Beam Hardening Artifacts Research Articles

Feasibility of radiation dose reduction with iterative reconstruction in abdominopelvic CT for patients with inappropriate arm positioning.

BackgroundThe arms-down position increases computed tomography (CT) radiation dose. Iterative reconstruction (IR) could enhance image quality without increasing radiation dose in patients with arms-down position.AimTo investigate the feasibility of reduced-dose CT with IR for patients with inappropriate arm positioningMethodsTwenty patients who underwent two-phase abdominopelvic CT including standard-dose and reduced-dose CT (performed with 80% of the radiation dose of the standard protocol) with their arms positioned in the abdominal area were included in this study. Reduced-dose CT images were reconstructed using filtered back projection (FBP), hybrid IR, and iterative model reconstruction (IMR). These images were compared with standard-dose CT images reconstructed with FBP. Objective image noise in the liver and subcutaneous fat was measured by standard deviation for the quantitative analysis. Then, two radiologists qualitatively assessed beam hardening artifacts, artificial texture, noise, sharpness, and overall image quality in consensus.ResultsReduced-dose CT with all IR levels had lower objective image noise compared to standard-dose CT with FBP reconstruction (P < 0.05). Quantitatively measured beam hardening artifacts were similar in reduced-dose CT with iDose levels 5–6 and fewer with IMR compared to standard-dose CT. In the qualitative analysis, beam hardening artifacts and noise decreased as the IR levels increased. However, artificial texture was significantly aggravated with iDose 5–6 and IMR, and overall image quality significantly worsened with IMR.ConclusionsIR algorithms can reduce beam hardening artifacts in a reduced-dose CT setting in patients with arms-down position, and an intermediate level of hybrid IR allows radiologists to obtain the best image quality. Because the retrospective and single-center nature of our study limited the number of patients, multicenter prospective clinical studies are required to validate our results.

Beam hardening artifacts of liquid embolic agents: comparison between Squid and Onyx

BackgroundInitial clinical experience with Squid shows subjectively reduced artifacts on post-embolization CT scans compared with Onyx. To further investigate these observations, we aimed to perform a comparison of artifacts between...

Characterization of electron density of the real tissues for radiotherapy planning using dual energy algorithm and stoichiometric calibration method

Introduction: Characterization of the relative electron density (𝜌e) of the body tissues is routinely provided by scanning the commercial phantom like RMI 467 at 120 kilovoltage (kVp) in radiotherapy planning. Recent studies showed that the calibrating Hounsfield Unit– 𝜌e curve could be obtained linearly using dual energy computed tomography (DECT) algorithm in commercial phantom like RMI 467. The aim of this study was to produce a more accurate calibrating HU–𝜌e curve by constructing an in- house phantom and applying dual energy algorithm. Materials and Methods: An in-house water filled phantom (33cm diameter) was made including ten water solutions plus composite cork as tissue substitute materials (TSM), and scanned at four kVps by multi-detector four slice CT. The dual energy algorithm was applied to two combination scans (80-140 and 100-140 kVp) and the linear HU–𝜌e curves were produced. The stoichiometric method reproduced the HUs of 31 real body tissues, that their compositions are available in ICRU-46 report. The HU–𝜌e curves for both kVp combination scans were produced. The t-test and compare means were performed between the mean and standard deviation of the relative and absolute differences (%) of the 𝜌e of 31 ICRU real tissues calculated for 120 kVp and both kVp combination scans in the current and previous studies, respectively Results: Applying an energy subtraction algorithm mitigated the 𝜌e calculation error of real tissues. The mean and standard deviation of the relative difference between the 𝜌e of 31 ICRU tissues (–0.23±1.89) were statistically significant compared with the mean and standard deviation of the 30 ICRU tissues (0.80±1.58), which extracted from the RMI 467 phantom at 120 kVp in previous study (p<0.024). The mean and standard deviation of absolute differences of the calculated 𝜌e of the 31 ICRU tissues at 100-140 kVp combination scans (0.14±0.11) compared to previous study using 100-140kVp scan (0.30±0.40) in a second generation dual source CT, were statistically significant (P<0.035). Conclusion: The stoichiometric calibration method and closeness of the 𝜌e of 11 TSMs can result in statistically significant smaller discrepancies in calculating the 𝜌e of real tissues at 120 kVp, compared to the previous studies with RMI 467. The stoichiometric fitting parameters were highly affected by beam hardening artifacts and image noise, especially at 80 kVp. Applying the energy subtraction algorithm can offer further error mitigation in 𝜌e calculation of real tissues by spectral separation and reduction of beam hardening artifacts and noise in two kVp combination scans compared to previous studies. Therefore, a dual energy algorithm in combination with stoichiometry can be used to decrease errors in calculation of the 𝜌e of real tissues, and could be used for radiotherapy planning and material differentiation in clinical practice.

Artifact reduction techniques in Cone Beam Computed Tomography (CBCT) imaging modality

Introduction: Cone beam computed tomography (CBCT) was introduced and became more common based on its low cost, fast image procedure rate and low radiation dose compared to CT. This imaging modality improved diagnostic and treatment-planning procedures by providing three-dimensional information with greatly reduced level of radiation dose compared to 2D dental imaging modalities for investigation of maxillofacial skeleton, dentition and the relationship of anatomical structures. However, CBCT is associated with multiple artifacts like. Extinction artifacts, beam hardening artifacts, partial volume effect, aliasing artifacts, ring artifacts and motion artifacts (misalignment artifacts), Noise and scatter. All of them leads to image quality reduction and have capability of Mistakenly considering as a pathological lesion. This study aimed to investigate Cone Beam Computed Tomography artifacts and their reduction procedures. Materials and Methods: A systematic search of the literature published from 2000 to 2017 in the PubMed, scopus and web of science databases was performed. The following key words combined in different ways: cone beam computed tomography, CBCT Artifacts and artifact reduction. Results: Artifact is caused by several factors containing reconstruction parameters like small field of views (FOVs), presence of metal objects, patient movement, etc. Artifact reduction methods can have divided into two categorize preprocessing in the projection domain and post processing in the image domain. Limitation of field of view, modification of patient head position or separating dental arches for scatter reduction, Application of high KVP in order to beam hardening reduction, iterative method and projection modification method for metal artifacts are recommended. In addition, Filtration, interpolation, iterative reconstruction and filtering algorithms, application of the smaller voxel size and respiratory gating are other suggested items for artifact reduction in CBCT. Conclusion: Multiple artifacts accompany CBCT imaging procedures. There for With the aim of improving the quality of the CBCT images; reducing the artifact caused scatter photons , various software-based and hardware-based correction methods are recommended .

An empirical correction method for beam-hardening artifact in Computerized Tomography (CT) images

A new empirical method has been proposed for the suppression of beam hardening artifacts. It utilizes discrete cosine transform based missing data estimation and an edge-preserving smoothing filter. The method does not need any information about the experiment specification or the X-ray spectrum used and the material being inspected. The corrections are done in the image domain. The proposed method is first tested on three test samples. It is then applied to the cylindrical sample made of Perspex, aluminiumand steel. The results are compared with that of the existing work and the outcome is promising. The horizontal line profile and other parametric comparisons indicate that the proposed method can suppress beam-hardening artifacts significantly. The application of Sobolev space error analysis has also been made to ensure good global reconstruction.

Direct quantitative material decomposition employing grating-based X-ray phase-contrast CT

Dual-energy CT has opened up a new level of quantitative X-ray imaging for many diagnostic applications. The energy dependence of the X-ray attenuation is the key to quantitative material decomposition of the volume under investigation. This material decomposition allows the calculation of virtual native images in contrast enhanced angiography, virtual monoenergetic images for beam-hardening artifact reduction and quantitative material maps, among others. These visualizations have been proven beneficial for various diagnostic questions. Here, we demonstrate a new method of ‘virtual dual-energy CT’ employing grating-based phase-contrast for quantitative material decomposition. Analogue to the measurement at two different energies, the applied phase-contrast measurement approach yields dual information in form of a phase-shift and an attenuation image. Based on these two image channels, all known dual-energy applications can be demonstrated with our technique. While still in a preclinical state, the method features the important advantages of direct access to the electron density via the phase image, simultaneous availability of the conventional attenuation image at the full energy spectrum and therefore inherently registered image channels. The transfer of this signal extraction approach to phase-contrast data multiplies the diagnostic information gained within a single CT acquisition. The method is demonstrated with a phantom consisting of exemplary solid and fluid materials as well as a chicken heart with an iodine filled tube simulating a vessel. For this first demonstration all measurements have been conducted at a compact laser-undulator synchrotron X-ray source with a tunable X-ray energy and a narrow spectral bandwidth, to validate the quantitativeness of the processing approach.

Optimal Virtual Monochromatic Image in “Twin-Beam” Imaging of Dual-Energy CT for Head-and-Neck Cancer Radiation Therapy

Monochromatic images synthesized from dual-energy CT (DECT) data have the potential to reduce beam-hardening artifacts and to provide quantitative measurements. The “twin-beam” imaging scheme in DECT is to simultaneously capture two CT images with different energy spectra, which can eliminate patient motion problem between two CT images. The purpose of this study is to investigate the new “twin-beam” imaging scheme of DECT in head-and-neck radiotherapy workflow and choose optimal monochromatic image for organ-at-risk (OAR) delineation in treatment planning. We synthesized monochromatic images at various energies from “twin-beam” DECT images. Specifically, we generated monochromatic images 40 keV to 190 keV at 5keV increment, and totally obtained 30 monochromatic images for each DECT image. We collected the Hounsfield unit (HU) numbers of OARs (brain stem, mandible, spinal cord and parotid glands), the HU numbers of marginal regions outside OARs and the noise levels for each monochromatic image. We then calculated the contrast-to-noise ratio (CNR) for the different OARs at each energy level to generate a serial of spectral curves for each OAR. Based on these spectral curves of CNR, the mono-energy corresponding to the curve peak (max CNR) was identified for each OAR of each patient. The virtual images at these identified mono-energy are the optimal monochromatic images for the delineations of corresponding OARs. Ten head-and-neck cancer patients scanned with the “twin-beam” imaging scheme were used to test the optimal monochromatic image for the delineation of OARs. Based on the maximized CNR, the optimal energy values were 81.86±2.58 keV for brain stem, 75.63±4.96 keV for mandible, 85.00±4.63 keV for spinal cord, and 83.13±2.59 keV for parotid glands. Overall, the optimal energy value for the delineation of these OARs for head-and-neck cancer patients was 81.41±5.12 keV. We have investigated this new “twin-beam” imaging scheme of DECT in head-and-neck radiotherapy workflow and demonstrated its clinical feasibility of choosing optimal virtual monochromatic images for improving OAR delineation in the head-and-neck radiotherapy planning. This could help us enable a stepwise clinical implementation of optimized “twin-beam” protocol for head-and-neck cancer patients, and has the potential to improve head-and-neck radiotherapy.

Cone‐Beam CT image contrast and attenuation‐map linearity improvement (CALI) for brain stereotactic radiosurgery procedures

A Contrast and Attenuation‐map Linearity Improvement (CALI) framework is proposed for cone‐beam CT (CBCT) images used for brain stereotactic radiosurgery (SRS). The proposed framework is tailored to improve soft tissue contrast of a new point‐of‐care image‐guided SRS system that employs a challenging half cone beam geometry, but can be readily reproduced on any CBCT platform. CALI includes a pre‐ and post‐processing step. In pre‐processing we apply a shading and beam hardening artifact correction to the projections, and in post‐processing step we correct the dome/capping artifact on reconstructed images caused by the spatial variations in X‐ray energy generated by the bowtie‐filter. The shading reduction together with the beam hardening and dome artifact correction algorithms aim to improve the linearity and accuracy of the CT‐numbers (CT#). The CALI framework was evaluated using CatPhan to quantify linearity, contrast‐to‐noise (CNR), and CT# accuracy, as well as subjectively on patient images acquired on a clinical system. Linearity of the reconstructed attenuation‐map was improved from 0.80 to 0.95. The CT# mean absolute measurement error was reduced from 76.1 to 26.9 HU. The CNR of the acrylic insert in the sensitometry module was improved from 1.8 to 7.8. The resulting clinical brain images showed substantial improvements in soft tissue contrast visibility, revealing structures such as ventricles which were otherwise undetectable in the original clinical images obtained from the system. The proposed reconstruction framework also improved CT# accuracy compared to the original images acquired on the system. For frameless image‐guided SRS, improving soft tissue visibility can facilitate evaluation of MR to CBCT co‐registration. Moreover, more accurate CT# may enable the use of CBCT for daily dose delivery measurements.

Determination of the optimal imaging parameters in industrial computed tomography for dimensional measurements on monomaterial workpieces

Industrial computed tomography (CT) plays a key role in 3D coordinate metrology as an alternative to conventional coordinate measuring machines. CT measurement uncertainty depends on the setup parameters with which CT scans are performed. Currently, there is no established model that can describe the relationship between CT setup parameters and measurement uncertainty, and thus determine the optimal settings for a given measurement task. In practice, CT users choose setup parameters intuitively causing high variability in the measurement results. In this study, we enhance and validate an analytical method for optimizing imaging parameters. The proposed method is based on the assumption that minimizing the contribution of imaging parameters to measurement uncertainty corresponds to (1) maximizing image contrast and signal, (2) minimizing geometric blurring, and (3) minimizing image noise and CT artifacts. It also requires information about the workpiece nominal geometry and material composition. The proposed method calculates the optimal photon energy for precise surface determination, given the workpiece position and orientation. Tube voltage and prefilter are determined so that the resulting x-ray spectrum has an effective energy equal to the optimal energy and beam hardening artifacts are minimized. Tube current is chosen to maximize image signal, while avoiding blurring and excessive generated tube power. Exposure time is chosen as the shortest time that fully exploits the detector dynamics. The proposed method was validated by analyzing the standard deviations of CT measurements on a test phantom. An analysis of variance on the uncertainty components showed that the predicted parameters were globally optimal.

Accurate Iterative FBP Reconstruction Method for Material Decomposition of Dual Energy CT.

Compared with traditional CT, dual energy CT (DECT) has the capability to improve material differentiation and reduce beam hardening artifacts, and thus has wide prospects of applications. In this paper, by linearizing the polychromatic projections with their first-order Taylor expansions, we derive an iterative reconstruction method for DECT. The method updates the basis material images by adding the residual images reconstructed from the residual projections to the current estimated basis material images, i.e., the iteration process of the proposed method is carried out in image domain, so it is applicable to both geometrically consistent and inconsistent projections. In addition, as the filtered back-projection method is used in the reconstruction of the residual images, the proposed method has a high degree of parallelism. Both numerical simulation and real-data experiments are performed, and the results confirm the effectiveness of the proposed reconstruction method.

A CBCT series slice image segmentation method.

Images of industrial cone-beam computed tomography (CBCT) contain noise and beam hardening artifacts, which induce difficulty and low precision in segmenting regions of interest. The primary objective of this study is to improve the segmentation precision of CBCT series slice images. This paper presents a method based on the Phansalkar to segment CBCT series slice images precisely. First, the basics of the proposed method and the necessity of changing the local window size are analysed. The adaptive accumulated Phansalkar, which collects each pixel's classification results in different local windows, is proposed. Second, the bimodal distribution of the histogram is used to calculate the appropriate local window size for each pixel adaptively. Third, the characteristics of the accumulated probability (the accumulated classification results divided by the accumulated times) are analysed, from which an adaptive method is applied to segment the accumulated probability. Last, experiments are conducted on CBCT series slice images of three workpieces and one computer-aided design (CAD) model with internal defects. The proposed new method can segment CBCT images with noise and beam-hardening well. Moreover, for the segmentation of all four CBCT series slice images, the new method acquired the highest BF and AOM scores (1 and 0.9981) with the smallest standard deviation (0.0013) as compared with other existing methods including CMF (continuous max-flow/min cut), MS (mean-shift), DRLSE (distance regularized level set evolution), and ARKFCM (adaptively regularized kernel-based fuzzy c-means clustering). The experimental results support that our new method can more precisely segment CBCT series slice images with noise and artifacts than many existing methods. Thus, the new method has prospective application value and can provide valuable technical support for the industrial CBCT image post-processing system.

Practical guidelines for handling head and neck computed tomography artifacts for quantitative image analysis

Radiomics studies have demonstrated the potential use of quantitative image features to improve prognostic stratification of patients with head and neck cancer. Imaging protocol parameters that can affect radiomics feature values have been investigated, but the effects of artifacts caused by intrinsic patient factors have not. Two such artifacts that are common in patients with head and neck cancer are streak artifacts caused by dental fillings and beam-hardening artifacts caused by bone. The purpose of this study was to test the impact of these artifacts and if needed, methods for compensating for these artifacts in head and neck radiomics studies. The robustness of feature values was tested by removing slices of the gross tumor volume (GTV) on computed tomography images from 30 patients with head and neck cancer; these images did not have streak artifacts or had artifacts far from the GTV. The range of each feature value over a percentage of the GTV was compared to the inter-patient variability at full volume. To determine the effects of beam-hardening artifacts, we scanned a phantom with 5 cartridges of different materials encased in polystyrene buildup. A cylindrical hole through the cartridges contained either a rod of polylactic acid to simulate water or a rod of polyvinyl chloride to simulate bone. A region of interest was drawn in each cartridge flush with the rod. Most features were robust with up to 50% of the original GTV removed. Most feature values did not significantly differ when measured with the polylactic acid rod or the polyvinyl chloride rod. Of those that did, the size of the difference did not exceed the inter-patient standard deviation in most cases. We conclude that simply removing slices affected by streak artifacts can enable these scans to be included in radiomics studies and that contours of structures can abut bone without being affected by beam hardening if needed.

Photon-counting CT: Technical Principles and Clinical Prospects.

Photon-counting CT is an emerging technology with the potential to dramatically change clinical CT. Photon-counting CT uses new energy-resolving x-ray detectors, with mechanisms that differ substantially from those of conventional energy-integrating detectors. Photon-counting CT detectors count the number of incoming photons and measure photon energy. This technique results in higher contrast-to-noise ratio, improved spatial resolution, and optimized spectral imaging. Photon-counting CT can reduce radiation exposure, reconstruct images at a higher resolution, correct beam-hardening artifacts, optimize the use of contrast agents, and create opportunities for quantitative imaging relative to current CT technology. In this review, the authors will explain the technical principles of photon-counting CT in nonmathematical terms for radiologists and clinicians. Following a general overview of the current status of photon-counting CT, they will explain potential clinical applications of this technology.

Role of dual energy CT to improve diagnosis of non-traumatic abdominal vascular emergencies.

Computed tomography angiography (CTA) is the modality of choice to evaluate abdominal vascular emergencies (AVE). CTA protocols are often complex and require acquisition of multiple phases to enable a variety of diagnosis such as acute bleeding, pseudoaneurysms, bowel ischemia, and dissection. With single energy CT (SECT), differentiating between calcium, coagulated blood, and contrast agents can be challenging based on their attenuation, especially when in small quantity or present as a mixture. With dual-energy CT (DECT), virtual monoenergetic (VM) and material decomposition (MD) image reconstructions enable more robust tissue characterization, improve contrast-enhancement, and reduce beam hardening artifacts. This article will demonstrate how radiologists can utilize DECT for various clinical scenarios in assessment of non-traumatic AVE.

A new approach for reducing beam hardening artifacts in polychromatic X-ray computed tomography using more accurate prior image.

Metal artifacts severely degrade CT image quality in clinical diagnosis, which are difficult to removed, especially for the beam hardening artifacts. The metal artifact reduction (MAR) based on prior images are the most frequently-used methods. However, there exists a lot misclassification in most prior images caused by absence of prior information such as the spectrum distribution of X-ray beam source, especially many or big metal included. The purpose of this work is to find a more accurate prior image to improve image quality. The proposed method comprise of following four steps. First, the metal image is segmented by thresholding an initial image, where the metal traces are identified in the initial projection data using the forward projection of the metal image. Second, the accurate absorbent model of certain metal image is calculated according to the spectrum distribution of certain X-ray beam source and energy-dependent attenuation coefficients of metal. Then, a new metal image is reconstructed by the general analytical reconstruction algorithm such as filtered back projection (FPB). The prior image is obtained by segmenting the difference image between the initial image and the new metal image into air, tissue and bone. Finally, the initial projection data are normalized by dividing the projection data of prior image pixel to pixel, the corrected image is obtained by interpolation, denormalization and reconstruction. Some clinical images with dental fillings and knee prostheses are used to evaluate the proposed algorithm and normalized metal artifact reduction (NMAR) and linear interpolation (LI) method. The results demonstrate the artifacts can be reduced efficiently by the proposed method. The proposed method could obtain an exact prior image using the prior information about X-ray beam source and energy-dependent attenuation coefficients of metal. As a result, the better performance of reducing beam hardening artifacts can be improved, even though there were many or big implants. Moreover, the process of the proposed method is rather simple and little extra calculation burden is necessary. It has superiorities over other algorithms when include big or many implants.

Comparative performance assessment of beam hardening correction algorithms applied on simulated data sets.

Beam hardening artefacts deteriorate the reconstructed image quality in industrial computed tomography. The appearances of beam hardening artefacts can be cupping effects or streaks. They impair the image fidelity to the object being scanned. This work aims at comparing a variety of commonly used beam hardening correction algorithms in the context of industrial computed tomography metrology. We choose four beam hardening correction algorithms of different types for the comparison. They are a single-material linearization algorithm, a multimaterial linearization algorithm, a dual-energy algorithm and an iterative reconstruction algorithm. Each beam hardening correction algorithm is applied to simulated data sets of a dual-material phantom consisting of multiple rods. The comparison is performed on data sets simulated both under ideal conditions and with the addition of quantum noise. The performance of each algorithm is assessed with respect to its effect on the final image quality (contrast-to-noise ratio, spatial resolution), artefact reduction (streaks, cupping effects) and dimensional measurement deviations. The metrics have been carefully designed in order to achieve a robust and quantifiable assessment. The results suggest that the single-material linearization algorithm can reduce beam hardening artefacts in the vicinity of one material. The multimaterial linearization algorithm can further reduce beam hardening artefacts induced by the other material and improve the dimensional measurement accuracy. The dual-energy method can eliminate beam hardening artefacts, and improve the low contrast visibility and dimensional measurement accuracy. The iterative algorithm is able to eliminate beam hardening streaks. However, it induces aliasing patterns around the object edge, and its performance depends critically upon computational power. The contrast-to-noise ratio and spatial resolution are declined by noise. Noise also increases the difficulty of image segmentation and quantitative analysis. LAY DESCRIPTION: X-ray computed tomography (CT) is a major breakthrough in digital imaging technology in the late 20th century. First used as an important tool in medical imaging, CT has gradually introduced to the nonmedical areas (e.g. industrial nondestructive testing). Inherently CT is more prone to artefacts comparing to the conventional real-time X-ray image. Beam hardening artefacts caused by the polychromatic nature of X-ray spectra are known to deteriorate the reconstructed image quality in industrial CT. A number of beam hardening correction algorithms exist and are used across medical CT. However, there is a lack of research on their effectiveness on industrial CT. This study presents an in-depth beam hardening correction algorithm comparison in industrial CT. Since this study takes various factors of the algorithm performance into account, it provides insights of the advantages and disadvantages of each algorithm and assists the choice of algorithm to meet specific needs of industry. Existing beam hardening correction algorithms are divided into the following four categories: linearization, segmentation based linearization, dual-energy and iterative methods. Since the linearization method can only correct single-material objects, we did not include it in the comparative study. Among the remaining categories, we chose one from each category for comparison, for methods in one peer category share similar physical and mathematical principles. The methods are polynomial fit, Joseph segmentation, dual energy and IMPACT iterative method. This study uses a simulated polychromatic data set of a multimaterial phantom. The central slice of the corrected reconstructions is then assessed and the results are presented. In this study, we will compare beam hardening correction methods with respect to their performance on image quality, the removal of image artefacts and the influence on dimensional accuracy.

Third generation dual-energy CT with 80/150 Sn kV for head and neck tumor imaging.

Dual-energy CT (DECT) provides additional image datasets which enable improved tumor delineation or reduction of beam hardening artifacts in patients with head and neck squamous cell carcinoma (SCC). To assess radiation dose and image quality of third-generation DECT of the head and neck in comparison to single-energy CT (SECT). Thirty patients with SCC who underwent both SECT (reference tube voltage 120 kVp) and DECT (80/150 Sn kVp) of the head and neck region for staging were retrospectively selected. Attenuation measurements of the sternomastoid muscle, internal jugular vein, submandibular gland and tongue were compared. Image noise was assessed at five anatomic levels. Subjective image quality was evaluated by two radiologists in consensus. CTDIvol was 55% lower with DECT (4.2 vs. 9.3 mGy; P = 0.002). Median image noise was equal or lower in DECT at all levels (nasopharynx: 3.9 vs. 5.8, P < 0.0001; floor of mouth: 3.6 vs. 4.5, P = 0.0002; arytenoids: 3.6 vs. 3.1, P = 0.096; lower thyroid: 4.4 vs. 5.7, P = 0.002; arch of aorta: 5.6 vs. 6.5, P = 0.001). Attenuation was significantly lower in DECT ( P < 0.05). Subjective image analysis revealed that DECT is equal or superior to SECT with regard to overall image quality (nasopharynx: 5 vs. 5, P = 1; floor of mouth: 5 vs. 5, P = 0.0041; arytenoids: 5 vs. 5, P = 0.6; lower thyroid: 5 vs. 3, P < 0.0001; arch of aorta: 5 vs. 4, P < 0.0001). Head and neck imaging with third-generation DECT can reduce radiation dose by half compared to SECT, while maintaining excellent image quality.

Pitfalls in the Imaging Interpretation of Intracranial Hemorrhage

Intracranial hemorrhage (ICH) is one of the most common pathologic findings in the emergent computed tomography (CT) imaging. ICH presents as hyperattenuation in parenchymal, subarachnoid, subdural, or epidural location. However, the initial interpretation of areas of hyperattenuation can be challenging as other pathologic or nonpathologic processes (eg, calcifications, vascular malformations, highly cellular tumors, iodinated contrast, or beam-hardening artifacts) can have similar appearance. ICH can also present as isoattenuation on CT, being difficult to distinguish from the brain parenchyma. Dual-energy CT can separate hemorrhage from other causes of hyperattenuation. Albeit, this type of technology has limited availability. Pitfalls on magnetic resonance imaging (MRI) are possible but less common. The characterization of hemorrhage on conventional MR sequences, and particularly on gradient recall echo or susceptibility-weighted imaging is improved. Thus, MRI is considered a problem-solving technique. Radiologists have a prominent role in the interpretation of the initial head CT, recognizing potential pitfalls or alternative diagnosis and if necessary recommending additional work-up. Key imaging findings and technical considerations in common and uncommon pitfalls of ICH are reviewed here.

Correction of severe beam-hardening artifacts via a high-order linearization function using a prior-image-based parameter selection method.

Polychromatic x-rays are used in most computed tomography scanners. In this case, a beam-hardening effect occurs, which degrades the image quality and distorts the shapes of objects in the reconstructed images. When the beam-hardening artifact is not severe, conventional correction methods can reduce the artifact reasonably well. However, highly dense materials, such as iron and titanium, can produce more severe beam-hardening artifacts, which often cannot be corrected by conventional methods. Moreover, when the size of the metal is large, severe darks bands due to photon starvation as well as beam-hardening are generated. The purpose of our study was to develop a new method for correcting severe beam-hardening artifacts and severe dark bands using a high-order polynomial correction function and a prior-image-based linearization method. The initial estimate of an image free of beam-hardening (a prior image) was constructed from the initial reconstruction of the original projection data. Its corresponding beam-hardening-free projection data (a prior projection) were calculated by a projection operator onto the prior image. A new beam-hardening correction function G(praw ) with many high-order terms was effectively determined via a simple minimization process applied to the difference between the original projection data and the prior projection data. Using the determined correction function G(praw ), a corrected linearized sinogram pcorr can be obtained, which became effectively linear for the line integrals of the object. Final beam-hardening corrected images can be reconstructed from the linearized sinogram. The proposed method was evaluated in both simulation and real experimental studies. All investigated cases in both simulations and real experiments showed that the proposed method effectively removed not only streaks for moderate beam-hardening artifacts but also dark bands for severe beam-hardening artifacts without causing structural and contrast distortion. The prior-image-based linearization method exhibited better correction performance than conventional methods. Because the proposed method did not require time-consuming iterative reconstruction processes to obtain the optimal correction function, it can expedite the correction procedure and incorporate more high-order terms in the linearization correction function in comparison to the conventional methods.

The Optimal Energy Level of Virtual Monochromatic Images From Spectral CT for Reducing Beam-Hardening Artifacts Due to Contrast Media in the Thorax.

The purpose of this study is to determine the optimal energy level of virtual monochromatic images from spectral CT compared with conventional polychromatic images for reducing beam-hardening artifacts caused by contrast media in the thorax. A total of 101 consecutive patients who underwent chest CT with contrast enhancement were retrospectively included in this study. The same contrast media and injection protocols were applied to the whole study population. Virtual monochromatic image datasets ranging from 70 to 200 keV and conventional polychromatic images were obtained. Readers' subjective image quality scores were recorded for conventional polychromatic and virtual monochromatic images obtained at 70, 100, 130, and 200 keV. Image noise, CT attenuation difference, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR) were also obtained in each algorithm. Comparisons of parameters between algorithms were performed. The best subjective image quality score and significantly lower image noise were observed for 130-keV virtual monochromatic images compared with conventional polychromatic images (all p < 0.001). Also, CT attenuation differences were significantly lower for both 100- and 130-keV virtual monochromatic images than for conventional polychromatic images (all p < 0.001). Meanwhile, the lowest differences in CT attenuation were observed for 100-keV virtual monochromatic images compared with conventional polychromatic images. However, there were no significant differences in CT attenuation between 100- and 130-keV virtual monochromatic images. SNR was similar between 130-keV virtual monochromatic images and conventional polychromatic images, although both SNR and CNR decreased as the energy level increased. Virtual monochromatic imaging reduced beam-hardening artifacts and improved image quality, and optimal evaluation of chest CT was best achieved at 100 and 130 keV.