Multi-energy blended CBCT spectral imaging and scatter-decoupled material decomposition using a spectral modulator with flying focal spot (SMFFS).

BACKGROUND: Cone-beam CT (CBCT) has been extensively employed in industrial and medical applications, such as image-guided radiotherapy and diagnostic imaging, with a growing demand for quantitative imaging using CBCT. However, conventional CBCT can be easily compromised by scatter and beam hardening artifacts, and the entanglement of scatter and spectral effects introduces additional complexity. PURPOSE: The intertwined scatter and spectral effects within CBCT pose significant challenges to the quantitative performance of spectral imaging. In this work, we present the first attempt to develop a stationary spectral modulator with flying focal spot (SMFFS) technology as a promising, low-cost approach to accurately solving the x-ray scattering problem and physically enabling spectral imaging in a unified framework, and with no significant misalignment in data sampling of spectral projections. METHODS: To deal with the intertwined scatter-spectral challenge, we propose a novel scatter-decoupled material decomposition (SDMD) method for SMFFS, which consists of four steps in total, including (1) spatial resolution-preserved and noise-suppressed multi-energy "residual" projection generation free from scatter, based on a hypothesis of scatter similarity; (2) first-pass material decomposition from the generated multi-energy residual projections in non-penumbra regions, with a structure similarity constraint to overcome the increased noise and penumbra effect; (3) scatter estimation for complete data; and (4) second-pass material decomposition for complete data by using a multi-material spectral correction method. Monte Carlo simulations of a pure-water cylinder phantom with different focal spot deflections are conducted to validate the scatter similarity hypothesis. Both numerical simulations using a clinical abdominal CT dataset, and physics experiments on a tabletop CBCT system using a Gammex multi-energy CT phantom and an anthropomorphic chest phantom, are carried out to demonstrate the feasibility of CBCT spectral imaging with SMFFS and our proposed SDMD method. RESULTS: Monte Carlo simulations show that focal spot deflections within a range of 2 mm share quite similar scatter distributions overall. Numerical simulations demonstrate that SMFFS with SDMD method can achieve better material decomposition and CT number accuracy with fewer artifacts. In physics experiments, for the Gammex phantom, the average error of the mean values ( E RMSE ROI $E^{\text{ROI}}_{\text{RMSE}}$ ) in selected regions of interest (ROIs) of virtual monochromatic image (VMI) at 70 keV is 8 HU in SMFFS cone-beam (CB) scan, and 19 and 210 HU in sequential 80/120 kVp (dual kVp, DKV) CB scan with and without scatter correction, respectively. For the chest phantom, the E RMSE ROI $E^{\text{ROI}}_{\text{RMSE}}$ in selected ROIs of VMIs is 12 HU for SMFFS CB scan, and 15 and 438 HU for sequential 80/140 kVp CB scan with and without scatter correction, respectively. Also, the non-uniformity among selected regions of the chest phantom is 14 HU for SMFFS CB scan, and 59 and 184 HU for the DKV CB scan with and without a traditional scatter correction method, respectively. CONCLUSIONS: We propose a SDMD method for CBCT with SMFFS. Our preliminary results show that SMFFS can enable spectral imaging with simultaneous scatter correction for CBCT and effectively improve its quantitative imaging performance.

Dual-energy head cone-beam CT using a dual-layer flat-panel detector: Hybrid material decomposition and a feasibility study.

BACKGROUND: Flat panel detector (FPD) based cone-beam computed tomography (CT) has made tremendous progress in the last two decades, with many new and advanced medical and industrial applications keeping emerging from diagnostic imaging and image guidance for radiotherapy and interventional surgery. The current cone-beam CT (CBCT), however, is still suboptimal for head CT scan which requires a high standard of image quality. While the dual-layer FPD technology is under extensive development and is promising to further advance CBCT from qualitative anatomic imaging to quantitative dual-energy CT, its potential of enabling head CBCT applications has not yet been fully investigated. PURPOSE: The relatively moderate energy separation from the dual-layer FPD and the overall low signal level especially at the bottom-layer detector, could raise significant challenges in performing high-quality dual-energy material decomposition (MD). In this work, we propose a hybrid, physics and model guided, MD algorithm that attempts to fully use the detected x-ray signals and prior-knowledge behind head CBCT using dual-layer FPD. METHODS: Firstly, a regular projection-domain MD is performed as initial results of our approach and for comparison as conventional method. Secondly, based on the combined projection, a dual-layer multi-material spectral correction (dMMSC) is applied to generate beam hardening free images. Thirdly, the dMMSC corrected projections are adopted as a physics-model based guidance to generate a hybrid MD. A set of physics experiments including fan-beam scan and cone-beam scan using a head phantom and a Gammex Multi-Energy CT phantom are conducted to validate our proposed approach. RESULTS: The combined reconstruction could reduce noise by about 10% with no visible resolution degradation. The fan-beam studies on the Gammex phantom demonstrated an improved MD performance, with the averaged iodine quantification error for the 5-15 mg/ml iodine inserts reduced from about 5.6% to 3.0% by the hybrid method. On fan-beam scan of the head phantom, our proposed hybrid MD could significantly reduce the streak artifacts, with CT number nonuniformity (NU) in the selected regions of interest (ROIs) reduced from 23 Hounsfield Units (HU) to 4.2 HU, and the corresponding noise suppressed from 31 to 6.5 HU. For cone-beam scan, after scatter correction (SC) and cone-beam artifact reduction (CBAR), our approach can also significantly improve image quality, with CT number NU in the selected ROI reduced from 24.2 to 6.6 HU and the noise level suppressed from 22.1 to 8.2 HU. CONCLUSIONS: Our proposed physics and model guided hybrid MD for dual-layer FPD based head CBCT can significantly improve the robustness of MD and suppress the low-signal artifact. This preliminary feasibility study also demonstrated that the dual-layer FPD is promising to enable head CBCT spectral imaging.

A comparative study of information retrieval in grating-based x-ray phase-contrast imaging.

The cosine-model analysis (CMA) method and the small angle x-ray scattering (SAXS) method are two major types of information retrieval algorithms, commonly utilized in x-ray phase-contrast imaging with a grating interferometer. However, there are significant differences between the two methods in algorithm implementation, and the existing literature has not completely revealed their intrinsic relationship. In this paper, we theoretically derive and experimentally verify the intrinsic connections between CMA and SAXS, and it is seen that SAXS can be interpreted well by the cosine-model assumption of CMA. To validate our analysis of the scattering distribution when applying the cosine model to the convolution used in SAXS, we applied a deconvolution process into CMA before using the Fourier transform to get the three contrasts. Furthermore, the principal component analysis (PCA) is introduced in this work, and two PCA-based retrieval algorithms are presented in order to simplify the iteration process of deconvolution in SAXS or to obtain absorption and dark-field signals instead of the Fourier transform in CMA. Applying a quantitative structural similarity (SSIM) index and a profile analysis to the results of an ex vivo mammography, it is proved that retrieved images via CMA and SAXS are consistent with each other (SSIM values are 1.0000, 0.9845 and 0.9767 respectively), and that the extra deconvolution process applied into CMA shows a good performance and our analytical analysis of the scattering distribution is valid when applying the cosine model to the convolution used in SAXS. Besides, it is concluded that PCA shows almost the same performance with the Fourier transform (SSIM values are 1.0000 for both absorption and dark-field images), and the simplified SAXS-analogous method works well with higher efficiency in computation and better stability relative to the original SAXS, while maintaining the similar level of image quality (SSIM values are 1.0000, 0.9839 and 0.9781 respectively).

Diagnosis of breast cancer based on microcalcifications using grating-based phase contrast CT.

OBJECTIVES: Microcalcifications are an important feature in the diagnosis of breast cancer, especially in the early stages. In this paper, a CT-based method is proposed to potentially distinguish benign and malignant breast diseases based on the distributions of microcalcifications using grating-based phase-contrast imaging on a conventional X-ray tube. METHODS: The method presented based on the ratio of dark-field signals to attenuation signals in CT images is compared with the existing method based on the ratio in projections, and the threshold for the classification of microcalcifications in the two types of breast diseases is obtained using our approach. The experiment was operated on paraffin-fixed specimens that originated from 20 female patients ranging from 27-65 years old. RESULTS: Compared with the method based on projection images (AUC = 0.87), the proposed method is more effective (AUC = 0.95) to distinguish the two types of diseases. The discrimination threshold of microcalcifications for the classification of diseases in CT images is found to be 3.78 based on the Youden index. CONCLUSIONS: The proposed method can be further developed to improve the early diagnosis and diagnostic accuracy and reduce the clinical misdiagnosis rate of breast cancer. KEY POINTS: • Microcalcifications are of special importance to indicate early breast cancer. • Grating-based phase-contrast imaging can improve the diagnosis of breast cancers. • The method described here can better classify benign and malignant breast diseases.

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.