The ability of dual- and multi-energy CT to differentiate materials of different effective atomic numbers makes possible several new and clinically relevant CT applications.

Dual- and Multi-Energy CT: Principles, Technical Approaches, and Clinical Applications

Artefacts are common in today's cone beam CT (CBCT). They are induced by discrepancies between the mathematical modelling and the actual physical imaging process. Since artefacts may interfere with the diagnostic process performed on CBCT data sets, every user should be aware of their presence. This article aims to discuss the most prominent artefacts identified in the scientific literature and review the existing knowledge on these artefacts. We also briefly review the basic three-dimensional (3D) reconstruction concept applied by today's CBCT scanners, as all artefacts are more or less directly related to it.

/pdf/artefacts-in-cbct-a-review-20vg8vej3u.pdf

Artefacts in CBCT: a review

Artifacts are commonly encountered in clinical CT and may obscure or simulate pathology. There are many different types of CT artifacts, including noise, beam hardening, scatter, pseudoenhancement, motion, cone-beam, helical, ring and metal artifacts. We review the cause and appearance of each type of artifact, correct some popular misconceptions and describe modern techniques for artifact reduction. Noise can be reduced using iterative reconstruction or by combining data from multiple scans. This enables lower radiation dose and higher resolution scans. Metal artifacts can also be reduced using iterative reconstruction, resulting in a more accurate diagnosis. Dual- and multi-energy (photon counting) CT can reduce beam hardening and provide better tissue contrast. Methods for reducing noise and out-of-field artifacts may enable ultra-high resolution limited field of view imaging of tumors and other structures.

/pdf/ct-artifacts-causes-and-reduction-techniques-3km19o9ami.pdf

CT artifacts: Causes and reduction techniques

Purpose: While modern clinical CT scanners under normal circumstances produce high quality images, severe artifacts degrade the image quality and the diagnostic value if metal prostheses or other metal objects are present in the field of measurement. Standard methods for metal artifact reduction (MAR) replace those parts of the projection data that are affected by metal (the so-called metal trace or metal shadow) by interpolation. However, while sinogram interpolation methods efficiently remove metal artifacts, new artifacts are often introduced, as interpolation cannot completely recover the information from the metal trace. The purpose of this work is to introduce a generalized normalization technique for MAR, allowing for efficient reduction of metal artifacts while adding almost no new ones. The method presented is compared to a standard MAR method, as well as MAR using simple length normalization.

Methods: In the first step, metal is segmented in the image domain by thresholding. A 3D forward projection identifies the metal trace in the original projections. Before interpolation, the projections are normalized based on a 3D forward projection of a prior image. This prior image is obtained, for example, by a multithreshold segmentation of the initial image. The original rawdata are divided by the projection data of the prior image and, after interpolation, denormalized again. Simulations and measurements are performed to compare normalized metal artifact reduction (NMAR) to standard MAR with linear interpolation and MAR based on simple length normalization.

Results: Promising results for clinical spiral cone-beam data are presented in this work. Included are patients with hip prostheses, dental fillings, and spine fixation, which were scanned at pitch values ranging from 0.9 to 3.2. Image quality is improved considerably, particularly for metal implants within bone structures or in their proximity. The improvements are evaluated by comparing profiles through images and sinograms for the different methods and by inspecting ROIs. NMAR outperforms both other methods in all cases. It reduces metal artifacts to a minimum, even close to metal regions. Even for patients with dental fillings, which cause most severe artifacts, satisfactory results are obtained with NMAR. In contrast to other methods, NMAR prevents the usual blurring of structures close to metal implants if the metal artifacts are moderate.

Conclusions: NMAR clearly outperforms the other methods for both moderate and severe artifacts. The proposed method reliably reduces metal artifacts from simulated as well as from clinical CT data. Computationally efficient and inexpensive compared to iterative methods, NMAR can be used as an additional step in any conventional sinogram inpainting-based MAR method.

Normalized metal artifact reduction (NMAR) in computed tomography

OBJECTIVE. We summarize how virtual monochromatic images are synthesized from dual-energy CT using image-domain and projection-domain methods. The quality of virtual monochromatic images is compared with that of polychromatic single-energy images acquired at different tube potentials and the same radiation dose. Clinical applications of dual-energy CT–based virtual monochromatic imaging are reviewed, including beam-hardening correction, contrast and noise optimization, metal artifact reduction, and material differentiation. CONCLUSION. Virtual monochromatic images synthesized from dual-energy CT data have the potential to reduce beam-hardening artifacts and to provide quantitative measurements. If there is no desire to obtain material-specific information or to correct for metal or beam-hardening artifacts from the dual-energy data, however, it is better to perform a conventional single-energy scan at the optimal tube potential.

https://www.ajronline.org/doi/pdfplus/10.2214/AJR.12.9121

Dual-Energy CT–Based Monochromatic Imaging

Purpose: Due to x-ray beam polychromaticity and scattered radiation, attenuation measurements tend to be underestimated. Cupping and beam hardening artifacts become apparent in the reconstructed CT images. If only one material such as water, for example, is present, these artifacts can be reduced by precorrecting the rawdata. Higher order beam hardening artifacts, as they result when a mixture of materials such as water and bone, or water and bone and iodine is present, require an iterative beam hardening correction where the image is segmented into different materials and those are forward projected to obtain new rawdata. Typically, the forward projection must correctly model the beam polychromaticity and account for all physical effects, including the energy dependence of the assumed materials in the patient, the detector response, and others. We propose a new algorithm that does not require any knowledge about spectra or attenuation coefficients and that does not need to be calibrated. The proposed method corrects beam hardening in single energy CT data. Methods: The only a priori knowledge entering EBHC is the segmentation of the object into different materials. Materials other than water are segmented from the original image, e.g., by using simple thresholding. Then, a (monochromatic) forward projectionmore » of these other materials is performed. The measured rawdata and the forward projected material-specific rawdata are monomially combined (e.g., multiplied or squared) and reconstructed to yield a set of correction volumes. These are then linearly combined and added to the original volume. The combination weights are determined to maximize the flatness of the new and corrected volume. EBHC is evaluated using data acquired with a modern cone-beam dual-source spiral CT scanner (Somatom Definition Flash, Siemens Healthcare, Forchheim, Germany), with a modern dual-source micro-CT scanner (TomoScope Synergy Twin, CT Imaging GmbH, Erlangen, Germany), and with a modern C-arm CT scanner (Axiom Artis dTA, Siemens Healthcare, Forchheim, Germany). A large variety of phantom, small animal, and patient data were used to demonstrate the data and system independence of EBHC. Results: Although no physics apart from the initial segmentation procedure enter the correction process, beam hardening artifacts were significantly reduced by EBHC. The image quality for clinical CT, micro-CT, and C-arm CT was highly improved. Only in the case of C-arm CT, where high scatter levels and calibration errors occur, the relative improvement was smaller. Conclusions: The empirical beam hardening correction is an interesting alternative to conventional iterative higher order beam hardening correction algorithms. It does not tend to over- or undercorrect the data. Apart from the segmentation step, EBHC does not require assumptions on the spectra or on the type of material involved. Potentially, it can therefore be applied to any CT image.« less

Empirical beam hardening correction (EBHC) for CT.

In flat-detector CT, imperfect or defect detector elements may cause concentric ring artifacts due to their continuous over- or underestimation of attenuation values, which often disturb image quality. Especially due to the demand for high-spatial resolution images and the necessary pixel read-out without arbitrary pixel-binning, ring artifacts become more pronounced and the reduction of these artifacts becomes a necessity. We here present a comparison of two dedicated ring artifact correction methods for flat-detector CT, on the basis of different median and mean filterings of the reconstructed image but each working in different geometric planes. While the first method works in Cartesian coordinates, the second method performs a transformation to polar coordinates. Both post-processing methods efficiently reduce ring artifacts in the reconstructed images and improve image quality. The transformation to polar coordinates turned out to be a necessary step for efficient ring artifact correction, since correction in Cartesian coordinates suffers from newly introduced artifacts as well as insufficient correction of artifacts close to the center of rotation.

http://iopscience.iop.org/article/10.1088/0031-9155/54/12/018/pdf

Comparison of ring artifact correction methods for flat-detector CT

BACKGROUND AND PURPOSE: Metallic implants induce massive artifacts in CT images which deteriorate image quality and often superimpose structures of interest. The purpose of this study was to apply and evaluate a dedicated MAR method for neuroradiologic intracranial clips and detachable platinum coiling events. We here report the first clinical results for MAR in FDCT. MATERIALS AND METHODS: FDCT volume scans of several patients treated with endovascular coiling or intracranial clipping were corrected by using a dedicated FDCT MAR correction algorithm combined with an edge-preserving attenuation-normalization method in the projection space. Corrected and uncorrected images were compared by 2 experienced radiologists and evaluated for several image-quality features. RESULTS: After application of our algorithm, implant delineation and visibility were highly improved. CT values compared with values in metal artifact−unaffected areas showed good agreement (average correction of 1300 HU). Image noise was reduced overall by 27%. Intracranial hemorrhage in the direct surroundings of the implanted coil or clip material was displayed without worrisome metal artifacts, and our algorithm even allowed diagnosis in areas where extensive information losses were seen. The high spatial resolution provided by FDCT imaging was well preserved. CONCLUSIONS: Our MAR method provided metal artifact−reduced images in every studied case. It reduced image noise and corrected CT values to levels comparable with images measured without metallic implants. An overall improvement of brain tissue modeling and implant visibility was achieved. MAR in neuroradiologic FDCT imaging is a promising step forward for better image quality and diagnosis in the presence of metallic implants.

http://www.ajnr.org/content/ajnr/31/4/634.full.pdf

Metal artifact reduction for clipping and coiling in interventional C-arm CT.

In high-resolution micro CT using flat detectors (FD), imperfect or defect detector elements may cause concentric-ring artifacts due to their continuous over- or underestimation of attenuation values, which often disturb image quality. We here present a dedicated image-based ring artifact correction method for high-resolution micro CT, based on median filtering of the reconstructed image and working on a transformed version of the reconstructed images in polar coordinates. This post-processing method reduced ring artifacts in the reconstructed images and improved image quality for phantom and in in vivo scans. Noise and artifacts were reduced both in transversal and in multi-planar reformations along the longitudinal axis.

https://iopscience.iop.org/article/10.1088/0031-9155/54/17/N02/pdf

Ring artifact correction for high-resolution micro CT.

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.

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

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