Harringtonknox1614

Respiratory motion-corrected coronary MR angiography (CMRA) has shown promise for assessing coronary disease. By incorporating coronal 2D image navigators (iNAVs), respiratory motion can be corrected for in a beat-to-beat basis using translational correction in the foot-head (FH) and right-left (RL) directions and in a bin-to-bin basis using non-rigid motion correction addressing the remaining FH, RL and anterior-posterior (AP) motion. However, with this approach beat-to-beat AP motion is not corrected for. In this work we investigate the effect of remaining beat-to-beat AP motion and propose a virtual 3D iNAV that exploits autofocus motion correction to enable beat-to-beat AP and improved RL intra-bin motion correction.

Free-breathing 3D whole-heart CMRA was acquired using a 3-fold undersampled variable-density Cartesian trajectory. Beat-to-beat 3D translational respiratory motion was estimated from the 2D iNAVs in FH and RL directions, and in AP direction with autofocus assuming a linear relationship beesidual AP motion, however the level of improvement was subject-dependent.Total intracranial volume (TICV) and posterior fossa volume (PFV) are essential covariates for brain volumetric analyses with structural magnetic resonance imaging (MRI). Detailed whole brain segmentation provides a non-invasive way to measure brain regions. Furthermore, increasing neuroimaging data are distributed in a skull-stripped manner for privacy protection. Therefore, generalizing deep learning brain segmentation for skull removal and intracranial measurements is an appealing task. However, data availability is challenging due to a limited set of manually traced atlases with whole brain and TICV/PFV labels. In this paper, we employ U-Net tiles to achieve automatic TICV estimation and whole brain segmentation simultaneously on brains w/and w/o the skull. To overcome the scarcity of manually traced whole brain volumes, a transfer learning method is introduced to estimate additional TICV and PFV labels during whole brain segmentation in T1-weighted MRI. Specifically, U-Net tiles are first pre-trained using large-scale BrainCOLOR atlases without TICV and PFV labels, which are created by multi-atlas segmentation. Then the pre-trained models are refined by training the additional TICV and PFV labels using limited BrainCOLOR atlases. We also extend our method to handle skull-stripped brain MR images. From the results, our method provides promising whole brain segmentation and volume estimation results for both brains w/and w/o skull in terms of mean Dice similarity coefficients and mean surface distance and absolute volume similarity. This method has been made available in open source (https//github.com/MASILab/SLANTbrainSeg_skullstripped).

Previous studies have demonstrated that BOLD signals in gray matter in resting-state functional MRI (RSfMRI) have variable time lags, representing apparent propagations of fMRI BOLD signals in gray matter. We complemented existing findings and explored the corresponding variations of signal latencies in white matter.

We used data from the Brain Genomics Superstruct Project, consisting of 1412 subjects (both sexes included) and divided the dataset into ten equal groups to study both the patterns and reproducibility of latency estimates within white matter. We constructed latency matrices by computing cross-covariances between voxel pairs. We also applied a clustering analysis to identify functional networks within white matter, based on which latency analysis was also performed to investigate lead/lag relationship at network level. A dataset consisting of various sensory states (eyes closed, eyes open and eyes open with fixation) was also included to examine the relationship between latency structure and different states.

Projections of voxel latencies from the latency matrices were highly correlated (average Pearson correlation coefficient=0.89) across the subgroups, confirming the reproducibility and structure of signal lags in white matter. Analysis of latencies within and between networks revealed a similar pattern of inter- and intra-network communication to that reported for gray matter. Lithocholic acid Moreover, a dominant direction, from inferior to superior regions, of BOLD signal propagation was revealed by higher resolution clustering. The variations of lag structure within white matter are associated with different sensory states.

These findings provide additional insight into the character and roles of white matter BOLD signals in brain functions.

These findings provide additional insight into the character and roles of white matter BOLD signals in brain functions.

Diffusion-weighted imaging (DWI) is a valuable tool for routine imaging of the pediatric brain. However, the commonly used single-shot (ss) echo-planar imaging (EPI) DWI sequence is prone to geometric distortions and T

*-blurring. This study aimed to investigate in a pediatric population the benefits of using multiplexed sensitivity-encoding (MUSE) without and with reversed polarity gradients (RPG) instead.

This retrospective study compared image quality, geometric distortions, and diffusion values between three different approaches for DWI (ssEPI, MUSE, and RPG-MUSE) in 14 patients (median age=4 (0.6-15) years, 11 males). Distortion levels were quantified and compared in two brain regions, i.e., the brain stem and the temporal lobes, using the Dice Coefficient and the Hausdorff Distance, with T

-weighted images as reference. Expected geometrical distortion was further evaluated by comparing the effective echo spacing between the DWI sequences. Apparent diffusion coefficient (ADC) values were determined in the genu of the corpus callosum and the optic nerves. Two raters graded overall image quality and image distortions on a Likert scale.

Distortion levels assessed with Dice coefficient and Hausdorff distance were significantly lower for MUSE (p<0.05) and RPG-MUSE (p<0.01) compared to ssEPI. No significant difference in ADC values was observed between methods. The RPG-MUSE method was graded by one rater as significantly higher in overall image quality than ssEPI (p<0.05) and by both raters as significantly lower in levels of image distortions than both MUSE (p<0.05) and ssEPI (p<0.05). These results were in agreement with the reduced effective echo spacing was that was attained with MUSE and RPG-MUSE.

For imaging of the pediatric brain, MUSE and even more so RPG-MUSE offers both improved geometric fidelity and image quality compared to ssEPI.

For imaging of the pediatric brain, MUSE and even more so RPG-MUSE offers both improved geometric fidelity and image quality compared to ssEPI.

Nonalbuminuric diabetic kidney disease (DKD) has become the prevailing DKD phenotype. We compared the risks of adverse outcomes among patients with this phenotype compared with other DKD phenotypes.

Multicenter prospective cohort study.

19,025 Chinese adults with type 2 diabetes enrolled in the Hong Kong Diabetes Biobank.

DKD phenotypes defined by baseline estimated glomerular filtration rate (eGFR) and albuminuria no DKD (no decreased eGFR or albuminuria), albuminuria without decreased eGFR, decreased eGFR without albuminuria, and albuminuria with decreased eGFR.

All-cause mortality, cardiovascular disease (CVD) events, hospitalization for heart failure (HF), and chronic kidney disease (CKD) progression (incident kidney failure or sustained eGFR reduction≥40%).

Multivariable Cox proportional or cause-specific hazards models to estimate the relative risks of death, CVD, hospitalization for HF, and CKD progression. Multiple imputation was used for missing covariates.

Mean participant age was 61.1eline eGFR.

Nonalbuminuric DKD was associated with higher risks of hospitalization for HF and of CKD progression than no DKD, regardless of baseline eGFR.Kidney fibrosis is a hallmark of chronic kidney disease (CKD) and a potential therapeutic target. However, there are conceptual and practical challenges to directly targeting kidney fibrosis. Whether fibrosis is mainly a cause or a consequence of CKD progression has been disputed. It is unclear whether specifically targeting fibrosis is feasible in clinical practice because most drugs that decrease fibrosis in preclinical models target additional and often multiple pathogenic pathways (eg, renin-angiotensin-aldosterone system blockade). Moreover, tools to assess whole-kidney fibrosis in routine clinical practice are lacking. Pirfenidone, a drug used for idiopathic pulmonary fibrosis, is undergoing a phase 2 trial for kidney fibrosis. Other drugs in use or being tested for idiopathic pulmonary fibrosis (eg, nintedanib, PRM-151, epigallocatechin gallate) are also potential candidates to treat kidney fibrosis. link2 Novel therapeutic approaches may include antagomirs (eg, lademirsen) or drugs targeting interleukin 11 or NKD2 (WNT signaling pathway inhibitor). Reversing the dysfunctional tubular cell metabolism that leads to kidney fibrosis offers additional therapeutic opportunities. However, any future drug targeting fibrosis of the kidneys should demonstrate added benefit to a standard of care that combines renin-angiotensin system with mineralocorticoid receptor (eg, finerenone) blockade or with sodium/glucose cotransporter 2 inhibitors.Individuals of South Asian (SA) ancestry are predisposed to a higher risk of atherosclerotic cardiovascular disease (ASCVD). Coronary artery calcium (CAC) volume and density can identify coronary plaque characteristics unique to SA that may provide important prognostic information to identify high risk individuals beyond traditional CAC scores. We used data from the Mediators of Atherosclerosis in South Asians Living in America (MASALA). CAC density and volume were assessed according to established protocols. ASCVD risk was estimated using the pooled cohort equations (PCE). Multivariable-adjusted linear regression models were used to study the association between the PCE and advanced CAC measures, and between cardiovascular risk factors and CAC density and volume. Our analyses included 1,155 participants (mean age 57 (SD 9) years, 52% men) with information on advanced CAC measures. After multivariable-adjustment, the PCE was associated with both CAC density (β 0.24, 95% CI 0.12,0.35) and CAC volume (β 0.43, 95% CI 0.38,0.48). High-density lipoprotein cholesterol was directly associated with CAC density while waist circumference was inversely associated with it. Body mass index, hypertension status, statin use, diabetes, and HOMA-IR were all directly associated with CAC volume. Estimated ASCVD risk was associated with both CAC volume and density. link3 Different cardiometabolic risk factors are associated with CAC density and volume. Future longitudinal studies are required to demonstrate the interrelationship of advanced CAC measures and cardiovascular risk factors with incident ASCVD outcomes.Several Apocynaceae species, most notably Tabernanthe iboga, Voacanga africana and many Tabernaemontana species, produce ibogan-type alkaloids. Although a large amount of information exists about the Tabernaemontana genus, knowledge concerning chemistry and biological activity remains lacking for several species, especially related to their effects on the central nervous system (CNS). The aim of this study was to evaluate the effect of Tabernaemontana arborea Rose ex J.D.Sm. (T. arborea) hydroalcoholic extract (30, 56.2 and 100 mg/kg, i.p.) and two of its main alkaloids (ibogaine and voacangine, 30 mg/kg, i.p.) on electroencephalographic (EEG) activity alone and in the presence of the chemical convulsant agent pentylenetetrazole (PTZ, 85 mg/kg, i.p.) in mice. EEG spectral power analysis showed that T. arborea extract (56.2 and 100 mg/kg) and ibogaine (30 mg/kg, i.p.) promoted a significant increase in the relative power of the delta band and a significant reduction in alpha band values, denoting a CNS depressant effect.