Metal Artifact Research Articles

Applications of dual-energy CT in acute musculoskeletal and trauma imaging-a review.

Recent advances in computed tomography have resulted in new applications of CT scans in musculoskeletal imaging. Dual-energy CT technology involves the acquisition of data at high and low kilovolts, allowing differentiation and quantification of materials with different X-ray absorption. Newer CT scanners with a variety of post-processing options allow interesting applications of dual-energy CT in musculoskeletal and trauma imaging. This article provides an overview of the basic principles and physics of DECT. We review applications of DECT in the evaluation of the acute painful joint with suspicion of gout, metal artefact reduction in the prosthetic joint and in imaging of patients following major trauma. We present a review of literature and case examples to illustrate the strengths and limitations of this modality in the diagnosis of acute musculoskeletal conditions.

Differentiation of radicular cysts and radicular granulomas via texture analysis of multi-slice computed tomography images.

This study aimed to establish a method for differentiating radicular cysts from granulomas via texture analysis (TA) of multi-slice computed tomography (CT) images. A total of 222 lesions with multi-slice computed tomography images acquired at our hospital between 2013 and 2022 that were pathologically diagnosed were included in this study. Cases of contrast-enhanced images, severe metallic artifacts, and lesions that were not sufficiently large to be analyzed were excluded. The images were chronologically divided into a training group and a validation group. The radiological characteristics were determined. Subsequently, a TA was performed. Pyradiomics software was used for the TA of three-dimensionally segmented volumes extracted from 2-mm slice thickness images with a soft-tissue algorithm. Features that differed significantly between the two lesions in the training group were extracted and used to create machine-learning models. The discriminative ability of these models was evaluated in the validation group using receiver operating characteristic curve analysis. A total of 131 lesions, comprising 28 radicular cysts and 103 granulomas, were analyzed. Forty-three texture features that exhibited significant variations were extracted. A support vector machine and decision tree model, with areas under the curves of 0.829 and 0.803, respectively, were created. These models showed high discriminative abilities, even for the validation group, with areas under the curve of 0.727 and 0.701, respectively. Both models showed superior performance compared with that of the models based on radiographic findings. Discriminatory models were established for the TA of radicular cysts and granulomas using CT images.

The added effect of artifact reduction algorithm and ultra-low dose protocols on the accuracy of measurements obtained using Planmeca Viso G7 cone beam computed tomography

Objective The aim of this study is to evaluate the accuracy of linear and volumetric measurements using Planmeca Viso G7 cone beam computed tomography (CBCT) examinations acquired with ultra-low dose (ULD) and metal artifact reduction algorithm (ARA) protocols. Materials and methods Eight metallic spherical objects different in size with pre scanning diameter measurements using a calibrated digital caliper were fixed on a five dry human mandible. The real physical diameters and linear measurements between the metallic objects were measured. A CBCT acquisition was obtained four times with the same proper field of view, 150 μm and 100 Kv, in four scans using the Planmeca Viso G7 CBCT, machine acquisition was done with and without ARA, ULD, which is ARA, and ULD. Both acquisition protocols are inherited options in the Planmeca Viso G7 CBCT machine. All images were interpreted with the Planmeca Romexis software. Results Linear and volumetric measurements were found to have a nonstatistically significant difference with real measurements in the acquisition with ARA and ULD, but with a statistically significant difference with the other three acquisition sequences. Conclusions Using the ARA in combination with the ULD as an acquisition tool in the CBCT machine results in accurate linear and volumetric measurements, enhances image quality, and reduces metallic artifact with the lowest radiation dose.

The effect of MATLAB-based metal artifact reduction software on radiotherapy dose distribution

The effect of MATLAB-based metal artifact reduction software on radiotherapy dose distribution

Quality Assessment Radiotherapy Planning of Breast Cancer Patients with Built-In Metal Port Implants

Purpose: To evaluate the quality of radiation planning for breast cancer patients with implants with a built-in metal port. Conduct a quantitative analysis of the quality of planning, assess the dose load on critical organs for this category of patients.Material and methods: Homogeneity and conformity indices were calculated, and dose loads in critical organs were assessed for irradiation plans using 3D conformal RT (3D CRT) technology for 23 breast cancer patients with a built-in metal port implants. Calculations were carried out both taking into account (outlining) the metal port and artifacts from it on CT images, and without taking it into account.Results: Based on the results of the analysis of the calculated values of conformity and homogeneity indices, doses in critical organs of irradiation plans for 23 patients with breast cancer, it was shown that the presence of a metal port and artifacts from it affects the nature of the dose distribution.Conclusions: When creating a 3D CRT treatment plan, it is necessary to delineate the metal port and artifacts and assign true densities.

An image-based metal artifact reduction technique utilizing forward projection in computed tomography.

The projection data generated via the forward projection of a computed tomography (CT) image (FP-data) have useful potentials in cases where only image data are available. However, there is a question of whether the FP-data generated from an image severely corrupted by metal artifacts can be used for the metal artifact reduction (MAR). The aim of this study was to investigate the feasibility of a MAR technique using FP-data by comparing its performance with that of a conventional robust MAR using projection data normalization (NMARconv). The NMARconv was modified to make use of FP-data (FPNMAR). A graphics processing unit was used to reduce the time required to generate FP-data and subsequent processes. The performances of FPNMAR and NMARconv were quantitatively compared using a normalized artifact index (AIn) for two cases each of hip prosthesis and dental fillings. Several clinical CT images with metal artifacts were processed by FPNMAR. The AIn values of FPNMAR and NMARconv were not significantly different from each other, showing almost the same performance between these two techniques. For all the clinical cases tested, FPNMAR significantly reduced the metal artifacts; thereby, the images of the soft tissues and bones obscured by the artifacts were notably recovered. The computation time per image was ~ 56ms. FPNMAR, which can be applied to CT images without accessing the projection data, exhibited almost the same performance as that of NMARconv, while consuming significantly shorter processing time. This capability testifies the potential of FPNMAR for wider use in clinical settings.

Optimising total knee replacement imaging: a novel 3D printed PET/CT anthropomorphic phantom for metal artefact simulation

PurposeArthroplasty phantoms, including total knee replacement (TKR) phantoms, have been frequently used to test metal artefact reduction methods applied to positron emission tomography/computed tomography (PET/CT) images. These phantoms generally simulate either simple anatomical features or simple activity distribution around the metal inserts in the PET/CT scans. 3D printing has been used recently to fabricate fillable anthropomorphic phantoms that accurately simulate volume and geometry. This study aims to describe the process of image segmentation, phantom modelling, 3D printing and validation of a population-based fillable TKR phantom that simulates human TKR PET/CT metal artefacts.Methods10 participants (5 male and 5 female) were scanned using 3T MRI and the images were segmented to create average male and average female 3D knee models, inversely with void cortical and porous trabecular compartments for 3D printing and contrast media. Virtual total knee replacement (TKR) surgery was implemented on these models to prepare the insertion locations for knee prosthetic implants. Subsequently, TKR models were printed using a 3D photopolymer resin printer and then injected with normal saline to test the phantoms for any leaks. Subsequently, diluted iodinated contrast media was injected into the cortical compartment and saline with 18F-FDG was injected into the trabecular compartment and the phantom was scanned with PET/CT. The images were then evaluated and compared to the human knee radiographic features reported in the literature.ResultsPhantoms were shown to be fluid-tight with distinct compartments. They showed comparable volume and geometry to the segmented human MRI knees. The phantoms demonstrated similar values for x-ray attenuation and Hounsfield units (HU) to the literature for both cortical and trabecular compartments. The phantoms displayed a uniform distribution for the radioactive tracer, resembling that seen in human trabecular bone PET. TKR phantom PET/CT images with metal inserts replicated the clinical metal artefacts seen clinically in the periprosthetic area.ConclusionThis novel, 3D-printed, and customisable phantom effectively mimics the geometric, radiographic and radiotracer distribution features of real TKRs. Importantly, it simulates TKR image metal artefacts, making it suitable for repeatable and comprehensive evaluation of various metal artefact reduction methods in future research.

Accuracy of cone-beam computed tomography in imaging the components of the periodontal phenotype.

The components and dimensions of the periodontal and peri-implant phenotype have a high relevance in contemporary dental research and should be taken into consideration in the decision-making process in the management of a variety of clinical scenarios to optimize the outcomes of therapy. Various assessment methods for quantifying and classifying the phenotypical dimensions have emerged and developed in recent decades. Nevertheless, the use of cone-beam computed tomography (CBCT) scans remains the most commonly used approach worldwide. However, the accuracy to adequately imaging and measuring the dimensions of the hard and soft tissue components around teeth may represent a significant challenge in different clinical scenarios due to factors such as the age of the patient and motion during the scan, presence of metallic artifacts causing streaks and gray-value distortion, overlapping of soft tissue structures, machine performance, file processing, and small voxel size among others. These factors pose a particular challenge when tiny structures are under investigation, for example, the buccal/lingual bony or soft tissue layer of lower/upper incisors. Therefore, this review addresses the underlying technical information of the use of CBCT scans, and suggests some recommendations on the utilization of this method of assessment to optimally use it despite its' system-inherent limitations.

Semi-supervised segmentation of metal-artifact contaminated industrial CT images using improved CycleGAN.

Accurate segmentation of industrial CT images is of great significance in industrial fields such as quality inspection and defect analysis. However, reconstruction of industrial CT images often suffers from typical metal artifacts caused by factors like beam hardening, scattering, statistical noise, and partial volume effects. Traditional segmentation methods are difficult to achieve precise segmentation of CT images mainly due to the presence of these metal artifacts. Furthermore, acquiring paired CT image data required by fully supervised networks proves to be extremely challenging. To address these issues, this paper introduces an improved CycleGAN approach for achieving semi-supervised segmentation of industrial CT images. This method not only eliminates the need for removing metal artifacts and noise, but also enables the direct conversion of metal artifact-contaminated images into segmented images without the requirement of paired data. The average values of quantitative assessment of image segmentation performance can reach 0.96645 for Dice Similarity Coefficient(Dice) and 0.93718 for Intersection over Union(IoU). In comparison to traditional segmentation methods, it presents significant improvements in both quantitative metrics and visual quality, provides valuable insights for further research.

Image Quality Enhancement for Digital Breast Tomosynthesis: High-Density Object Artifact Reduction.

Breast cancer has a high incidence and mortality rate among women, early diagnosis is essential as it gives insight regarding the most appropriate therapeutic strategy for each case. Among all imaging diagnostic methods, digital breast tomosynthesis (DBT) is effective for early breast cancer detection. In DBT images, high-density object artifacts are generated when imaging objects with high X-ray absorptivity, which include metal artifacts, ripple artifacts, and deformation artifacts. In this study, we analyze the causes of these artifacts and propose a set of high-density object reconstruction methods based on iterative algorithms. Our method includes a reprojection-based high-density object projection data segmentation algorithm and an iterative reconstruction algorithm based on volume expansion. The experiments on simulation data and the human breast data with artificial surgical needles prove the effectiveness of our method. By using our algorithm, the problem of distorting the shape, size, and position of high-density objects during DBT reconstruction is raised, the influence of these artifacts is reduced, and the quality of the DBT reconstructed image is improved. We hope that our algorithm might contribute to promoting the usage of DBT.

Improving the quality of computed tomography brain images in the presence of cochlear implant induced metal artefacts through the additional use of tissue mimicking materials alongside metal artefact reduction software

IntroductionMetal artefact reduction software (MAR) can be used to improve Computed Tomography (CT) image quality in the presence of implanted metalwork; however, this software is not effective for superficial metallic structures such as cochlear implants (CI).This study aimed to investigate whether the effectiveness of MAR software could be improved for brain scans with CI present through the use of tissue mimicking materials (TMM) placed exteriorly to the implant. MethodsIn this two-part study, a CI was positioned on the surface of water and anthropomorphic phantoms and imaged using a helical CT brain protocol. Three TMM, Superflab, Sure Thermal heat packs, and Bart's Bolus, were utilised and images were acquired to assess the resulting artefact reduction in terms of CT numbers, noise and artefact index (Aind). Changes in CTDIvol were assessed for the anthropomorphic phantom scans. ResultsIn the water phantom, statistically significant reductions in CT number (p = 0.038) and noise (p = 0.033) were observed for Superflab, whilst the heat packs produced similar significant reductions in CT number (p < 0.001) and noise (p = 0.001) for the anthropomorphic phantom images. Aind values were significantly reduced through the use of Superflab (p = 0.009) and the heat packs (p < 0.001). No significant effects were observed for Bart's Bolus. CTDIvol increases of generally less than 5% were observed for scans with TMM in place. ConclusionThe additional use of TMM alongside MAR software yielded statistically significant reductions in CI induced metal artefacts on both water and anthropomorphic phantom scans with minimal dose increases. Implications for practiceThe extent of metal artefacts in clinical head scans with CI in place could be significantly reduced through combined use of TMM and MAR software, consequently providing greater diagnostic confidence in the images.

ANCIENT EGYPTIAN METAL ARTIFACTS: LASTING FOR THOUSANDS OF YEARS AGAINST CORROSION

Metals were used to make artifacts and medical tools in ancient times. This review article focuses on the gold and silver metal artifacts of the ancient Egyptian and their protection against corrosion. There is no doubt that Egypt is an open museum because the ancient Egyptians planted the monuments everywhere in the deserts. There are many types of artifacts, such as statues, jewelries, furniture, weapons, paints, etc. They have used different types of materials to make all these monuments, such as marbles, wood, stones, metals. They have used different types of metals, such as gold, silver, iron, and copper. The museums in Egypt accommodate huge number of metals artifacts. Ancient Egyptian produced fine and gorgeous artifacts, especially rings, bracelets, and necklaces. The artifacts were created to be resistant to degradation and corrosion over a long period of time. They have used different ways of protection, such as paints, alloying, chemicals etc.

Photon-Counting Detector CT Virtual Monoenergetic Images in Cervical Trauma Imaging-Optimization of Dental Metal Artifacts and Image Quality.

The aim of this study was to analyze the extent of dental metal artifacts in virtual monoenergetic (VME) images, as they often compromise image quality by obscuring soft tissue affecting vascular attenuation reducing sensitivity in the detection of dissections. Neck photon-counting CT datasets of 50 patients undergoing contrast-enhanced trauma CT were analyzed. Hyperattenuation and hypoattenuation artifacts, muscle with and without artifacts and vessels with and without artifacts were measured at energy levels from 40 keV to 190 keV. The corrected artifact burden, corrected image noise and artifact index were calculated. We also assessed subjective image quality on a Likert-scale. Our study showed a lower artifact burden and less noise in artifact-affected areas above the energy levels of 70 keV for hyperattenuation artifacts (conventional polychromatic CT images 1123 ± 625 HU vs. 70 keV VME 1089 ± 733 HU, p = 0.125) and above of 80 keV for hypoattenuation artifacts (conventional CT images -1166 ± 779 HU vs. 80 keV VME -1170 ± 851 HU, p = 0.927). Vascular structures were less hampered by metal artifacts than muscles (e.g., corrected artifact burden at 40 keV muscle 158 ± 125 HU vs. vessels -63 ± 158 HU p < 0.001), which was also reflected in the subjective image assessment, which showed better ratings at higher keV values and overall better ratings for vascular structures than for the overall artifact burden. Our research suggests 70 keV might be the best compromise for reducing metal artifacts affecting vascular structures and preventing vascular contrast if solely using VME reconstructions. VME imaging shows only significant effects on the general artifact burden. Vascular structures generally experience fewer metal artifacts than soft tissue due to their greater distance from the teeth, which are a common source of such artifacts.

Image quality and metal artifact reduction in total hip arthroplasty CT: deep learning-based algorithm versus virtual monoenergetic imaging and orthopedic metal artifact reduction

BackgroundTo compare image quality, metal artifacts, and diagnostic confidence of conventional computed tomography (CT) images of unilateral total hip arthroplasty patients (THA) with deep learning-based metal artifact reduction (DL-MAR) to conventional CT and 130-keV monoenergetic images with and without orthopedic metal artifact reduction (O-MAR).MethodsConventional CT and 130-keV monoenergetic images with and without O-MAR and DL-MAR images of 28 unilateral THA patients were reconstructed. Image quality, metal artifacts, and diagnostic confidence in bone, pelvic organs, and soft tissue adjacent to the prosthesis were jointly scored by two experienced musculoskeletal radiologists. Contrast-to-noise ratios (CNR) between bladder and fat and muscle and fat were measured. Wilcoxon signed-rank tests with Holm-Bonferroni correction were used.ResultsSignificantly higher image quality, higher diagnostic confidence, and less severe metal artifacts were observed on DL-MAR and images with O-MAR compared to images without O-MAR (p < 0.001 for all comparisons). Higher image quality, higher diagnostic confidence for bone and soft tissue adjacent to the prosthesis, and less severe metal artifacts were observed on DL-MAR when compared to conventional images and 130-keV monoenergetic images with O-MAR (p ≤ 0.014). CNRs were higher for DL-MAR and images with O-MAR compared to images without O-MAR (p < 0.001). Higher CNRs were observed on DL-MAR images compared to conventional images and 130-keV monoenergetic images with O-MAR (p ≤ 0.010).ConclusionsDL-MAR showed higher image quality, diagnostic confidence, and superior metal artifact reduction compared to conventional CT images and 130-keV monoenergetic images with and without O-MAR in unilateral THA patients.Relevance statementDL-MAR resulted into improved image quality, stronger reduction of metal artifacts, and improved diagnostic confidence compared to conventional and virtual monoenergetic images with and without metal artifact reduction, bringing DL-based metal artifact reduction closer to clinical application.Key points• Metal artifacts introduced by total hip arthroplasty hamper radiologic assessment on CT.• A deep-learning algorithm (DL-MAR) was compared to dual-layer CT images with O-MAR.• DL-MAR showed best image quality and diagnostic confidence.• Highest contrast-to-noise ratios were observed on the DL-MAR images.Graphical

Nonconvex weighted variational metal artifacts removal via convergent primal-dual algorithms

Direct reconstruction through filtered back projection engenders metal artifacts in polychromatic computed tomography images, attributed to highly attenuating implants, which further poses great challenges for subsequent image analysis. Inpainting the metal trace directly in the Radon domain for the extant variational method leads to strong edge diffusion and potential inherent artifacts. With normalization based on pre-segmentation, the inpainted outcome can be notably ameliorated. However, its reconstructive fidelity is heavily contingent on the precision of the pre-segmentation, and highly accurate segmentation of images with metal artifacts is non-trivial in actuality. In this paper, we propose a nonconvex weighted variational approach for metal artifact reduction. Specifically, in lieu of employing a binary function with zeros in the metal trace, an adaptive weight function is designed in the Radon domain, with zeros in the overlapping regions of multiple disjoint metals as well as areas of highly attenuated projections, and the inverse square root of the measured projection in other regions. A nonconvex L1−αL2 regularization term is incorporated to further enhance edge contrast, alongside a box-constraint in the image domain. Efficient first-order primal-dual algorithms, proven to be globally convergent and of low computational cost owing to the closed-form solution of all subproblems, are devised to resolve such a constrained nonconvex model. Both simulated and real experiments are conducted with comparisons to other variational algorithms, validating the superiority of the presented method. Especially in comparison to Reweighted JSR, our proposed algorithm can curtail the total computational cost to at most one-third, and for the case of inaccurate pre-segmentation, the recovery outcomes by the proposed algorithms are notably enhanced.

A kV–MV approach to CBCT metal artifact reduction using multi-layer MV-CBCT

Objective. To demonstrate that complete cone beam CT (CBCT) scans from both MV-energy and kV-energy LINAC sources can reduce metal artifacts in radiotherapy guidance, while maintaining standard-of-care x-ray doses levels. Approach. MV-CBCT and kV-CBCT scans are acquired at half normal dose. The impact of lowered dose on MV-CBCT data quality is mitigated by the use of a 4-layer MV-imager prototype and reduced LINAC energy settings (2.5 MV) to improve photon capture. Additionally, the MV-CBCT is used to determine the 3D position and pose of metal implants, which in turn is used to guide model-based poly-energetic correction and interleaving of the kV-CBCT and MV-CBCT data. Certain edge-preserving regularization steps incorporated into the model-based correction algorithm further reduce MV data noise. Main results. The method was tested in digital phantoms and a real pelvis phantom with large 2.5″ spherical inserts, emulating hip replacements of different materials. The proposed method demonstrated an appealing compromise between the high contrast of kV-CBCT and low artifact content of MV-CBCT. Contrast-to-noise improved 3-fold compared to MV-CBCT with a clinical 1-layer architecture at matched dose (37 mGy) and edge blur levels. Visual delineation of the bladder and prostate improved noteably over kV- or MV-CBCT alone. Significance. The proposed method demonstrates that a full MV-CBCT scan can be combined with kV-CBCT to reduce metal artifacts without resorting to complicated beam collimation strategies to limit the MV-CBCT dose contribution. Additionally, significant improvements in CNR can be achieved as compared to metal artifact reduction through current clinical MV-CBCT practices.

Needle artifact reduction during interventional CT procedures using a silver filter

BackgroundMAR algorithms have not been productized in interventional imaging because they are too time-consuming. Application of a beam hardening filter can mitigate metal artifacts and doesn’t increase computational burden. We evaluate the ability to reduce metal artifacts of a 0.5 mm silver (Ag) additional filter in a Multidetector Computed Tomography (MDCT) scanner during CT-guided biopsy procedures.MethodsA biopsy needle was positioned inside the lung field of an anthropomorphic phantom (Lungman, Kyoto Kagaku, Kyoto, Japan). CT acquisitions were performed with beam energies of 100 kV, 120 kV, 135 kV, and 120 kV with the Ag filter and reconstructed using a filtered back projection algorithm. For each measurement, the CTDIvol was kept constant at 1 mGy. Quantitative profiles placed in three regions of the artifact (needle, needle tip, and trajectory artifacts) were used to obtain metrics (FWHM, FWTM, width at − 100 HU, and absolute error in HU) to evaluate the blooming artifact, artifact width, change in CT number, and artifact range. An image quality analysis was carried out through image noise measurement. A one-way analysis of variance (ANOVA) test was used to find significant differences between the conventional CT beam energies and the Ag filtered 120 kV beam.ResultsThe 120 kV-Ag is shown to have the shortest range of artifacts compared to the other beam energies. For needle tip and trajectory artifacts, a significant reduction of − 53.6% (p < 0.001) and − 48.7% (p < 0.001) in the drop of the CT number was found, respectively, in comparison with the reference beam of 120 kV as well as a significant decrease of up to − 34.7% in the artifact width (width at − 100 HU, p < 0.001). Also, a significant reduction in the blooming artifact of − 14.2% (FWHM, p < 0.001) and − 53.3% (FWTM, p < 0.001) was found in the needle artifact. No significant changes (p > 0.05) in image noise between the conventional energies and the 120 kV-Ag were found.ConclusionsA 0.5 mm Ag additional MDCT filter demonstrated consistent metal artifact reduction generated by the biopsy needle. This reduction may lead to a better depiction of the target and surrounding structures while maintaining image quality.

Effect of metal artifact reduction level on the assessment of dental implant positioning by cone-beam computed tomography.

This study evaluated the effect of metal artifact reduction (MAR) level and tube current on the assessment of dental implant positioning relative to the mandibular canal (MC) through cone-beam computed tomography (CBCT). Titanium dental implants were placed in dried mandibles at 0.5 mm superior to the MC (Group 1/n = 8), 0.5 mm inside the MC with perforation of the cortex (Group 2/n = 10). CBCT scans were obtained with different levels of MAR (off, medium and high) and two tube currents (4 mA and 8 mA). Four examiners analyzed the images and scored the contact between the implant and the MC using a 5-point scale. Sensitivity, specificity, area under receiver operating characteristic curve (ROC) and frequency of scores were calculated. Data were compared with ANOVA two-way and Tukey's test and scores with Chi-Square test. Specificity and area under ROC curve decreased significantly when MAR level was high compared with MAR-medium and MAR-off. The frequency of score 3 (inconclusive) was the highest, and scores 1 and 5 (definitely no contact and definitely contact, respectively) were the lowest with MAR-high, regardless of the tube current. When MAR was off, there were higher frequencies of scores 1 and 5. The level of MAR influences the assessment of the relationship between the dental implant and the MC. MAR-high led to lower diagnostic accuracy compared with MAR-medium and off. This paper shows that high level of MAR can interfere in the diagnostic of dental implant positioning relative to the mandibular canal, decreasing its accuracy.

Dual-energy computed tomography imaging with megavoltage and kilovoltage X-ray spectra.

Single-energy computed tomography (CT) often suffers from poor contrast yet remains critical for effective radiotherapy treatment. Modern therapy systems are often equipped with both megavoltage (MV) and kilovoltage (kV) X-ray sources and thus already possess hardware for dual-energy (DE) CT. There is unexplored potential for enhanced image contrast using MV-kV DE-CT in radiotherapy contexts. A single-line integral toy model was designed for computing basis material signal-to-noise ratio (SNR) using estimation theory. Five dose-matched spectra (3kV, 2 MV) and three variables were considered: spectral combination, spectral dose allocation, and object material composition. The single-line model was extended to a simulated CT acquisition of an anthropomorphic phantom with and without a metal implant. Basis material sinograms were computed and synthesized into virtual monoenergetic images (VMIs). MV-kV and kV-kV VMIs were compared with single-energy images. The 80kV-140kV pair typically yielded the best SNRs, but for bone thicknesses , the detunedMV-80kV pair surpassed it. Peak MV-kV SNR was achieved with dose allocated to the MV spectrum. In CT simulations of the pelvis with a steel implant, MV-kV VMIs yielded a higher contrast-to-noise ratio (CNR) than single-energy CT and kV-kV DE-CT. Without steel, the MV-kV VMIs produced higher contrast but lower CNR than single-energy CT. This work analyzes MV-kV DE-CT imaging and assesses its potential advantages. The technique may be used for metal artifact correction and generation of VMIs with higher native contrast than single-energy CT. Improved denoising is generally necessary for greater CNR without metal.

The Use of Portable, Very Low-field (0.064T) MRI to Image Cochlear Implants: Metallic Image Artifact in Comparison to Traditional, Stationary 3T MRI.

To assess image artifact when imaging a cochlear implant (CI) with a conventional 3T MRI machine compared with a very low-field (0.064T) MRI. None. Diagnostic study. Image artifact size associated with the CI affixed to an MRI phantom at very low-field 0.064T MRI versus 3T MRI. The longest diameter of the image artifact was 125 mm for the 3T MRI and 86 mm for the 0.064T MRI, representing 45% longer image artifact generated in the 3T MRI. The actual volume of the imaging phantom was 1371 cm3. The volume of the image artifact was measured as 379 cm3 in the 3T MRI, representing a loss of 27.6% of the actual volume of the imaging phantom. The volume of image artifact was measured as 170 cm3 in the 0.064T MRI, representing a loss of 12.4% of the phantom volume. 3T MRI had better image quality. This result was not surprising given that larger magnetic field strength is known to provide higher resolution. There was 15% less image artifact generated in the very low-field MRI machine compared with a conventional 3T device. And there was also subjectively increased distortion of the imaging phantom at 3T MRI compared with the 0.064T MRI. With minimized safety concerns and a much lower cost than conventional 3T machines, very low-field scanners may find expanded clinical uses. This preclinical study explores the potential utility of very low-field MRI in scanning CI recipients.