Metal Artifact Reduction Algorithm Research Articles

Advanced Imaging of Total Knee Arthroplasty.

The prevalence of total knee arthroplasty (TKA) is increasing with the aging population. Although long-term results are satisfactory, suspected postoperative complications often require imaging with the implant in place. Advancements in computed tomography (CT), such as tin prefiltration, metal artifact reduction algorithms, dual-energy CT with virtual monoenergetic imaging postprocessing, and the application of cone-beam CT and photon-counting detector CT, allow a better depiction of the tissues adjacent to the metal. For magnetic resonance imaging (MRI), high bandwidth (BW) optimization, the combination of view angle tilting and high BW, as well as multispectral imaging techniques with multiacquisition variable-resonance image combination or slice encoding metal artifact correction, have significantly improved imaging around metal implants, turning MRI into a useful clinical tool for patients with suspected TKA complications.

Effect of a metal artifact reduction algorithm on dehiscence and fenestration detection around zirconia implants with cone beam computed tomography

ObjectiveTo assess the efficacy of the metal artifact reduction algorithm (MARA) of the Cranex 3D cone beam computed tomography (CBCT) device in the detection of peri-implant dehiscence and fenestration around zirconia implants. Study designIn total, 60 implants were placed in bovine ribs. Dehiscence and fenestration defects were created around the implants, after which 60 CBCT images were obtained with and 60 without activation of MARA. Three radiologists examined the images for the presence of defects. The area under the curve (AUC) from receiver operating characteristic analysis, sensitivity, and specificity were calculated to assess the ability to discriminate the presence vs. absence of bone defects. One-way analysis of variance was employed to analyze outcomes measures. The significance level was established at 5% (α = 0.05). ResultsAUC values indicated excellent discrimination of dehiscence on images with MARA activation and an excellent to outstanding range of discrimination with MARA deactivation. For fenestration, MARA activation and deactivation both led to outstanding discrimination. Sensitivity and specificity values revealed that activation of MARA was helpful in distinguishing the presence vs. absence of dehiscence, while both MARA conditions were helpful for fenestration. However, there were no statistically significant differences between MARA activation and deactivation for any outcome measure (P>0.05). ConclusionCBCT is suitable for detecting peri-implant defects, but MARA application does not significantly affect peri-implant dehiscence and fenestration detection. Statement of Clinical RelevanceEarly diagnosis of defects in cortical bone around zirconia dental implants is important for maintaining function and aesthetics. Cone beam computed tomography is suitable for detecting peri-implant defects, but metal artifact reduction algorithms do not significantly affect diagnostic outcomes.

Improvement of metal artifact reduction in dental CBCT using a CdTe photon-counting detector: Simulation study

In dental cone-beam computed tomography (CBCT), the image quality often degrades when patients have metallic objects such as metal implants and/or metal prostheses. Metal artifacts typically appear as streaks and shadows in the reconstructed CT images, limiting their clinical usefulness. Although various metal artifact reduction (MAR) methods are used in dental CBCT, no algorithm that can robustly remove metal artifacts has been universally accepted. Recent research has explored the potential benefits of using of a photon-counting detector (PCD) to advance enhanced MAR. PCD can classify x-ray photons into several different energy bins, allowing for more precise measurements of x-ray attenuation. Therefore, in this study, we propose a new MAR method based on the use of a PCD, named the high-energy trace normalized-MAR (HT-NMAR) algorithm, to ensure improved image quality. The proposed MAR algorithm consists of three main steps: 1) Segmentation of the metal trace using a high-energy binned sinogram, 2) Generation of a residual artifact-reduced prior, 3) Sinogram completion with the segmented metal trace and the prior, followed by CBCT reconstruction. We conducted a simulation on a numerical head phantom with metal inserts using a PCD simulation toolkit to demonstrate its efficacy. Our simulation study indicates that the proposed MAR method considerably reduces metal artifacts in CBCT and shows a better image performance than other existing MAR methods in reducing streak artifacts without any contrast anomaly.

Do metal artifact reduction algorithms influence the detection of implant-related injuries to the inferior alveolar canal in CBCT images?

BackgroundThe routine application of dental implants for replacing missing teeth has revolutionized restorative and prosthetic dentistry. However, cone beam computed tomography (CBCT) evaluations of structures adjacent to the implants are limited by metal artifacts. There are several methods for reducing metal artifacts, but this remains a challenging task. This study aimed to examine the effectiveness of metal artifact reduction (MAR) algorithms in identifying injuries of implants to the inferior alveolar canal in CBCT images.MethodIn this in vitro study, mono-cortical bone windows were created and the inferior alveolar canal was revealed. Using 36 implants, pilot drill and penetration damage of the implant tip into the canal was simulated and compared to the control implants with distance from the canal. CBCT images were evaluated by four experienced observers with and without the MAR algorithm and compared to direct vision as the gold standard. The values of accuracy, sensitivity, and specificity were obtained and compared by receiver operating characteristic (ROC) curve (α = 0.05).ResultThe area under the ROC curve values for detection of pilot drill injuries varied between 0.840–0.917 and 0.639–0.854 in the active and inactive MAR conditions, respectively. The increase in ROC area was only significant for one of the observers (P = 0.010). For diagnosing penetrative injuries, the area under the ROC curve values was between 0.990–1.000 and 0.722–1.000 in the active and inactive MAR conditions, respectively. The improvement of ROC curve values in active MAR mode was only significant for one of the observers (P = 0.006).ConclusionActivation of MAR improved the diagnostic values of CBCT images in detecting both types of implant-related injuries to the inferior alveolar canal. However, for most observers, this increase was not statistically significant.

Severe metallosis following catastrophic failure of total shoulder arthroplasty - a case report.

Metallosis is an unusual but consequential complication arising from orthopedic hardware implantation, characterized by the deposition of metallic particles in the periprosthetic soft tissues. The incidence of metallosis associated with shoulder arthroplasties is exceptionally rare since the shoulder is not a weight-bearing joint, making it less susceptible to mechanical wear and, consequently, to conditions like particle disease and metallosis. Nevertheless, anomalous metal-on-metal interactions can develop in total shoulder arthroplasties if the polyethylene component fails due to wear, fracture, or dissociation. If left unaddressed, metallosis can incite an adverse immune-mediated local tissue response, culminating in joint destruction and adjacent soft tissues and muscle necrosis.In this case report, the diagnosis of metallosis was made in a patient with an anatomic total shoulder arthroplasty using a state-of-the-art photon counting detector CT supplemented by post-processing metal artifact reduction algorithms. This advanced imaging approach was effective in discerning the source of implant failure and in identifying manifestations of severe metallosis including osteolysis and pseudotumor formation. Advanced imaging methods can accurately characterize the severity and extent of metallosis, thereby helping guide surgical planning to mitigate serious complications associated with this condition.

A Quantitative Evaluation of the Effectiveness of the Metal Artifact Reduction Algorithm in Cone Beam Computed Tomographic Images with Stainless Steel Orthodontic Brackets and Arch Wires: An Ex Vivo Study.

The presence of high-density and high-atomic number materials results in the generation of artifacts in cone beam computed tomographic (CBCT) images. To minimize artifacts in CBCT images, the metal artifact reduction (MAR) tool was developed. This study aims to quantitatively evaluate the effectiveness of the MAR algorithm in CBCT images of teeth with stainless steel orthodontic brackets with or without arch wires in buccal and lingual positions obtained using the Galileos Sirona CBCT scanner. In this in vitro study, 20 stainless steel brackets were attached to the maxillary dentition from the right second premolar to the left second premolar teeth of a human skull. In the first group, 10 brackets were bonded to the buccal surface, and in the second group, 10 brackets were bonded to the palatal surface of these teeth. CBCT scans were obtained for each group with or without orthodontic stainless steel wires using a Galileos Sirona CBCT scanner with exposure parameters of 85 kVp and 21 mAs. CBCT images were obtained two times with and two times without MAR activation. The DICOM format of the CBCT images was imported to ImageJ software (version 1.54), and the contrast-to-noise ratio (CNR) was calculated and compared for each bracket in 15 and 20 mm distances and 20, 40, and 90 degrees on each side. Statistical analysis was performed using the t test (α = 0.05). CNR values of different distances and different teeth were not significantly different between the two MAR modes (p > 0.05). MAR activation had a significant impact in increasing CNR and reducing artifacts only when brackets were in palatal (p = 0.03). In the other bracket and wire positions, the effect of the MAR algorithm on CNR was not significant (p > 0.05). In conclusion, MAR activation significantly increased CNR, but only when the brackets were in a palatal position. In the other bracket and wire positions, the effect of the MAR algorithm is not significant.

A New Iterative Metal Artifact Reduction Algorithm for Both Energy-Integrating and Photon-Counting CT Systems.

The aim of this study was to introduce and evaluate a new metal artifact reduction framework (iMARv2) that addresses the drawbacks (residual artifacts after correction and user preferences for image quality) associated with the current clinically applied iMAR. A new iMARv2 has been introduced, combining the current iMAR with new modular components to remove residual metal artifacts after image correction. The postcorrection image impression is adjustable with user-selectable strength settings. Phantom scans from an energy-integrating and a photon-counting detector CT were used to assess image quality, including a Gammex phantom and anthropomorphic phantoms. In addition, 36 clinical cases (with metallic implants such as dental fillings, hip replacements, and spinal screws) were reconstructed and evaluated in a blinded and randomized reader study. The Gammex phantom showed lower HU errors compared with the uncorrected image at almost all iMAR and iMARv2 settings evaluated, with only minor differences between iMAR and the different iMARv2 settings. In addition, the anthropomorphic phantoms showed a trend toward lower errors with higher iMARv2 strength settings. On average, the iMARv2 strength 3 performed best of all the clinical reconstructions evaluated, with a significant increase in diagnostic confidence and decrease in artifacts. All hip and dental cases showed a significant increase in diagnostic confidence and decrease in artifact strength, and the improvements from iMARv2 in the dental cases were significant compared with iMAR. There were no significant improvements in the spine. This work has introduced and evaluated a new method for metal artifact reduction and demonstrated its utility in routine clinical datasets. The greatest improvements were seen in dental fillings, where iMARv2 significantly improved image quality compared with conventional iMAR.

Optimization of the "Perth CT" Protocol for Preoperative Planning and Postoperative Evaluation in Total Knee Arthroplasty.

Background and Objectives: Total knee arthroplasty (TKA) has become the treatment of choice for advanced osteoarthritis. The aim of this paper was to show the possibilities of optimizing the Perth CT protocol, which is highly effective for preoperative planning and postoperative assessment of alignment. Materials and Methods: The cross-sectional study comprised 16 patients for preoperative planning or postoperative evaluation of TKA. All patients were examined with the standard and optimized Perth CT protocol using advance techniques, including automatic exposure control (AEC), iterative image reconstruction (IR), as well as a single-energy projection-based metal artifact reduction algorithm for eliminating prosthesis artifacts. The effective radiation dose (E) was determined based on the dose report. Imaging quality is determined according to subjective and objective (values of signal to noise ratio (SdNR) and figure of merit (FOM)) criteria. Results: The effective radiation dose with the optimized protocol was significantly lower compared to the standard protocol (p < 0.001), while in patients with the knee prosthesis, E increased significantly less with the optimized protocol compared to the standard protocol. No significant difference was observed in the subjective evaluation of image quality between protocols (p > 0.05). Analyzing the objective criteria for image quality optimized protocols resulted in lower SdNR values and higher FOM values. No significant difference of image quality was determined using the SdNR and FOM as per the specified protocols and parts of extremities, and for the presence of prothesis. Conclusions: Retrospecting the ALARA ('As Low As Reasonably Achievable') principles, it is possible to optimize the Perth CT protocol by reducing the kV and mAs values and by changing the collimation and increasing the pitch factor. Advanced IR techniques were used in both protocols, and AEC was used in the optimized protocol. The effective dose of radiation can be reduced five times, and the image quality will be satisfactory.

Dual-energy CT revisited: a focused review of clinical use cases.

Dual-energy CT (DECT) has been available for more than 15 years and has undergone continuous technical development and refinement. Recently, the first photon-counting CT scanner became clinically available and has the potential to further expand the possibilities of spectral imaging. Numerous studies on DECT have been published since its creation, highlighting the clinical applications of the various reconstructions enabled by DECT. The aim of this focused review is to succinctly summarize basic principles and available technical concepts of DECT and to discuss established applications relevant to the daily clinical routine. DECT is instrumental for a broad variety of clinical use cases. While some DECT applications can enhance day-to-day clinical practice, others are still subject to broad-scale validation and should therefore be handled with restraint in the clinical routine. · Virtual monoenergetic images, virtual unenhanced images, and iodine maps are the most well-investigated and relevant dual-energy CT reconstructions for clinical application.. · Low-keV virtual monoenergetic images (VMIs) yield superior image and iodine contrast, which can be leveraged for improved vessel assessment and lesion conspicuity, or to reduce contrast media or radiation dose. VMIs at intermediate energies can serve as a replacement for conventional grey-scale images. VMIs at high keV enable efficient artifact reduction, which can be further optimized in combination with dedicated metal artifact reduction algorithms.. · Iodine maps and virtual unenhanced images can improve lesion detection in oncologic imaging and enable lesion assessment in monophasic CT examinations, which may allow a reduction of correlative and follow-up imaging..

Pedicle Screw Pseudofracture on Computed Tomography Secondary to Metal Artifact Reduction.

Metal artifact reduction (MAR) algorithms are commonly used in computed tomography (CT) scans where metal implants are involved. However, MAR algorithms also have the potential to create new artifacts in reconstructed images. We present a case of a screw pseudofracture due to MAR on CT.

Utility of spectral CT with orthopedic metal artifact reduction algorithms for 125I seeds implantation in mediastinal and hepatic tumors.

Virtual monochromatic image (VMI) combined with orthopedic metal artifact reduction algorithms (VMI + O-MAR) can effectively reduce artifacts caused by metal implants of different types. Nevertheless, so far, no study has systematically evaluated the efficacy of VMI + O-MAR in reducing various types of metal artifacts induced by 125I seeds. The aim of this study was to assess the effectiveness of combining spectral computed tomography (CT) images with O-MAR in reducing metal artifacts and improving the image quality affected by artifacts in patients after 125I radioactive seeds implantation (RSI). A total of 45 patients who underwent dual-layer detector spectral CT (DLCT; IQon, Philips Healthcare) scanning of mediastinal and hepatic tumors after 125I RSI were retrospectively included. Spectral data were reconstructed into conventional image (CI), VMI, CI combined with O-MAR (CI + O-MAR), and VMI + O-MAR to evaluate the de-artifact effect and image quality improvement. Objective indicators included signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and artifact index (AI) of lesions affected by artifacts. Subjective indicators included assessment of overcorrected artifacts and new artifacts, different morphology of artifacts, and overall image quality. In artifact-affected lesion areas, SNR and CNR in the CI/VMI + O-MAR groups were better than those in CI groups (all P values <0.05). The AI showed a downward trend as VMI keV increased (all P values <0.001). The AI values of the CI/VMI (50-150 keV) group were all higher than the groups of CI/VMI + O-MAR (50-150 keV) (P<0.001). Overcorrection artifacts and new artifacts were concentrated in the VMI50/70 keV groups. In the evaluation of artifact morphology, as the VMI keV increased, the number of near-field banding artifacts in hyperdense artifacts gradually decreased, whereas the number of minimal or no artifacts increased, and the total number of hyperdense artifacts were decreased. The diagnostic and image quality scores of hyperdense artifacts were higher than those of hypodense artifacts as VMI keV increased. High VMI level combined with O-MAR substantially improve objective and subjective image quality, lesion display ability, and diagnostic confidence of CT follow-up after 125I RSI, especially at the VMI + O-MAR 150 keV level.

Simulation-driven training of vision transformers enables metal artifact reduction of highly truncated CBCT scans.

Due to the high attenuation of metals, severe artifacts occur in cone beam computed tomography (CBCT). The metal segmentation in CBCT projections usually serves as a prerequisite for metal artifact reduction (MAR)algorithms. The occurrence of truncation caused by the limited detector size leads to the incomplete acquisition of metal masks from the threshold-based method in CBCT volume. Therefore, segmenting metal directly in CBCT projections is pursued in thiswork. Since the generation of high quality clinical training data is a constant challenge, this study proposes to generate simulated digital radiographs (dataI) based on real CT data combined with self-designed computer aided design (CAD) implants. In addition to the simulated projections generated from 3D volumes, 2D x-ray images combined with projections of implants serve as the complementary data set (dataII) to improve the network performance. In this work, SwinConvUNet consisting of shift window (Swin) vision transformers (ViTs) with patch merging as encoder is proposed for metalsegmentation. The model's performance is evaluated on accurately labeled test datasets obtained from cadaver scans as well as the unlabeled clinical projections. When trained on the dataI only, the convolutional neural network (CNN) encoder-based networks UNet and TransUNet achieve only limited performance on the cadaver test data, with an average dice score of 0.821 and 0.850. After using both dataII and dataI during training, the average dice scores for the two models increase to 0.906 and 0.919, respectively. By replacing the CNN encoder with Swin transformer, the proposed SwinConvUNet reaches an average dice score of 0.933 for cadaver projections when only trained on the dataI. Furthermore, SwinConvUNet has the largest average dice score of 0.953 for cadaver projections when trained on the combined dataset. Our experiments quantitatively demonstrate the effectiveness of the combination of the projections simulated under two pathways for network training. Besides, the proposed SwinConvUNet trained on the simulated projections performs state-of-the-art, robust metal segmentation as demonstrated on experiments on cadaver and clinical data sets. With the accurate segmentations from the proposed model, MAR can be conducted even for highly truncated CBCTscans.

Dosimetric impact of CT metal artifact reduction for spinal implants in stereotactic body radiotherapy planning.

Metal artifacts due to spinal implants may affect the accuracy of dose calculation for radiotherapy. However, the dosimetric impact of metal artifact reduction (MAR) for spinal implants in stereotactic body radiotherapy (SBRT) plans has not been well studied. The objective of this study was to evaluate the dosimetric impact of MAR in spinal SBRT planning with three clinically common dose calculation algorithms. Gammex phantom and 10 patients' computed tomography (CT) images were studied to investigate the effects of titanium implants. A commercial orthopedic MAR algorithm was employed to reduce artifacts. Dose calculations for SBRT were conducted on both artifact-corrected and uncorrected images using three commercial algorithms [analytical anisotropic algorithm (AAA), Acuros XB (AXB), and Monte Carlo (MC)]. Dose discrepancies between artifact-corrected and uncorrected cases were appraised using a dose-volume histogram (DVH) and 3-dimensional (3D) gamma analysis with different distance to agreement (DTA) and dose difference criteria. The gamma agreement index (GAI) was denoted as G(∆D, DTA). Statistical analysis of t-test was utilized to evaluate the dose differences of different algorithms. The phantom study demonstrated that titanium metal artifacts can be effectively reduced. The patient cases study showed that dose differences between the artifact-corrected and uncorrected datasets were small evaluated by gamma index and DVH. Gamma analysis found that even the strict criterion local G(1,1) had average values ≥93.9% for the three algorithms. For all DVH metrics, average differences did not exceed 0.7% in planning target volume (PTV) and 2.1% in planning risk volume of spinal cord (PRV-SC). Statistical analysis showed that the observed dose differences of MC method were significantly larger than those of AAA (P<0.01 for D98% of PTV and P<0.001 for D0.1cc of spinal cord) and AXB methods (P<0.001 for D98% and P<0.0001 for D0.1cc). Dosimetric impact of artifacts caused by titanium implants is not significant in spinal SBRT planning, which indicates that dose calculation algorithms might not be very sensitive to CT number variation caused by titanium inserts.

An Innovative Metal Artifact Reduction Algorithm based on Res-U-Net GANs

During X-ray computed tomography (CT) scans, the metal implants in the patient's body will produce severe artifacts, which reduce the image quality and interferes with the doctor's judgment. Therefore, it is necessary to develop an algorithm for removing metal artifacts in CT images and reconstructing high-quality images. In this paper, we proposed a generative adversarial networks (GANs)-based metal artifact reduction algorithm for the image domain, Res-U-Net GANs. This method can effectively suppress noise and remove metal artifacts in CT images. Our new approach includes a generator and a discriminator. The generator contains several residual blocks, a U-Net structure and skip connections. And a weighted joint loss function is also used for training. These structures can reduce metal artifacts in images, improve image quality, and restore implant details. We use SSIM, PSNR and RMSE to evaluate the performance of the proposed method. The mean SSIM, PSNR and RMSE of the testing set images are 0.977, 39.044 and 0.011, respectively. And the trained model which is compiled and encapsulated, also show excellent performance in processing clinical data sets, which can remove metal artifacts in clinical CT images. We consider that the proposed algorithm can remove metal artifacts in CT images and restore image details, which is very helpful for radiologists.

Influence of an adjacent zirconium implant, tube current, and metal artifact reduction algorithm on horizontal root fracture diagnosis in cone beam computed tomography

We evaluated the influence of an adjacent zirconium implant, tube current (mA), and a metal artifact reduction algorithm (MARA) on horizontal root fracture (HRF) diagnosis in cone beam computed tomography (CBCT). Nineteen teeth (9 with HRF, 10 without) were individually placed in a human maxilla. Scan volumes were acquired without and with a zirconium implant adjacent to the tooth at settings of 4, 8, and 10 mA, with MARA disabled and enabled, using a 5×5 cm field of view, 0.085-mm voxel size, and 90 kV. Four maxillofacial radiologists individually assessed the scans. Diagnostic metrics were compared by multiway analysis of variance (α=5%). Inter- and intraexaminer agreements for HRF diagnosis were evaluated with the weighted kappa test. Area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were significantly lower in the presence of the implant (P≤.005). AUC values were higher in scans obtained with 8 and 10 mA compared with 4 mA (P=0.010), but 10 mA without MARA was better with the implant present. MARA did not significantly influence outcomes (P≥0.240). Inter- and intraexaminer agreements ranged from moderate to almost perfect. The presence of the zirconium implant impairs HRF detection. Settings of 8 or 10 mA improve HRF detection regardless MARA condition without the implant. With an adjacent implant, 10 mA without MARA is recommended to improve diagnostic performance.

The value of metal artifact reduction and iterative algorithms in dual energy CT angiography in patients after complex endovascular aortic aneurysm repair

Rationale and objectivesEvaluation of the diagnostic value of linearly blended (LB) and virtual monoenergetic images (VMI) reconstruction techniques with and without metal artifacts reduction (MAR) and of adaptive statistical iterative reconstructions (ASIR) in the assessment of target vessels after branched/fenestrated endovascular aortic repair (f/brEVAR) procedures. Materials and methodsCT scans of 28 patients were used in this study. Arterial phase of examination was obtained using a dual-energy fast-kVp switching scanner. CT numbers in the aorta, celiac trunk, superior mesenteric artery, and renal arteries were measured in the following reconstructions: LB, VMI 60 keV, VMI MAR 60 keV, VMI ASIR 60 % 60 keV. Contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) were calculated for each reconstruction. Luminal diameters (measurements at 2 levels of stent) and subjective image quality (5-point Likert scale) were assessed (2 readers, blinded to the type of reconstruction). ResultsThe highest mean values of CNR and SNR in vascular structures were obtained in VMI MAR 60 keV (CNR 12.526 ± 2.46, SNR 17.398 ± 2.52), lower in VMI 60 keV (CNR 11.508 ± 2.01, SNR 16.524 ± 2.07) and VMI ASIR (CNR 11.086 ± 1.78, SNR 15.928 ± 1.82), and the lowest in LB (CNR 6.808 ± 0.79, SNR 11.492 ± 0.79) reconstructions. There were no statistically significant differences in the measurements of the stent width between reconstructions (p > 0.05). The highest subjective image quality was obtained in the ASIR VMI (4.25 ± 0.44) and the lowest in the MAR VMI (1.57 ± 0.5) reconstruction. ConclusionDespite obtaining the highest values of SNR and CNR in the MAR VMI reconstruction, the subjective diagnostic value was the lowest for this technique due to significant artifacts. The type of reconstruction did not significantly affect vessel diameter measurements (p > 0.05). Iterative reconstructions raised both objective and subjective image quality.

Evaluation of a Novel Metal Artifact Reduction Algorithm for Reconstruction of Cone Beam CT (CBCT) Images Acquired on a New Imaging System

The presence of metal implants, dental work or prosthetics can produce image artifacts and distort Hounsfield units (HU) in patient CBCT images. The purpose of this work was to characterize a novel metal artifact reduction (MAR) algorithm for reconstruction of CBCT images obtained by a new imaging system and compare improvements in image quality with a conventional iterative reconstruction algorithm. Preliminary analyses show that the novel reconstruction algorithm implemented on the new imaging system produces image quality and HU comparable to standard fan-beam CT MATERIALS/METHODS: A 30 cm (length) x 30 cm (width) x 11 cm (depth) solid water phantom was fitted with a central cavity measuring 5.5 cm x 5.5 cm x 0.5 cm. Metal inserts of copper, aluminum, stainless steel, and titanium (5.5 cm x 5.5 cm x 1 - 5 mm in thickness) and sample dental implant materials (Amalgam, Au, Co-Cr, and Ti 6Al-Yv) were sequentially used to fill the cavity. CBCT images were acquired and reconstructed using the novel MAR and conventional iterative algorithms both on the on the new system. Images were also taken with the cavity filled with solid water for comparison. Eight image quality metrics were measured in six volumes of interest (VOIs) surrounding the cavity and compared to baseline VOI metrics for solid water-only images: HU mean, signal-to-noise ratio, contrast-to-noise ratio, artifact index, standard deviation, range, skewness, and kurtosis. The mean and standard deviation of HU within a shell-structure surrounding the cavity were calculated to evaluate the dependence of these values on distance from the center of the cavity. The artifact volume of the phantom (excluding the cavity) was estimated by calculating the 5th and 95th percentiles of HU in the CBCT of the phantom with the solid water insert, then summing the volume of all voxels with HU values outside this range. The eight image quality metrics extracted from the chosen VOIs were closer to baseline when using the novel MAR compared to conventional iterative reconstruction. It was also determined that mean HU returned to expected solid water background at a shorter distance from metal sample in the novel MAR images, and the standard deviation remained lower for the novel MAR images at all distances from the insert. These experimental outcomes were obtained for all high-density material inserts except for aluminum. The artifact volume was decreased using the novel MAR algorithm for all metal inserts excluding aluminum (p = 0.00013), and all dental implants (p = 0.00028). The novel MAR reconstruction algorithm shows a much lower sensitivity to metal artifacts, and significant improvement in image quality for all metal samples except for aluminum. These results justify the use of the novel MAR reconstruction for patients with metal implants and highlight advantages of the new CBCT imaging system for more accurate imaging and targeted treatment.

Feasibility of In Vivo Metal Artifact Reduction in Contrast-Enhanced Dedicated Spiral Breast Computed Tomography.

Radiopaque breast markers cause artifacts in dedicated spiral breast-computed tomography (SBCT). This study investigates the extent of artifacts in different marker types and the feasibility of reducing artifacts through a metal artifact reduction (MAR) algorithm. The pilot study included 18 women who underwent contrast-enhanced SBCT. In total, 20 markers of 4 different types were analyzed for artifacts. The extent of artifacts with and without MAR was measured via the consensus of two readers. Image noise was quantitatively evaluated, and the effect of MAR on the detectability of breast lesions was evaluated on a 3-point Likert scale. Breast markers caused significant artifacts that impaired image quality and the detectability of lesions. MAR decreased artifact size in all analyzed cases, even in cases with multiple markers in a single slice. The median length of in-plain artifacts significantly decreased from 31 mm (range 11-51 mm) in uncorrected to 2 mm (range 1-5 mm) in corrected images (p ≤ 0.05). Artifact size was dependent on marker size. Image noise in slices affected by artifacts was significantly lower in corrected (13.6 ± 2.2 HU) than in uncorrected images (19.2 ± 6.8 HU, p ≤ 0.05). MAR improved the detectability of lesions affected by artifacts in 5 out of 11 cases. MAR is feasible in SBCT and improves the image quality and detectability of lesions.

Spectral photon-counting CT: Image quality evaluation using a metal-containing bovine bone specimen

PurposeTo find the optimal imaging parameters for a photon-counting detector CT (PCD-CT) and to compare it to an energy-integrating detector CT (EID-CT) in terms of image quality and metal artefact severity using a metal-containing bovine knee specimen. MethodsA bovine knee with a stainless-steel plate and screws was imaged in a whole-body research PCD-CT at 120 kV and 140 kV and in an EID dual-source CT (DSCT) at Sn150 kV and 80/Sn150 kV. PCD-CT virtual monoenergetic 72 and 150 keV images and EID-CT images processed with and without metal artefact reduction algorithms (iMAR) were compared. Four radiologists rated the visualisation of bony structures and metal artefact severity. The Friedman test and Wilcoxon signed-rank test with Bonferroni’s correction were used. P-values of ≤ 0.0001 were considered statistically significant. Distributions of HU values of regions of interest (ROIs) in artefact-affected areas were analysed. ResultsPCD-CT 140 kV 150 keV images received the highest scores and were significantly better than EID-CT Sn150 kV images. PCD-CT 72 keV images were rated significantly lower than all the others. HU-value variation was larger in the 120 kV and the 72 keV images. The ROI analysis revealed no large difference between scanners regarding artefact severity. ConclusionPCD-CT 140 kV 150 keV images of a metal-containing bovine knee specimen provided the best image quality. They were superior to, or as good as, the best EID-CT images; even without the presumed advantage of tin filter and metal artefact reduction algorithms. PCD-CT is a promising method for reducing metal artefacts.

Zirconia implants interfere with the evaluation of peri-implant bone defects in cone beam computed tomography (CBCT) images even with artifact reduction, a pilot study.

Three-dimensional cone beam computed tomography (CBCT) imaging can be considered, especially in patients with complicated peri-implantitis (PI). Artifacts induced by dense materials are the drawback of CBCT imaging and the peri-implant bone condition may not be assessed reliably because the artifacts are present in the same area. This pilot study investigates the performance of the artifact reduction algorithm (ARA) of the Planmeca Viso G7 CBCT device (Planmeca, Helsinki, Finland) with three different implant materials and imaging parameters. Three pairs of dental implants consisting of titanium, zirconia, and fiber reinforced composite (FRC) were set into a pig mandible. A vertical defect simulating peri-implantitis bone loss was made on the buccal side of one of each implant. The defect was identified and measured by two observers and compared to the actual dimensions. In addition, the bone structure and the marginal cortex visibility between the implants were estimated visually. The bone defect and its dimensions with the zirconia implant could not be identified in any image with or without the metal artifact reduction algorithm. The bone defect of titanium and FRC implants were identified with all three imaging parameters or even without ARA. The interobserver agreement between the two observers was almost perfect for all categories analyzed. Peri-implantitis defect of the zirconia implant and the peri-implant bone structure of the zirconia implants cannot be recognized reliably with any ARA levels, or any imaging parameters used with the Planmeca Viso G7. The need for ARA when imaging the peri-implant bone condition of the titanium and FRC implants may be unnecessary.