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The DTU is managing the UK sites for a global study testing if either chloroquine or hydroxychloroquine can prevent COVID-19 in vital frontline healthcare workers.
Background: Segmentation of the left atrium (LA) is required to evaluate atrial size and function, which are important imaging biomarkers for a wide range of cardiovascular conditions, such as atrial fibrillation, stroke, and diastolic dysfunction. LA segmentations are currently being performed manually, which is time-consuming and observer-dependent. Methods: This study presents an automated image processing algorithm for time-resolved LA segmentation in cardiac magnetic resonance imaging (MRI) long-axis cine images of the 2-chamber (2ch) and 4-chamber (4ch) views using active contours. The proposed algorithm combines mitral valve tracking, automated threshold calculation, edge detection on a radially resampled image, edge tracking based on Dijkstra’s algorithm, and post-processing involving smoothing and interpolation. The algorithm was evaluated in 37 patients diagnosed mainly with paroxysmal atrial fibrillation. Segmentation accuracy was assessed using the Dice similarity coefficient (DSC) and Hausdorff distance (HD), with manual segmentations in all time frames as the reference standard. For inter-observer variability analysis, a second observer performed manual segmentations at end-diastole and end-systole on all subjects. Results: The proposed automated method achieved high performance in segmenting the LA in long-axis cine sequences, with a DSC of 0.96 for 2ch and 0.95 for 4ch, and an HD of 5.5 mm for 2ch and 6.4 mm for 4ch. The manual inter-observer variability analysis had an average DSC of 0.95 and an average HD of 4.9 mm. Conclusion: The proposed automated method achieved performance on par with human experts analyzing MRI images for evaluation of atrial size and function. [MediaObject not available: see fulltext.]
Assessment of diastolic function and atrial remodeling by MRI – validation and correlation with echocardiography and filling pressure
Atrial fibrosis can be estimated noninvasively by magnetic resonance imaging (MRI) using late gadolinium enhancement (LGE), but diastolic dysfunction is clinically assessed by transthoracic echocardiography (TTE), and rarely by MRI. This study aimed to evaluate well-established diastolic parameters using MRI, and validate them with TTE and left ventricular (LV) filling pressures, and to study the relationship between left atrial (LA) remodeling and parameters of diastolic function. The study retrospectively included 105 patients (53 ± 16 years, 39 females) who underwent 3D LGE MRI between 2012 and 2016. Medical charts were reviewed for the echocardiographic diastolic parameters E, A, and e′ by TTE, and pressure catheterizations. E and A were measured from in-plane phase-contrast cardiac MRI images, and e′ by feature-tracking, and validated with TTE. Interobserver and intraobserver variability was examined. Furthermore, LA volumes, function, and atrial LGE was correlated with diastolic parameters. Evaluation of e′ in MRI had strong agreement with TTE (r = 0.75, P
Valvular imaging in the era of feature-tracking: A slice-following cardiac MR sequence to measure mitral flow
Background: In mitral valve dysfunction, noninvasive measurement of transmitral blood flow is an important clinical examination. Flow imaging of the mitral valve, however, is challenging, since it moves in and out of the image plane during the cardiac cycle. Purpose: To more accurately measure mitral flow, a slice-following MRI phase contrast sequence is proposed. This study aimed to implement such a sequence, validate its slice-following functionality in a phantom and healthy subjects, and test its feasibility in patients with mitral valve dysfunction. Study Type: Prospective. Phantom and Subjects: The slice-following functionality was validated in a cone-shaped phantom by measuring the depicted slice radius. Sixteen healthy subjects and 10 mitral valve dysfunction patients were enrolled at two sites. Field Strength/Sequence: 1.5T and 3T gradient echo cine phase contrast. Assessment: A single breath-hold retrospectively gated sequence using offline feature-tracking of the mitral valve was developed. Valve displacements were measured and imported to the scanner, allowing the slice position to change dynamically based on the cardiac phase. Mitral valve imaging was performed with slice-following and static imaging planes. Validation was performed by comparing mitral stroke volume with planimetric and aortic stroke volume. Statistical Tests: Measurements were compared using linear regression, Pearson's R, parametric paired t-tests, Bland–Altman analysis, and intraclass correlation coefficient (ICC). Results: Phantom experiments confirmed accurate slice displacements. Slice-following was feasible in all subjects, yielding physiologically accurate mitral flow patterns. In healthy subjects, mitral and aortic stroke volumes agreed, with ICC = 0.72 and 0.90 for static and slice-following planes; with bias ±1 SDs 23.2 ± 13.2 mls and 8.4 ± 10.8 mls, respectively. Agreement with planimetry was stronger, with ICC = 0.84 and 0.96; bias ±1 SDs 13.7 ± 13.7 mls and –2.0 ± 8.8 mls for static and slice-following planes, respectively. Data Conclusion: Slice-following outperformed the conventional sequence and improved the accuracy of transmitral flow, which is important for assessment of diastolic function and mitral regurgitation. Level of Evidence: 2. Technical Efficacy: Stage 2. J. Magn. Reson. Imaging 2020;51:1412–1421.
Ensemble of Deep Convolutional Neural Networks with Monte Carlo Dropout Sampling for Automated Image Segmentation Quality Control and Robust Deep Learning Using Small Datasets
Recent progress on deep learning (DL)-based medical image segmentation can enable fast extraction of clinical parameters for efficient clinical workflows. However, current DL methods can still fail and require manual visual inspection of outputs, which is time-consuming and diminishes the advantages of automation. For clinical applications, it is essential to develop DL approaches that can not only perform accurate segmentation, but also predict the segmentation quality and flag poor-quality results to avoid errors in diagnosis. To achieve robust performance, DL-based methods often require large datasets, which are not always readily available. It would be highly desirable to be able to train DL models using only small datasets, but this requires a quality prediction method to ensure reliability. We present a novel segmentation framework utilizing an ensemble of deep convolutional neural networks with Monte Carlo sampling. The proposed framework merges the advantages of both state-of-the-art deep ensembles and Bayesian approaches, to provide robust segmentation with inherent quality control. We successfully developed and tested this framework using just a small MRI dataset of 45 subjects. The framework obtained high mean Dice similarity coefficients (DSC) for segmentation of the endocardium (0.922) and the epicardium (0.942); importantly, segmentation DSC can be accurately predicted with low mean absolute errors (≤0.035), in the absence of the manual ground truth. Furthermore, binary classification of segmentation quality achieved a near-perfect accuracy of 99%. The proposed framework can enable fast and reliable medical image analysis with accurate quality control, and training of DL-based methods using even small datasets.
Deep neural network ensemble for on-the-fly quality control-driven segmentation of cardiac MRI T1 mapping.
Recent developments in artificial intelligence have generated increasing interest to deploy automated image analysis for diagnostic imaging and large-scale clinical applications. However, inaccuracy from automated methods could lead to incorrect conclusions, diagnoses or even harm to patients. Manual inspection for potential inaccuracies is labor-intensive and time-consuming, hampering progress towards fast and accurate clinical reporting in high volumes. To promote reliable fully-automated image analysis, we propose a quality control-driven (QCD) segmentation framework. It is an ensemble of neural networks that integrate image analysis and quality control. The novelty of this framework is the selection of the most optimal segmentation based on predicted segmentation accuracy, on-the-fly. Additionally, this framework visualizes segmentation agreement to provide traceability of the quality control process. In this work, we demonstrated the utility of the framework in cardiovascular magnetic resonance T1-mapping - a quantitative technique for myocardial tissue characterization. The framework achieved near-perfect agreement with expert image analysts in estimating myocardial T1 value (r=0.987,p
A Chest Patch for Continuous Vital Sign Monitoring: Clinical Validation Study During Movement and Controlled Hypoxia.
BACKGROUND: The standard of care in general wards includes periodic manual measurements, with the data entered into track-and-trigger charts, either on paper or electronically. Wearable devices may support health care staff, improve patient safety, and promote early deterioration detection in the interval between periodic measurements. However, regulatory standards for ambulatory cardiac monitors estimating heart rate (HR) and respiratory rate (RR) do not specify performance criteria during patient movement or clinical conditions in which the patient's oxygen saturation varies. Therefore, further validation is required before clinical implementation and deployment of any wearable system that provides continuous vital sign measurements. OBJECTIVE: The objective of this study is to determine the agreement between a chest-worn patch (VitalPatch) and a gold standard reference device for HR and RR measurements during movement and gradual desaturation (modeling a hypoxic episode) in a controlled environment. METHODS: After the VitalPatch and gold standard devices (Philips MX450) were applied, participants performed different movements in seven consecutive stages: at rest, sit-to-stand, tapping, rubbing, drinking, turning pages, and using a tablet. Hypoxia was then induced, and the participants' oxygen saturation gradually reduced to 80% in a controlled environment. The primary outcome measure was accuracy, defined as the mean absolute error (MAE) of the VitalPatch estimates when compared with HR and RR gold standards (3-lead electrocardiography and capnography, respectively). We defined these as clinically acceptable if the rates were within 5 beats per minute for HR and 3 respirations per minute (rpm) for RR. RESULTS: Complete data sets were acquired for 29 participants. In the movement phase, the HR estimates were within prespecified limits for all movements. For RR, estimates were also within the acceptable range, with the exception of the sit-to-stand and turning page movements, showing an MAE of 3.05 (95% CI 2.48-3.58) rpm and 3.45 (95% CI 2.71-4.11) rpm, respectively. For the hypoxia phase, both HR and RR estimates were within limits, with an overall MAE of 0.72 (95% CI 0.66-0.78) beats per minute and 1.89 (95% CI 1.75-2.03) rpm, respectively. There were no significant differences in the accuracy of HR and RR estimations between normoxia (≥90%), mild (89.9%-85%), and severe hypoxia (<85%). CONCLUSIONS: The VitalPatch was highly accurate throughout both the movement and hypoxia phases of the study, except for RR estimation during the two types of movements. This study demonstrated that VitalPatch can be safely tested in clinical environments to support earlier detection of cardiorespiratory deterioration. TRIAL REGISTRATION: ISRCTN Registry ISRCTN61535692; https://www.isrctn.com/ISRCTN61535692.
Mitochondrial DNA variants modulate N-formylmethionine, proteostasis and risk of late-onset human diseases.
Mitochondrial DNA (mtDNA) variants influence the risk of late-onset human diseases, but the reasons for this are poorly understood. Undertaking a hypothesis-free analysis of 5,689 blood-derived biomarkers with mtDNA variants in 16,220 healthy donors, here we show that variants defining mtDNA haplogroups Uk and H4 modulate the level of circulating N-formylmethionine (fMet), which initiates mitochondrial protein translation. In human cytoplasmic hybrid (cybrid) lines, fMet modulated both mitochondrial and cytosolic proteins on multiple levels, through transcription, post-translational modification and proteolysis by an N-degron pathway, abolishing known differences between mtDNA haplogroups. In a further 11,966 individuals, fMet levels contributed to all-cause mortality and the disease risk of several common cardiovascular disorders. Together, these findings indicate that fMet plays a key role in common age-related disease through pleiotropic effects on cell proteostasis.
SUMMARYThousands of genetic associations with phenotypes of blood cells are known, but few are with phenotypes relevant to cell function. We performed GWAS of 63 flow-cytometry phenotypes, including measures of cell granularity, nucleic acid content, and reactivity, in 39,656 participants in the INTERVAL study, identifying 2,172 variant-trait associations. These include associations mediated by functional cellular structures such as secretory granules, implicated in vascular, thrombotic, inflammatory and neoplastic diseases. By integrating our results with epigenetic data and with signals from molecular abundance/disease GWAS, we infer the hematopoietic origins of population phenotypic variation and identify the transcription factor FOG2 as a regulator of plateletα-granularity. We show how flow cytometry genetics can suggest cell types mediating complex disease risk and suggest efficacious drug targets, presenting Daclizumab/Vedolizumab in autoimmune disease as positive controls. Finally, we add to existing evidence supporting IL7/IL7-R as drug targets for multiple sclerosis.
Automated assessment of CD8+ T-lymphocytes and stroma fractions complement conventional staging of colorectal cancer.
BACKGROUND: Tumor development is critically dependent on the supporting stroma consisting of inflammatory cells and fibroblasts. This study intended to improve prognostic prediction for early colorectal cancer (CRC) by combined estimation of T-lymphocyte and stroma fractions with conventional markers. METHODS: In total 509 and 1041 stage II/ΙΙΙ CRC from the VICTOR and QUASAR 2 trials were included as a training set and a validation set, respectively. Intratumoral CD8+ T-lymphocytes and stroma were identified and quantified by machine-based learning on digital sections. The primary endpoint was to evaluate the prognostic value of the combined marker for time to recurrence (TTR). FINDINGS: For low-risk patients (n = 598; stage Ⅱ, and stage ΙΙΙ pT1-3 pN1 with neither lymphatic (L-) nor vascular (V-) invasion), low stroma fraction (n = 511) identified a good prognostic subgroup with 5-year TTR of 86% (95% CI 83-89), versus the high stroma subgroup TTR of 78% (HR = 1.75, 95% CI 1.05-2.92; P = 0.029). For high-risk patients (n = 394; stage ΙΙΙ pT3 pN1 L+/V+, pT4, or pN2), combined low CD8+ and high stroma fraction identified a poor prognostic subgroup (n = 34) with 5-year TTR of 29% (95% CI 17-50), versus the high CD8+ fraction and low stroma fraction subgroup (n = 138) of 64% (HR = 2.86, 95% CI 1.75-4.69; P
Age-dependent changes in protein incorporation into collagen-rich tissues of mice by in vivo pulsed SILAC labelling
Collagen-rich tissues have poor reparative capacity that predisposes to common age-related disorders such as osteoporosis and osteoarthritis. We used in vivo pulsed SILAC labelling to quantify new protein incorporation into cartilage, bone, and skin of mice across the healthy life course. We report dynamic turnover of the matrisome, the proteins of the extracellular matrix, in bone and cartilage during skeletal maturation, which was markedly reduced after skeletal maturity. Comparing young adult with older adult mice, new protein incorporation was reduced in all tissues. STRING clustering revealed changes in epigenetic modulators across all tissues, a decline in chondroprotective growth factors such as FGF2 and TGFβ in cartilage, and clusters indicating mitochondrial dysregulation and reduced collagen synthesis in bone. Several pathways were implicated in age-related disease. Fewer changes were observed for skin. This methodology provides dynamic protein data at a tissue level, uncovering age-related molecular changes that may predispose to disease.
Adenosine-to-inosine editing of endogenous Z-form RNA by the deaminase ADAR1 prevents spontaneous MAVS-dependent type I interferon responses.
Nucleic acids are powerful triggers of innate immunity and can adopt the Z-conformation, an unusual left-handed double helix. Here, we studied the biological function(s) of Z-RNA recognition by the adenosine deaminase ADAR1, mutations in which cause Aicardi-Goutières syndrome. Adar1mZα/mZα mice, bearing two point mutations in the Z-nucleic acid binding (Zα) domain that abolish Z-RNA binding, displayed spontaneous induction of type I interferons (IFNs) in multiple organs, including in the lung, where both stromal and hematopoietic cells showed IFN-stimulated gene (ISG) induction. Lung neutrophils expressed ISGs induced by the transcription factor IRF3, indicating an initiating role for neutrophils in this IFN response. The IFN response in Adar1mZα/mZα mice required the adaptor MAVS, implicating cytosolic RNA sensing. Adenosine-to-inosine changes were enriched in transposable elements and revealed a specific requirement of ADAR1's Zα domain in editing of a subset of RNAs. Thus, endogenous RNAs in Z-conformation have immunostimulatory potential curtailed by ADAR1, with relevance to autoinflammatory disease in humans.
Clinical outcomes and the impact of prior oral anticoagulant use in patients with coronavirus disease 2019 admitted to hospitals in the UK — a multicentre observational study
Coagulation dysfunction and thrombosis are major complications in patients with coronavirus disease 2019 (COVID-19). Patients on oral anticoagulants (OAC) prior to diagnosis of COVID-19 may therefore have better outcomes. In this multicentre observational study of 5 883 patients (≥18 years) admitted to 26 UK hospitals between 1 April 2020 and 31 July 2020, overall mortality was 29·2%. Incidences of thrombosis, major bleeding (MB) and multiorgan failure (MOF) were 5·4%, 1·7% and 3·3% respectively. The presence of thrombosis, MB, or MOF was associated with a 1·8, 4·5 or 5·9-fold increased risk of dying, respectively. Of the 5 883 patients studied, 83·6% (n = 4 920) were not on OAC and 16·4% (n = 963) were taking OAC at the time of admission. There was no difference in mortality between patients on OAC vs no OAC prior to admission when compared in an adjusted multivariate analysis [hazard ratio (HR) 1·05, 95% confidence interval (CI) 0·93–1·19; P = 0·15] or in an adjusted propensity score analysis (HR 0·92 95% CI 0·58–1·450; P = 0·18). In multivariate and adjusted propensity score analyses, the only significant association of no anticoagulation prior to diagnosis of COVID-19 was admission to the Intensive-Care Unit (ICU) (HR 1·98, 95% CI 1·37–2·85). Thrombosis, MB, and MOF were associated with higher mortality. Our results indicate that patients may have benefit from prior OAC use, especially reduced admission to ICU, without any increase in bleeding.
ABSTRACTBackgroundObesity is a major global health problem, and is associated with increased cardiometabolic morbidity and mortality. Protein glycosylation is a frequent postranslational modification, highly responsive to numerous pathophysiological conditions and ageing. The prospect of biological age reduction, by reverting glycosylation changes through metabolic intervention, opens many possibilities. We have investigated whether weight loss interventions affect inflammation- and ageing-associated IgG glycosylation changes, in a longitudinal cohort of bariatric surgery patients. To support potential findings, BMI-related glycosylation changes were monitored in a longitudinal twins cohort.MethodsIgG N-glycans were chromatographically profiled in 37 obese patients, subjected to low-calorie diet, followed by bariatric surgery, across multiple timepoints. Similarly, plasma-derived IgG N-glycan traits were longitudinally monitored in 1,680 participants from the TwinsUK cohort.ResultsLow-calorie diet induced a marked decrease in the levels of IgG N-glycans with bisecting GlcNAc, whose higher levels are usually associated with ageing and inflammatory conditions. Bariatric surgery resulted in extensive alterations of the IgG glycome that accompanied progressive weight loss during one-year follow-up. We observed a significant increase in digalactosylated and sialylated glycans, and a substantial decrease in agalactosylated and core fucosylated IgG glycans. In general, this IgG glycan profile is associated with a younger biological age and reflects an enhanced anti-inflammatory IgG potential. Loss of BMI over a 20 year period in the TwinsUK cohort validated a weight loss-associated agalactosylation decrease and an increase in digalactosylation.ConclusionsAltogether, these findings highlight that weight loss substantially affects IgG N-glycosylation, resulting in reduced biological and immune age.GRAPHICAL ABSTRACTHIGHLIGHTSObesity is associated to inflammation-related agalactosylated and bisected IgG glycoformsIgG galactosylation and sialylation increase after bariatric surgery-induced weight lossProgressive decrease of BMI is associated to increased IgG galactosylation, implying a reduction of biological age
AbstractSteroid hormones, including glucocorticoids and androgens, exert a wide variety of effects in the body across almost all tissues. The steroid A-ring 5β-reductase (AKR1D1) is expressed in human liver and testes, and three splice variants have been identified (AKR1D1-001, AKR1D1-002, AKR1D1-006). Amongst these, AKR1D1-002 is the best described; it modulates steroid hormone availability and catalyses an important step in bile acid synthesis. However, specific activity and expression of AKR1D1-001 and AKR1D1-006 are unknown.AKR1D1-002, AKR1D1-001 and AKR1D1-006 were measured in human liver biopsies and human hepatoma cell lines by qPCR. Three-dimensional (3D) structures of AKR1D1 variants were determined using in silico approaches. AKR1D1 variants were over-expressed in HEK293 cells, and successful overexpression confirmed by qPCR and western blotting. Steroid hormone clearance was measured by mass spectrometry and ELISA, and steroid receptor activation determined by luciferase reporter assays.AKR1D1-002 and AKR1D1-001 are expressed in human liver, and only AKR1D1-006 is expressed in human testes. Following over-expression in HEK293 cells, AKR1D1-001 and AKR1D1-006 protein levels were lower than AKR1D1-002, but significantly increased following treatment with the proteasomal inhibitor, MG-132. AKR1D1-002 efficiently metabolised glucocorticoids and androgens and decreased receptor activation. AKR1D1-001 and AKR1D1-006 poorly metabolised dexamethasone, but neither protein metabolised cortisol, prednisolone or testosterone.We have demonstrated the differential expression and role of AKR1D1 splice variants to regulate steroid hormone clearance and receptor activation. AKR1D1-002 is the predominant functional protein in steroidogenic and metabolic tissues. In addition, AKR1D1-001 and AKR1D1-006 may have a limited role in the regulation of synthetic glucocorticoid action.
Ct threshold values, a proxy for viral load in community SARS-CoV-2 cases, demonstrate wide variation across populations and over time.
Background: Information on SARS-CoV-2 in representative community surveillance is limited, particularly cycle threshold (Ct) values (a proxy for viral load). Methods: We included all positive nose and throat swabs 26 April 2020 to 13 March 2021 from the UK's national COVID-19 Infection Survey, tested by RT-PCR for the N, S, and ORF1ab genes. We investigated predictors of median Ct value using quantile regression. Results: Of 3,312,159 nose and throat swabs, 27,902 (0.83%) were RT-PCR-positive, 10,317 (37%), 11,012 (40%), and 6550 (23%) for 3, 2, or 1 of the N, S, and ORF1ab genes, respectively, with median Ct = 29.2 (~215 copies/ml; IQR Ct = 21.9-32.8, 14-56,400 copies/ml). Independent predictors of lower Cts (i.e. higher viral load) included self-reported symptoms and more genes detected, with at most small effects of sex, ethnicity, and age. Single-gene positives almost invariably had Ct > 30, but Cts varied widely in triple-gene positives, including without symptoms. Population-level Cts changed over time, with declining Ct preceding increasing SARS-CoV-2 positivity. Of 6189 participants with IgG S-antibody tests post-first RT-PCR-positive, 4808 (78%) were ever antibody-positive; Cts were significantly higher in those remaining antibody negative. Conclusions: Marked variation in community SARS-CoV-2 Ct values suggests that they could be a useful epidemiological early-warning indicator. Funding: Department of Health and Social Care, National Institutes of Health Research, Huo Family Foundation, Medical Research Council UK; Wellcome Trust.