has successfully demonstrated its capability of reconstructing accurate images out of a single scan in circular CBCT.

Image-domain shading correction for cone-beam CT without prior patient information

In the era of high-precision radiotherapy, cone-beam CT (CBCT) is frequently utilized for on-board treatment guidance. However, CBCT images usually contain severe shading artifacts due to strong photon scatter from illumination of a large volume and non-optimized patient-specific data measurements, limiting the full clinical applications of CBCT. Many algorithms have been proposed to alleviate this problem by data correction on projections. Sophisticated methods have also been designed when prior patient information is available. Nevertheless, a standard, efficient, and effective approach with large applicability remains elusive for current clinical practice. In this work, we develop a novel algorithm for shading correction directly on CBCT images. Distinct from other image-domain correction methods, our approach does not rely on prior patient information or prior assumption of patient data. In CBCT, projection errors (mostly from scatter and non-ideal usage of bowtie filter) result in dominant low-frequency shading artifacts in image domain. In circular scan geometry, these artifacts often show global or local radial patterns. Hence, the raw CBCT images are first preprocessed into the polar coordinate system. Median filtering and polynomial fitting are applied on the transformed image to estimate the low-frequency shading artifacts (referred to as the bias field) angle-by-angle and slice-by-slice. The low-pass filtering process is done firstly along the angular direction and then the radial direction to preserve image contrast. The estimated bias field is then converted back to the Cartesian coordinate system, followed by 3D low-pass filtering to eliminate possible high-frequency components. The shading-corrected image is finally obtained as the uncorrected volume divided by the bias field. The proposed algorithm was evaluated on CBCT images of a pelvis patient and a head patient. Mean CT number values and spatial non-uniformity on the reconstructed images were used as image quality metrics. Within selected regions of interest, the average CT number error was reduced from around 300 HU to 42 and 38 HU, and the spatial nonuniformity error was reduced from above 17.5% to 2.1% and 1.7% for the pelvis and the head patients, respectively. As our method suppresses only low-frequency shading artifacts, patient anatomy and contrast were retained in the corrected images for both cases. Our shading correction algorithm on CBCT images offers several advantages. It has a high efficiency, since it is deterministic and directly operates on the reconstructed images. It requires no prior information or assumptions, which not only achieves the merits of CBCT-based treatment monitoring by retaining the patient anatomy, but also facilitates its clinical use as an efficient image-correction solution.

Reduction of scatter-induced image noise in cone beam computed tomography: effect of field of view size and position

OBJECTIVE

To measure the effect of field of view (FOV) size and position on scatter-induced image noise in cone beam computed tomography (CBCT).

STUDY DESIGN

A polymethyl methacrylate (PMMA) phantom containing air and aluminum underwent CBCT scanning, using seven FOVs ranging between 4 × 4 cm and 14 × 10 cm, positioned both centrally and according to a dental scan. Signal difference to noise ratio (SDNR) was measured on two-dimensional (2-D) projection images.

RESULTS

At a central position, SDNR decreased with increasing FOV size, ranging between 9.8 (14 × 10 cm) and 10.9 (4 × 4 cm). For dental FOV positions, SDNR values were between 6.3 (14 × 10 cm) and 9.5 (4 × 4 cm). To reach a constant SDNR, a dose reduction up to 76% was possible for small FOVs compared with the 14 × 10 cm FOV.

CONCLUSIONS

The use of small FOVs and peripheral FOV positioning decreases scatter at the detector, resulting in a considerable potential for reduction of radiation dose to the patient.

Spatial frequency spectrum of the x-ray scatter distribution in CBCT projections

PURPOSE

X-ray scatter is a source of significant image quality loss in cone-beam computed tomography (CBCT). The use of Monte Carlo (MC) simulations separating primary and scattered photons has allowed the structure and nature of the scatter distribution in CBCT to become better elucidated. This work seeks to quantify the structure and determine a suitable basis function for the scatter distribution by examining its spectral components using Fourier analysis.

METHODS

The scatter distribution projection data were simulated using a CBCT MC model based on the EGSnrc code. CBCT projection data, with separated primary and scatter signal, were generated for a 30.6 cm diameter water cylinder [single angle projection with varying axis-to-detector distance (ADD) and bowtie filters] and two anthropomorphic phantoms (head and pelvis, 360 projections sampled every 1°, with and without a compensator). The Fourier transform of the resulting scatter distributions was computed and analyzed both qualitatively and quantitatively. A novel metric called the scatter frequency width (SFW) is introduced to determine the scatter distribution's frequency content. The frequency content results are used to determine a set basis functions, consisting of low-frequency sine and cosine functions, to fit and denoise the scatter distribution generated from MC simulations using a reduced number of photons and projections. The signal recovery is implemented using Fourier filtering (low-pass Butterworth filter) and interpolation. Estimates of the scatter distribution are used to correct and reconstruct simulated projections.

RESULTS

The spatial and angular frequencies are contained within a maximum frequency of 0.1 cm(-1) and 7/(2π) rad(-1) for the imaging scenarios examined, with these values varying depending on the object and imaging setup (e.g., ADD and compensator). These data indicate spatial and angular sampling every 5 cm and π/7 rad (~25°) can be used to properly capture the scatter distribution, with reduced sampling possible depending on the imaging scenario. Using a low-pass Butterworth filter, tuned with the SFW values, to denoise the scatter projection data generated from MC simulations using 10(6) photons resulted in an error reduction of greater than 85% for the estimating scatter in single and multiple projections. Analysis showed that the use of a compensator helped reduce the error in estimating the scatter distribution from limited photon simulations by more than 37% when compared to the case without a compensator for the head and pelvis phantoms. Reconstructions of simulated head phantom projections corrected by the filtered and interpolated scatter estimates showed improvements in overall image quality.

CONCLUSIONS

The spatial frequency content of the scatter distribution in CBCT is found to be contained within the low frequency domain. The frequency content is modulated both by object and imaging parameters (ADD and compensator). The low-frequency nature of the scatter distribution allows for a limited set of sine and cosine basis functions to be used to accurately represent the scatter signal in the presence of noise and reduced data sampling decreasing MC based scatter estimation time. Compensator induced modulation of the scatter distribution reduces the frequency content and improves the fitting results.

Low-dose and scatter-free cone-beam CT imaging using a stationary beam blocker in a single scan: phantom studies

Excessive imaging dose from repeated scans and poor image quality mainly due to scatter contamination are the two bottlenecks of cone-beam CT (CBCT) imaging. Compressed sensing (CS) reconstruction algorithms show promises in recovering faithful signals from low-dose projection data but do not serve well the needs of accurate CBCT imaging if effective scatter correction is not in place. Scatter can be accurately measured and removed using measurement-based methods. However, these approaches are considered unpractical in the conventional FDK reconstruction, due to the inevitable primary loss for scatter measurement. We combine measurement-based scatter correction and CS-based iterative reconstruction to generate scatter-free images from low-dose projections. We distribute blocked areas on the detector where primary signals are considered redundant in a full scan. Scatter distribution is estimated by interpolating/extrapolating measured scatter samples inside blocked areas. CS-based iterative reconstruction is finally carried out on the undersampled data to obtain scatter-free and low-dose CBCT images. With only 25% of conventional full-scan dose, our method reduces the average CT number error from 250 HU to 24 HU and increases the contrast by a factor of 2.1 on Catphan 600 phantom. On an anthropomorphic head phantom, the average CT number error is reduced from 224 HU to 10 HU in the central uniform area.

Analysis and interpretation of the first monochromatic X-ray tomography data collected at the Australian Synchrotron Imaging and Medical beamline

The first monochromatic X-ray tomography experiments conducted at the Imaging and Medical beamline of the Australian Synchrotron are reported. The sample was a phantom comprising nylon line, Al wire and finer Cu wire twisted together. Data sets were collected at four different X-ray energies. In order to quantitatively account for the experimental values obtained for the Hounsfield (or CT) number, it was necessary to consider various issues including the point-spread function for the X-ray imaging system and harmonic contamination of the X-ray beam. The analysis and interpretation of the data includes detailed considerations of the resolution and efficiency of the CCD detector, calculations of the X-ray spectrum prior to monochromatization, allowance for the response of the double-crystal Si monochromator used (via X-ray dynamical theory), as well as a thorough assessment of the role of X-ray phase-contrast effects. Computer simulations relating to the tomography experiments also provide valuable insights into these important issues. It was found that a significant discrepancy between theory and experiment for the Cu wire could be largely resolved in terms of the effect of the point-spread function. The findings of this study are important in respect of any attempts to extract quantitative information from X-ray tomography data, across a wide range of disciplines, including materials and life sciences.

Quantitative cone-beam CT imaging in radiation therapy using planning CT as a prior: first patient studies

PURPOSE

Quantitative cone-beam CT (CBCT) imaging is on increasing demand for high-performance image guided radiation therapy (IGRT). However, the current CBCT has poor image qualities mainly due to scatter contamination. Its current clinical application is therefore limited to patient setup based on only bony structures. To improve CBCT imaging for quantitative use, we recently proposed a correction method using planning CT (pCT) as the prior knowledge. Promising phantom results have been obtained on a tabletop CBCT system, using a correction scheme with rigid registration and without iterations. More challenges arise in clinical implementations of our method, especially because patients have large organ deformation in different scans. In this paper, we propose an improved framework to extend our method from bench to bedside by including several new components.

METHODS

The basic principle of our correction algorithm is to estimate the primary signals of CBCT projections via forward projection on the pCT image, and then to obtain the low-frequency errors in CBCT raw projections by subtracting the estimated primary signals and low-pass filtering. We improve the algorithm by using deformable registration to minimize the geometry difference between the pCT and the CBCT images. Since the registration performance relies on the accuracy of the CBCT image, we design an optional iterative scheme to update the CBCT image used in the registration. Large correction errors result from the mismatched objects in the pCT and the CBCT scans. Another optional step of gas pocket and couch matching is added into the framework to reduce these effects.

RESULTS

The proposed method is evaluated on four prostate patients, of which two cases are presented in detail to investigate the method performance for a large variety of patient geometry in clinical practice. The first patient has small anatomical changes from the planning to the treatment room. Our algorithm works well even without the optional iterations and the gas pocket and couch matching. The image correction on the second patient is more challenging due to the effects of gas pockets and attenuating couch. The improved framework with all new components is used to fully evaluate the correction performance. The enhanced image quality has been evaluated using mean CT number and spatial nonuniformity (SNU) error as well as contrast improvement factor. If the pCT image is considered as the ground truth, on the four patients, the overall mean CT number error is reduced from over 300 HU to below 16 HU in the selected regions of interest (ROIs), and the SNU error is suppressed from over 18% to below 2%. The average soft-tissue contrast is improved by an average factor of 2.6.

CONCLUSIONS

We further improve our pCT-based CBCT correction algorithm for clinical use. Superior correction performance has been demonstrated on four patient studies. By providing quantitative CBCT images, our approach significantly increases the accuracy of advanced CBCT-based clinical applications for IGRT.

Reducing metal artifacts in computed tomography caused by hip endoprostheses using a physics-based approach

PURPOSE

Metal-induced artifacts may cause severe problems in clinical computed tomography (CT) imaging and may impair diagnosis as well as overall image quality. Many approaches for reducing these artifacts tackle the problem by simply ignoring or interpolating the metal traces in the raw data, which results in a general information loss and additional artifacts in the corrected image. It was the objective of this study to develop an approach aiming at correcting several physical artifact sources. We have also tried to minimize the impact on spatial resolution and attempted to avoid new artifacts resulting from the correction.

MATERIALS AND METHODS

The algorithm works with a first volumetric reconstruction followed by threshold-based metal prostheses segmentation. The segmented metal implants are then forward projected and the resulting sinogram entries are squared and combined, followed by a second reconstruction to yield correction volumes. The resulting volumes are then combined linearly with a combination weight determined to minimize the flatness of the initial image. A directional filtering algorithm following the beam hardening correction applies a nonlinear convolution in the metal traces of the sinogram which reduces existing metal-induced noise artifacts. Phantom measurements on a polyethylene (PE) disc with different inserts and a semi-anthropomorphic hip phantom with optional bone and titanium inserts were used for evaluating the algorithm. Patient datasets containing uni- and bilateral hip endoprostheses verified the applicability and efficiency on realistic clinical cases.

RESULTS

Deviations in CT values were reduced to below 3 HU on average. Image noise reduction of up to 70% was achieved (average noise reduction of 37%) with a more homogeneous CT value distribution in soft-tissue areas. A comparison to standard interpolation methods showed superior artifact suppression without producing artifacts caused by interpolation and without the general information loss in the close vicinity to the implants. The impact on spatial resolution was minimized as compared with interpolation algorithms.

CONCLUSIONS

Metal artifacts caused by hip-endoprostheses were strongly reduced. Soft tissue areas and skeletal structures surrounding the implants were well restored. The correction works by postprocessing CT datasets and it is applicable to any reconstructed image without a priori knowledge.

Shading correction for on-board cone-beam CT in radiation therapy using planning MDCT images

PURPOSE

Applications of cone-beam CT (CBCT) to image-guided radiationtherapy (IGRT) are hampered by shading artifacts in the reconstructed images. These artifacts are mainly due to scatter contamination in the projections but also can result from uncorrected beam hardening effects as well as nonlinearities in responses of the amorphous silicon flat panel detectors. While currently, CBCT is mainly used to provide patient geometry information for treatment setup, more demanding applications requiring high-quality CBCT images are under investigation. To tackle these challenges, many CBCT correction algorithms have been proposed; yet, a standard approach still remains unclear. In this work, we propose a shading correction method for CBCT that addresses artifacts from low-frequency projection errors. The method is consistent with the current workflow of radiation therapy.

METHODS

With much smaller inherent scatter signals and more accurate detectors, diagnostic multidetector CT (MDCT) provides high quality CT images that are routinely used for radiation treatment planning. Using the MDCT image as "free" prior information, we first estimate the primary projections in the CBCT scan via forward projection of the spatially registered MDCT data. Since most of the CBCT shading artifacts stem from low-frequency errors in the projections such as scatter, these errors can be accurately estimated by low-pass filtering the difference between the estimated and raw CBCT projections. The error estimates are then subtracted from the raw CBCT projections. Our method is distinct from other published correction methods that use the MDCT image as a prior because it is projection-based and uses limited patient anatomical information from the MDCT image. The merit of CBCT-based treatment monitoring is therefore retained.

RESULTS

The proposed method is evaluated using two phantom studies on tabletop systems. On the Catphan 600 phantom, our approach reduces the reconstruction error from 348 Hounsfield unit (HU) without correction to 4 HU around the object center after correction, and from 375 HU to 17 HU in the high-contrast regions. In the selected regions of interest (ROIs), the average image contrast is increased by a factor of 3.3. When noise suppression is implemented, the proposed correction substantially improves the contrast-to-noise ratio (CNR) and therefore the visibility of low-contrast objects, as seen in a more challenging pelvis phantom study. Besides a significant improvement in image uniformity, a low-contrast object of approximately 25 HU, which is otherwise buried in the shading artifacts, can be clearly identified after the proposed correction due to a CNR increase of 3.1. Compared to a kernel-based scatter correction method coupled with an analytical beam hardening correction, our approach also shows an overall improved performance with some residual artifacts.

CONCLUSIONS

By providing effective shading correction, our approach has the potential to improve the accuracy of more advanced CBCT-based clinical applications for IGRT, such as tumor delineation and dose calculation.