The effect of iterative model reconstruction on coronary artery calcium quantification

Coronary artery calcium (CAC) scoring with computed tomography (CT) is an established tool for quantifying calcified atherosclerotic plaque burden. Despite the widespread use of novel image reconstruction techniques in CT, the effect of iterative model reconstruction on CAC score remains unclear. We sought to assess the impact of iterative model based reconstruction (IMR) on coronary artery calcium quantification as compared to the standard filtered back projection (FBP) algorithm and hybrid iterative reconstruction (HIR). In addition, we aimed to simulate the impact of iterative reconstruction techniques on calcium scoring based risk stratification of a larger asymptomatic population. We studied 63 individuals who underwent CAC scoring. Images were reconstructed with FBP, HIR and IMR and CAC scores were measured. We estimated the cardiovascular risk reclassification rate of IMR versus HIR and FBP in a larger asymptomatic population (n = 504). The median CAC scores were 147.7 (IQR 9.6-582.9), 107.0 (IQR 5.9-526.6) and 115.1 (IQR 9.3-508.3) for FBP, HIR and IMR, respectively. The HIR and IMR resulted in lower CAC scores as compared to FBP (both p < 0.001), however there was no difference between HIR and IMR (p = 0.855). The CAC score decreased by 7.2 % in HIR and 7.3 % in IMR as compared to FBP, resulting in a risk reclassification rate of 2.4 % for both HIR and IMR. The utilization of IMR for CAC scoring reduces the measured calcium quantity. However, the CAC score based risk stratification demonstrated modest reclassification in IMR and HIR versus FBP

Minimum Information about a Biosynthetic Gene cluster

A wide variety of enzymatic pathways that produce specialized metabolites in bacteria, fungi and plants are known to be encoded in biosynthetic gene clusters. Information about these clusters, pathways and metabolites is currently dispersed throughout the literature, making it difficult to exploit. To facilitate consistent and systematic deposition and retrieval of data on biosynthetic gene clusters, we propose the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard.Chemistry and Chemical Biolog

Additive value of semiautomated quantification of coronary artery disease using cardiac computed tomographic angiography to predict future acute coronary syndrome

The purpose of this study was to investigate whether the use of a semiautomated plaque quantification algorithm (reporting volumetric and geometric plaque properties) provides additional prognostic value for the development of acute coronary syndromes (ACS) as compared with conventional reading from cardiac computed tomography angiography (CCTA). CCTA enables the visualization of coronary plaque characteristics, of which some have been shown to predict ACS. A total of 1,650 patients underwent 64-slice CCTA and were followed up for ACS for a mean 26 ± 10 months. In 25 patients who had ACS and 101 random controls (selected from 993 patients with coronary artery disease but without coronary event), coronary artery disease was evaluated using conventional reading (calcium score, luminal stenosis, morphology), and then independently quantified using semiautomated software (plaque volume, burden area [plaque area divided by vessel area times 100%], noncalcified percentage, attenuation, remodeling). Clinical risk profile was calculated with Framingham risk score (FRS). There were no significant differences in conventional reading parameters between controls and patients who had ACS. Semiautomated plaque quantification showed that compared to controls, ACS patients had higher total plaque volume (median: 94 mm(3) vs. 29 mm(3)) and total noncalcified volume (28 mm(3) vs. 4 mm(3), p ≤ 0.001 for both). In addition, per-plaque maximal volume (median: 56 mm(3) vs. 24 mm(3)), noncalcified percentage (62% vs. 26%), and plaque burden (57% vs. 36%) in ACS patients were significantly higher (p <0.01 for all). A receiver-operating characteristic model predicting for ACS incorporating FRS and conventional CCTA reading had an area under the curve of 0.64; a second model also incorporating semiautomated plaque quantification had an area under the curve of 0.79 (p <0.05). The semiautomated plaque quantification algorithm identified several parameters predictive for ACS and provided incremental prognostic value over clinical risk profile and conventional CT reading. The application of this tool may improve risk stratification in patients undergoing CCT

Predicting the presence of macrovascular causes in non-traumatic intracerebral haemorrhage: The DIAGRAM prediction score

Objective: A substantial part of non-traumatic intracerebral haemorrhages (ICH) arises from a macrovascular cause, but there is little guidance on selection of patients for additional diagnostic work-up. We aimed to develop and externally validate a model for predicting the probability of a macrovascular cause in patients with non-traumatic ICH. Methods: The DIagnostic AngioGRAphy to find vascular Malformations (DIAGRAM) study (n=298; 69 macrovascular cause; 23%) is a prospective, multicentre study assessing yield and accuracy of CT angiography (CTA), MRI/magnetic resonance angiography (MRA) and intra-arterial catheter angiography in diagnosing macrovascular causes in patients with non-traumatic ICH. We considered prespecified patient and ICH characteristics in multivariable logistic regression analyses as predictors for a macrovascular cause. We combined independent predictors in a model, which we validated in an external cohort of 173 patients with ICH (78 macrovascular cause, 45%). Results: Independent predictors were younger age, lobar or posterior fossa (vs deep) location of ICH, and absence of small vessel disease (SVD). A model that combined these predictors showed good performance in the development data (c-statistic 0.83; 95% C I 0.78 to 0.88) and moderate performance in external validation (c-statistic 0.66; 95% CI 0.58 to 0.74). When CTA results were added, the c-statistic was excellent (0.91; 95% CI 0.88 to 0.94) and good after external validation (0.88; 95% CI 0.83 to 0.94). Predicted probabilities varied from 1% in patients aged 51-70 years with deep ICH and SVD, to more than 50% in patients aged 18-50 years with lobar or posterior fossa ICH without SVD. Conclusion: The DIAGRAM scores help to predict the probability of a macrovascular cause in patients with nontraumatic ICH based on age, ICH location, SVD and CTA

Minimum Information about a Biosynthetic Gene cluster

© 2015 Nature America, Inc. All rights reserved. A wide variety of enzymatic pathways that produce specialized metabolites in bacteria, fungi and plants are known to be encoded in biosynthetic gene clusters. Information about these clusters, pathways and metabolites is currently dispersed throughout the literature, making it difficult to exploit. To facilitate consistent and systematic deposition and retrieval of data on biosynthetic gene clusters, we propose the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard

Search for intermediate-mass black hole binaries in the third observing run of Advanced LIGO and Advanced Virgo

International audienceIntermediate-mass black holes (IMBHs) span the approximate mass range 100−105 M⊙, between black holes (BHs) that formed by stellar collapse and the supermassive BHs at the centers of galaxies. Mergers of IMBH binaries are the most energetic gravitational-wave sources accessible by the terrestrial detector network. Searches of the first two observing runs of Advanced LIGO and Advanced Virgo did not yield any significant IMBH binary signals. In the third observing run (O3), the increased network sensitivity enabled the detection of GW190521, a signal consistent with a binary merger of mass ∼150 M⊙ providing direct evidence of IMBH formation. Here, we report on a dedicated search of O3 data for further IMBH binary mergers, combining both modeled (matched filter) and model-independent search methods. We find some marginal candidates, but none are sufficiently significant to indicate detection of further IMBH mergers. We quantify the sensitivity of the individual search methods and of the combined search using a suite of IMBH binary signals obtained via numerical relativity, including the effects of spins misaligned with the binary orbital axis, and present the resulting upper limits on astrophysical merger rates. Our most stringent limit is for equal mass and aligned spin BH binary of total mass 200 M⊙ and effective aligned spin 0.8 at 0.056 Gpc−3 yr−1 (90% confidence), a factor of 3.5 more constraining than previous LIGO-Virgo limits. We also update the estimated rate of mergers similar to GW190521 to 0.08 Gpc−3 yr−1.Key words: gravitational waves / stars: black holes / black hole physicsCorresponding author: W. Del Pozzo, e-mail: [email protected]† Deceased, August 2020

Open data from the first and second observing runs of Advanced LIGO and Advanced Virgo

Advanced LIGO and Advanced Virgo are monitoring the sky and collecting gravitational-wave strain data with sufficient sensitivity to detect signals routinely. In this paper we describe the data recorded by these instruments during their first and second observing runs. The main data products are gravitational-wave strain time series sampled at 16384 Hz. The datasets that include this strain measurement can be freely accessed through the Gravitational Wave Open Science Center at http://gw-openscience.org, together with data-quality information essential for the analysis of LIGO and Virgo data, documentation, tutorials, and supporting software