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While the presence of adipose tissue and its involvement by prostatic cancer (extraprostatic extension) is well-recognized in prostate biopsies, adipose tissue in transurethral resections of the prostate (TURP) is largely unexplored. Herein, 200 consecutive TURPs and related specimens were reviewed, including a separate 3-year analysis of specimens containing prostatic cancer, with the following data collected: presence of fat, presence of cancer within fat, and quantity of fat. For specimens with both fat and prostatic cancer, specimen weight and tumor volume were recorded. Within the 200 consecutive TURPs and related specimens, adipose tissue was identified in 20%; 55% had 2.5 mm of adipose tissue; the number of fragments with adipose tissue ranged from 1 to 14. No correlation between specimen weight and measured extent of adipose tissue or number of fragments with adipose tissue was identified. Of all the specimens with prostatic cancer, 15/56 (27%) involved adipose tissue, with two specimens with large cancer volume (>90%) demonstrating extensive involvement of adipose tissue. Adipose tissue is frequently present within TURP and related specimens with variability in extent. The etiology behind encountering adipose tissue is uncertain, and it could represent resection into peri-prostatic fat, intraprostatic fat, or bladder neck fat sampling. Although encountering adipose tissue involved by cancer in TURP and related specimens may imply extraprostatic extension (pT3a), further studies are needed to corroborate these findings as well as to determine if these should be included in reported synoptics.
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Ethylmercury (EtHg), similar to methylmercury (MeHg), is highly neurotoxic and bioaccumulative. Although recent studies suggested its occurrence in natural soils and sediments, the common propylation derivatization for EtHg analysis might generate EtHg artifacts, potentially leading to its overestimation in environmental samples. Furthermore, the extensive environmental prevalence of EtHg remains unverified, keeping its importance largely uncertain. This study investigated the formation of EtHg artifacts during propylation derivatization, evaluating artifacts formation and recoveries under different extraction methods with real samples, and confirmed the widespread occurrence of EtHg in Chinese wetlands. EtHg artifacts were obviously present during the propylation derivatization and strongly dependent on the levels of Hg2+ (0.1-10 ng) in the derivatization solution (R² = 0.99), accounting for 1.38-2.14% of Hg2+. CuSO4-HNO3CH2Cl2 extraction (effectively removing Hg2+) combined with propylation derivatization offers excellent recovery (81-86%) and low artifacts (< LOD: 1.98 × 10-4 ng/g) for EtHg measurement in soils/sediments, with results aligning with those from online solid phase extraction-high performance liquid chromatography-inductively coupled plasma mass spectrometry (R2 = 0.99). Additionally, we observed the occurrence of EtHg in soil and sediment samples across 14 Chinese wetlands, with concentrations varying from 6.08 to 171 pg/g, similar to MeHg concentrations at some sites. EtHg positively correlates with MeHg, total Hg, and total organic carbon across all samples, indicating a possible biological formation. These findings help better understand and predict the prevalence of EtHg in wetlands and its key role in environmental Hg cycle.
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BACKGROUND: Computed tomography (CT) is widely in clinics and is affected by metal implants. Metal segmentation is crucial for metal artifact correction, and the common threshold method often fails to accurately segment metals. PURPOSE: This study aims to segment metal implants in CT images using a diffusion model and further validate it with clinical artifact images and phantom images of known size. METHODS: A retrospective study was conducted on 100 patients who received radiation therapy without metal artifacts, and simulated artifact data were generated using publicly available mask data. The study utilized 11,280 slices for training and verification, and 2,820 slices for testing. Metal mask segmentation was performed using DiffSeg, a diffusion model incorporating conditional dynamic coding and a global frequency parser (GFParser). Conditional dynamic coding fuses the current segmentation mask and prior images at multiple scales, while GFParser helps eliminate high-frequency noise in the mask. Clinical artifact images and phantom images are also used for model validation. RESULTS: Compared with the ground truth, the accuracy of DiffSeg for metal segmentation of simulated data was 97.89% and that of DSC was 95.45%. The mask shape obtained by threshold segmentation covered the ground truth and DSCs were 82.92% and 84.19% for threshold segmentation based on 2500 HU and 3000 HU. Evaluation metrics and visualization results show that DiffSeg performs better than other classical deep learning networks, especially for clinical CT, artifact data, and phantom data. CONCLUSION: DiffSeg efficiently and robustly segments metal masks in artifact data with conditional dynamic coding and GFParser. Future work will involve embedding the metal segmentation model in metal artifact reduction to improve the reduction effect.
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Artefactos , Metales , Fantasmas de Imagen , Prótesis e Implantes , Tomografía Computarizada por Rayos X , Humanos , Tomografía Computarizada por Rayos X/métodos , Estudios Retrospectivos , AlgoritmosRESUMEN
The combined supine-prone imaging protocol for SPECT myocardial perfusion imaging offers significant advantages over supine imaging alone. By comparing supine and prone images, one can distinguish attenuation artifacts in the inferior and anterior walls from true perfusion defects, thus improving specificity and diagnostic accuracy. The recommended protocol is to perform prone imaging after supine stress imaging when perfusion defects are noted. The additional prone imaging time is 20%-40% less than the standard supine imaging time. Implementing prone imaging can optimize patient care and provide substantial benefits for nuclear cardiology labs, especially those without attenuation correction.
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Background: In dogs undergoing vertebral column stabilization, post-operative computed tomography (CT) evaluates implant placement. The impact on the interpretation of metallic artifact associated with titanium implants in dogs remains to be established. Our objective was to quantify metallic artifact on CT associated with titanium pedicle screws. Methods: The study design included an in vitro model and a retrospective review of 11 dogs with vertebral column stabilization. Twenty four titanium pedicle screws (6 each: 2.0 mm, 2.7 mm, 3.5 mm, and 4.5 mm) were inserted into a 20% ballistic gel, and CT scan of the construct was performed. Three blinded raters used a bone window to measure the maximum width (effective size) of each screw, one rater measured effective size using an ultrawide window and 45 titanium pedicle screws (3×2.0 mm, 5×2.7 mm, 30×3.5 mm, and 7×4.5 mm) in 11 clinical cases. Effective size measurements were compared to actual screw sizes. Results: The effective size was 26.9-43.8%, 9.2-18.5%, and 21.1-30.5% larger than the actual size for the in vitro system (bone window), in vitro system (ultrawide window), and clinical cases, respectively. The mean gross difference for the in vitro measurements varied by implant size (p < 0.001) and was positively correlated with implant size (r = 0.846), but the mean percentage difference was negatively correlated with implant size (p < 0.001). Overestimation was larger for the in vitro model bone window compared to the ultrawide window (p < 0.001) and clinical cases (p = 0.001). Conclusion: Metallic artifact associated with titanium pedicle screws on CT resulted in an overestimation of screw size. This information might aid in the interpretation of implant placement on post-operative imaging.
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This paper will focus on analyzing the argument with appealing to nature against synthetic biology and provide a counter-argument against it through demonstrating the ambiguity of the concept of nature, denying the existence of a morally significant line between natural and non/unnatural, and disproving the allegations against synthetic biology raised by the argument appealing to nature. The paper consists of two parts following a brief introduction. The first part will describe the argument appealing to nature against synthetic biology, and identify the deficiencies of the argument per se, e.g., the ambiguity of the concept 'nature'; and the problems in the morally significant line between the natural and the non/unnatural. The second part will discuss the allegations to synthetic biology stemming from this argument, e.g., committing metaphysical and ethical mistakes, and doing possible harms to the environment.
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The presence of facial jewelry and medical devices within a radiographic field of view may promote the formation of artifacts that challenge diagnostic interpretation. The objective of this article is to describe a previously unreported radiographic anomaly produced by an oral piercing site below the lower lip. This unusual artifact masqueraded as a severe resorptive defect, dental caries, or cervical abfraction and occurred following removal of an extremely large labret below the lower lip and subsequent acquisition of a radiographic image. The radiolucency was ultimately attributed to an extensive aperture below the lower lip created by a series of sequentially larger soft tissue expanders. Clinicians should seek correlation of atypical radiographic presentations with soft tissue defects secondary to injury or intentional oral piercing.
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Artefactos , Perforación del Cuerpo , Labio , Humanos , Labio/lesiones , Labio/diagnóstico por imagen , Labio/cirugía , Perforación del Cuerpo/efectos adversos , Femenino , Radiografía Dental , Mucosa Bucal/diagnóstico por imagen , AdultoRESUMEN
BACKGROUND: Within the Open Biological and Biomedical Ontology (OBO) Foundry, many ontologies represent the execution of a plan specification as a process in which a realizable entity that concretizes the plan specification, a "realizable concretization" (RC), is realized. This representation, which we call the "RC-account", provides a straightforward way to relate a plan specification to the entity that bears the realizable concretization and the process that realizes the realizable concretization. However, the adequacy of the RC-account has not been evaluated in the scientific literature. In this manuscript, we provide this evaluation and, thereby, give ontology developers sound reasons to use or not use the RC-account pattern. RESULTS: Analysis of the RC-account reveals that it is not adequate for representing failed plans. If the realizable concretization is flawed in some way, it is unclear what (if any) relation holds between the realizable entity and the plan specification. If the execution (i.e., realization) of the realizable concretization fails to carry out the actions given in the plan specification, it is unclear under the RC-account how to directly relate the failed execution to the entity carrying out the instructions given in the plan specification. These issues are exacerbated in the presence of changing plans. CONCLUSIONS: We propose two solutions for representing failed plans. The first uses the Common Core Ontologies 'prescribed by' relation to connect a plan specification to the entity or process that utilizes the plan specification as a guide. The second, more complex, solution incorporates the process of creating a plan (in the sense of an intention to execute a plan specification) into the representation of executing plan specifications. We hypothesize that the first solution (i.e., use of 'prescribed by') is adequate for most situations. However, more research is needed to test this hypothesis as well as explore the other solutions presented in this manuscript.
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Ontologías BiológicasRESUMEN
Despite the growing adoption of wearable photoplethysmography (PPG) devices in personal health management, their measurement accuracy remains limited due to susceptibility to noise. This paper proposes a novel signal completion technique using generative adversarial networks that ensures both global and local consistency. Our approach innovatively addresses both short- and long-term PPG variations to restore waveforms while maintaining waveform consistency within and between pulses. We evaluated our model by removing up to 50 % of segments from segmented PPG waveforms and comparing the original and reconstructed waveforms, including systolic peak information. The results demonstrate that our method accurately reconstructs waveforms with high fidelity, producing natural and seamless transitions without discontinuities at reconstructed boundaries. Additionally, the reconstructed waveforms preserve typical PPG shapes with minimal distortion, underscoring the effectiveness and novelty of our technique.
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The prestige target selectivity and imaging depth of optical-resolution photoacoustic microscope (OR-PAM) have gained attentions to enable advanced intra-cellular visualizations. However, the broad-band nature of photoacoustic signals is prone to noise and artifacts caused by the inefficient light-to-pressure translation, resulting in poor image quality. The present study foresees application of singular value decomposition (SVD) to effectively extract the photoacoustic signals from these noise and artifacts. Although spatiotemporal SVD succeeded in ultrasound flow signal extraction, the conventional multi frame model is not suitable for data acquired with scanning OR-PAM due to the burden of accessing multiple frames. To utilize SVD on the OR-PAM, this study began with exploring SVD applied on multiple A-lines of photoacoustic signal instead of frames. Upon explorations, an obstacle of uncertain presence of unwanted singular vectors was observed. To tackle this, a data-driven weighting matrix was designed to extract relevant singular vectors based on the analyses of temporal-spatial singular vectors. Evaluation on the extraction capability by the SVD with the weighting matrix showed a superior signal quality with efficient computation against past studies. In summary, this study contributes to the field by providing exploration of SVD applied on A-line signals as well as its practical utilization to distinguish and recover photoacoustic signals from noise and artifact components.
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Metal artifacts notoriously pose significant challenge in computed tomography (CT), leading to inaccuracies in image formation and interpretation. Artifact reduction tools have been designed to improve cone beam computed tomography (CBCT) image quality by reducing artifacts caused by certain high-density materials. Metal artifact reduction (MAR) tools are specific algorithms that are applied during image reconstruction to minimize or eliminate artifacts degrading CBCT images. The purpose of the study is to evaluate the effect of a MAR algorithm on image quality in CBCT performed for evaluating patients before transarterial radioembolization (TARE). We retrospectively included 40 consecutive patients (aged 65 ± 13 years; 23 males) who underwent 45 CBCT examinations (Allura FD 20, XperCT Roll protocol, Philips Healthcare, Best, The Netherlands) in the setting of evaluation for TARE between January 2017 and December 2018. Artifacts caused by coils, catheters, and surgical clips were scored subjectively by four readers on a 5-point scale (1 = artifacts affecting diagnostic information to 5 = no artifacts) using a side-by-side display of uncorrected and MAR-corrected images. In addition, readers scored tumor visibility and vessel discrimination. MAR-corrected images were assigned higher scores, indicating better image quality. The differences between the measurements with and without MAR were most impressive for coils with a mean improvement of 1.6 points (95%CI [1.5 1.8]) on the 5-point likert scale, followed by catheters 1.4 points (95%CI [1.3 1.5]) and clips 0.7 points (95%CI [0.3 1.1]). Improvements for other artifact sources were consistent but relatively small (below 0.25 points on average). Interrater agreement was good to perfect (Kendall's W coefficient = 0.68-0.95) and was higher for MAR-corrected images, indicating that MAR improves diagnostic accuracy. A metal artifact reduction algorithm can improve diagnostic and interventional accuracy of cone beam CT in patients undergoing radioembolization by reducing artifacts caused by diagnostic catheters and coils, lowering interference of metal artifacts with adjacent major structures, and improving tumor visibility.
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Algoritmos , Artefactos , Tomografía Computarizada de Haz Cónico , Metales , Humanos , Tomografía Computarizada de Haz Cónico/métodos , Femenino , Anciano , Masculino , Estudios Retrospectivos , Persona de Mediana Edad , Neoplasias Hepáticas/radioterapia , Neoplasias Hepáticas/diagnóstico por imagen , Embolización Terapéutica/métodos , Procesamiento de Imagen Asistido por Computador/métodosRESUMEN
Purpose: We aimed to compare the diagnostic performance of different cone-beam computed tomography (CBCT) scan modes with and without the application of a metal artifact reduction (MAR) option under 5 different restorative materials. Material and methods: Our research was an in vitro study with 150 caries-free premolars and molars. The teeth were randomly divided into experimental (with artificially induced caries, n = 75) and control (without caries, n = 75) groups and were prepared based on 5 types of restorative materials, including conventional composites (Filtek Z250, Gradia), flow composite, glass ionomer, and amalgam. The teeth were examined under 2 CBCT scan modes (high-resolution [HIRes] and standard) with and without MAR application. Finally, the diagnostic accuracy index values (area under the receiver operating characteristic curve [AUC], sensitivity, and specificity) were calculated. Results: The AUC of standard scan mode with the MAR option was significantly lower than that of HIRes with MAR (p = 0.018) and without MAR option (p = 0.011) in detecting recurrent caries. Also, without MAR option, the diagnostic accuracy (AUC) of the standard mode was significantly lower than that of the HIRes (p = 0.020). Similar findings were observed for sensitivity and specificity. Moreover, diagnostic performance of standard and HIRes scan modes with and without MAR in the amalgam group was lower than that in other restorative material groups. Conclusions: Diagnostic performance of HIRes CBCT mode was higher than that of standard mode for recurrent caries and remained unaffected by MAR application. However, the accuracy in detecting recurrent caries was lower in the amalgam group compared with other restorative material groups.
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Asymmetric hot spots in the axial skeleton on bone scintigraphy may confound diagnosis. We describe an unexpected artifact of 99mTc-methylene diphosphonate near the breast in a 55-y-old woman with breast cancer. The initial whole-body bone scintigraphy revealed a solitary focal lesion in the anterior ribs on the left side. After careful tracking, we determined that this hot spot originated from the adhesive bandage. The patient had placed it in her left front pocket after removing it from the injection site. She was rescanned after the bandage had been removed from her pocket.
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PURPOSE: The aim of this study was to evaluate artifacts in the skull base region of head computed tomography (CT) images with various tilt angles relative to the orbitomeatal line. METHODS: CT images of a head phantom acquired by helical and non-helical scanning with the tilt angles set from 0 to 20 degrees in 5-degree increments were evaluated in this study. Regions of interest (ROIs) were set at the cerebellum, temporal lobe, frontal lobe, and basal ganglia in the phantom images. Artifacts were evaluated by the coefficient of variation (CV) of the mean CT value between ROIs and the location parameter (ß) of the Gumbel method. RESULTS: The CV and ß values increased with increasing tilt angle for both helical and nonhelical images in the frontal lobes, but both decreased in the cerebellar region. In the temporal lobe and basal ganglia, there was no trend of change with tilt angle. CONCLUSION: Increasing the tilt angle relative to the OM line increased artifacts at the frontal lobes and decreased artifacts at the cerebellar region.
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This research aimed to introduce an auto-adaptive metal artifact reduction (aMAR) algorithm in cone-beam computed tomography (CBCT) to assess the levels of the pre-implant alveolar crest. Dental implants as a treatment modality for edentulous patients consist of a titanium alloy, which creates a metal artifact, resulting in a dark dental structure in the CBCT scans. Metallic artifacts are limiting factors for the precise detection in CBCT images. These are related to the dark areas around materials and metallic structures (e.g., restorations, implants, and endodontic instruments). To overcome this problem, the metal artifact reduction (MAR) program has been recommended as a post-procedure stage for CBCT image reconstruction. Recent developments offer CBCT scanners with an aMAR option with a greater dynamic range to help overcome the challenges of peri-implant bone evaluation to reach accurate dental diagnoses.
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Image quality plays a pivotal role in the accurate diagnosis and effective management of diseases in radiology. This review explores the principles, methodologies, and strategies for assessing and optimizing image quality across various imaging modalities, including X-ray, computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, and nuclear medicine. We discuss key factors influencing image quality, such as spatial resolution, noise, contrast, and artifacts, and highlight techniques for quality assurance, image optimization, and dose reduction in clinical practice.
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Lossy image coding techniques usually result in various undesirable compression artifacts. Recently, deep convolutional neural networks have seen encouraging advances in compression artifact reduction. However, most of them focus on the restoration of the luma channel without considering the chroma components. Besides, most deep convolutional neural networks are hard to deploy in practical applications because of their high model complexity. In this article, we propose a dual-stage feedback network (DSFN) for lightweight color image compression artifact reduction. Specifically, we propose a novel curriculum learning strategy to drive a DSFN to reduce color image compression artifacts in a luma-to-RGB manner. In the first stage, the DSFN is dedicated to reconstructing the luma channel, whose high-level features containing rich structural information are then rerouted to the second stage by a feedback connection to guide the RGB image restoration. Furthermore, we present a novel enhanced feedback block for efficient high-level feature extraction, in which an adaptive iterative self-refinement module is carefully designed to refine the low-level features progressively, and an enhanced separable convolution is advanced to exploit multiscale image information fully. Extensive experiments show the notable advantage of our DSFN over several state-of-the-art methods in both quantitative indices and visual effects with lower model complexity.
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Current research focuses on improving electrocardiogram (ECG) monitoring systems to enable real-time and long-term usage, with a specific focus on facilitating remote monitoring of ECG data. This advancement is crucial for improving cardiovascular health by facilitating early detection and management of cardiovascular disease (CVD). To efficiently meet these demands, user-friendly and comfortable ECG sensors that surpass wet electrodes are essential. This has led to increased interest in ECG capacitive electrodes, which facilitate signal detection without requiring gel preparation or direct conductive contact with the body. This feature makes them suitable for wearables or integrated measurement devices. However, ongoing research is essential as the signals they measure often lack sufficient clinical accuracy due to susceptibility to interferences, particularly Motion Artifacts (MAs). While our primary focus is on studying MAs, we also address other limitations crucial for designing a high Signal-to-Noise Ratio (SNR) circuit and effectively mitigating MAs. The literature on the origins and models of MAs in capacitive electrodes is insufficient, which we aim to address alongside discussing mitigation methods. We bring attention to digital signal processing approaches, especially those using reference signals like Electrode-Tissue Impedance (ETI), as highly promising. Finally, we discuss its challenges, proposed solutions, and offer insights into future research directions.
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Dual-energy computed tomography (DECT) has emerged as a transformative tool in the past decade. Initially employed in gout within the field of rheumatology to distinguish and quantify monosodium urate crystals through its dual-material discrimination capability, DECT has since broadened its clinical applications. It now encompasses various rheumatic diseases, employing advanced techniques such as bone marrow edema assessment, iodine mapping, and collagen-specific imaging. This review article aims to examine the unique characteristics of DECT, discuss its strengths and limitations, illustrate its applications for accurately evaluating various rheumatic diseases in clinical practice, and propose future directions for DECT in rheumatology.