A cone-beam X-ray computed tomography data collection designed for machine learning

Unlike previous works, this open data collection consists of X-ray cone-beam (CB) computed tomography (CT) datasets specifically designed for machine learning applications and high cone-angle artefact reduction. Forty-two walnuts were scanned with a laboratory X-ray set-up to provide not only data from a single object but from a class of objects with natural variability. For each walnut, CB projections on three different source orbits were acquired to provide CB data with different cone angles as well as being able to compute artefact-free, high-quality ground truth images from the combined data that can be used for supervised learning. We provide the complete image reconstruction pipeline: raw projection data, a description of the scanning geometry, pre-processing and reconstruction scripts using open software, and the reconstructed volumes. Due to this, the dataset can not only be used for high cone-angle artefact reduction but also for algorithm development and evaluation for other tasks, such as image reconstruction from limited or sparse-angle (low-dose) scanning, super resolution, or segmentation

Just-in-time deep learning for real-time X-ray computed tomography

Real-time X-ray tomography pipelines, such as implemented by RECAST3D, compute and visualize tomographic reconstructions in milliseconds, and enable the observation of dynamic experiments in synchrotron beamlines and laboratory scanners. For extending real-time reconstruction by image processing and analysis components, Deep Neural Networks (DNNs) are a promising technology, due to their strong performance and much faster run-times compared to conventional algorithms. DNNs may prevent experiment repetition by simplifying real-time steering and optimization of the ongoing experiment. The main challenge of integrating DNNs into real-time tomography pipelines, however, is that they need to learn their task from representative data before the start of the experiment. In scientific environments, such training data may not exist, and other uncertain and variable factors, such as the set-up configuration, reconstruction parameters, or user interaction, cannot easily be anticipated beforehand, either. To overcome these problems, we developed just-in-time learning, an online DNN training strategy that takes advantage of the spatio-temporal continuity of consecutive reconstructions in the tomographic pipeline. This allows training and deploying comparatively small DNNs during the experiment. We provide software implementations, and study the feasibility and challenges of the approach by training the self-supervised Noise2Inverse denoising task with X-ray data replayed from real-world dynamic experiments

Explorative imaging and its implementation at the FleX-ray laboratory

In tomographic imaging, the traditional process consists of an expert and an operator collecting data, the expert working on the reconstructed slices and drawing conclusions. The quality of reconstructions depends heavily on the quality of the collected data, except that, in the traditional process of imaging, the expert has very little influence over the acquisition parameters, experimental plan or the collected data. It is often the case that the expert has to draw limited conclusions from the reconstructions, or adapt a research question to data available. This method of imaging is static and sequential, and limits the potential of tomography as a research tool. In this paper, we propose a more dynamic process of imaging where experiments are tailored around a sample or the research question; intermediate reconstructions and analysis are available almost instantaneously, and expert has input at any stage of the process (including during acquisition) to improve acquisition or image reconstruction. Through various applications of 2D, 3D and dynamic 3D imaging at the FleX-ray Laboratory, we present the unexpected journey of exploration a research question undergoes, and the surprising benefits it yields

Emulation of X-ray light-field cameras

X-ray plenoptic cameras acquire multi-view X-ray transmission images in a single exposure (light-field). Their development is challenging: designs have appeared only recently, and they are still affected by important limitations. Concurrently, the lack of available real X-ray light-field data hinders dedicated algorithmic development. Here, we present a physical emulation setup for rapidly exploring the parameter space of both existing and conceptual camera designs. This will assist and accelerate the design of X-ray plenoptic imaging solutions, and provide a tool for generating unlimited real X-ray plenoptic data. We also demonstrate that X-ray light-fields allow for reconstructing sharp spatial structures in three-dimensions (3D) from single-shot data

Inhibition of the NLRP3/IL-1β axis protects against sepsis-induced cardiomyopathy

BACKGROUND: Septic cardiomyopathy worsens the prognosis of critically ill patients. Clinical data suggest that interleukin-1β (IL-1β), activated by the NLRP3 inflammasome, compromises cardiac function. Whether or not deleting Nlrp3 would prevent cardiac atrophy and improve diastolic cardiac function in sepsis was unclear. Here, we investigated the role of NLRP3/IL-1β in sepsis-induced cardiomyopathy and cardiac atrophy. METHODS: Male Nlrp3 knockout (KO) and wild-type (WT) mice were exposed to polymicrobial sepsis by caecal ligation and puncture (CLP) surgery (KO, n = 27; WT, n = 33) to induce septic cardiomyopathy. Sham-treated mice served as controls (KO, n = 11; WT, n = 16). Heart weights and morphology, echocardiography and analyses of gene and protein expression were used to evaluate septic cardiomyopathy and cardiac atrophy. IL-1β effects on primary and immortalized cardiomyocytes were investigated by morphological and molecular analyses. IonOptix and real-time deformability cytometry (RT-DC) analysis were used to investigate functional and mechanical effects of IL-1β on cardiomyocytes. RESULTS: Heart morphology and echocardiography revealed preserved systolic (stroke volume: WT sham vs. WT CLP: 33.1 ± 7.2 μL vs. 24.6 ± 8.7 μL, P < 0.05; KO sham vs. KO CLP: 28.3 ± 8.1 μL vs. 29.9 ± 9.9 μL, n.s.; P < 0.05 vs. WT CLP) and diastolic (peak E wave velocity: WT sham vs. WT CLP: 750 ± 132 vs. 522 ± 200 mm/s, P < 0.001; KO sham vs. KO CLP: 709 ± 152 vs. 639 ± 165 mm/s, n.s.; P < 0.05 vs. WT CLP) cardiac function and attenuated cardiac (heart weight-tibia length ratio: WT CLP vs. WT sham: -26.6%, P < 0.05; KO CLP vs. KO sham: -3.3%, n.s.; P < 0.05 vs. WT CLP) and cardiomyocyte atrophy in KO mice during sepsis. IonOptix measurements showed that IL-1β decreased contractility (cell shortening: IL-1β: -15.4 ± 2.3%, P < 0.001 vs. vehicle, IL-1RA: -6.1 ± 3.3%, P < 0.05 vs. IL-1β) and relaxation of adult rat ventricular cardiomyocytes (time-to-50% relengthening: IL-1β: 2071 ± 225 ms, P < 0.001 vs. vehicle, IL-1RA: 564 ± 247 ms, P < 0.001 vs. IL-1β), which was attenuated by an IL-1 receptor antagonist (IL-1RA). RT-DC analysis indicated that IL-1β reduced cardiomyocyte size (P < 0.001) and deformation (P < 0.05). RNA sequencing showed that genes involved in NF-κB signalling, autophagy and lysosomal protein degradation were enriched in hearts of septic WT but not in septic KO mice. Western blotting and qPCR disclosed that IL-1β activated NF-κB and its target genes, caused atrophy and decreased myosin protein in myocytes, which was accompanied by an increased autophagy gene expression. These effects were attenuated by IL-1RA. CONCLUSIONS: IL-1β causes atrophy, impairs contractility and relaxation and decreases deformation of cardiomyocytes. Because NLRP3/IL-1β pathway inhibition attenuates cardiac atrophy and cardiomyopathy in sepsis, it could be useful to prevent septic cardiomyopathy

Energy metabolites as biomarkers in ischemic and dilated cardiomyopathy

With more than 25 million people affected, heart failure (HF) is a global threat. As energy production pathways are known to play a pivotal role in HF, we sought here to identify key metabolic changes in ischemic- and non-ischemic HF by using a multi-OMICS approach. Serum metabolites and mRNAseq and epigenetic DNA methylation profiles were analyzed from blood and left ventricular heart biopsy specimens of the same individuals. In total we collected serum from n = 82 patients with Dilated Cardiomyopathy (DCM) and n = 51 controls in the screening stage. We identified several metabolites involved in glycolysis and citric acid cycle to be elevated up to 5.7-fold in DCM (p = 1.7 × 10(-6)). Interestingly, cardiac mRNA and epigenetic changes of genes encoding rate-limiting enzymes of these pathways could also be found and validated in our second stage of metabolite assessment in n = 52 DCM, n = 39 ischemic HF and n = 57 controls. In conclusion, we identified a new set of metabolomic biomarkers for HF. We were able to identify underlying biological cascades that potentially represent suitable intervention targets

Discovery of Genetic Variation on Chromosome 5q22 Associated with Mortality in Heart Failure

Failure of the human heart to maintain sufficient output of blood for the demands of the body, heart failure, is a common condition with high mortality even with modern therapeutic alternatives. To identify molecular determinant

Impella versus extracorporal life support in cardiogenic shock: a propensity score adjusted analysis

Aims: The mortality in cardiogenic shock (CS) is high. The role of specific mechanical circulatory support (MCS) systems is unclear. We aimed to compare patients receiving Impella versus ECLS (extracorporal life support) with regard to baseline characteristics, feasibility, and outcomes in CS. Methods and results: This is a retrospective cohort study including CS patients over 18 years with a complete follow-up of the primary endpoint and available baseline lactate level, receiving haemodynamic support either by Impella 2.5 or ECLS from two European registries. The decision for device implementation was made at the discretion of the treating physician. The primary endpoint of this study was all-cause mortality at 30 days. A propensity score for the use of Impella was calculated, and multivariable logistic regression was used to obtain adjusted odds ratios (aOR). In total, 149 patients were included, receiving either Impella (n = 73) or ECLS (n = 76) for CS. The feasibility of device implantation was high (87%) and similar (aOR: 3.14; 95% CI: 0.18–56.50; P = 0.41) with both systems. The rates of vascular injuries (aOR: 0.95; 95% CI: 0.10–3.50; P = 0.56) and bleedings requiring transfusions (aOR: 0.44; 95% CI: 0.09–2.10; P = 0.29) were similar in ECLS patients and Impella patients. The use of Impella or ECLS was not associated with increased odds of mortality (aOR: 4.19; 95% CI: 0.53–33.25; P = 0.17), after correction for propensity score and baseline lactate level. Baseline lactate level was independently associated with increased odds of 30 day mortality (per mmol/L increase; OR: 1.29; 95% CI: 1.14–1.45; P < 0.001). Conclusions: In CS patients, the adjusted mortality rates of both ECLS and Impella were high and similar. The baseline lactate level was a potent predictor of mortality and could play a role in patient selection for therapy in future studies. In patients with profound CS, the type of device is likely to be less important compared with other parameters including non-cardiac and neurological factors

Genetic Interactions with Age, Sex, Body Mass Index, and Hypertension in Relation to Atrial Fibrillation: The AFGen Consortium

It is unclear whether genetic markers interact with risk factors to influence atrial fibrillation (AF) risk. We performed genome-wide interaction analyses between genetic variants and age, sex, hypertension, and body mass index in the AFGen Consortium. Study-specific results were combined using meta-analysis (88,383 individuals of European descent, including 7,292 with AF). Variants with nominal interaction associations in the discovery analysis were tested for association in four independent studies (131,441 individuals, including 5,722 with AF). In the discovery analysis, the AF risk associated with the minor rs6817105 allele (at the PITX2 locus) was greater among subjects ≤ 65 years of age than among those > 65 years (interaction p-value = 4.0 × 10-5). The interaction p-value exceeded genome-wide significance in combined discovery and replication analyses (interaction p-value = 1.7 × 10-8). We observed one genome-wide significant interaction with body mass index and several suggestive interactions with age, sex, and body mass index in the discovery analysis. However, none was replicated in the independent sample. Our findings suggest that the pathogenesis of AF may differ according to age in individuals of European descent, but we did not observe evidence of statistically significant genetic interactions with sex, body mass index, or hypertension on AF risk