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Deep brain stimulation (DBS) is an interdisciplinary and reversible therapy that uses high-frequency electrical stimulation to correct aberrant neural pathways in motor and cognitive neurological disorders. However, the high frequency of the waves used in DBS can interfere with electrical recording devices (e.g., electrocardiogram, electroencephalogram, cardiac monitor), creating artifacts that hinder their interpretation. The compatibility of DBS with these devices varies and depends on factors such as the underlying disease and the configuration of the neurostimulator. In emergencies where obtaining an electrocardiogram is crucial, the need for more consensus on reducing electrical artifacts in patients with DBS becomes a significant challenge. Various strategies have been proposed to attenuate the artifact generated by DBS, such as changing the DBS configuration from monopolar to bipolar, temporarily deactivating DBS during electrocardiographic recording, applying frequency filters both lower and higher than those used by DBS, and using non-standard leads. However, the inexperience of medical personnel, variability in DBS models, or the lack of a controller at the time of approach limit the application of these strategies. Current evidence on their reproducibility and efficacy is limited. Due to the growing elderly population and the rising utilization of DBS, it is imperative to create electrocardiographic methods that are easily accessible and reproducible for general physicians and emergency services.

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Photoacoustic (PA) imaging has the potential to deliver non-invasive diagnostic information. However, skin tone differences bias PA target visualization, as the elevated optical absorption of melanated skin decreases optical fluence within the imaging plane and increases the presence of acoustic clutter. This paper demonstrates that short-lag spatial coherence (SLSC) beamforming mitigates this bias. PA data from the forearm of 18 volunteers were acquired with 750-, 810-, and 870-nm wavelengths. Skin tones ranging from light to dark were objectively quantified using the individual typology angle (ITA°). The signal-to-noise ratio (SNR) of the radial artery (RA) and surrounding clutter were measured. Clutter was minimal (e.g., -16 dB relative to the RA) with lighter skin tones and increased to -8 dB with darker tones, which compromised RA visualization in conventional PA images. SLSC beamforming achieved a median SNR improvement of 3.8 dB, resulting in better RA visualization for all skin tones.

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Three-dimensional cone-beam computed tomography (CBCT) has an important role in the detection of vertical root fractures (VRFs). The effect of artifact generation by high-density objects like dental implants on image quality was well documented. This study aimed to assess the effect of tooth-implant distance and the application of metal artifact reduction (MAR) algorithm on the detection of VRFs on CBCT scans. This study was conducted on 20 endodontically treated single-rooted teeth. VRFs were induced in 10 teeth, while the other 10 remained intact. The implant was inserted in the right second premolar socket area, and two teeth were inserted in right canine and right first premolar sockets area randomly and underwent CBCT with and without the application of MAR algorithm. SPSS 21 was used to analyze the results (alpha=0.05). According to the findings of this study, all four variables of sensitivity, specificity, accuracy, and positive predictive values in diagnosis were higher in cases without MAR software at both close(roots in first premolar sockets) and far distances (roots in canine sockets) from the implant. However, the highest rate of diagnosis accuracy of the first and second radiologists was in the far distance group from the implant without MAR, and the lowest rate of diagnosis accuracy in the first and second radiologists was in the close distance to the implant. Applying MAR algorithm had no positive effect on detection of VRFs on CBCT scans in both close and distant scenarios.

La tomografía computarizada de haz cónico tridimensional (CBCT) tiene un papel importante en la detección de fracturas radiculares verticales (VRF). El efecto de la generación de artefactos por objetos de alta densidad como los implantes dentales en la calidad de la imagen está bien documentado. Este estudio tuvo como objetivo evaluar el efecto de la distancia entre el diente y el implante y la aplicación del algoritmo de reducción de artefactos metálicos (MAR) en la detección de VRF en escaneos CBCT. Este estudio se realizó en 20 dientes uniradiculares tratados endodónticamente. Se indujeron VRF en 10 dientes, mientras que los otros 10 permanecieron intactos. El implante se insertó en el área del alveolo del segundo premolar derecho, y dos dientes se insertaron en el canino derecho y en el área del alvéolo del primer premolar derecho al azar y se sometieron a CBCT con y sin la aplicación del algoritmo MAR. Se utilizó SPSS 21 para analizar los resultados (alfa=0,05). De acuerdo con los hallazgos de este estudio, las cuatro variables de sensibilidad, especificidad, precisión y valores predictivos positivos en el diagnóstico fueron más altas en los casos sin el software MAR tanto en distancias cercanas (raíces en las cavidades de los primeros premolares) como lejanas (raíces en las cavidades de los caninos) del implante. Sin embargo, la tasa más alta de precisión diagnóstica del primer y segundo radiólogo fue en el grupo de mayor distancia al implante sin MAR, y la tasa más baja de precisión diagnóstica en el primer y segundo radiólogo fue en la distancia cercana al implante. La aplicación del algoritmo MAR no tuvo un efecto positivo en la detección de VRF en escaneos CBCT en escenarios cercanos y distantes.

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Objetivo: disminuir el efecto de artefacto que generan objetos de alta densidad mediante la utilización de filtros de distintos materiales y espesores, ubicados en lugares estratégicos del tomógrafo. Material y métodos: se utilizaron filtros de aluminio y de cobre ubicados en lugares estratégicos en el equipo tomográfico. Se realizaron cortes oblicuos en piezas dentarias con restauraciones metálicas y en implantes; se midió la extensión del artefacto en ancho y alto en cada adquisición tomográfica. Resultados: se hallaron diferencias significativas respecto a la disminución de la dispersión de acuerdo con cada filtro con respecto a la no utilización de estos elementos. Conclusión: la utilización de filtros logró disminuir el efecto de artefacto en estructuras de alta densidad, obteniendo una mejor calidad de imagen para el diagnóstico, permitiendo que el software pueda reconstruir una imagen real (AU)

Objective: to diminish the artifact effect generated by high density objects by using filters of different materials and thickness, located in strategic places of the tomograph. Material and methods: aluminum and copper filters located in strategic places in the tomographic equipment were used. Oblique cuts were made on dental pieces with metal restorations and implants; the extension of the artifact in width and height was measured in each tomographic acquisition. Results: significant differences were found regarding the decrease of the dispersion according to each filter with respect to the non-use of these elements. Conclusion: the use of filters achieves to diminish the artifact effect in structures of high density, obtaining a better image quality for the diagnosis, allowing the software to reconstruct a real image (AU)

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The Electroencephalography (EEG)-based motor imagery (MI) paradigm is one of the most studied technologies for Brain-Computer Interface (BCI) development. Still, the low Signal-to-Noise Ratio (SNR) poses a challenge when constructing EEG-based BCI systems. Moreover, the non-stationary and nonlinear signal issues, the low-spatial data resolution, and the inter- and intra-subject variability hamper the extraction of discriminant features. Indeed, subjects with poor motor skills have difficulties in practicing MI tasks against low SNR scenarios. Here, we propose a subject-dependent preprocessing approach that includes the well-known Surface Laplacian Filtering and Independent Component Analysis algorithms to remove signal artifacts based on the MI performance. In addition, power- and phase-based functional connectivity measures are studied to extract relevant and interpretable patterns and identify subjects of inefficency. As a result, our proposal, Subject-dependent Artifact Removal (SD-AR), improves the MI classification performance in subjects with poor motor skills. Consequently, electrooculography and volume-conduction EEG artifacts are mitigated within a functional connectivity feature-extraction strategy, which favors the classification performance of a straightforward linear classifier.

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BACKGROUND: Pain after thoracic surgery impairs lung function and increases the rate of postoperative pulmonary complications. Ultrasound-guided percutaneous cryoanalgesia of intercostal nerves constitutes a valid option for adequate postoperative analgesia. A key issue for a successful cryoanalgesia is placing the cryoprobe tip close to the intercostal nerve. This report describes an ultrasound technique using a high-resolution ultrasound probe to accomplish this goal. FINDINGS: Images of five anesthetized patients undergoing uniportal video-thoracoscopic surgeries are used as clinical examples. In the lateral position, a high-frequency 12 MHz probe is placed longitudinally at 5-7 cm parallel to the spine at the 4th, 5th, and 6th ipsilateral intercostal spaces. Ultrasound images detect the intercostal neurovascular bundle and a 14G angiocath is placed beside the nerve. The cryoprobe is inserted throughout the 14G catheter and the cryoanalgesia cycle is performed for 3 min. Two ultrasound signs confirm the right cryoprobe position close to the nerve: one is a color Doppler twinkling artifact that is seen as the quick shift of colors that delineates the cryoprobe contour. The other is a spherical hypoechoic image caused by the ice ball formed at the cryoprobe tip. CONCLUSIONS: Ultrasound images obtained with a high-frequency probe allow precise location of the cryoprobe tip close to the intercostal nerve for cold axonotmesis.

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PURPOSE: The use of psychometric instruments to measure latent concepts is common. The development of these instruments usually involves mechanisms to reduce response bias, such as the inclusion of reversed items. The aim of this study was to investigate method effects related to the wording direction of the Social Physique Anxiety Scale (SPAS) items, a one-dimensional instrument that assesses individual's level of anxiety when others observe their body. METHODS: In total, 152 Brazilian adults (65.8% female) answered 2 formats of the SPAS: the original with 12 items (7 regular and 5 reversed); and a new format with all items written in the same direction (i.e., regular). Both formats were filled out at different times and alternately. Differential item functioning analysis (DIF) and confirmatory factor analysis were conducted. RESULTS: The original SPAS did not fit the data, but after allowing covariances between all reversed items, the fit improved. The wording effect was supported by the DIF, indicating a better fit to the data for the new format with all items worded in the same direction. CONCLUSION: The wording of the SPAS items had effect on the psychometric properties of instrument. When the wording of the reversed items was modified, the factor model fitted the data. Future studies should take these findings into account and evaluate the SPAS with all items worded in the same direction in different contexts. LEVEL OF EVIDENCE: Descriptive (cross-sectional) study, Level V.

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Abstract The aim of this study was to compare the influence of endodontic sealers artifacts on the detection of vertical root fracture in cone beam computed tomography (CBCT). Premolars and central incisors were assigned into five different groups: Control, Pulp Canal Sealer, AH Plus, Sealer 26, and BC Sealer (n= 10, per group). VRFs were mechanically induced and the teeth were inserted into an image phantom. Subsequently, CBCT (Cranex 3Dx, Soredex, Tuusula, Finland) images were obtained and two observers were asked separately to identify root fracture, by visual analysis. For both premolar and central incisors, kappa coefficients of intraobserver agreement varied from good to excellent (K: 80% - 87%), and the values for interobserver agreement varied from fair to moderate (K: 30% - 35%). As follows, the area under the curve (AUC) of receiver operating characteristic (ROC) values for VRFs highlighted that the use of BC sealer reduced the observers' ability to discriminate VRFs relative to other sealers. Moreover, sensitivity values for premolars teeth ranged from 20% to 60%, and specificity ranged from 60% to 100%; while sensitivity values for central incisors ranged from 30% to 70%, and specificity ranged from 70% to 100%. In conclusion, the low sensitivity values, mainly for premolars, demonstrated the difficulty in VRF diagnosis. Furthermore, BC Sealer induced significantly more imaging artifacts than other sealers. These results highlighting that endodontic sealers may interfere with the diagnosis of VRFs.

Resumo O objetivo deste estudo foi comparar a influência dos artefatos de cimentos endodônticos na detecção de fratura radicular vertical (FRV) em tomografia computadorizada de feixe cônico (TCFC). Pré-molares e incisivos centrais foram divididos em cinco grupos diferentes: Controle, Pulp Canal Sealer, AH Plus, Sealer 26 e BC Sealer (n = 10, por grupo). As FRVs foram induzidas mecanicamente e os dentes inseridos em uma réplica da mandibula humana. Posteriormente, imagens de TCFC (Cranex 3Dx, Soredex, Tuusula, Finlândia) foram obtidas e dois observadores foram solicitados a identificar fratura radicular separadamente, o critério utilizado foi a análise visual. Tanto para pré-molares quanto para incisivos centrais, os coeficientes kappa de concordância intraobservador variaram de bom a excelente (K: 80% - 87%), e os valores de concordância interobservador variaram de regular a moderado (K: 30% - 35%). A seguir, a área sob a curva (AUC) dos valores da característica de operação do receptor (ROC) para FRVs destacou que o uso do cimento BC Sealer reduziu a capacidade dos observadores de discriminar FRVs em relação a outros cimentos endodônticos. Além disso, os valores de sensibilidade para pré-molares variaram de 20% a 60%, e a especificidade variou de 60% a 100%; enquanto os valores de sensibilidade para incisivos centrais variaram de 30% a 70%, e a especificidade variou de 70% a 100%. Em conclusão, os baixos valores de sensibilidade, principalmente para pré-molares, demonstraram uma dificuldade no diagnóstico de FRV. Além disso, o BC Sealer induziu significativamente mais artefatos de imagem do que outros cimentos. Esses resultados evidenciam que os cimentos endodônticos podem interferir no diagnóstico das FRVs.

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Introduction: Electroencephalographic (EEG) data quality is severely compromised when recorded inside the magnetic resonance (MR) environment. Here we characterized the impact of the ballistocardiographic (BCG) artifact on resting-state EEG spectral properties and compared the effectiveness of seven common BCG correction methods to preserve EEG spectral features. We also assessed if these methods retained posterior alpha power reactivity to an eyes closure-opening (EC-EO) task and compared the results from EEG-informed fMRI analysis using different BCG correction approaches. Method: Electroencephalographic data from 20 healthy young adults were recorded outside the MR environment and during simultaneous fMRI acquisition. The gradient artifact was effectively removed from EEG-fMRI acquisitions using Average Artifact Subtraction (AAS). The BCG artifact was corrected with seven methods: AAS, Optimal Basis Set (OBS), Independent Component Analysis (ICA), OBS followed by ICA, AAS followed by ICA, PROJIC-AAS and PROJIC-OBS. EEG signal preservation was assessed by comparing the spectral power of traditional frequency bands from the corrected rs-EEG-fMRI data with the data recorded outside the scanner. We then assessed the preservation of posterior alpha functional reactivity by computing the ratio between the EC and EO conditions during the EC-EO task. EEG-informed fMRI analysis of the EC-EO task was performed using alpha power-derived BOLD signal predictors obtained from the EEG signals corrected with different methods. Results: The BCG artifact caused significant distortions (increased absolute power, altered relative power) across all frequency bands. Artifact residuals/signal losses were present after applying all correction methods. The EEG reactivity to the EC-EO task was better preserved with ICA-based correction approaches, particularly when using ICA feature extraction to isolate alpha power fluctuations, which allowed to accurately predict hemodynamic signal fluctuations during the EEG-informed fMRI analysis. Discussion: Current software solutions for the BCG artifact problem offer limited efficiency to preserve the EEG spectral power properties using this particular EEG setup. The state-of-the-art approaches tested here can be further refined and should be combined with hardware implementations to better preserve EEG signal properties during simultaneous EEG-fMRI. Existing and novel BCG artifact correction methods should be validated by evaluating signal preservation of both ERPs and spontaneous EEG spectral power.

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BACKGROUND: According to the European Reference Organization for Quality Assurance Breast Screening and European Diagnostic Services, the spatial accuracy of reconstructed images and reconstruction artifacts must be evaluated in digital breast tomosynthesis (DBT) quality control procedures. PURPOSE: To propose a computational algorithm to evaluate the geometric distortion and artifact spreading (GDAS) in DBT images. MATERIAL AND METHODS: The proposed algorithm analyzed tomosynthesis images of a phantom that contains aluminum spheres (1 mm in diameter) arranged in a rectangular matrix spaced 5 cm apart that was inserted in 5-mm-thick polymethylmethacrylate (PMMA). RESULTS: The obtained results were compared with the values provided by the algorithm developed by the National Coordinating Center for the Physics of Mammography (NCCPM). In the comparison, the results depended on the dimensions of the region of interest (ROI). This dependence proves the benefit of the proposed algorithm because it allows the user to select the ROI. CONCLUSION: The computational algorithm proved to be useful for the evaluation of GDAS in DBT images, in the same way as the reference algorithm (NCCPM), as well as allowing the selection of the ROI dimensions that best suit the spreading of the artifact in the analyzed images.

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Image quality (IQ) assessment plays an important role in the medical world. New methods to evaluate image quality have been developed, but their application in the context of computer tomography is yet limited. In this paper the performance of fifteen well-known full reference (FR) IQ metrics is compared with human judgment using images affected by metal artifacts and processed with metal artifact reduction methods from a phantom. Five region of interest with different sizes were selected. IQ was evaluated by seven experienced radiologists completely blinded to the information. To measure the correlation between FR-IQ, and the score assigned by radiologists non-parametric Spearman rank-order correlation coefficient and Kendall's Rank-order Correlation coefficient were used; so as root mean square error and the mean absolute error to measure the prediction accuracy. Cohen's kappa was employed with the purpose of assessing inter-observer agreement. The metrics GMSD, IWMSE, IWPSNR, WSNR and OSS-PSNR were the best ranked. Inter-observer agreement was between 0.596 and 0.954, with p<0.001 in all study. The objective scores predicted by these methods correlate consistently with the subjective evaluations. The application of this metrics will make possible a better evaluation of metal artifact reduction algorithms in future works.

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OBJECTIVE: To compare the expression of the volumetric alteration (VA) artifact between cylindrical and convex triangular fields of view (FOVs) using high-density materials in different positions in two cone-beam computed tomography (CBCT) devices. MATERIALS AND METHODS: Cylinders of five high-density materials (amalgam, chromium-cobalt, gutta-percha, titanium, and zirconium) with known physical volume were individually submitted to CBCT acquisition in four positions inside a polymethylmethacrylate phantom using two different FOV shapes (convex triangular and cylindrical) on the Veraviewepocs® R100 (R100) and Veraview® X800 (X800) devices. Two oral radiologists obtained the tomographic volumes by segmenting each cylinder. The difference between the tomographic and physical volumes corresponded to the VA. These values were analyzed by intraclass correlation coefficient and analysis of variance for repeated measures with Tukey post hoc test (α = 5%). RESULTS: The FOV influenced the VA only in the X800 device (p = 0.014): the VA in the triangular FOV was greater than in the cylindrical FOV. The VA in the triangular FOV of the X800 device was greater than the R100 device (p < 0.0001). The material influenced the expression of the VA only in the R100 device (p < 0.0001); gutta-percha presented the highest VA, being underestimated, and differing from the other materials (p < 0.01). CONCLUSION: The triangular FOV increased the VA of high-density materials in the X800 device. CLINICAL RELEVANCE: It is important to know if there is an influence on the volumetric alteration artifact of dental materials due to the different image formation geometry in the convex triangular FOV.

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BACKGROUND: SmoothSilk implants (SSI) are the first generation of implants to incorporate a radio-frequency identification device (RFID-M), a non-invasive traceability system. Although the RFID-M is considered compatible with magnetic resonance imaging (MRI), the size of the artifact and its influence on breast tissue vary. This prospective study assessed safety and MRI issues in a cohort of breast reconstruction patients. METHODS: Forty-four SSI were used for breast reconstruction in patients undergoing treatment for breast cancer. All patients were evaluated for magnetic field interactions, MRI-related heating and artifacts in a 1.5-T MRI unit using standard T1/T2-weighted sequences utilized in clinical assessment of breast tissue/implants. RESULTS: Mean patient age was 41.5 years (27-53ys) and body mass index was 28+-6.44 kg/m2. In 18/22 patients (81.8%), mastectomies were unilateral. No patients reported local heat/discomfort. All implants showed RFID-M-related artifacts with an estimated mean volume in T1 of 42.9cm3 (26.2-63.6cm3; SD±8.6 and 95% CI, 40.37-45.45) and in T2 of 60.5cm3 (35.4-97.2cm3; SD±14.7 and 95% CI, 56.29-65.01). Artifact volume was smaller in T1 than in T2, to a statistically significant degree (p <0.001). There were no statistically significant differences in artifact volume according to surgical indication, breast side or implant volume. There were 4/44 (9%) cases of minor rotation (<45°). In all cases, adequate analysis of the breast tissue was performed. CONCLUSIONS: The results demonstrate that SSI with RFID-M technology presented an artifact volume of 42.9cm3 and 60.5cm3 in T1 and T2 images, respectively. Our findings provide detailed information on the quality and location of MRI artifacts in a reconstructed cohort which can help guide clinical decision-making for patients. To our knowledge, this is the first time RFID-M breast implants have been prospectively evaluated for clinical and MRI issues in a cohort of reconstructive patients. LEVEL OF EVIDENCE IV: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

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The literature provides many works that focused on cell nuclei segmentation in histological images. However, automatic segmentation of bone canals is still a less explored field. In this sense, this paper presents a method for automatic segmentation approach to assist specialists in the analysis of the bone vascular network. We evaluated the method on an image set through sensitivity, specificity and accuracy metrics and the Dice coefficient. We compared the results with other automatic segmentation methods (neighborhood valley emphasis (NVE), valley emphasis (VE) and Otsu). Results show that our approach is proved to be more efficient than comparable methods and a feasible alternative to analyze the bone vascular network.

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The reduction of metal artifacts remains a challenge in computed tomography because they decrease image quality, and consequently might affect the medical diagnosis. The objective of this study is to present a novel method to correct metal artifacts based solely on the CT-slices. The proposed method consists of four steps. First, metal implants in the original CT-slice are segmented using an entropy based method, producing a metal image. Second, a prior image is acquired using three transformations: Gaussian filter, Parisotto and Schoenlieb inpainting method with the Mumford-Shah image model and L0 Gradient Minimization method (L0GM). Next, based on the projections from the original CT-slice, prior image and metal image, the sinogram is corrected in the traces affected by metal in the process called normalization and denormalization. Finally, the reconstructed image is obtained by FBP and a Nonlocal Means (NLM) filtering. The efficacy of the algorithm is evaluated by comparing five image quality metrics of the images and by inspecting regions of interest (ROI). Phantom data as well as clinical datasets are included. The proposed method is compared with three established metal artifact reduction (MAR) methods. The results from a phantom and clinical dataset show the visible reduction of artifacts. The conclusion is that IMIF-MAR method can reduce streak metal artifacts effectively and avoid new artifacts around metal implants, while preserving the anatomical structures. Considering both clinical and phantom studies, the proposed MAR algorithm improves the quality of clinical images affected by metal artifacts, and could be integrated in clinical setting.

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AIM: To evaluate the influence of the tube current and metal artifact reduction (MAR) tool on the diagnosis of vertical root fractures (VRF) in a tooth adjacent to a zirconium implant, in cone-beam computed tomography (CBCT) images. METHODOLOGY: Thirty single-rooted teeth (15 with VRF and 15 control group) were individually positioned in a mandible, and scanned with the OP300 CBCT unit. Images were acquired using a standardized protocol: 5 × 5 cm field of view, 0.08-mm voxel size, and 90 kVp. Each tooth was scanned with and without a zirconium implant in its vicinity, using different tube currents (4 mA, 8 mA, and 10 mA) and conditions of MAR (enabled × disabled). Diagnostic values were calculated for each protocol, and compared by multi-way analysis of variance. RESULTS: The ROC curve and sensitivity values did not differ significantly among the tube currents, regardless of the presence of the implant and MAR condition (p > 0.05). There were also no significant differences among the tube currents for the specificity values (p > 0.05); however, the specificity differed significantly between the "with implant" and "without implant" conditions, within the same MAR condition and tube current (p < 0.05). Specificity was significantly lower when the implant was present (p < 0.05). CONCLUSION: The presence of a zirconium implant impairs the diagnosis of VRF in teeth adjacent to the artifact-generator material. Neither the tube current nor the MAR tool is effective in improving this diagnostic task. Therefore, in this clinical scenario, the use of the lowest tube current (4 mA), without MAR activation, is recommended. CLINICAL RELEVANCE: Considering that the tube current is one of the main factors that influence the radiation dose and image quality in CBCT, and that metal artifacts negatively influence the diagnosis of VRF in areas adjacent to the artifact-generator material, it is important to evaluate the effect of this energetic parameter in the diagnosis of VRF in teeth adjacent to zirconium implants.

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Abstract Objectives: To investigate the diagnostic performance of single-source dual-energy computed tomography (DECT) based on gemstone spectral imaging technology (including Discovery CT750HD and Revolution CT) in patients with suspected feet/ankles gouty arthritis, and evaluate the urate deposition with a novel semi-quantitative DECT scoring system. Methods: A total of 196 patients were consecutively included. Feet and ankles were evaluated in all patients by single-source DECT scan. The 2015 EULAR/ACR criteria were used as the reference for the diagnosis of gout. The sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of DECT for the diagnosis of gout in the early (≤1 year), middle (1-3 years), and late (> 3 years) disease durations were calculated. Besides, a novel semi-quantitative DECT scoring system was assessed for the measurement of urate deposition, and the correlation between the scores and the clinical and serological data were also evaluated. Moreover, the influences of artifacts on the diagnostic performance of DECT were also determined. Results: The sensitivity, specificity, and AUC of DECT in 196 patients were 38.10, 96.43%, and 0.673 in the early-stage group; 62.96, 100.00%, and 0.815 in the middle-stage group; and 77.55, 87.50%, and 0.825 in the late-stage group, respectively. The overall diagnostic accuracies in the AUC of DECT (Discovery CT750HD and Revolution CT) in the middle and late stages of gout were higher than that in the early stage of gout. Besides, the monosodium urate crystals were deposited on the first metatarsophalangeal joints and ankles/midfeet. Age, the presence of tophus, bone erosion, and disease duration considerably affected the total urate score. No statistical difference in the positive detection of nail artifact, skin artifact, vascular calcification, and noise artifact was found between the case and control groups. Conclusion: DECT (Discovery CT750HD and Revolution CT) showed promising diagnostic accuracy for the detection of urate crystal deposition in gout but had limited diagnostic sensitivity for short-stage gout. Longer disease duration, the presence of tophus, and bone erosion were associated with the urate crystal score system. The artifacts do not remarkably affect the diagnostic performance of DECT in gout.

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Removal of artifacts induced by muscle activity is crucial for analysis of the electroencephalogram (EEG), and continues to be a challenge in experiments where the subject may speak, change facial expressions, or move. Ensemble empirical mode decomposition with canonical correlation analysis (EEMD-CCA) has been proven to be an efficient method for denoising of EEG contaminated with muscle artifacts. EEMD-CCA, likewise the majority of algorithms, does not incorporate any statistical information of the artifact, namely, electromyogram (EMG) recorded over the muscles actively contaminating the EEG. In this paper, we propose to extend EEMD-CCA in order to include an EMG array as information to aid the removal of artifacts, assessing the performance gain achieved when the number of EMG channels grow. By filtering adaptively (recursive least squares, EMG array as reference) each component resulting from CCA, we aim to ameliorate the distortion of brain signals induced by artifacts and denoising methods. We simulated several noise scenarios based on a linear contamination model, between real and synthetic EEG and EMG signals, and varied the number of EMG channels available to the filter. Our results exhibit a substantial improvement in the performance as the number of EMG electrodes increase from 2 to 16. Further increasing the number of EMG channels up to 128 did not have a significant impact on the performance. We conclude by recommending the use of EMG electrodes to filter components, as it is a computationally inexpensive enhancement that impacts significantly on performance using only a few electrodes.

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INTRODUCTION: The aim of this study was to assess 2 cone-beam computed tomographic systems on the detection of artificially induced vertical root fractures (VRFs) and artifact intensity using birooted teeth restored with different intracanal materials. METHODS: The sample consisted of 20 extracted birooted premolars. Root fracture was induced in half of the sample. Seven intracanal material combinations were used in each tooth, 1 at a time: unrestored, gutta-percha, a buccal root with gutta-percha and a lingual root with a fiberglass post, a buccal root with gutta-percha and a lingual root with a metal core fiberglass post, fiberglass posts, metal core fiberglass posts, and NiCr posts. Cone-beam computed tomographic scans were acquired using CS 9000 3D (Carestream Dental Rochester, NY) and OP300 (Instrumentarium Dental Inc, Tuusula, Finland) units. Exposure parameters were fixed at 90 kV and 8 mA. The voxel size and field of view were set at 0.085 mm and 5 × 5 cm for OP300 and 0.076 mm and 5 × 3.75 cm for CS 9000, respectively. Two observers assessed all images using a 5-point confidence scale for VRF detection and a 4-point score for artifact interference. The sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve were compared using 2-way analysis of variance and the Tukey test (α = 0.05). Artifact interference was evaluated by descriptive statistics and the chi-square test. RESULTS: There were significant differences between scanners (P > .05) and among the different intracanal material groups (OP300) (P < .05) for specificity. When a metal post was present in both roots, severe artifact interference was observed in all images. CONCLUSIONS: CS 9000 3D presented better performance than OP300 on VRF detection of endodontically treated teeth. Unrestored teeth and teeth filled with fiberglass posts were considered the groups with the lowest artifact interference and the highest VRF detection results.

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O objetivo deste estudo foi analisar a influência do tamanho campo de visão ou FOV (field of view) e o posicionamento na arcada de estruturas densas na formação de artefatos em exames de tomografia computadorizada de feixe cônico(TCFC). Foram utilizadas raízes de dentes bovinos em um simulador de mandíbula em acrílico simulando a posição dos dentes. A obtenção das imagens ocorreu por meio dos tomógrafos Kodak 9000 com FOV pequeno e o Kodak 9500 com FOVs médio e grande. Para aquisição das imagens, o simulador foi posicionado sempre de forma padronizada. O grupo controle foi estabelecido a partir do escaneamento de seis raízes de dentes bovinos hígidas. Cada uma das seis raízes foi substituída por um implante ou raiz bovina preenchida com guta-percha (materiais hiperdensos) e uma nova imagem tomográfica foi realizada em cada tomógrafo para cada modificação. Todas as imagens foram avaliadas no software Image J para avaliação dos valores de cinza na região cervical, média e apical de cada raiz e comparadas com a imagem do grupo controle. Foi verificado que a interação entre tamanho do FOV, material e região não foi significativa (p=0,983). A interação entre material e região, não tiveram diferenças significativas (p=0,904). Para a relação entre tamanho do FOV e material evidenciou-se a presença de diferença significativa (p<0,001). Observou-se que os valores no FOV médio e pequeno apresentaram p<0,001, quando confrontado com o grupo controle. Concluiu-se que os valores de cinza não se diferem conforme localização do material hiperdenso dentro da arcada e que o FOV pequeno é o que apresenta menor média quando se compara material e região. (AU)

The objective of this study was to analyze the influence of the field of view or FOV (field of view) size and the positioning in the arch of dense structures in the formation of artifacts in cone beam computed tomography (TCFC) exams. Bovine tooth roots were used in an acrylic jaw simulator simulating the position of the teeth. The images were obtained using Kodak 9000 tomographs with small FOV and Kodak 9500 with medium and large FOVs. For image acquisition, the simulator was always positioned in a standardized way. The gold standard was established by scanning six roots of healthy bovine teeth. Each of the six roots was replaced by an implant or bovine root filled with gutta-percha (hyperdense materials) and a new tomographic image was performed on each tomography for each modification. All images were evaluated using the Image J software to assess the gray values in the cervical, middle and apical regions of each root and compared with the gold standard image. It was found that the interaction between FOV size, material and region was not significant (p = 0.983). The interaction between material and region, did not have significant differences (p = 0.904). For the relationship between FOV size and material, the presence of a significant difference was evidenced (p <0.001). It was observed that the values in the medium and small FOV presented p <0.001, when compared with the gold standard. It was concluded that the gray values do not differ according to the location of the hyperdense material within the arch and that the small FOV is the one with the lowest average when comparing material and region. (AU)

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