Magnetic resonance imaging phantoms for quality-control of myocardial T1 and ECV mapping: specific formulation, long-term stability and variation with heart rate and temperature

Background: Magnetic resonance imaging (MRI) phantoms are routinely used for quality assurance in MRI centres; however their long term stability for verification of myocardial T1/ extracellular volume fraction (ECV) mapping has never been investigated. Methods: Nickel-chloride agarose gel phantoms were formulated in a reproducible laboratory procedure to mimic blood and myocardial T1 and T2 values, native and late after Gadolinium administration as used in T1/ECV mapping. The phantoms were imaged weekly with an 11 heart beat MOLLI sequence for T1 and long TR spin-echo sequences for T2, in a carefully controlled reproducible manner for 12 months. Results: There were only small relative changes seen in all the native and post gadolinium T1 values (up to 9.0 % maximal relative change in T1 values) or phantom ECV (up to 8.3 % maximal relative change of ECV, up to 2.2 % maximal absolute change in ECV) during this period. All native and post gadolinium T2 values remained stable over time with <2 % change. Temperature sensitivity testing showed MOLLI T1 values in the long T1 phantoms increasing by 23.9 ms per degree increase and short T1 phantoms increasing by 0.3 ms per degree increase. There was a small absolute increase in ECV of 0.069 % (~0.22 % relative increase in ECV) per degree increase. Variation in heart rate testing showed a 0.13 % absolute increase in ECV (~0.45 % relative increase in ECV) per 10 heart rate increase. Conclusions: These are the first phantoms reported in the literature modeling T1 and T2 values for blood and myocardium specifically for the T1mapping/ECV mapping application, with stability tested rigorously over a 12 month period. This work has significant implications for the utility of such phantoms in improving the accuracy of serial scans for myocardial tissue characterisation by T1 mapping methods and in multicentre work

In vivo hippocampal subfield volumes in bipolar disorder—A mega-analysis from The Enhancing Neuro Imaging Genetics through Meta-Analysis Bipolar Disorder Working Group

The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta‐Analysis Bipolar Disorder workinggroup, study hippocampal subfield volumetry in BD. T1‐weighted magnetic resonance imaging scans from 4,698 individuals (BD = 1,472, healthy controls [HC] = 3,226) from 23 sites worldwide were processed with FreeSurfer. We used linear mixed‐effects models and mega‐analysis to investigate differences in hippocampal subfield volumes between BD and HC, followed by analyses of clinical characteristics and medication use. BD showed significantly smaller volumes of the whole hippocampus (Cohen's d = −0.20), cornu ammonis (CA)1 (d = −0.18), CA2/3 (d = −0.11), CA4 (d = −0.19), molecular layer (d = −0.21), granule cell layer of dentate gyrus (d = −0.21), hippocampal tail (d = −0.10), subiculum (d = −0.15), presubiculum (d = −0.18), and hippocampal amygdala transition area (d = −0.17) compared to HC. Lithium users did not show volume differences compared to HC, while non‐users did. Antipsychotics or antiepileptic use was associated with smaller volumes. In this largest study of hippocampal subfields in BD to date, we show widespread reductions in nine of 12 subfields studied. The associations were modulated by medication use and specifically the lack of differences between lithium users and HC supports a possible protective role of lithium in BD

Using structural MRI to identify bipolar disorders - 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group

Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47–67.00, ROC-AUC = 71.49%, 95% CI = 69.39–73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70–60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen’s Kappa = 0.83, 95% CI = 0.829–0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data

Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals

Fronto-limbic white matter (WM) abnormalities are assumed to lie at the heart of the pathophysiology of bipolar disorder (BD); however, diffusion tensor imaging (DTI) studies have reported heterogeneous results and it is not clear how the clinical heterogeneity is related to the observed differences. This study aimed to identify WM abnormalities that differentiate patients with BD from healthy controls (HC) in the largest DTI dataset of patients with BD to date, collected via the ENIGMA network. We gathered individual tensor-derived regional metrics from 26 cohorts leading to a sample size of N = 3033 (1482 BD and 1551 HC). Mean fractional anisotropy (FA) from 43 regions of interest (ROI) and average whole-brain FA were entered into univariate mega- and meta-analyses to differentiate patients with BD from HC. Mega-analysis revealed significantly lower FA in patients with BD compared with HC in 29 regions, with the highest effect sizes observed within the corpus callosum (R2 = 0.041, Pcorr < 0.001) and cingulum (right: R2 = 0.041, left: R2 = 0.040, Pcorr < 0.001). Lithium medication, later onset and short disease duration were related to higher FA along multiple ROIs. Results of the meta-analysis showed similar effects. We demonstrated widespread WM abnormalities in BD and highlighted that altered WM connectivity within the corpus callosum and the cingulum are strongly associated with BD. These brain abnormalities could represent a biomarker for use in the diagnosis of BD. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org

CaMKIIδ post-translational modifications increase affinity for calmodulin inside cardiac ventricular myocytes

Persistent over-activation of CaMKII (Calcium/Calmodulin-dependent protein Kinase II) in the heart is implicated in arrhythmias, heart failure, pathological remodeling, and other cardiovascular diseases. Several post-translational modifications (PTMs)-including autophosphorylation, oxidation, S-nitrosylation, and O-GlcNAcylation-have been shown to trap CaMKII in an autonomously active state. The molecular mechanisms by which these PTMs regulate calmodulin (CaM) binding to CaMKIIδ-the primary cardiac isoform-has not been well-studied particularly in its native myocyte environment. Typically, CaMKII activates upon Ca-CaM binding during locally elevated [Ca]free and deactivates upon Ca-CaM dissociation when [Ca]free returns to basal levels. To assess the effects of CaMKIIδ PTMs on CaM binding, we developed a novel FRET (Förster resonance energy transfer) approach to directly measure CaM binding to and dissociation from CaMKIIδ in live cardiac myocytes. We demonstrate that autophosphorylation of CaMKIIδ increases affinity for CaM in its native environment and that this increase is dependent on [Ca]free. This leads to a 3-fold slowing of CaM dissociation from CaMKIIδ (time constant slows from ~0.5 to 1.5&nbsp;s) when [Ca]free is reduced with physiological kinetics. Moreover, oxidation further slows CaM dissociation from CaMKIIδ T287D (phosphomimetic) upon rapid [Ca]free chelation and increases FRET between CaM and CaMKIIδ T287A (phosphoresistant). The CaM dissociation kinetics-measured here in myocytes-are similar to the interval between heartbeats, and integrative memory would be expected as a function of heart rate. Furthermore, the PTM-induced slowing of dissociation between beats would greatly promote persistent CaMKIIδ activity in the heart. Together, these findings suggest a significant role of PTM-induced changes in CaMKIIδ affinity for CaM and memory under physiological and pathophysiological processes in the heart

Satisfaction with dental care among patients who receive invasive or non-invasive treatment for non-cavitated early dental caries: findings from one region of the National Dental PBRN

Abstract Background The objectives were to: (1) quantify patient satisfaction with treatment for early dental caries overall, and according to whether or not (2a) the patient received invasive treatment; (2b) was high-risk for dental caries, and had dental insurance; and (3) encourage practitioners to begin using non-invasive approaches to early caries management. Methods Ten practitioners recorded patient, lesion, and treatment information about non-cavitated early caries lesions. Information on 276 consecutive patients with complete data was included, who received either non-invasive (no dental restoration) or invasive (dental restoration) treatment. Patients completed a patient satisfaction questionnaire and were classified as dissatisfied if they did not “agree” or “strongly agree” with any of 14 satisfaction items. Results Patients had a mean (± SD) age of 41.8 (±15.8) years, 64% were female and 88% were white. Twenty-five percent (n = 68) were dissatisfied in at least one of the 14 satisfaction items. Satisfaction levels did not significantly vary by patient’s gender, race, caries risk category, or affected tooth surface location. Overall, 11% (28 of 276) received invasive treatment; satisfaction did not differ between patients who had invasive or non-invasive treatment. Seven patients received invasive treatment at their request even though that was not what their practitioner recommended; 5 out of 6 were satisfied with their treatment nonetheless. Conclusions About one-fourth of patients treated for non-cavitated early caries were dissatisfied with at least some aspect of their dental care experience. Satisfaction of patients who received invasive treatment did not differ from those who received non-invasive treatment

The GFDL Global Ocean and Sea Ice Model OM4.0: Model Description and Simulation Features

We document the configuration and emergent simulation features from the Geophysical Fluid Dynamics Laboratory (GFDL) OM4.0 ocean/sea ice model. OM4 serves as the ocean/sea ice component for the GFDL climate and Earth system models. It is also used for climate science research and is contributing to the Coupled Model Intercomparison Project version 6 Ocean Model Intercomparison Project. The ocean component of OM4 uses version 6 of the Modular Ocean Model and the sea ice component uses version 2 of the Sea Ice Simulator, which have identical horizontal grid layouts (Arakawa C-grid). We follow the Coordinated Ocean-sea ice Reference Experiments protocol to assess simulation quality across a broad suite of climate-relevant features. We present results from two versions differing by horizontal grid spacing and physical parameterizations: OM4p5 has nominal 0.5 degrees spacing and includes mesoscale eddy parameterizations and OM4p25 has nominal 0.25 degrees spacing with no mesoscale eddy parameterization. Modular Ocean Model version 6 makes use of a vertical Lagrangian-remap algorithm that enables general vertical coordinates. We show that use of a hybrid depth-isopycnal coordinate reduces the middepth ocean warming drift commonly found in pure z* vertical coordinate ocean models. To test the need for the mesoscale eddy parameterization used in OM4p5, we examine the results from a simulation that removes the eddy parameterization. The water mass structure and model drift are physically degraded relative to OM4p5, thus supporting the key role for a mesoscale closure at this resolution.National Oceanic and Atmospheric Administration, U.S. Department of CommerceNational Oceanic Atmospheric Admin (NOAA) - USA [NA14OAR4320106]; Carbon Mitigation Initiative (CMI) project at Princeton University - BP; Natural Sciences and Engineering Research Council of Canada (NSERC)Natural Sciences and Engineering Research Council of Canada [RGPIN-2018-04985]; National Science FoundationNational Science Foundation (NSF) [1536350]Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]