[en] Statistical reconstruction (SR) methods provide a general and flexible framework for obtaining tomographic images from projections. For several applications SR has been shown to outperform analytical algorithms in terms of resolution-noise trade-off achieved in the reconstructions. A disadvantage of SR is the long computational time required to obtain the reconstructions, in particular when large data sets characteristic for x-ray computer tomography (CT) are involved. As was shown recently, by combining statistical methods with block iterative acceleration schemes [e.g., like in the ordered subsets convex (OSC) algorithm], the reconstruction time for x-ray CT applications can be reduced by about two orders of magnitude. There are, however, some factors lengthening the reconstruction process that hamper both accelerated and standard statistical algorithms to similar degree. In this simulation study based on monoenergetic and scatter-free projection data, we demonstrate that one of these factors is the extremely high number of iterations needed to remove artifacts that can appear around high-contrast structures. We also show (using the OSC method) that these artifacts can be adequately suppressed if statistical reconstruction is initialized with images generated by means of Radon inversion algorithms like filtered back projection (FBP). This allows the reconstruction time to be shortened by even as much as one order of magnitude. Although the initialization of the statistical algorithm with FBP image introduces some additional noise into the first iteration of OSC reconstruction, the resolution-noise trade-off and the contrast-to-noise ratio of final images are not markedly compromised

[en] For the purpose of obtaining x-ray tomographic images, statistical reconstruction (SR) provides a general framework with possible advantages over analytical algorithms such as filtered backprojection (FBP) in terms of flexibility, resolution, contrast and image noise. However, SR images may be seriously affected by some artefacts that are not present in FBP images. These artefacts appear as aliasing patterns and as severe overshoots in the areas of sharp intensity transitions ('edge artefacts'). We characterize this inherent property of iterative reconstructions and hypothesize how discretization errors during reconstruction contribute to the formation of the artefacts. An adequate solution to the problem is to perform the reconstructions on an image grid that is finer than that typically employed for FBP reconstruction, followed by a downsampling of the resulting image to a granularity normally used for display. Furthermore, it is shown that such a procedure is much more effective than post-filtering of the reconstructions. Resulting SR images have superior noise-resolution trade-off compared to FBP, which may facilitate dose reduction during CT examinations

[en] X-ray CT images obtained with iterative reconstruction (IR) can be hampered by the so-called edge and aliasing artefacts, which appear as interference patterns and severe overshoots in the areas of sharp intensity transitions. Previously, we have demonstrated that these artefacts are caused by discretization errors during the projection simulation step in IR. Although these errors are inherent to IR, they can be adequately suppressed by reconstruction on an image grid that is finer than that typically used for analytical methods such as filtered back-projection. Two other methods that may prevent edge artefacts are: (i) smoothing the projections prior to reconstruction or (ii) using an image representation different from voxels; spherically symmetric Kaiser-Bessel functions are a frequently employed example of such a representation. In this paper, we compare reconstruction on a fine grid with the two above-mentioned alternative strategies for edge artefact reduction. We show that the use of a fine grid results in a more adequate suppression of artefacts than the smoothing of projections or using the Kaiser-Bessel image representation

[en] Dual-energy (DE) decomposition has been adopted in orthopedic imaging to measure bone composition and visualize intraarticular contrast enhancement. One of the potential applications involves monitoring of callus mineralization for longitudinal assessment of fracture healing. However, fracture repair usually involves internal fixation hardware that can generate significant artifacts in reconstructed images. To address this challenge, we develop a novel algorithm that combines simultaneous reconstruction-decomposition using a previously reported method for model-based material decomposition (MBMD) augmented by the known-component (KC) reconstruction framework to mitigate metal artifacts. We apply the proposed algorithm to simulated DE data representative of a dedicated extremity cone-beam CT (CBCT) employing an x-ray unit with three vertically arranged sources. The scanner generates DE data with non-coinciding high- and low-energy projection rays when the central source is operated at high tube potential and the peripheral sources at low potential. The proposed algorithm was validated using a digital extremity phantom containing varying concentrations of Ca-water mixtures and Ti implants. Decomposition accuracy was compared to MBMD without the KC model. The proposed method suppressed metal artifacts and yielded estimated Ca concentrations that approached the reconstructions of an implant-free phantom for most mixture regions. In the vicinity of simple components, the errors of Ca density estimates obtained by incorporating KC in MBMD were ∼1.5–5× lower than the errors of conventional MBMD; for cases with complex implants, the errors were ∼3–5× lower. In conclusion, the proposed method can achieve accurate bone mineral density measurements in the presence of metal implants using non-coinciding DE projections acquired on a multisource CBCT system. (paper)

[en] Application of model-based iterative reconstruction (MBIR) to high resolution cone-beam CT (CBCT) is computationally challenging because of the very fine discretization (voxel size  <100 µ m) of the reconstructed volume. Moreover, standard MBIR techniques require that the complete transaxial support for the acquired projections is reconstructed, thus precluding acceleration by restricting the reconstruction to a region-of-interest. To reduce the computational burden of high resolution MBIR, we propose a multiresolution penalized-weighted least squares (PWLS) algorithm, where the volume is parameterized as a union of fine and coarse voxel grids as well as selective binning of detector pixels. We introduce a penalty function designed to regularize across the boundaries between the two grids. The algorithm was evaluated in simulation studies emulating an extremity CBCT system and in a physical study on a test-bench. Artifacts arising from the mismatched discretization of the fine and coarse sub-volumes were investigated. The fine grid region was parameterized using 0.15 mm voxels and the voxel size in the coarse grid region was varied by changing a downsampling factor. No significant artifacts were found in either of the regions for downsampling factors of up to 4×. For a typical extremities CBCT volume size, this downsampling corresponds to an acceleration of the reconstruction that is more than five times faster than a brute force solution that applies fine voxel parameterization to the entire volume. For certain configurations of the coarse and fine grid regions, in particular when the boundary between the regions does not cross high attenuation gradients, downsampling factors as high as 10×  can be used without introducing artifacts, yielding a ∼50×  speedup in PWLS. The proposed multiresolution algorithm significantly reduces the computational burden of high resolution iterative CBCT reconstruction and can be extended to other applications of MBIR where computationally expensive, high-fidelity forward models are applied only to a sub-region of the field-of-view. (paper)

[en] C-arm cone-beam CT (CBCT) can provide intraoperative 3D imaging capability for surgical guidance, but workflow and radiation dose are the significant barriers to broad utilization. One main reason is that each 3D image acquisition requires a complete scan with a full radiation dose to present a completely new 3D image every time. In this paper, we propose to utilize patient-specific CT or CBCT as prior knowledge to accurately reconstruct the aspects of the region that have changed by the surgical procedure from only a sparse set of x-rays. The proposed methods consist of a 3D–2D registration between the prior volume and a sparse set of intraoperative x-rays, creating digitally reconstructed radiographs (DRRs) from the registered prior volume, computing difference images by subtracting DRRs from the intraoperative x-rays, a penalized likelihood reconstruction of the volume of change (VOC) from the difference images, and finally a fusion of VOC reconstruction with the prior volume to visualize the entire surgical field. When the surgical changes are local and relatively small, the VOC reconstruction involves only a small volume size and a small number of projections, allowing less computation and lower radiation dose than is needed to reconstruct the entire surgical field. We applied this approach to sacroplasty phantom data obtained from a CBCT test bench and vertebroplasty data with a fresh cadaver acquired from a C-arm CBCT system with a flat-panel detector. The VOCs were reconstructed from a varying number of images (10–66 images) and compared to the CBCT ground truth using four different metrics (mean squared error, correlation coefficient, structural similarity index and perceptual difference model). The results show promising reconstruction quality with structural similarity to the ground truth close to 1 even when only 15–20 images were used, allowing dose reduction by the factor of 10–20. (paper)

[en] Joint space morphology can be indicative of the risk, presence, progression, and/or treatment response of disease or trauma. We describe a novel methodology of characterizing joint space morphology in high-resolution 3D images (e.g. cone-beam CT (CBCT)) using a model based on elementary electrostatics that overcomes a variety of basic limitations of existing 2D and 3D methods. The method models each surface of a joint as a conductor at fixed electrostatic potential and characterizes the intra-articular space in terms of the electric field lines resulting from the solution of Gauss’ Law and the Laplace equation. As a test case, the method was applied to discrimination of healthy and osteoarthritic subjects (N = 39) in 3D images of the knee acquired on an extremity CBCT system. The method demonstrated improved diagnostic performance (area under the receiver operating characteristic curve, AUC > 0.98) compared to simpler methods of quantitative measurement and qualitative image-based assessment by three expert musculoskeletal radiologists (AUC = 0.87, p-value = 0.007). The method is applicable to simple (e.g. the knee or elbow) or multi-axial joints (e.g. the wrist or ankle) and may provide a useful means of quantitatively assessing a variety of joint pathologies. (paper)

[en] A prototype cone-beam CT (CBCT) head scanner featuring model-based iterative reconstruction (MBIR) has been recently developed and demonstrated the potential for reliable detection of acute intracranial hemorrhage (ICH), which is vital to diagnosis of traumatic brain injury and hemorrhagic stroke. However, data truncation (e.g. due to the head holder) can result in artifacts that reduce image uniformity and challenge ICH detection. We propose a multi-resolution MBIR method with an extended reconstruction field of view (RFOV) to mitigate truncation effects in CBCT of the head. The image volume includes a fine voxel size in the (inner) nontruncated region and a coarse voxel size in the (outer) truncated region. This multi-resolution scheme allows extension of the RFOV to mitigate truncation effects while introducing minimal increase in computational complexity. The multi-resolution method was incorporated in a penalized weighted least-squares (PWLS) reconstruction framework previously developed for CBCT of the head. Experiments involving an anthropomorphic head phantom with truncation due to a carbon-fiber holder were shown to result in severe artifacts in conventional single-resolution PWLS, whereas extending the RFOV within the multi-resolution framework strongly reduced truncation artifacts. For the same extended RFOV, the multi-resolution approach reduced computation time compared to the single-resolution approach (viz. time reduced by 40.7%, 83.0%, and over 95% for an image volume of 600³, 800³, 1000³ voxels). Algorithm parameters (e.g. regularization strength, the ratio of the fine and coarse voxel size, and RFOV size) were investigated to guide reliable parameter selection. The findings provide a promising method for truncation artifact reduction in CBCT and may be useful for other MBIR methods and applications for which truncation is a challenge. (paper)

[en] The effects of detector readout gain mode and bowtie filters on cone-beam CT (CBCT) image quality and dose were characterized for a new CBCT system developed for point-of-care imaging of the head, with potential application to diagnosis of traumatic brain injury, intracranial hemorrhage (ICH), and stroke. A detector performance model was extended to include the effects of detector readout gain on electronic digitization noise. The noise performance for high-gain (HG), low-gain (LG), and dual-gain (DG) detector readout was evaluated, and the benefit associated with HG mode in regions free from detector saturation was quantified. Such benefit could be realized (without detector saturation) either via DG mode or by incorporation of a bowtie filter. Therefore, three bowtie filters were investigated that varied in thickness and curvature. A polyenergetic gain correction method was developed to equalize the detector response between the flood-field and projection data in the presence of a bowtie. The effect of bowtie filters on dose, scatter-to-primary ratio, contrast, and noise was quantified in phantom studies, and results were compared to a high-speed Monte Carlo (MC) simulation to characterize x-ray scatter and dose distributions in the head. Imaging in DG mode improved the contrast-to-noise ratio (CNR) by ∼15% compared to LG mode at a dose (D ₀, measured at the center of a 16 cm CTDI phantom) of 19 mGy. MC dose calculations agreed with CTDI measurements and showed that bowtie filters reduce peripheral dose by as much as 50% at the same central dose. Bowtie filters were found to increase the CNR per unit square-root dose near the center of the image by ∼5–20% depending on bowtie thickness, but reduced CNR in the periphery by ∼10–40%. Images acquired at equal CTDI_w with and without a bowtie demonstrated a 24% increase in CNR at the center of an anthropomorphic head phantom. Combining a thick bowtie filter with a short arc (180°  +  fan angle) scan centered on the posterior of the head reduced dose to the eye lens by up to 90%. Acquisition in DG mode (without a bowtie filter) was beneficial to the detection of small, low contrast lesions (e.g. subtle ICH) in CBCT. While bowtie filters were found to reduce dose, mitigate sensor saturation at the periphery in HG mode, and improve CNR at the center of the image, the image quality at the periphery was slightly reduced compared to DG mode, and the use of a bowtie required careful implementation of the polyenergetic flood-field correction to avoid artifacts. (paper)

[en] To evaluate the influence of weight-bearing (WB) load in standard axial ankle syndesmotic measurements using cone beam CT (CBCT) examination of asymptomatic uninjured ankles. In this IRB approved, prospective study, patients with previous unilateral ankle fractures were recruited. We simultaneously scanned the injured ankles and asymptomatic contralateral ankles of 27 patients in both WB and NWB modes. For this study, only asymptomatic contralateral ankles with normal plain radiographs were included. Twelve standardized syndesmosis measurements at two axial planes (10 mm above the tibial plafond and 5 mm below the talar dome) were obtained by two expert readers using a custom CBCT viewer with the capability for geometric measurements between user-identified anatomical landmarks. Inter-reader reliability between two readers was obtained using the intra-class correlation coefficient (ICC). We compared the WB and NWB measurements using paired t test. Significant agreement was observed between two readers for both WB and NWB measurements (p $<$0.05). ICC values for WB and NWB measurements had a range of 50-95 and 31-71 respectively. Mean values of the medial clear space on WB images (1.75, 95% confidence interval $[$95% CI$]$: 1.6, 1.9) were significantly lower than on NWB images (2.05, 95% CI: 1.8, 2.2) measurements (p $<$0.001). There was no significant difference between the remaining WB and NWB measurements. Measurements obtained from WB images are reliable. Except for the medial clear space, no significant difference in syndesmotic measurements were observed during the WB mode of CBCT acquisition, implying that the tibio-fibular relationship remains unchanged when the physiological axial weight-bearing load is applied. (orig.)