Artifact Reduction Algorithm Research Articles

Distortion or magnification? An in vitro cone-beam CT study of dimensional changes of objects with different compositions.

To assess whether dimensional changes occur as shape distortion (unevenly), contraction or magnification (evenly) in cone beam computed tomography (CBCT) considering materials, anatomical regions and metal artefact reduction algorithms. Four cylinders of amalgam (Am), cobalt-chromium (Co-Cr), gutta-percha (Gu), titanium (Ti) and zirconium (Zi) were inserted inside a polymethylmethacrylate phantom in anterior and posterior regions for acquisitions in Picasso Trio and OP300 with MAR enabled and disabled. Two observers measured the dimensions of each cylinder in three axes: Y (height), Z (antero posterior diameter) and X (latero-lateral diameter). Repeated measures ANOVA with Tukey post-hoc test compared the data (α = 5%). Shape distortion occurred for all materials in anterior region of Picasso Trio without MAR (p < 0.05). With MAR enabled, Gu and Ti contracted (p ≥ 0.05), while the others showed distortion (p < 0.05). In posterior region, all materials distorted in both MAR conditions (p < 0.05), except Gu, which magnified without MAR (p ≥ 0.05) and contracted unevenly with MAR (p < 0.05). In anterior region of OP300, all materials magnified without MAR, (p ≥ 0.05) and had shape distortion with MAR (p < 0.05). In posterior region, only Am showed magnification without MAR (p ≥ 0.05), while all materials presented shape distortion with MAR (p < 0.05). Dimensional changes of high-density materials in CBCT can be either a magnification, a contraction or a distortion; the last condition is the most prevalent. Furthermore, changes differ considering material, anatomical region and MAR condition.

Geometric and dosimetric impact of 3D generative adversarial network-based metal artifact reduction algorithm on VMAT and IMPT for the head and neck region

BackgroundWe investigated the geometric and dosimetric impact of three-dimensional (3D) generative adversarial network (GAN)-based metal artifact reduction (MAR) algorithms on volumetric-modulated arc therapy (VMAT) and intensity-modulated proton therapy (IMPT) for the head and neck region, based on artifact-free computed tomography (CT) volumes with dental fillings.MethodsThirteen metal-free CT volumes of the head and neck regions were obtained from The Cancer Imaging Archive. To simulate metal artifacts on CT volumes, we defined 3D regions of the teeth for pseudo-dental fillings from the metal-free CT volumes. HU values of 4000 HU were assigned to the selected teeth region of interest. Two different CT volumes, one with four (m4) and the other with eight (m8) pseudo-dental fillings, were generated for each case. These CT volumes were used as the Reference. CT volumes with metal artifacts were then generated from the Reference CT volumes (Artifacts). On the Artifacts CT volumes, metal artifacts were manually corrected for using the water density override method with a value of 1.0 g/cm3 (Water). By contrast, the CT volumes with reduced metal artifacts using 3D GAN model extension of CycleGAN were also generated (GAN-MAR). The structural similarity (SSIM) index within the planning target volume was calculated as quantitative error metric between the Reference CT volumes and the other volumes. After creating VMAT and IMPT plans on the Reference CT volumes, the reference plans were recalculated for the remaining CT volumes.ResultsThe time required to generate a single GAN-MAR CT volume was approximately 30 s. The median SSIMs were lower in the m8 group than those in the m4 group, and ANOVA showed a significant difference in the SSIM for the m8 group (p < 0.05). Although the median differences in D98%, D50% and D2% were larger in the m8 group than the m4 group, those from the reference plans were within 3% for VMAT and 1% for IMPT.ConclusionsThe GAN-MAR CT volumes generated in a short time were closer to the Reference CT volumes than the Water and Artifacts CT volumes. The observed dosimetric differences compared to the reference plan were clinically acceptable.

Photon-counting normalized metal artifact reduction (NMAR) in diagnostic CT.

Metal artifacts can drastically reduce the diagnostic value of computed tomography (CT) images. Even the state-of-the-art algorithms cannot remove them completely. Photon-counting CT inherently provides spectral information, similar to dual-energy CT. Many applications, such as material decomposition, are not possible when metal artifacts are present. Our aim is to develop a prior-based metal artifact reduction specifically for photon-counting CT that can correct each bin image individually or in their combinations. Photon-counting CT sorts incoming photons into several energy bins, producing bin and threshold images containing spectral information. We use this spectral information to obtain a better prior image for the state-of-the-art metal artifact reduction algorithm FSNMAR. First, we apply a non-linear transformation to the bin images to obtain bone-emphasized images. Subsequently, we forward-project the bin images and bone-emphasized images and multiply the resulting sinograms with each other element-wise to mimic beam hardening effects. These sinograms are reconstructed and linearly combined to produce an artifact-reduced image. The coefficients of this linear combination are automatically determined by minimizing a threshold-based cost function in the image domain. After thresholding, we obtain the prior image for FSNMAR, which is applied to the individual bin images and the lowest threshold image. We test our photon-counting normalized metal artifact reduction (PCNMAR) on forensic CT data and compare it to conventional FSNMAR, where the prior is generated via linear sinogram inpainting. For numerical analysis, we compute both the standard deviation in an ROI with metal artifacts and the CNR of soft tissue and fat. PCNMAR can effectively reduce metal artifacts without sacrificing the overall image quality. Compared to FSNMAR, our method produces fewer secondary artifacts and is more consistent with the measurements. Areas that contain metal, air, and soft tissue are more accurate in PCNMAR. In some cases, the standard deviation in the artifact ROI is reduced by more than 50% relative to FSNMAR, while the CNR values are similar. If extreme artifacts are present, PCNMAR is unable to outperform FSNMAR. Using either two, four, or only the highest energy bin to produce the prior image yielded comparable results. PCNMAR is an effective method of reducing metal artifacts in photon-counting CT. The spectral information available in photon-counting CT is highly beneficial for metal artifact reduction, especially the high-energy bin, which inherently contains fewer artifacts. While scanning with four instead of two bins does not provide a better artifact reduction, it allows for more freedom in the selection of energy thresholds.

Accuracy of digital model generated from CT data with metal artifact reduction algorithm

This study investigated whether metal artifact reduction (MAR) applied computed tomography (CT) scans could be used to generate precise digital models and explored possible correlations between the amount of metal artifact and model accuracy. Thirty maxillofacial CT scans were randomly selected and a MAR algorithm was applied. By subtracting the original and MAR-applied CT images, the amount of metal artifact was quantified. Digital models were generated from the original and the MAR-applied CT data. Paired digital models were superimposed and shape deviation in planar surface was measured at 10 points in 4 planes. Statistical analyses were performed to compare deviations and to assess correlations between the amount of artifact and deviation. The MAR algorithm reduced metal artifact in all cases. The overall mean deviation of the MAR-applied models was 0.0868 mm, with no significant difference according to the reference plane. The amount of artifact did not significantly influence the accuracy of the digital models. MAR-applied CT is a convenient source for digital modeling with clinically acceptable accuracy. The MAR algorithm can be used regardless of the amount of metal artifact, which are generated by dental prostheses, for the quick and convenient manipulation of dental digital models.

Noncontact Monitoring of Heart Rate and Heart Rate Variability in Geriatric Patients Using Photoplethysmography Imaging.

Geriatric patients, especially those with dementia or in a delirious state, do not accept conventional contact-based monitoring. Therefore, we propose to measure heart rate (HR) and heart rate variability (HRV) of geriatric patients in a noncontact and unobtrusive way using photoplethysmography imaging (PPGI). PPGI video sequences were recorded from 10 geriatric patients and 10 healthy elderly people using a monochrome camera operating in the near-infrared spectrum and a colour camera operating in the visible spectrum. PPGI waveforms were extracted from both cameras using superpixel-based regions of interests (ROI). A classifier based on bagged trees was trained to automatically select artefact-free ROIs for HR estimation. HRV was calculated in the time-domain and frequency-domain. an RMSE of 1.03bpm and a correlation of 0.8 with the reference was achieved using the NIR camera for HR estimation. Using the RGB camera, RMSE and correlation improved to 0.48bpm and 0.95, respectively. Correlation for HRV in the frequency-domain (LF/HF-ratio) was 0.50 using the NIR camera and 0.70 using the RGB camera. We were able to demonstrate that PPGI is very suitable to measure HR and HRV in geriatric patients. We strongly believe that PPGI will become clinically relevant in monitoring of geriatric patients. we are the first group to measure both HR and HRV in awake geriatric patients using PPGI. Moreover, we systematically evaluate the effects of the spectrum (near-infrared vs. visible), ROI, and additional motion artefact reduction algorithms on the accuracy of estimated HR and HRV.

Metal artefact reduction in the oral cavity using deep learning reconstruction algorithm in ultra-high-resolution computed tomography: a phantom study.

This study aimed to improve the impact of the metal artefact reduction (MAR) algorithm for the oral cavity by assessing the effect of acquisition and reconstruction parameters on an ultra-high-resolution CT (UHRCT) scanner. The mandible tooth phantom with and without the lesion was scanned using super-high-resolution, high-resolution (HR), and normal-resolution (NR) modes. Images were reconstructed with deep learning-based reconstruction (DLR) and hybrid iterative reconstruction (HIR) using the MAR algorithm. Two dental radiologists independently graded the degree of metal artefact (1, very severe; 5, minimum) and lesion shape reproducibility (1, slight; 5, almost perfect). The signal-to-artefact ratio (SAR), accuracy of the CT number of the lesion, and image noise were calculated quantitatively. The Tukey-Kramer method with a p-value of less than 0.05 was used to determine statistical significance. The HRDLR visual score was better than the NRHIR score in terms of degree of metal artefact (4.6 ± 0.5 and 2.6 ± 0.5, p < 0.0001) and lesion shape reproducibility (4.5 ± 0.5 and 2.9 ± 1.1, p = 0.0005). The SAR of HRDLR was significantly better than that of NRHIR (4.9 ± 0.4 and 2.1 ± 0.2, p < 0.0001), and the absolute percentage error of the CT number in HRDLR was lower than that in NRHIR (0.8% in HRDLR and 23.8% in NRIR). The image noise of HRDLR was lower than that of NRHIR (15.7 ± 1.4 and 51.6 ± 15.3, p < 0.0001). Our study demonstrated that the combination of HR mode and DLR in UHRCT scanner improved the impact of the MAR algorithm in the oral cavity.

Single-energy versus dual-energy imaging during CT-guided biopsy using dedicated metal artifact reduction algorithm in an in vivo pig model.

PurposeTo evaluate dual-energy CT (DE) and dedicated metal artifact reduction algorithms (iMAR) during CT-guided biopsy in comparison to single-energy CT (SE).MethodsA trocar was placed in the liver of six pigs. CT acquisitions were performed with SE and dose equivalent DE at four dose levels(1.7–13.5mGy). Iterative reconstructions were performed with and without iMAR. ROIs were placed in four positions e.g. at the trocar tip(TROCAR) and liver parenchyma adjacent to the trocar tip(LIVER-1) by two independent observers for quantitative analysis using CT numbers, noise, SNR and CNR. Qualitative image analysis was performed regarding overall image quality and artifacts generated by iMAR.ResultsThere were no significant differences in CT numbers between DE and SE at TROCAR and LIVER-1 irrespective of iMAR. iMAR significantly reduced metal artifacts at LIVER-1 for all exposure settings for DE and SE(p = 0.02-0.04), but not at TROCAR. SNR, CNR and noise were comparable for DE and SE. SNR was best for high dose levels of 6.7/13.5mGy. Mean difference in the Blant-Altman analysis was -8.43 to 0.36. Cohen’s kappa for qualitative interreader-agreement was 0.901.ConclusionsiMAR independently reduced metal artifacts more effectively and efficiently than CT acquisition in DE at any dose setting and its application is feasible during CT-guided liver biopsy.

CLIMAR: classified linear interpolation based metal artifact reduction for severe metal artifact reduction in x-ray CT imaging

In x-ray CT imaging, the existence of metal in the imaging field of view deteriorates the quality of the reconstructed image. This is because rays penetrating dense metal implants are highly corrupted, causing huge inconsistency between projection data. The result appears as strong artifacts such as black and white streaks on the reconstructed image disturbing correct diagnosis. For several decades, there have been various trials to reduce metal artifacts for better image quality. As the computing power of computer processors became more powerful, more complex algorithms with improved performance have been introduced. For instance, the initially developed metal artifact reduction (MAR) algorithms based on simple sinogram interpolation were combined with computationally expensive iterative reconstruction techniques to pursue better image quality. Recently, even machine learning based techniques have been introduced, which require huge amounts of computations for training. In this paper, we introduce an image based novel MAR algorithm in which severe metal artifacts such as black shadings are detected by the proposed method in a straightforward manner based on a linear interpolation. To do that, a new concept of metal artifact classification is devised using linear interpolation in the virtual projection domain. The proposed method reduces severe artifacts very quickly and effectively and has good performance to keep the detailed body structure preserved. Results of qualitative and quantitative comparisons with other representative algorithms such as LIMAR and NMAR support the excellence of the proposed algorithm. Thanks to the nature of reducing artifacts in the image itself and its low computational cost, the proposed algorithm can function as an initial image generator for other MAR algorithms, as well as being integrated in the modalities under limited computation power such as mobile CT scanners.

Application of an auto-edge counting method for quantification of metal artifacts in CBCT images: a multivariate analysis of object position, field of view size, tube voltage, and metal artifact reduction algorithm

The objective was to assess the effects of object position, field of view (FOV) size, peak kilovoltage (kVp), and a metal artifact reduction (MAR) algorithm on metal artifacts in cone beam computed tomography (CBCT) as measured with an auto-edge counting method. A titanium implant and a stainless steel intracanal post in a root were inserted in bovine rib blocks. CBCT scans were acquired with changes in object position (incisor, canine, and premolar-molar areas), FOV, kVp, and MAR (on or off) mode. Images were quantitatively analyzed in MATLAB by using the Canny edge detection algorithm. Four-way analysis of variance and Tukey tests were applied for data analysis. The implant produced no significant differences in number of artifacts among the object positions through changing the kVp and MAR mode for all FOV sizes (P > .05). The intracanal post scanned with the medium-sized FOV, high kVp, and MAR off mode generated significant differences among object positions (P=.033). Among the variables assessed, FOV size and MAR mode had a significant influence on the number of artifacts (P ≤ .039). Reduction of FOV size and application of the MAR tool significantly decreased the number of streak artifacts. The Canny edge detection algorithm could be an efficient method of metal artifact quantification.

Comprehensive assessments of the open mouth dynamic maneuver and metal artifact reduction algorithm on computed tomography images of the oral cavity and oropharynx.

ObjectivesTo determine the optimal utility of the open mouth maneuver and Metal Artifact Reduction for the Orthopedic Implants (O-MAR) technique for CT of the oral cavity and oropharynx.MethodsBetween July 2017 and May 2019, 59 subjects who underwent both conventional and open mouth head and neck CT scans were included in this retrospective study. All images were reconstructed using the O-MAR algorithm. With conventional CT with/without the O-MAR (CTc_O/CTc) and open mouth CT with/without O-MAR (CTo_O/CTo), one reader measured the noise level in multiple anatomic regions of the oral cavity and oropharynx. Visual scores for the streak artifact and overall subjective image quality were assessed by two independent readers.ResultsFor the mobile tongue, retromolar trigone, and palatine tonsil, the mean noise was significantly lower, and the mean visual scores were significantly higher, with CTo than with CTc or CTc_O (all, P < 0.001). The mean visual scores were higher with CTo_O than with CTo for the mobile tongue and palatine tonsil (all, P < 0.001). Contrarily, for the mouth floor and tongue base, the mean noise was significantly higher with CTo_O than with CTc or CTc_O, and the mean visual scores were significantly higher with CTc than with CTo or CTo_O (all, P < 0.001).ConclusionsThe open mouth maneuver and O-MAR technique can have different influences on the CT image quality according to the anatomical subsites of the oral cavity and oropharynx.

Reduction of CT artifacts from cardiac implantable electronic devices using a combination of virtual monoenergetic images and post-processing algorithms

ObjectivesTo evaluate the reduction of artifacts from cardiac implantable electronic devices (CIEDs) by virtual monoenergetic images (VMI), metal artifact reduction (MAR) algorithms, and their combination (VMIMAR) derived from spectral detector CT (SDCT) of the chest compared to conventional CT images (CI).MethodsIn this retrospective study, we included 34 patients (mean age 74.6 ± 8.6 years), who underwent a SDCT of the chest and had a CIED in place. CI, MAR, VMI, and VMIMAR (10 keV increment, range: 100–200 keV) were reconstructed. Mean and standard deviation of attenuation (HU) among hypo- and hyperdense artifacts adjacent to CIED generator and leads were determined using ROIs. Two radiologists qualitatively evaluated artifact reduction and diagnostic assessment of adjacent tissue.ResultsCompared to CI, MAR and VMIMAR ≥ 100 keV significantly increased attenuation in hypodense and significantly decreased attenuation in hyperdense artifacts at CIED generator and leads (p < 0.05). VMI ≥ 100 keV alone only significantly decreased hyperdense artifacts at the generator (p < 0.05). Qualitatively, VMI ≥ 100 keV, MAR, and VMIMAR ≥ 100 keV provided significant reduction of hyper- and hypodense artifacts resulting from the generator and improved diagnostic assessment of surrounding structures (p < 0.05). Diagnostic assessment of structures adjoining to the leads was only improved by MAR and VMIMAR 100 keV (p < 0.05), whereas keV values ≥ 140 with and without MAR significantly worsened diagnostic assessment (p < 0.05).ConclusionsThe combination of VMI and MAR as well as MAR as a standalone approach provides effective reduction of artifacts from CIEDs. Still, higher keV values should be applied with caution due to a loss of soft tissue and vessel contrast along the leads.Key Points• The combination of VMI and MAR as well as MAR as a standalone approach enables effective reduction of artifacts from CIEDs.• Higher keV values of both VMI and VMIMARat CIED leads should be applied with caution since diagnostic assessment can be hampered by a loss of soft tissue and vessel contrast.• Recommended keV values for CIED generators are between 140 and 200 keV and for leads around 100 keV.

Assessment of cardiac implantable electric device lead perforation using a metal artifact reduction algorithm in cardiac computed tomography

PurposeCT is considered the non-invasive gold standard for evaluating cardiac implantable electronic devices (CIEDs) lead perforation, but metal artifacts caused by the lead tip affect the image quality and make a definitive diagnosis challenging. We compared the performances of the metal artifact reduction (MAR) algorithm and the conventional algorithm for identification of the right ventricular (RV) lead tip position in cardiac CT studies of patients with CIEDs. MethodForty-seven consecutive patients (26 men; age 70.3 ± 15.4 years) with CIEDs underwent cardiac CT. Using the conventional and MAR algorithm, two image reconstructions were performed for each scan. We calculated the artifact index (AI) to assess the quantitative capability of the MAR algorithm for artifact reduction and visually assessed the RV lead tip position on both images as follows: non-perforation, perforation, and equivocal. ResultsThe mean AIs were significantly lower with the MAR algorithm than with the conventional algorithm (96.7 ± 40.1 HU vs. 284.6 ± 134.1 HU, P < 0.001). Thirteen (27.7 %) patients were diagnosed as equivocal using the conventional algorithm but were diagnosed with perforation (2 patients) and non-perforation (11 patients) using the MAR algorithm (equivocal rate: 27.7 % vs. 0%, P < 0.001). Using the MAR algorithm, all cases were diagnosed with perforation (6 patients, 12.8 %) or non-perforation (41 patients, 87.2 %). ConclusionsThe MAR algorithm effectively reduced metal artifacts and allowed us to diagnose the presence or absence of perforation in all cases, whereas definitive diagnosis was difficult with the use of conventional algorithm in 27.7 % of cases.

Assessment of the efficiency of a pre- versus post-acquisition metal artifact reduction algorithm in the presence of 3 different dental implant materials using multiple CBCT settings: An in vitro study.

PurposeThe aim of this study was to assess artifacts generated in cone-beam computed tomography (CBCT) of 3 types of dental implants using 3 metal artifact reduction (MAR) algorithm conditions (pre-acquisition MAR, postacquisition MAR, and no MAR), and 2 peak kilovoltage (kVp) settings.Materials and MethodsTitanium-zirconium, titanium, and zirconium alloy implants were placed in a dry mandible. CBCT images were acquired using 84 and 90 kVp and at normal resolution for all 3 MAR conditions. The images were analyzed using ImageJ software (National Institutes of Health, Bethesda, MD) to calculate the intensity of artifacts for each combination of material and settings. A 3-factor analysis of variance model with up to 3-way interactions was used to determine whether there was a statistically significant difference in the mean intensity of artifacts associated with each factor.ResultsThe analysis of all 3 MAR conditions showed that using no MAR resulted in substantially more severe artifacts than either of the 2 MAR algorithms for the 3 implant materials; however, there were no significant differences between pre- and post-acquisition MAR. The 90 kVp setting generated less intense artifacts on average than the 84 kVp setting. The titanium-zirconium alloy generated significantly less intense artifacts than zirconium. Titanium generated artifacts at an intermediate level relative to the other 2 implant materials, but was not statistically significantly different from either.ConclusionThis in vitro study suggests that artifacts can be minimized by using a titanium-zirconium alloy at the 90 kVp setting, with either MAR setting.

Measurement of Peri-Implant Bone Width with and without Metal Artifact Reduction Algorithm Using Two Cone-Beam Computed Tomography Software Programs

Objective: To assess the effect of metal artifact reduction (MAR) algorithm of two cone-beam computed tomography (CBCT) software programs on the accuracy of peri-implant bone width measurements . Material and Methods: This in vitro study evaluated 35 bovine rib bone blocks measuring 8 x 8 x 11 mm. Titanium implants were inserted in bone blocks and placed in a wax model of mandible. CBCT scans were obtained with ProMax 3D and Cranex 3D CBCT systems with and without the MAR algorithm. The width of buccal and lingual bone plates surrounding the implant was measured on CBCT scans by two observers. The Cronbach’s alpha was calculated to assess inter-observer agreement. The area under the curve (AUC), sensitivity and specificity values were calculated and compared. Results: The two observers had an excellent agreement. The accuracy of Cranex 3D was higher than that of ProMax 3D (p<0.05). Both CBCT systems showed higher accuracy when the MAR algorithm was not used (p<0.05). Both CBCT systems showed higher accuracy for measuring the width of the lingual plate than buccal plate (p<0.05) . Conclusion: The application of MAR algorithm did not notably increase the measurement accuracy in any CBCT system. Cranex 3D showed generally higher measurement accuracy than ProMax 3D.

Evaluation of image quality of a novel computed tomography metal artifact management technique on an anthropomorphic head and neck phantom.

Background and purposeArtefacts caused by dental amalgam implants present a common challenge in computed tomography (CT) and therefore treatment planning dose calculations. The goal was to perform a quantitative image quality analysis of our Artifact Management for Proton Planning (AMPP) algorithm which used gantry tilts for managing metal artefacts on Head and Neck (HN) CT scans and major vendors’ commercial approaches.Materials and methodsMetal artefact reduction (MAR) algorithms were evaluated using an anthropomorphic phantom with a removable jaw for the acquisition of images with and without (baseline) metal artifacts. AMPP made use of two angled CT scans to generate one artifact-reduced image set. The MAR algorithms from four vendors were applied to the images with artefacts and the analysis was performed with respective baselines. Planar HU difference maps and volumetric HU differences were analyzed.ResultsAMPP algorithm outperformed all vendors’ commercial approaches in the elimination of artefacts in the oropharyngeal region, showing the lowest percent of pixels outside +− 20 HU criteria, 4%; whereas those in the MAR-corrected images ranged from 26% to 67%. In the region of interest within the affected slices, the commercial MAR algorithms showed inconsistent performance, whereas the AMPP algorithm performed consistently well throughout the phantom’s posterior region.ConclusionsA novel MAR algorithm was evaluated and compared to four commercial algorithms using an anthropomorphic phantom. Unanimously, the analysis showed the AMPP algorithm outperformed vendors’ commercial approaches, showing the potential to be broadly implemented, improve visualizations in patient anatomy and provide accurate HU information.

Comparison of the Quality of Various Polychromatic and Monochromatic Dual-Energy CT Images with or without a Metal Artifact Reduction Algorithm to Evaluate Total Knee Arthroplasty.

ObjectiveTo compare the quality of various polychromatic and monochromatic images with or without using an iterative metal artifact reduction algorithm (iMAR) obtained from a dual-energy computed tomography (CT) to evaluate total knee arthroplasty.Materials and MethodsWe included 58 patients (28 male and 30 female; mean age [range], 71.4 [61–83] years) who underwent 74 knee examinations after total knee arthroplasty using dual-energy CT. CT image sets consisted of polychromatic image sets that linearly blended 80 kVp and tin-filtered 140 kVp using weighting factors of 0.4, 0, and −0.3, and monochromatic images at 130, 150, 170, and 190 keV. These image sets were obtained with and without applying iMAR, creating a total of 14 image sets. Two readers qualitatively ranked the image quality (1 [lowest quality] through 14 [highest quality]). Volumes of high- and low-density artifacts and contrast-to-noise ratios (CNRs) between the bone and fat tissue were quantitatively measured in a subset of 25 knees unaffected by metal artifacts.ResultsiMAR-applied, polychromatic images using weighting factors of −0.3 and 0.0 (P−0.3i and P0.0i, respectively) showed the highest image-quality rank scores (median of 14 for both by one reader and 13 and 14, respectively, by the other reader; p < 0.001). All iMAR-applied image series showed higher rank scores than the iMAR-unapplied ones. The smallest volumes of low-density artifacts were found in P−0.3i, P0.0i, and iMAR-applied monochromatic images at 130 keV. The smallest volumes of high-density artifacts were noted in P−0.3i. The CNRs were best in polychromatic images using a weighting factor of 0.4 with or without iMAR application, followed by polychromatic images using a weighting factor of 0.0 with or without iMAR application.ConclusionPolychromatic images combined with iMAR application, P−0.3i and P0.0i, provided better image qualities and substantial metal artifact reduction compared with other image sets.

Metal artifacts reduction in computed tomography: A phantom study to compare the effectiveness of metal artifact reduction algorithm, model-based iterative reconstruction, and virtual monochromatic imaging.

The purpose of this study was to compare the effectiveness of a metal artifact reduction algorithm (MAR), model-based iterative reconstruction (MBIR), and virtual monochromatic imaging (VMI) for reducing metal artifacts in CT imaging.A phantom study was performed for quantitatively evaluating the dark bands and fine streak artifacts generated by unilateral hip prostheses. Images were obtained by conventional scanning at 120 kilovolt peak, and reconstructed using filtered back projection, MAR, and MBIR. Furthermore, virtual monochromatic images (VMIs) at 70 kilo-electron volts (keV) and 140 keV with/without use of MAR were obtained by dual-energy CT. The extents and mean CT values of the dark bands and the differences in the standard deviations and location parameters of the fine streak artifacts evaluated by the Gumbel method in the images obtained by each of the methods were statistically compared by analyses of variance.Significant reduction of the extent of the dark bands was observed in the images reconstructed using MAR than in those not reconstructed using MAR (all, P < .01). Images obtained by VMI at 70 keV and 140 keV with use of MAR showed significantly increased mean CT values of the dark bands as compared to those obtained by reconstructions without use of MAR (all, <.01). Significant reduction of the difference in the standard deviations used to evaluate fine streak artifacts was observed in each of the image sets obtained with VMI at 140 keV with/without MAR and conventional CT with MBIR as compared to the images obtained using other methods (all, P < .05), except between VMI at 140 keV without MAR and conventional CT with MAR. The location parameter to evaluate fine streak artifacts was significantly reduced in CT images obtained using MBIR and in images obtained by VMI at 140 keV with/without MAR as compared to those obtained using other reconstruction methods (all, P < .01).In our present study, MAR appeared to be the most effective reconstruction method for reducing dark bands in CT images, and MBIR and VMI at 140 keV appeared to the most effective for reducing streak artifacts.

Evaluation of radiation treatment planning by computed tomography metal artifact reduction algorithm

Introduction: The objective of this study was to evaluate the usefulness of Computed Tomography(CT) images acquired through repeated subtraction reconstruction algorithms to reduce metal artifacts in CT Treatment Planning System(TPS).Materials and methods: Origin images of Gammex phantom and Rando phantom and non orthopedic metal artifact reduction(O-MAR) images were obtained after high density implantation. O-MAR applied images were also obtained. For evaluation of images, regions of interest(ROI) were set at five tissue rods and three points directly affected by artifacts in Gammex phantom. CT number and noise were compared and analyzed. To investigate dose change according to CT number change of the surrounding artifact, a three virtual cylindrical target volume was formed on Rando phantom CT images. The average dose was then compared and analyzed.Results: CT number difference according to the application of O-MAR showed significant difference among lung and bone rod and 3 ROI directly affected. Noise difference according to O-MAR application was significantly different in rod except for bone rod. In the treatment plan using Rando phantom, non-O-MAR and O-MAR images showed -4.3 ~ 1.9% and -0.4 ~ 2.3% dose differences, respectively.Conclusion: Applying a metal artifact reduction reconstruction algorithm can reduce image distortion due to high density implantation, improve image quality, and correct CT number.

15-year follow-up of MoM 36-mm THA: clinical, laboratory, and radiological (CT and MRI) prospective assessment.

There is limited knowledge of the long-term results of metal-on-metal total hip arthroplasty (MoM THA), particularly concerning adverse local tissue reaction (ALTR), Co/Cr ions level and revision rate. Even if MoM bearing surfaces are no longer used, long-term data could help in defining the course and best management for these patients. The purpose of this study is to investigate the clinical outcomes, describe radiological findings including CT metal artefact reduction algorithm for orthopaedic implants (O-MAR) and MRI multi acquisition variable resonance image combination (MAVRIC) in 36-mm MoM THA. In this long-term prospective study, 46 consecutive patients with primary MoM THA (mono- or bilateral) were enrolled between 2004 and 2005. Pinnacle acetabular cup, Summit cementless stem with 36-mm metal head and Ultamet CoCr alloy liner (Depuy Inc.) were implanted, in the same centre by the same senior surgeon. Patients were reviewed at 5-, 10- and 15-years, including Co/Cr levels and standard radiographs at every follow-up, whilst the 15-year follow-up included hip sonography, MRI MAVRIC and CT O-MAR. At 15 years, the overall survival rate of the implants (both stems and cups) was 83% (30/36). Revisions were performed in 9% (4/46) because of ALTR, 2% (1/46) septic loosening and 2% periprosthetic fracture. Both Cr and Co concentration increased over time, even though remaining at low level risk at 15 years: Co from 0.11 (+/- 0.18) to 4.29 (+/- 3.26) and Cr from 0.38 (+/- 0.32) to 1.37 (+/- 1.15). Functional scores in non-revised patients showed good to excellent results in more than 90%. Engh-score correlated with time from surgery (p = 0.017) and with sonographic, CT and RM findings (p < 0.05). Concordance has been found between CT and MRI findings (sign-rank test, p = 0.241; Intraclass Correlation Coefficients 0.987); however, no specific MRI or CT lesion patterns could be recognised among symptomatic and non-symptomatic patients. The long-term rate of ALTR after 36-mm MoM THA was comparable with previous studies; a regular follow-up for those implants is mandatory. During follow-up Co-Cr levels increased over time and radiography was a suitable screening technique; the Engh score in particular, proved to be a reliable assessment tool. CT O-MAR and MRI with MAVRIC protocols may add valuable data in clinical practice, although MRI is significantly more efficient than CT in the identification of ALTR lesions, peri-articular effusion and in the evaluation of soft tissues.

Dosimetric impact of commercial CT metal artifact reduction algorithms and a novel in-house algorithm for proton therapy of head and neck cancer.

To compare the dosimetric impact of all major commercial vendors' metal artifact reduction (MAR) algorithms to one another, as well as to a novel in-house technique (AMPP) using an anthropomorphic head phantom. The phantom was an Alderson phantom, modified to allow for artifact-filled and baseline (no artifacts) computed tomography (CT) scans using teeth capsules made with metal amalgams or bone-equivalent materials. It also included a cylindrical insert that was accessible from the bottom of the neck and designed to introduce soft tissue features into the phantom that were used in the analysis. The phantom was scanned with the metal teeth in place using each respective vendor's MAR algorithm: OMAR (Philips), iMAR (Siemens), SEMAR (Canon), and SmartMAR (GE); the AMPP algorithm was designed in-house. Uncorrected and baseline (bone-equivalent teeth) image sets were also acquired using a Siemens scanner. Proton spot scanning treatment plans were designed on the baseline image set for five targets in the phantom. Once optimized, the proton beams were copied onto the different artifact-corrected image sets, with no reoptimization of the beams' parameters, to evaluate dose distribution differences in the different MAR-corrected and -uncorrected image sets. Dose distribution differences were evaluated by comparing dose-volume histogram (DVH) metrics, including planning target volume D95 and clinical target volume D99 coverages, V100, D0.03cc, and heterogeneity indexes, along with a qualitative and water equivalent thickness (WET) analysis. Uncorrected CT metal artifacts and commercial MAR algorithms negatively impacted the proton dose distributions of all five target shapes and locations in an inconsistent manner, sometimes overdosing by as much as 11.1% (D0.03) or underdosing by as much as 11.7% (V100) the planning target volumes. The AMPP-corrected images, however, provided dose distributions that consistently agreed with the baseline dose distribution. The dosimetry results also suggest that the commercial MAR algorithms' performances varied more with target location and less with target shape. Once relocated further from the metal, the target showed dose distributions that agreed more with the baseline for all commercial solutions, improving the overdosing by as much as 6%, implying inadequate HU correction from commercial MAR algorithms. In comparison to the baseline, HU profile shapes were considerably altered by commercial algorithms and reference values showed differences that represent stopping power percentage differences of 2.7-10%. The AMPP algorithm plans showed the smallest WET differences with the baseline (0.06cm on average), while the commercial image sets created differences that ranged from 0.11 to 0.54cm. Computed tomography metal artifacts negatively impacted proton dose distributions on all five targets analyzed. The commercial MAR solutions performed inconsistently throughout all targets compared to the metal-free baseline. A lack of CTV coverage and an increased number of hotspots were observed throughout all commercial solutions. Dose distribution errors were related to the proximity to the artifacts, demonstrating the inability of commercial techniques to adequately correct severe artifacts. In contrast, AMPP consistently showed dose distributions that best matched the baseline, likely because it makes use of accurate HU information, as opposed to interpolated data like commercial algorithms.