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Atrial fibrillation (AF) is the most common sustained arrhythmia worldwide and remains a major cause of morbidity and mortality. Unfortunately, a significant proportion of patients have persistent AF, for which conventional catheter ablation is less effective. However, convergent ablation has emerged in recent years as a hybrid treatment targeting both the epicardium and endocardium in a multidisciplinary joint cardiothoracic and electrophysiology procedure, with promising efficacy outcomes in recent studies. This treatment is increasingly being performed in the United Kingdom. This review article discusses the rationale and evidence behind convergent ablation, along with factors that need to be considered when setting up a successful ablation service.
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Background: Simultaneous multi-slice (SMS) bSSFP imaging enables stress myocardial perfusion imaging with high spatial resolution and increased spatial coverage. Standard parallel imaging techniques (e.g., TGRAPPA) can be used for image reconstruction but result in high noise level. Alternatively, iterative reconstruction techniques based on temporal regularization (ITER) improve image quality but are associated with reduced temporal signal fidelity and long computation time limiting their online use. The aim is to develop an image reconstruction technique for SMS-bSSFP myocardial perfusion imaging combining parallel imaging and image-based denoising using a novel noise map estimation network (NoiseMapNet), which preserves both sharpness and temporal signal profiles and that has low computational cost. Methods: The proposed reconstruction of SMS images consists of a standard temporal parallel imaging reconstruction (TGRAPPA) with motion correction (MOCO) followed by image denoising using NoiseMapNet. NoiseMapNet is a deep learning network based on a 2D Unet architecture and aims to predict a noise map from an input noisy image, which is then subtracted from the noisy image to generate the denoised image. This approach was evaluated in 17 patients who underwent stress perfusion imaging using a SMS-bSSFP sequence. Images were reconstructed with (a) TGRAPPA with MOCO (thereafter referred to as TGRAPPA), (b) iterative reconstruction with integrated motion compensation (ITER), and (c) proposed NoiseMapNet-based reconstruction. Normalized mean squared error (NMSE) with respect to TGRAPPA, myocardial sharpness, image quality, perceived SNR (pSNR), and number of diagnostic segments were evaluated. Results: NMSE of NoiseMapNet was lower than using ITER for both myocardium (0.045 ± 0.021 vs. 0.172 ± 0.041, p < 0.001) and left ventricular blood pool (0.025 ± 0.014 vs. 0.069 ± 0.020, p < 0.001). There were no significant differences between all methods for myocardial sharpness (p = 0.77) and number of diagnostic segments (p = 0.36). ITER led to higher image quality than NoiseMapNet/TGRAPPA (2.7 ± 0.4 vs. 1.8 ± 0.4/1.3 ± 0.6, p < 0.001) and higher pSNR than NoiseMapNet/TGRAPPA (3.0 ± 0.0 vs. 2.0 ± 0.0/1.3 ± 0.6, p < 0.001). Importantly, NoiseMapNet yielded higher pSNR (p < 0.001) and image quality (p < 0.008) than TGRAPPA. Computation time of NoiseMapNet was only 20s for one entire dataset. Conclusion: NoiseMapNet-based reconstruction enables fast SMS image reconstruction for stress myocardial perfusion imaging while preserving sharpness and temporal signal profiles.
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Tuberculous meningitis (TBM) is the most lethal form of tuberculosis. Clinical features, such as coma, can predict death, but they are insufficient for the accurate prognosis of other outcomes, especially when impacted by co-morbidities such as HIV infection. Brain magnetic resonance imaging (MRI) characterises the extent and severity of disease and may enable more accurate prediction of complications and poor outcomes. We analysed clinical and brain MRI data from a prospective longitudinal study of 216 adults with TBM; 73 (34%) were HIV-positive, a factor highly correlated with mortality. We implemented an end-to-end framework to model clinical and imaging features to predict disease progression. Our model used state-of-the-art machine learning models for automatic imaging feature encoding, and time-series models for forecasting, to predict TBM progression. The proposed approach is designed to be robust to missing data via a novel tailored model optimisation framework. Our model achieved a 60% balanced accuracy in predicting the prognosis of TBM patients over the six different classes. HIV status did not alter the performance of the models. Furthermore, our approach identified brain morphological lesions caused by TBM in both HIV and non-HIV-infected, associating lesions to the disease staging with an overall accuracy of 96%. These results suggest that the lesions caused by TBM are analogous in both populations, regardless of the severity of the disease. Lastly, our models correctly identified changes in disease symptomatology and severity in 80% of the cases. Our approach is the first attempt at predicting the prognosis of TBM by combining imaging and clinical data, via a machine learning model. The approach has the potential to accurately predict disease progression and enable timely clinical intervention.
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Encéfalo , Aprendizado de Máquina , Imageamento por Ressonância Magnética , Tuberculose Meníngea , Humanos , Tuberculose Meníngea/diagnóstico por imagem , Imageamento por Ressonância Magnética/métodos , Prognóstico , Masculino , Feminino , Adulto , Encéfalo/diagnóstico por imagem , Encéfalo/patologia , Pessoa de Meia-Idade , Estudos Prospectivos , Progressão da Doença , Infecções por HIV/complicações , Infecções por HIV/diagnóstico por imagem , Estudos LongitudinaisRESUMO
INTRODUCTION: Atrial remodelling (AR) is the persistent change in atrial structure and/or function and contributes to the initiation, maintenance and progression of atrial fibrillation (AF) in a reciprocal self-perpetuating relationship. Left atrial (LA) size, geometry, fibrosis, wall thickness (LAWT) and ejection fraction (LAEF) have all been shown to vary with pathological atrial remodelling. The association of these global remodelling markers with each other for differentiating structural phenotypes in AF is not well investigated. METHOD: Patients referred for first-time AF ablation and controls without AF were prospectively recruited to undergo cardiac computed tomographic angiography (CCTA) and magnetic resonance imaging (MRI) with 3D atrial late-gadolinium enhanced (LGE) sequences. LAWT, atrial myocardial mass, LA volume and sphericity were calculated from CT. Biplane LA EF and LA fibrosis burden were derived from atrial MRI. Results were compared between patients with AF and controls. RESULTS: Forty two AF patients (64.3% male, age 64.6 ± 10.2 years, CHA2DS2-VASc 2.48 ± 1.5, 69.0% paroxysmal AF, 31% persistent AF, LVEF 57.9 ± 10.5%) and 37 controls (64.9% male, age 56.6 ± 7.2, CHA2DS2-VASc 1.54 ± 1.1, LVEF 60.4 ± 4.9%) were recruited. Patients with AF had a significantly higher LAWT (1.45 ± 0.52 mm vs 1.12 ± 0.42 mm, p = 0.003), tissue mass (15.81 ± 6.53 g vs. 12.18 ± 5.01 g, p = 0.011), fibrosis burden (9.33 ± 8.35% vs 2.41 ± 3.60%, p = 0.013), left atrial size/volume (95.68 ± 26.63 mL vs 81.22 ± 20.64 mL, p = 0.011) and lower LAEF (50.3 ± 15.3% vs 65.2 ± 8.6%, p < 0.001) compared to controls. There was no significant correlation between % fibrosis with LAWT (p = 0.29), mass (p = 0.89), volume (p = 0.49) or sphericity (p = 0.79). LAWT had a statistically significant weak positive correlation with LA volume (r = 0.25, p = .041), but not with sphericity (p = 0.86). LAEF had a statistically significant but weak negative correlation with fibrosis (r = -0.33, p = 0.008) and LAWT (r = -0.24, p = 0.07). CONCLUSION: AF is associated with significant quantifiable structural changes that are evident in LA size, tissue thickness, total LA tissue mass and fibrosis. These individual remodelling markers do not or only weakly correlate with each other suggesting different remodelling subtypes exist (e.g. fibrotic vs hypertrophic vs dilated). If confirmed, such a detailed understanding of the structural changes observed has the potential to inform clinical management strategies targeting individual mechanisms underlying the disease process.
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BACKGROUND: Congenital heart disease (CHD) has been linked to impaired placental and fetal brain development. Assessing the placenta and fetal brain in parallel may help further our understanding of the relationship between development of these organs. HYPOTHESIS: 1) Placental and fetal brain oxygenation are correlated, 2) oxygenation in these organs is reduced in CHD compared to healthy controls, and 3) placental structure is altered in CHD. STUDY TYPE: Retrospective case-control. POPULATION: Fifty-one human fetuses with CHD (32 male; median [IQR] gestational age [GA] = 32.0 [30.9-32.9] weeks) and 30 from uncomplicated pregnancies with normal birth outcomes (18 male; median [IQR] GA = 34.5 [31.9-36.7] weeks). FIELD STRENGTH/SEQUENCE: 1.5 T single-shot multi-echo-gradient-echo echo-planar imaging. ASSESSMENT: Masking was performed using an automated nnUnet model. Mean brain and placental T2* and quantitative measures of placental texture, volume, and morphology were calculated. STATISTICAL TESTS: Spearman's correlation coefficient for determining the association between brain and placental T2*, and between brain and placental characteristics with GA. P-values for comparing brain T2*, placenta T2*, and placental characteristics between groups derived from ANOVA. Significance level P < 0.05. RESULTS: There was a significant positive association between placental and fetal brain T2* (â´ = 0.46). Placental and fetal brain T2* showed a significant negative correlation with GA (placental T2* â´ = -0.65; fetal brain T2* â´ = -0.32). Both placental and fetal brain T2* values were significantly reduced in CHD, after adjusting for GA (placental T2*: control = 97 [±24] msec, CHD = 83 [±23] msec; brain T2*: control = 218 [±26] msec, CHD = 202 [±25] msec). Placental texture and morphology were also significantly altered in CHD (Texture: control = 0.84 [0.83-0.87], CHD = 0.80 [0.78-0.84]; Morphology: control = 9.9 [±2.2], CHD = 10.8 [±2.0]). For all fetuses, there was a significant positive association between placental T2* and placental texture (â´ = 0.46). CONCLUSION: Placental and fetal brain T2* values are associated in healthy fetuses and those with CHD. Placental and fetal brain oxygenation are reduced in CHD. Placental appearance is significantly altered in CHD and shows associations with placental oxygenation, suggesting altered placental development and function may be related. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 3.
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Rapid and accessible testing was paramount in the management of the COVID-19 pandemic. Our university established KCL TEST: a SARS-CoV-2 asymptomatic testing programme that enabled sensitive and accessible PCR testing of SARS-CoV-2 RNA in saliva. Here, we describe our learnings and provide our blueprint for launching diagnostic laboratories, particularly in low-resource settings. Between December 2020 and July 2022, we performed 158277 PCRs for our staff, students, and their household contacts, free of charge. Our average turnaround time was 16 h and 37 min from user registration to result delivery. KCL TEST combined open-source automation and in-house non-commercial reagents, which allows for rapid implementation and repurposing. Importantly, our data parallel those of the UK Office for National Statistics, though we detected a lower positive rate and virtually no delta wave. Our observations strongly support regular asymptomatic community testing as an important measure for decreasing outbreaks and providing safe working spaces. Universities can therefore provide agile, resilient, and accurate testing that reflects the infection rate and trend of the general population. Our findings call for the early integration of academic institutions in pandemic preparedness, with capabilities to rapidly deploy highly skilled staff, as well as develop, test, and accommodate efficient low-cost pipelines.
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BACKGROUND: In double aortic arch (DAA) one of the arches can demonstrate atretic portions postnatally, leading to diagnostic uncertainty due to overlap with isolated right aortic arch (RAA) variants. The main objective of this study is to demonstrate the morphological evolution of different DAA phenotypes from prenatal to postnatal life using 3D fetal cardiac magnetic resonance imaging (CMR) and postnatal CT/CMR imaging. METHODS: 3D fetal CMR was undertaken in fetuses with suspected DAA over a six-year period (Jan 2016 - Jan 2022). All cases with surgical confirmation of DAA were retrospectively studied and morphology on fetal CMR was compared to postnatal CT/CMR and surgical findings. RESULTS: 32 fetuses with surgically confirmed DAA underwent fetal CMR. All demonstrated a complete DAA with left-sided arterial duct. The RAA was dominant in 30/32 (94%). Postnatal CT/CMR was undertaken at median age of 3.3months (IQR 2.0-3.9) demonstrating DAA with patency of both arches in 9/32 (28%), with 6 showing signs of coarctation of the left aortic arch (LAA). The LAA isthmus was not present on CT/CMR in 22/32(69%), the transverse arch between left carotid and left subclavian artery was not present in 1 case. CONCLUSIONS: Fetal CMR provides novel insights into perinatal evolution of DAA. The smaller LAA can develop coarctation or atresia related to postnatal constriction of the arterial duct, making diagnosis of DAA challenging with contrast-enhanced CT/CMR. This highlights the potentially important role for prenatal 3D vascular imaging and might improve intepretation of postnatal imaging.
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Muscle ultrasound has been shown to be a valid and safe imaging modality to assess muscle wasting in critically ill patients in the intensive care unit (ICU). This typically involves manual delineation to measure the rectus femoris cross-sectional area (RFCSA), which is a subjective, time-consuming, and laborious task that requires significant expertise. We aimed to develop and evaluate an AI tool that performs automated recognition and measurement of RFCSA to support non-expert operators in measurement of the RFCSA using muscle ultrasound. Twenty patients were recruited between Feb 2023 and July 2023 and were randomized sequentially to operators using AI (n = 10) or non-AI (n = 10). Muscle loss during ICU stay was similar for both methods: 26 ± 15% for AI and 23 ± 11% for the non-AI, respectively (p = 0.13). In total 59 ultrasound examinations were carried out (30 without AI and 29 with AI). When assisted by our AI tool, the operators showed less variability between measurements with higher intraclass correlation coefficients (ICCs 0.999 95% CI 0.998-0.999 vs. 0.982 95% CI 0.962-0.993) and lower Bland Altman limits of agreement (± 1.9% vs. ± 6.6%) compared to not using the AI tool. The time spent on scans reduced significantly from a median of 19.6 min (IQR 16.9-21.7) to 9.4 min (IQR 7.2-11.7) compared to when using the AI tool (p < 0.001). AI-assisted muscle ultrasound removes the need for manual tracing, increases reproducibility and saves time. This system may aid monitoring muscle size in ICU patients assisting rehabilitation programmes.
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Estado Terminal , Unidades de Terapia Intensiva , Atrofia Muscular , Ultrassonografia , Humanos , Masculino , Ultrassonografia/métodos , Feminino , Pessoa de Meia-Idade , Idoso , Atrofia Muscular/diagnóstico por imagem , Músculo Esquelético/diagnóstico por imagem , Músculo Quadríceps/diagnóstico por imagem , Inteligência Artificial , AdultoRESUMO
This investigation aims to study the effect of laser cladding parameters on the microstructure of Stellite 6 on the X19CrMoNbVN11-1 stainless-steel substrate. First, Stellite 6 powder was coated on the X19CrMoNbVN11-1 substrate using the laser cladding method. The effect of laser cladding parameters (i.e., laser power, scanning speed, and powder feed rate) was studied on the microstructure of deposits. The secondary dendritic arm spacing was assessed, and the structural defects were studied (e.g., lack of bonding, porosity, and crack). The results revealed that the microstructure has changed from coating/substrate interface to coating surface, from plate-cellular to columnar and equiaxed dendrites. Also, an increase in the laser power increased the cellular structure in the coating/substrate interface and equiaxed dendrites in the coating surface. The cooling rate (G × R) increased by increasing the scanning and powder injection rates. The microstructure of the Stellite 6 was composed of cobalt solid-solution γFCC.
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Dark-blood late gadolinium enhancement (LGE) has been shown to improve the visualization and quantification of areas of ischemic scar compared to standard bright-blood LGE. Recently, the performance of various semi-automated quantification methods has been evaluated for the assessment of infarct size using both dark-blood LGE and conventional bright-blood LGE with histopathology as a reference standard. However, the impact of this sequence on different quantification strategies in vivo remains uncertain. In this study, various semi-automated scar quantification methods were evaluated for a range of different ischemic and non-ischemic pathologies encountered in clinical practice. A total of 62 patients referred for clinical cardiovascular magnetic resonance (CMR) were retrospectively included. All patients had a confirmed diagnosis of either ischemic heart disease (IHD; n = 21), dilated/non-ischemic cardiomyopathy (NICM; n = 21), or hypertrophic cardiomyopathy (HCM; n = 20) and underwent CMR on a 1.5 T scanner including both bright- and dark-blood LGE using a standard PSIR sequence. Both methods used identical sequence settings as per clinical protocol, apart from the inversion time parameter, which was set differently. All short-axis LGE images with scar were manually segmented for epicardial and endocardial borders. The extent of LGE was then measured visually by manual signal thresholding, and semi-automatically by signal thresholding using the standard deviation (SD) and the full width at half maximum (FWHM) methods. For all quantification methods in the IHD group, except the 6 SD method, dark-blood LGE detected significantly more enhancement compared to bright-blood LGE (p < 0.05 for all methods). For both bright-blood and dark-blood LGE, the 6 SD method correlated best with manual thresholding (16.9% vs. 17.1% and 20.1% vs. 20.4%, respectively). For the NICM group, no significant differences between LGE methods were found. For bright-blood LGE, the 5 SD method agreed best with manual thresholding (9.3% vs. 11.0%), while for dark-blood LGE the 4 SD method agreed best (12.6% vs. 11.5%). Similarly, for the HCM group no significant differences between LGE methods were found. For bright-blood LGE, the 6 SD method agreed best with manual thresholding (10.9% vs. 12.2%), while for dark-blood LGE the 5 SD method agreed best (13.2% vs. 11.5%). Semi-automated LGE quantification using dark-blood LGE images is feasible in both patients with ischemic and non-ischemic scar patterns. Given the advantage in detecting scar in patients with ischemic heart disease and no disadvantage in patients with non-ischemic scar, dark-blood LGE can be readily and widely adopted into clinical practice without compromising on quantification.
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Cardiomiopatia Hipertrófica , Isquemia Miocárdica , Humanos , Meios de Contraste , Gadolínio , Cicatriz/diagnóstico por imagem , Estudos Retrospectivos , Miocárdio , Isquemia Miocárdica/diagnóstico por imagem , Espectroscopia de Ressonância MagnéticaRESUMO
BACKGROUND: Machine learning (ML) models have been proposed to predict risk related to transvenous lead extraction (TLE). OBJECTIVE: The purpose of this study was to test whether integrating imaging data into an existing ML model increases its ability to predict major adverse events (MAEs; procedure-related major complications and procedure-related deaths) and lengthy procedures (≥100 minutes). METHODS: We hypothesized certain features-(1) lead angulation, (2) coil percentage inside the superior vena cava (SVC), and (3) number of overlapping leads in the SVC-detected from a pre-TLE plain anteroposterior chest radiograph (CXR) would improve prediction of MAE and long procedural times. A deep-learning convolutional neural network was developed to automatically detect these CXR features. RESULTS: A total of 1050 cases were included, with 24 MAEs (2.3%) . The neural network was able to detect (1) heart border with 100% accuracy; (2) coils with 98% accuracy; and (3) acute angle in the right ventricle and SVC with 91% and 70% accuracy, respectively. The following features significantly improved MAE prediction: (1) ≥50% coil within the SVC; (2) ≥2 overlapping leads in the SVC; and (3) acute lead angulation. Balanced accuracy (0.74-0.87), sensitivity (68%-83%), specificity (72%-91%), and area under the curve (AUC) (0.767-0.962) all improved with imaging biomarkers. Prediction of lengthy procedures also improved: balanced accuracy (0.76-0.86), sensitivity (75%-85%), specificity (63%-87%), and AUC (0.684-0.913). CONCLUSION: Risk prediction tools integrating imaging biomarkers significantly increases the ability of ML models to predict risk of MAE and long procedural time related to TLE.
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Remoção de Dispositivo , Aprendizado de Máquina , Humanos , Masculino , Feminino , Remoção de Dispositivo/métodos , Medição de Risco/métodos , Idoso , Desfibriladores Implantáveis/efeitos adversos , Estudos Retrospectivos , Veia Cava Superior/diagnóstico por imagem , Pessoa de Meia-Idade , Redes Neurais de Computação , BiomarcadoresRESUMO
The effectiveness of electromagnetic interference (EMI) shielding is valuable for construction materials and can be enhanced by the addition of nickel particles to silicone rubber. This investigation reports the chemical reduction process employed to produce nickel powders. The resulting powders were analyzed through SEM imaging and X-ray diffraction analysis, which indicated the production of crystalline, pure nickel powders with spherical morphology. Subsequently, the study delves into nickel filler content enhances the shielding effectiveness (1.2-2.6 GHz) of gaskets by increasing the absorption loss SEA, due to the increase in electrical conductivity. The experimentation was conducted using three samples, revealing that increasing the weight percentage of filler from 30 to 70 % resulted in a considerable reduction in electrical resistivity to 0.6 Ω cm. Moreover, the shielding effectiveness was observed to increased to above 55 dBm when tested across a frequency range of 1.2-2.6 GHz.
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Large-cohort studies using cardiovascular imaging and diagnostic datasets have assessed cardiac anatomy, function, and outcomes, but typically do not reveal underlying biological mechanisms. Cardiac digital twins (CDTs) provide personalized physics- and physiology-constrained in-silico representations, enabling inference of multi-scale properties tied to these mechanisms. We constructed 3464 anatomically-accurate CDTs using cardiac magnetic resonance images from UK biobank and personalised their myocardial conduction velocities (CVs) from electrocardiograms (ECG), through an automated framework. We found well-known sex-specific differences in QRS duration were fully explained by myocardial anatomy, as CV remained consistent across sexes. Conversely, significant associations of CV with ageing and increased BMI suggest myocardial tissue remodelling. Novel associations were observed with left ventricular ejection fraction and mental-health phenotypes, through a phenome-wide association study, and CV was also linked with adverse clinical outcomes. Our study highlights the utility of population-based CDTs in assessing intersubject variability and uncovering strong links with mental health.
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PURPOSE: MR-guided cardiac catheterization procedures currently use passive tracking approaches to follow a gadolinium-filled catheter balloon during catheter navigation. This requires frequent manual tracking and repositioning of the imaging slice during navigation. In this study, a novel framework for automatic real-time catheter tracking during MR-guided cardiac catheterization is presented. METHODS: The proposed framework includes two imaging modes (Calibration and Runtime). The sequence starts in Calibration mode, in which the 3D catheter coordinates are determined using a stack of 10-20 contiguous saturated slices combined with real-time image processing. The sequence then automatically switches to Runtime mode, where three contiguous slices (acquired with partial saturation), initially centered on the catheter balloon using the Calibration feedback, are acquired continuously. The 3D catheter balloon coordinates are estimated in real time from each Runtime slice stack using image processing. Each Runtime stack is repositioned to maintain the catheter balloon in the central slice based on the prior Runtime feedback. The sequence switches back to Calibration mode if the catheter is not detected. This framework was evaluated in a heart phantom and 3 patients undergoing MR-guided cardiac catheterization. Catheter detection accuracy and rate of catheter visibility were evaluated. RESULTS: The automatic detection accuracy for the catheter balloon during the Calibration/Runtime mode was 100%/95% in phantom and 100%/97 ± 3% in patients. During Runtime, the catheter was visible in 82% and 98 ± 2% of the real-time measurements in the phantom and patients, respectively. CONCLUSION: The proposed framework enabled real-time continuous automatic tracking of a gadolinium-filled catheter balloon during MR-guided cardiac catheterization.
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Cateterismo Cardíaco , Gadolínio , Humanos , Cateterismo Cardíaco/métodos , Catéteres , Imagens de Fantasmas , CoraçãoRESUMO
This research study was conducted to investigate the laser melting parameters of NiCrAlY-APS coating. High-temperature oxidation was investigated using yttria partially stabilized zirconia (YSZ) ceramic coating. Also, the oxidation behavior of the TBC coating was investigated and studied before to and after laser surface melting of the NiCrAlY coating. Microstructural characterization was done using a scanning electron microscope (SEM), elemental analysis by energy dispersive spectroscopy (EDS), and phase analysis by X-ray diffraction (XRD). Surface melting was then performed in the power range of 150-300 W and scanning speed of 2-6 mm s-1. Surface melting was also conducted on the coating using two strategies: single-pass and multi-pass. The obtained results showed that the average melting depth and thickness reduction were directly related to the laser power, while they had an inverse relation with the laser scanning speed. Furthermore, multi-pass surface melting parameters reduced porosity to less than 0.1 %. Roughness measurements also showed a decrease in the coating's surface hardness after surface melting, as compared to the APS coating. The structure consisted of oriented columnar dendrites after melting the laser. The adhesion strength of the TBC coating and laser surface melting coating was at 41 MPa and 53 MPa, respectively. After 200 h of oxidation in the G1504 sample, the TGO layer's growth was decreased; due to the growth of a single oxide layer, it had better oxidation resistance in comparison to the other sample.
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In the present study, the tensile strength, fracture surface, hardness, and amount of residual stress in Inconel 625 super alloy cladded with direct metal deposition (DLD) process in the states before and after stress relief was studied. Residual stresses on the cladding layer surface were determined via XRD method. According to results, the yield strength of Am sample increased by 10% compared to thecast sample (reference sample). Although the yield strength experiebced an increase, the ductility followed an opposite trend falling from 42.5% to 26%. According to residual stress test outcomes, tensile residual stress of 361 MPa in the additive-manufactured sample. After stress relaxation heat treatment and almost complete removal of residual stress, the ductility reached 52.5%, the ultimate strength was also improved by 17% from cast sample. Also, after stress relaxation, the hardness of the sample and its fluctuations are reduced.
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Aims: Artificial intelligence (AI) techniques have been proposed for automating analysis of short-axis (SAX) cine cardiac magnetic resonance (CMR), but no CMR analysis tool exists to automatically analyse large (unstructured) clinical CMR datasets. We develop and validate a robust AI tool for start-to-end automatic quantification of cardiac function from SAX cine CMR in large clinical databases. Methods and results: Our pipeline for processing and analysing CMR databases includes automated steps to identify the correct data, robust image pre-processing, an AI algorithm for biventricular segmentation of SAX CMR and estimation of functional biomarkers, and automated post-analysis quality control to detect and correct errors. The segmentation algorithm was trained on 2793 CMR scans from two NHS hospitals and validated on additional cases from this dataset (n = 414) and five external datasets (n = 6888), including scans of patients with a range of diseases acquired at 12 different centres using CMR scanners from all major vendors. Median absolute errors in cardiac biomarkers were within the range of inter-observer variability: <8.4 mL (left ventricle volume), <9.2 mL (right ventricle volume), <13.3 g (left ventricular mass), and <5.9% (ejection fraction) across all datasets. Stratification of cases according to phenotypes of cardiac disease and scanner vendors showed good performance across all groups. Conclusion: We show that our proposed tool, which combines image pre-processing steps, a domain-generalizable AI algorithm trained on a large-scale multi-domain CMR dataset and quality control steps, allows robust analysis of (clinical or research) databases from multiple centres, vendors, and cardiac diseases. This enables translation of our tool for use in fully automated processing of large multi-centre databases.
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Radiofrequency catheter ablation is an established treatment strategy for ventricular tachycardia, but remains associated with a low success rate. MR guidance of ventricular tachycardia shows promises to improve the success rate of these procedures, especially due to its potential to provide real-time information on lesion formation using cardiac MR thermometry. Modern low field MRI scanners (<1â T) are of major interest for MR-guided ablations as the potential benefits include lower costs, increased patient access and device compatibility through reduced device-induced imaging artefacts and safety constraints. However, the feasibility of cardiac MR thermometry at low field remains unknown. In this study, we demonstrate the feasibility of cardiac MR thermometry at 0.55â T and characterized its in vivo stability (i.e., precision) using state-of-the-art techniques based on the proton resonance frequency shift method. Nine healthy volunteers were scanned using a cardiac MR thermometry protocol based on single-shot EPI imaging (3 slices in the left ventricle, 150 dynamics, TE = 41â ms). The reconstruction pipeline included image registration to align all the images, multi-baseline approach (look-up-table length = 30) to correct for respiration-induced phase variations, and temporal filtering to reduce noise in temperature maps. The stability of thermometry was defined as the pixel-wise standard deviation of temperature changes over time. Cardiac MR thermometry was successfully acquired in all subjects and the stability averaged across all subjects was 1.8 ± 1.0°C. Without multi-baseline correction, the overall stability was 2.8 ± 1.6°C. In conclusion, cardiac MR thermometry is feasible at 0.55â T and further studies on MR-guided catheter ablations at low field are warranted.
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In this study, the chemical reduction method was applied to synthesize silver nanoparticles used to prepare conductive inks. The two variables of polyvinylpyrrolidone (PVP)-stabilized mole in the 0.01-0.03 mol range and hydrazine reducing mole in the 0.1-0.5 mol range, along with constants such as precursor mole (silver nitrate), complexing mole (ethylene diamine) and solvent mole (water), were used. Nine random samples proposed by the Design Expert software were examined and studied. X-ray diffraction (XRD) patterns, field emission scanning electron microscopy (FE-SEM), transmission electron microscopy (TEM) and dynamic light scattering (DLS) were then used to characterize and evaluate the synthesized nanoparticles. According to the results obtained by XRD, FE-SEM and TEM analyses, the sample with 0.025 mol and 0.3 mol PVP had the minimum size of silver nanoparticles, which was around 20 nm, so it was chosen as the optimal sample for further research. The conductive ink was also prepared with the optimal sample of silver nanoparticles in 40% by weight and then characterized and evaluated by applying ultraviolet-visible (UV-Vis), simultaneous thermal analysis (STA), FE-SEM and electrical conductivity analysis. Finally, conductive ink was applied to polyethylene terephthalate (PET) and acrylonitrile butadiene styrene (ABS) substrates. The surface electrical resistance of conductive ink on PET and ABS substrates was then measured at about 6.4 Ω and 2.2 Ω, respectively.
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BACKGROUND: Congenital heart disease (CHD) is common and is associated with impaired early brain development and neurodevelopmental outcomes, yet the exact mechanisms underlying these associations are unclear. PURPOSE: To utilize MRI data from a cohort of fetuses with CHD as well as typically developing fetuses to test the hypothesis that expected cerebral substrate delivery is associated with total and regional fetal brain volumes. STUDY TYPE: Retrospective case-control study. POPULATION: Three hundred eighty fetuses (188 male), comprising 45 healthy controls and 335 with isolated CHD, scanned between 29 and 37 weeks gestation. Fetuses with CHD were assigned into one of four groups based on expected cerebral substrate delivery. FIELD STRENGTH/SEQUENCE: T2-weighted single-shot fast-spin-echo sequences and a balanced steady-state free precession gradient echo sequence were obtained on a 1.5 T scanner. ASSESSMENT: Images were motion-corrected and reconstructed using an automated slice-to-volume registration reconstruction technique, before undergoing segmentation using an automated pipeline and convolutional neural network that had undergone semi-supervised training. Differences in total, regional brain (cortical gray matter, white matter, deep gray matter, cerebellum, and brainstem) and brain:body volumes were compared between groups. STATISTICAL TESTS: ANOVA was used to test for differences in brain volumes between groups, after accounting for sex and gestational age at scan. PFDR -values <0.05 were considered statistically significant. RESULTS: Total and regional brain volumes were smaller in fetuses where cerebral substrate delivery is reduced. No significant differences were observed in total or regional brain volumes between control fetuses and fetuses with CHD but normal cerebral substrate delivery (all PFDR > 0.12). Severely reduced cerebral substrate delivery is associated with lower brain:body volume ratios. DATA CONCLUSION: Total and regional brain volumes are smaller in fetuses with CHD where there is a reduction in cerebral substrate delivery, but not in those where cerebral substrate delivery is expected to be normal. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 3.