Artifact Index Research Articles

Metal Artifact Reduction in Head CT Performed for Patients with Deep Brain Stimulation Devices: Effectiveness of a Single-Energy Metal Artifact Reduction Algorithm.

Deep brain stimulation electrodes induce massive artifacts on CT images, deteriorating the diagnostic value of examinations. We aimed to investigate the usefulness and potential limitations of a single-energy metal artifact reduction algorithm in head CT performed in patients with implanted deep brain stimulation devices. Thirty-four patients with deep brain stimulation (bilateral, n = 28) who underwent head CT on a 320-detector row scanner and whose images were reconstructed with and without single-energy metal artifact reduction at the examinations were retrospectively included. The severity of artifacts around electrodes was assessed objectively using SDs and an artifact index. Two radiologists subjectively evaluated the severity of artifacts from electrodes, the visibility of electrode localization and surrounding structures, and overall diagnostic confidence on 4-point scales. Background image quality (GM-WM contrast and image noise) was subjectively and objectively assessed. The presence and location of artifacts newly produced by single-energy metal artifact reduction were analyzed. Single-energy metal artifact reduction provided lower objective and subjective metal artifacts and improved visualization of electrode localization and surrounding structures and diagnostic confidence compared with non-single-energy metal artifact reduction images, with statistical significance (all, P < .01). No significant differences were observed in GM-WM contrast and image noise (all, P ≥ .11). The new artifacts from single-energy metal artifact reduction were prominently observed in patients with bilateral deep brain stimulation at high convexity, possibly induced by deep brain stimulation leads placed under the parietal scalp. Single-energy metal artifact reduction substantially reduces the metal artifacts from deep brain stimulation electrodes and improves the visibility of intracranial structures without affecting background image quality. However, non-single-energy metal artifact reduction images should be simultaneously reviewed to accurately assess the entire intracranial area, particularly in patients with bilateral deep brain stimulation.

Algorithm-based artifact reduction in patients with arms-down positioning in computed tomography

PurposeArm-artifact, a type of streak artifact frequently observed in computed tomography (CT) images obtained at arms-down positioning in polytrauma patients, is known to degrade image quality. This study aimed to develop a novel arm-artifact reduction algorithm (AAR) applied to projection data. MethodsA phantom resembling an adult abdomen with two arms was scanned using a 16-row CT scanner. The projection data were processed by AAR, and CT images were reconstructed. The artifact reduction for the same phantom was compared with that achieved by two latest iterative reconstruction (IR) techniques (IR1 and IR2) using a normalized artifact index (nAI) at two locations (ventral and dorsal side). Image blurring as a processing side effect was compared with IR2 of the model-based IR using a plastic needle phantom. Additionally, the projection data of two clinical cases were processed using AAR, and the image noise was evaluated. ResultsAAR and IR2 significantly reduced nAI by 87.5% and 74.0%, respectively at the ventral side and 84.2% and 69.6%, respectively, at the dorsal side compared with each filtered back projection (P < 0.01), whereas IR1 did not. The proposed algorithm mostly maintained the original spatial resolution, compared with IR2, which yielded apparent image blurring. The image noise in the clinical cases was also reduced significantly (P < 0.01). ConclusionsAAR was more effective and superior than the latest IR techniques and is expected to improve the image quality of polytrauma CT imaging with arms-down positioning.

Preliminary study on the elimination of artifacts of five kinds of dental prosthetic materials by energy spectrum CT multi-material artifact reduction technology

Objective: To investigate the effect of the multi-material artifact reduction (MMAR) algorithm of spectral CT in reducing the beam hardening artifacts in dental restoration material. Methods: Three-unit fixed bridge restorations were fabricated on the first to third molars in pig jaw. Gold alloy, zirconia, cobalt chromium alloy, nickel chromium alloy and pure titanium were used as materials for these fixed bridges. After restoration delivery, the pig jaw was scaned using energy spectrum CT machines. Images in regular 120 kVp scan mode were used as conventional group, and reconstructed single-energy horizontal images of 80, 90, 100, 110, 120, 130 and 140 keV in energy spectrum scanning mode were used as energy spectrum group, and reconstructed images applied MMAR technology in energy spectrum scanning mode were used as energy spectrum MMAR group. Each group was scanned 10 times to measure CT value and noise of muscles around dental prosthetic materials and adjacent non-artifact layers. Artifact index was calculated. Two radiologists scored the image quality of each group subjectively. Kruskal Wallis rank sum test was used to compare the difference of image noise, artifact index and subjective score among the control group and the best keV condition in the energy spectrum group and the energy spectrum MMAR group. Results: The image noise of energy spectrum group and energy spectrum MMAR group decreased gradually with the increase of single energy level. The artifact index of pure titanium restorations in conventional group, energy spectrum group and energy spectrum MMAR group were 71.0±8.0, 21.4±2.7 and 14.7±2.7 respectively, and these values were significantly lower than those of other materials in the same group (P<0.05). The subjective image quality scores in energy spectrum MMAR group were as follows: 3.0±0.2 for gold alloy, 4.3±0.5 for zirconia, 3.0±0.4 for cobalt chromium alloy, 3.1±0.4 for cobalt chromium alloy, and 4.6±0.5 for pure titanium. These scores were significantly smaller than those in the conventional group (P<0.05). There was no significant difference in noise between energy spectrum group and energy spectrum MMAR group (P>0.05), and the noise values in energy spectrum group and energy spectrum MMAR group were significantly lower than that in the conventional group (P<0.05). Conclusions: Artifacts of pure titanium is minimal. Energy spectrum CT combined with MMAR technology can effectively reduce the artifacts of gold, zirconia, cobalt-chromium alloy, nickel-titanium alloy and pure titanium. This technique can be used as an effective method to remove artifacts of dental prosthesis.

Application of Monochromatic Imaging and Metal Artifact Reduction Software in Computed Tomography Angiography after Treatment of Cerebral Aneurysms.

This study aimed to evaluate the image quality and degree of metal artifact reduction using the new-generation gemstone spectral imaging (GSI) and metal artifact reduction software (MARs) and to demonstrate the optimal monochromatic energy level for dual-energy cerebral computed tomography angiography (CTA) in patients with intracranial aneurysm after endovascular treatment. A total of 20 patients with cerebral aneurysms treated with coils or clips underwent CTA using gemstone spectral computed tomography. Artifact index was calculated at each energy level with and without MARs. Signal-to-noise (SNR) and contrast-to-noise (CNR) ratios were calculated on all axial images with MARs; subjective evaluation was done by using a 4-point scale and a 3-point scale for assessing noise and vessel contrast, respectively, and compared between the monochromatic energy levels. The artifact index value of group GSI-MARs was significantly lower than that of group GSI at each monochromatic energy level (all, P < 0.01). Contrast-to-noise ratio and SNR of the parent arteries decreased as the energy increased from 40 to 140 keV in group GSI-MARs (all, P < 0.01). Signal-to-noise ratio and CNR between each 2 adjacent monochromatic energy level showed significant difference (all, P < 0.01). Subjective evaluation showed that a monochromatic energy level between 40 and 70 keV provided the optimal image quality. Gemstone spectral imaging with MARs could reduce metal artifacts and improve the image quality of cerebral CTA after coil or clip treatment. The new generation of GSI could provide better CNR and SNR at lower energy level, and the best image quality was obtained at energy level 40 to 70 keV for GSI-MARs.

Development of a denoising convolutional neural network-based algorithm for metal artifact reduction in digital tomosynthesis for arthroplasty: A phantom study.

The present study aimed to develop a denoising convolutional neural network metal artifact reduction hybrid reconstruction (DnCNN-MARHR) algorithm for decreasing metal objects in digital tomosynthesis (DT) for arthroplasty by using projection data. For metal artifact reduction (MAR), we implemented a DnCNN-MARHR algorithm based on a training network (mini-batch stochastic gradient descent algorithm with momentum) to estimate the residual reference (140 keV virtual monochromatic [VM]) and object (70 kV with metal artifacts) images. For this, we used projection data and subtracted the estimated residual images from the object images, involving hybrid and subjectively reconstructed image usage (back projection and maximum likelihood expectation maximization [MLEM]). The DnCNN-MARHR algorithm was compared with the dual-energy material decomposition reconstruction algorithm (DEMDRA), VM, MLEM, established and commonly used filtered back projection (FBP), and a simultaneous algebraic reconstruction technique-total variation (SART-TV) with MAR processing. MAR was compared using artifact index (AI) and texture analysis. Artifact spread functions (ASFs) for images that were out-of-plane and in-focus were evaluated using a prosthesis phantom. The overall performance of the DnCNN-MARHR algorithm was adequate with regard to the ASF, and the derived images showed better results, without being influenced by the metal type (AI was almost equal to the best value for the DEMDRA). In the ASF analysis, the DnCNN-MARHR algorithm generated better MAR compared with that obtained employing usual algorithms for reconstruction using MAR processing. In addition, comparison of the difference (mean square error) between DnCNN-MARHR and the conventional algorithm resulted in the smallest VM. The DnCNN-MARHR algorithm showed the best performance with regard to image homogeneity in the texture analysis. The proposed algorithm is particularly useful for reducing artifacts in the longitudinal direction, and it is not affected by tissue misclassification.

Effective temporal resolution and image quality of volume scanning in 320-row detector CT.

To measure the effective temporal resolution (eTR) and image quality for three reconstruction modes for non-helical volume scanning in area detector CT. Temporal sensitivity profiles (TSPs) were obtained and the full width of the TSP at half maximum was used as an index of the eTR. Image quality was assessed by image noise and the corrected artifact index. The half reconstruction mode had a higher eTR than the full and automatic patient motion collection (APMC) reconstructions. Compared to full reconstruction, the image noise with APMC and half reconstruction were increased by 16% and 35%. The corrected artifact index was lowest with APMC. The square root of full width at tenth maximum of the TSP showed a high coefficient of determination (R2 = 0.934) for image noise. This study revealed the TSPs and eTRs for non-helical volume scanning in area detector CT. A high eTR resulted in higher image noise.

Application of a multi-material artifact reduction algorithm in a wide-detector CT in the evaluation of the portal venous angiography of postoperative TIPS and embolization

Objective: To assess the effect of monochromatic images and metal artifact reduction (MAR) on the image quality of spectral CT portal venous angiography in patients with operation of after the performing transjugular intrahepatic portosystemic stent shunt(TIPS) and embolization. Methods: From December 2017 to April 2018, the examination data of 28 patients with portal hypertension due to cirrhosis who underwent portal vein angiography 1 month after TIPS and embolization were prospectively collected. After spectral CT scanning in revolution CT, the monochromatic energy levels(60 keV, 120 keV), 60 keV + 120 keV, 120kV-like + 120 keV fused images combined with MAR algorithm were reconstructed. Quantitative parameters such as image artifact index (AI) and qualitative visual evaluation scores were recorded and compared. Results: The 120 keV monochromatic images showed the lowest AI value(30.8±8.5, 18.2±4.3) and highest metal artifacts reduction effect. The 60 keV monochromatic images showed the highest AI value (57.3±15.7, 32.1±7.9) and the lowest metal artifacts reduction effect. The AI value of 60 keV + 120 keV fused images was lower than that of 60 keV images(26.2%, 24.7%). The difference of AI value between each group was statistically significant(all P<0.05). The interobserver agreement in the subjective image scores was moderate with kappa value of 0.824. The overall image quality score of 60 keV + 120 keV fused image and the noise score of 120 kV-like+120 keV were higher than the remaining groups. The differences of the subjective scores among each group were statistically significant(all P<0.05). Conclusion: The spectral CT with MAR algorithm can effectively improve the image quality of portal vein angiography after the TIPS and embolization therapy and the 60 keV + 120 keV fused images can eliminate artifacts and ensure a clear display of blood vessels.

Metal Artifact Reduction in Virtual Monoenergetic Spectral Dual-Energy CT of Patients With Metallic Orthopedic Implants in the Distal Radius.

The purpose of this study was to evaluate the image quality of virtual monoenergetic images obtained from dual-layer-detector spectral CT of patients with metallic orthopedic implants of the distal radius. A retrospective analysis was performed between April 2016 and January 2017. Forty-three consecutively registered patients (33 women, 10 men; mean age, 50.7 ± 15.4 years) with metallic implants for distal radius fractures underwent dual-layer-detector spectral CT. Sixteen virtual monoenergetic image sets ranging from 50 to 200 keV were generated from the single slice with the most pronounced low-attenuation artifact from implants. Image quality was quantitatively assessed on the basis of the attenuation of the artifacts and reference tissue, background image noise, and artifact index. Qualitative assessment included degree of artifact, diagnostic image quality of the periimplant bones, and delineation of fracture lines. The Friedman rank sum test and kappa analysis were used for statistical analysis. There were statistically significant differences in quantitative and qualitative parameters at different monoenergy levels (all p < 0.001). Artifact index was the lowest at 120 keV. Low-attenuation artifacts in the periimplant regions were least pronounced at 110 keV, and the diagnostic image quality of periimplant bone was best at 130 keV. Fracture lines were well delineated in all cases at 80-110 keV (p < 0.001). The optimal energy setting for incurring the fewest metallic artifacts and obtaining the best diagnostic image quality from distal radius implants during dual-layer-detector spectral CT is the range of 110-130 keV.

Value of Monochromatic Imaging on Spectral Detector CT in Metal Artifact Reduction of Denture Implants

Objective To evaluate the role of monochromatic imaging in reducing metal artifacts and improving image quality in patients with denture implants undergoing head/neck plain CT. Methods Forty patients with denture implants undergoing head/neck plain CT on a dual-layer spectral detector CT were enrolled. The conventional and monochromatic 110 keV images were reconstructed from the same acquisition. The regions of interests (ROIs) were placed on the artifact streak (CT1),the soft tissue affected by the artifact (CT2),and the unaffected tissue (CT3). The artifact index (AI) and standard deviation (SD) were calculated. The image quality was compared.Results The attenuation of CT1 was significantly improved on monochromatic images than on conventional images [-195.00 (-700.40,44.80) vs. -336.50 (-1024.00,-77.00),P=0.00]. The attenuation of CT2 was significant different between monochromatic and conventional images [46.10 (-0.20,91.60) vs. 102.80 (4.60,210.20),P=0.00]. The difference between CT2 and CT3 was significantly smaller on monochromatic images than on conventional images [14.55 (0.00,44.00) vs. 51.30 (0.30,168.30),P=0.00]. The SD of CT2 was significantly smaller on monochromatic images than on conventional images [14.75 (7.80,35.00) vs. 23.25 (7.60,56.00),P=0.00]. The AI was significantly improved by monochromatic imaging [12.76 (3.53,34.14) vs. 19.00 (2.43,54.32),P=0.00]. Conclusion The monochromatic imaging can effectively reduce the artifacts caused by denture implants and improve image quality on head/neck plain CT.

Development of a novel algorithm for metal artifact reduction in digital tomosynthesis using projection-based dual-energy material decomposition for arthroplasty: A phantom study

In this study, a novel dual-energy (DE) material decomposition reconstruction algorithm (DEMDRA) was developed using projection data with the aim of reducing metal artifacts during digital tomosynthesis (DT) for implants. Using the three-material decomposition method and decomposition projection data specific for each material, a novel DEMDRA was implemented to reduce metal artifacts via weighted hybrid reconstructed images [maximum likelihood expectation maximization (MLEM) and shift-and-add (SAA)]. Pulsed X-ray exposures with rapid switching between low and high tube potential kVp were used for DE-DT imaging, and the images were compared using conventional filtered back projection (FBP), MLEM, the simultaneous algebraic reconstruction technique total variation (SART-TV), virtual monochromatic processing, and metal artifact reduction (MAR)-processing algorithms. The reductions in metal artifacts were compared using an artifact index (AI), Gumbel distribution of the largest variations, and the artifact spread functions (ASFs) for prosthesis phantom. The novel DEMDRA yielded an adequately effective overall performance in terms of the AI, and the resulting images yielded good results independently of the type of metal used in the prosthetic phantom, as well as good noise artifact removal, particularly at greater distances from metal objects. Furthermore, the DEMDRA represented the minimum in the model of largest variations. Regarding the ASF analysis, the novel DEMDRA yielded superior metal artifact reduction when compared with conventional reconstruction algorithms with and without MAR processing. Finally, the DEMDRA was particularly useful for reducing high-frequency artifacts.

Evaluation of the Quality of CT Images Acquired with Smart Metal Artifact Reduction Software.

ObjectiveTo evaluate the practical effectiveness of smart metal artifact reduction (SMAR) in reducing artifacts caused by metallic implants.MethodsPatients with metal implants underwent computed tomography (CT) examinations on high definition CT scanner, and the data were reconstructed with adaptive statistical iterative reconstruction (ASiR) with value weighted to 40% and smart metal artifact reduction (SMAR) technology. The comparison was assessed by both subjective and objective assessment between the two groups of images. In terms of subjective assessment, three radiologists evaluated image quality and assigned a score for visualization of anatomic structures in the critical areas of interest. Objectively, the absolute CT value of the difference (ΔCT) and artifacts index (AI) were adopted in this study for the quantitative assessment of metal artifacts.ResultsIn subjective image quality assessment, three radiologists scored SMAR images higher than 40% ASiR images (P<0.01) and the result suggested that visualization of critical anatomic structures around the region of the metal object was significantly improved by using SMAR compared with 40% ASiR. The ΔCT and AI for quantitative assessment of metal artifacts showed that SMAR appeared to be superior for reducing metal artifacts (P<0.05) and indicated that this technical approach was more effective in improving the quality of CT images.ConclusionA variety of hardware (dental filling, embolization coil, instrumented spine, hip implant, knee implant) are processed with the SMAR algorithm to demonstrate good recovery of soft tissue around the metal. This artifact reduction allows for the clearer visualization of structures hidden underneath.

A Development of Clinical Decision Support System for Video Head Impulse Test Based on Fuzzy Inference System

This paper represents the clinical decision support system for video head impulse test (vHIT) based on fuzzy inference system. It examines the eye and head movement recorded by the eye movement tracking device, calculates the vestibulo-ocular reflex (VOR) gain, and applies fuzzy inference system to output the normality and artifact index of the test result. The position VOR gain and the proportion of covert and overt catch-up saccades (CUS) within the dataset are used as the input of the inference system. In addition, this system yields one more factor, the artifact index, which represents the current interference in the dataset. Data of fifteen vestibular neuritis patients and two of normal subjects were evaluated. The artifact index appears to be very high in the lesion side of vestibular neuritis (VN) patients, indicating highly theoretical contradictions, which are low gain but without CUS, or normal gain with the appearance of CUS. Both intact side and normal subject show high normality and low artifact index, even though the intact side has slightly lower normality and higher artifact index. In conclusion, this is a robust system, which is the first one that takes gain and CUS into account, to output not only the normality of the vHIT dataset, but also the artifacts.

Suggestion of the Relative Artifact Index for Noise-independent Evaluation of the Streak Artifact

The aim of this study was to inspect the usefulness of relative artifact index (AIr), which divided artifact index (AI) by standard deviation of the noise image for noise-independent evaluation of the streak artifact in computed tomography images. A water phantom without/with a cylindrical phantom filled with diluted contrast medium was scanned with different tube voltages (100/120/140 kV) and radiation doses (5/10/20 mGy), then images were reconstructed with different kernels (B10/30/50f). AI, location parameter in Gumbel method and AIr were measured in each condition and compared. The higher tube voltage or radiation dose or lower spatial resolution kernel, the lower quantitative values were presented by both AI and Gumbel method. AIr showed quantitative values independent of radiation dose and kernel, and substantial artifact amounts affected only by tube voltage. Our results showed AIr can evaluate quantitative artifact amount independent of image noise.

The Effect of Metal Artifact Reduction at Different Rotation Time in Computed Tomography

The purpose of the study was to examine the metal artifact-reducing effects of single energy metal artifact reduction (SEMAR) at different rotation time. Helical and volume scans were employed to photograph a self-made phantom at various rotation time. Metal artifacts were examined using artifact index (AI) values and visual scores. At rotation times of 0.35, 0.4, 0.5, 0.6, 0.75, and 1.0 s/rotation on the helical scans (SEMAR-ON), AI values were 66.6, 64.3, 39.7, 39.7, 40.8, and 15.4, respectively, and visual scores were 3.2, 3.4, 3.0, 3.1, 3.0, and 2.8, respectively. Similar results were obtained on the volume scans. Specifically, the AI values reduced with a decreasing rotation time, although the visual scores did not significantly differ with a rotation time changes. The metal artifact-reducing effects of SEMAR are not altered by the rotation time.

Thin-slice brain CT with iterative model reconstruction algorithm for small lacunar lesions detection: Image quality and diagnostic accuracy evaluation.

This study was aimed to evaluate the image quality and lacunar lesion detection of thin-slice brain computed tomography (CT) images with different reconstruction algorithms, including filtered back projection (FBP), hybrid iterative reconstruction (HIR), and iterative model reconstruction (IMR) by comparison of routine slice images with FBP reconstruction. Sixty-one patients underwent noncontrast brain CT and images were reconstructed with a routine slice of 5.0 mm by FBP and thin slice of 1.0 mm by IMR, HIR, and FBP algorithms, respectively. Objective analyses included CT attenuation, noise, artifacts index of posterior cranial fossa, and contrast-to-noise ratio (CNR). Subjective analyses were performed according to overall image quality using a 5-point scale [1 (unacceptable) to 5 (excellent)]. In addition, lacunar lesion detection was compared in images with different reconstruction settings among 26 patients with lacunar lesions, with magnetic resonance imaging (MRI) as reference.Thin-slice IMR images enabled the lowest noise, artifacts index, and the best CNR. Both IMR and HIR thin-slice images enabled better scores in subjective image quality than routine slice FBP images. Moreover, both thin-slice IMR and HIR images enabled higher sensitivity and positive predictive value (PPV) in lesion detection of 35-mm lacunar lesions compared with routine slice FBP images.Thin-slice IMR images improve image quality, meanwhile yield better detection of small lacunar lesions in brain CT compared with routine slice FBP images.

Utilization of independent component analysis for accurate pathological ripple detection in intracranial EEG recordings recorded extra- and intra-operatively

ObjectiveTo develop and validate a detector that identifies ripple (80–200 Hz) events in intracranial EEG (iEEG) recordings in a referential montage and utilizes independent component analysis (ICA) to eliminate or reduce high-frequency artifact contamination. Also, investigate the correspondence of detected ripples and the seizure onset zone (SOZ). MethodsiEEG recordings from 16 patients were first band-pass filtered (80–600 Hz) and Infomax ICA was next applied to derive the first independent component (IC1). IC1 was subsequently pruned, and an artifact index was derived to reduce the identification of high-frequency events introduced by the reference electrode signal. A Hilbert detector identified ripple events in the processed iEEG recordings using amplitude and duration criteria. The identified ripple events were further classified and characterized as true or false ripple on spikes, or ripples on oscillations by utilizing a topographical analysis to their time-frequency plot, and confirmed by visual inspection. ResultsThe signal to noise ratio was improved by pruning IC1. The precision of the detector for ripple events was 91.27 ± 4.3%, and the sensitivity of the detector was 79.4 ± 3.0% (N = 16 patients, 5842 ripple events). The sensitivity and precision of the detector was equivalent in iEEG recordings obtained during sleep or intra-operatively. Across all the patients, true ripple on spike rates and also the rates of false ripple on spikes, that were generated due to filter ringing, classified the seizure onset zone (SOZ) with an area under the receiver operating curve (AUROC) of >76%. The magnitude and spectral content of true ripple on spikes generated in the SOZ was distinct as compared with the ripples generated in the NSOZ (p < .001). ConclusionsUtilizing ICA to analyze iEEG recordings in referential montage provides many benefits to the study of high-frequency oscillations. The ripple rates and properties defined using this approach may accurately delineate the seizure onset zone. SignificanceStrategies to improve the spatial resolution of intracranial EEG and reduce artifact can help improve the clinical utility of HFO biomarkers.

The effect of a multi-material artifact reduction algorithm in a wide-detector CT system to reduce the beam hardening artifacts in CT imaging

Objective To investigate the effect of the multi-material artifact reduction (MMAR) algorithm of wide-detector CT system in reducing the beam hardening artifacts in brain CT imaging. Methods Nine tubes with various iodine concentrations (0.1-16.0 mgI/ml) were placed in a uniform phantom filled with soft-tissue equivalent material. The phantom was scanned using different combinations of the tube voltage and current as follows: 80 kV/530 mA, 100 kV/295 mA, 120 kV/190 mA and 140 kV/135 mA. The scanning was performed using the GE Discovery 750 and GE Revolution CT scanners, respectively. The CT values and standard deviations of the uniform areas between tubes were measured. The artifact index(AI) was calculated by using the standard deviation value outside the tubes as background noise. The artifact index values under different kV/mA combinations with different scanners were compared. CT brain images of 36 patients (n=18 on Discovery CT and n=18 on Revolution CT) were randomly selected. CT values of normal brain tissue and dark bands areas in the posterior fossa were measured for each case. The AI was calculated for these cases as for the phantom study. Paired t test was performed for phantom data analysis, and independent t test was performed for the clinical cases data analysis. Results The average AI values with Revolution CT(4.96±1.39, 4.80±1.57, 4.56±1.45, 4.76±1.57) were smaller than those of Discovery 750 (11.90±6.61, 11.17±5.61, 8.85±4.59, 8.77±3.85) under different tube voltage settings (t=3.714, 4.186, 3.745, 4.634, P<0.001) . The higher the iodine concentration difference between tube pairs was, the higher the artifact index;As for clinical data, the difference in AI values between Revolution CT(2.31±0.95) and Discovery 750(3.91±1.32) was found statistically significant (t=4.066, P<0.001) . Conclusion The multi-material artifact reduction algorithm implemented on the wide-detector Revolution CT scanner can significantly reduce beam hardening artifacts. Key words: Beam hardening artifacts; Tomography, X-ray computed; Multi-material artifact reduction

Reduction of metal artifacts from unilateral hip arthroplasty on dual-energy CT with metal artifact reduction software.

Background The evaluation of hip arthroplasty is a challenge in computed tomography (CT). The virtual monochromatic spectral (VMS) images with metal artifact reduction software (MARs) in spectral CT can reduce the artifacts and improve the image quality. Purpose To evaluate the effects of VMS images and MARs for metal artifact reduction in patients with unilateral hip arthroplasty. Material and Methods Thirty-five patients underwent dual-energy CT. Four sets of VMS images without MARs and four sets of VMS images with MARs were obtained. Artifact index (AI), CT number, and SD value were assessed at the periprosthetic region and the pelvic organs. The scores of two observers for different images and the inter-observer agreement were evaluated. Results The AIs in 120 and 140 keV images were significantly lower than those in 80 and 100 keV images. The AIs of the periprosthetic region in VMS images with MARs were significantly lower than those in VMS images without MARs, while the AIs of pelvic organs were not significantly different. VMS images with MARs improved the accuracy of CT numbers for the periprosthetic region. The inter-observer agreements were good for all the images. VMS images with MARs at 120 and 140 keV had higher subjective scores and could improve the image quality, leading to reliable diagnosis of prosthesis-related problems. Conclusion VMS images with MARs at 120 and 140 keV could significantly reduce the artifacts from hip arthroplasty and improve the image quality at the periprosthetic region but had no obvious advantage for pelvic organs.

Evaluation of digital tomosynthesis reconstruction algorithms used to reduce metal artifacts for arthroplasty: A phantom study

To investigate methods to reduce metal artifacts during digital tomosynthesis for arthroplasty, we evaluated five algorithms with and without metal artifact reduction (MAR)-processing tested under different radiation doses (0.54, 0.47, and 0.33mSv): adaptive steepest descent projection onto convex sets (ASD-POCS), simultaneous algebraic reconstruction technique total variation (SART-TV), filtered back projection (FBP), maximum likelihood expectation maximization (MLEM), and SART. The algorithms were assessed by determining the artifact index (AI) and artifact spread function (ASF) on a prosthesis phantom. The AI data were statistically analyzed by two-way analysis of variance. Without MAR-processing, the greatest degree of effectiveness of the MLEM algorithm for reducing prosthetic phantom-related metal artifacts was achieved by quantification using the AI (MLEM vs. ASD-POCS, SART-TV, SART, and FBP; all P<0.05). With MAR-processing, the greatest degree of effectiveness of the MLEM, ASD-POCS, SART-TV, and SART algorithms for reducing prosthetic phantom-related metal artifacts was achieved by quantification using the AI (MLEM, ASD-POCS, SART-TV, and SART vs. FBP; all P<0.05). When assessed by ASF, metal artifact reduction was largest for the MLEM algorithm without MAR-processing and ASD-POCS, SART-TV, and SART algorithm with MAR-processing. In ASF, the effect of metal artifact reduction was always greater at reduced radiation doses, regardless of which reconstruction algorithm with and without MAR-processing was used. In this phantom study, the MLEM algorithm without MAR-processing and ASD-POCS, SART-TV, and SART algorithm with MAR-processing gave improved metal artifact reduction.

Single energy metal artifact reduction technique in the evaluation of postoperative tumor endoprostheses in the knee joint

Objective To evaluate the effect of the single energy metal artifact reduction (SEMAR) algorithm with a 320 multi-slice computed tomography (MSCT) volume scanner in patients with knee tumor prostheses. Methods From November 2015 to March 2016, 23 consecutive patients with knee tumor prostheses who underwent a 320-MSCT scan were collected. And the raw data were reconstructed using two different methods: conventional iterative reconstruction (IR) alone and IR associated with SEMAR. The ROI were objectively and subjectively assessed at osteotomy level and articular level, and the Wilcoxon signed rank test was used for them. Results Compared with IR, objectively, artifact index (AI) values of the osteotomy level decreased 44.8% to 74.1% and that of the articular level decreased 73.2% to 93.2%; subjectively, the scores of image quality of two levels were increased 0.5 to 2.0 scores and 1.0 to 4.0 scores by SEMAR respectively. The objective and subject image quality of periprosthetic structures were all significantly improved by the SEMAR algorithm (P<0.05). Conclusion The SEMAR algorithm significantly reduced the metal artifact of knee tumor prostheses, improved the image quality of periprosthetic structures and may increase diagnostic confidence of prosthetic complications in patients with modular knee tumor prostheses, especially at the osteotomy level. Key words: Knee prosthesis; Tomography,X-ray computed