Search

Abstract Measurements of frequency offset are commonly required in MRI. The standard method measures the signal phase as a function of evolution time. Here we use a single shot turbo-spin-echo acquisition method to measure frequency offset at a single evolution time. After excitation the transverse magnetisation evolves during the evolution time, and is then repeatedly refocused. The phase is conjugated between alternate echoes. Using partial parallel acquisition techniques we obtain separate odd- and even- echo images. An iterative procedure ensures self-consistency between them. The difference in phase between the two images yields frequency offset maps. The technique was implemented at 3 Tesla and tested on a healthy human volunteer for a range of evolution times between 6 and 42 ms. A standard method using a similar readout train and multiple evolution times was used as a gold-standard measure. In a statistical comparison with the gold standard no evidence for bias or offset was found. There was no systematic variation in precision or accuracy as a function of evolution time. We conclude that the presented approach represents a viable method for the rapid generation of frequency offset maps with a high image quality and minimal distortion.

In this study, we optimized the variable flip angle (VFA) acquisition scheme using numerical simulations to shorten the acquisition time of multicompartment relaxometry for myelin water imaging (MCR-MWI) to a clinically practical range in the absence of advanced image reconstruction methods. As the primary objective of this study, the test-retest repeatability of myelin water fraction (MWF) measurements of MCR-MWI is evaluated on three gradient echo (GRE) sequence settings using the optimized VFA schemes with different echo times and repetition times, emulating various scanner setups. The cross-protocol reproducibility of MCR-MWI and MCR with diffusion-informed myelin water imaging (MCR-DIMWI) is also examined. As a secondary objective, we explore the bundle-specific profiles of various microstructural parameters from MCR-(DI)MWI and their cross-correlations to determine if these parameters possess supplementary microstructure information beyond myelin concentration.Numerical simulations indicate that MCR-MWI can be performed with a minimum of three flip angles covering a wide range of T1 weightings without adding significant bias. This is supported by the results of an in vivo experiment, allowing whole-brain 1.5 mm isotropic MWF maps to be acquired in 9 min, reducing the total scan time to 40% of the original implementation without significant quality degradation. Good test-retest repeatability is observed for MCR-MWI for all three GRE protocols. While good correlations can also be found in MWF across protocols, systematic differences are observed. Bundle-specific MWF analysis reveals that certain white matter bundles are similar in all participants. We also found that microstructure relaxation parameters have low linear correlations with MWF. MCR-MWI is a reproducible measure of myelin. However, attention should be paid to the protocol related MWF differences when comparing different studies, as the MWF bias up to 0.5% can be observed across the protocols examined in this work.

Ion-solid interactions are governed by a range of complex processes the direct experimental observation of which pose their own set of challenges. Here, the authors present a joint experimental and first-principles approach to study and describe the underlying mechanism of electron capture for an ion travelling through layers of graphene with monolayer precision.

Abstract Layer specific functional MRI requires high spatial resolution data. To compensate the associated poor signal to noise ratio it is common to integrate the signal from voxels at a given cortical depth. If the region is sufficiently large then physiological noise will be the dominant noise source. In this work, activation profiles in response to the same visual stimulus are compared at 1.5 T, 3 T and 7 T using a multi-echo, gradient echo (GE) FLASH sequence, with a 0.75 mm isotropic voxel size and the cortical integration approach. The results show that after integrating over a cortical volume of 40, 60 and 100 mm3 (at 7 T, 3 T, and 1.5 T, respectively), the signal is in the physiological noise dominated regime. The activation profiles obtained are similar for equivalent echo times. BOLD-like noise is found to be the dominant source of physiological noise. Consequently, the functional contrast to noise ratio is not strongly echo-time or field-strength dependent. We conclude that laminar GE-BOLD fMRI at lower field strengths is feasible but that larger patches of cortex will need to be examined, and that the acquisition efficiency is reduced.

Multi-echo gradient echo (ME-GRE) magnetic resonance signal evolution in white matter has a strong dependence on the orientation of myelinated axons with respect to the main static field. Although analytical solutions have been able to predict some of the white matter (WM) signal behaviour of the hollow cylinder model, it has been shown that realistic models of WM offer a better description of the signal behaviour observed.In this work, we present a pipeline to (i) generate realistic 2D WM models with their microstructure based on real axon morphology with adjustable fiber volume fraction (FVF) and g-ratio. We (ii) simulate their interaction with the static magnetic field to be able to simulate their MR signal. For the first time, we (iii) demonstrate that realistic 2D WM models can be used to simulate a MR signal that provides a good approximation of the signal obtained from a real 3D WM model derived from electron microscopy. We then (iv) demonstrate in silico that 2D WM models can be used to predict microstructural parameters in a robust way if ME-GRE multi-orientation data is available and the main fiber orientation in each pixel is known using DTI. A deep learning network was trained and characterized in its ability to recover the desired microstructural parameters such as FVF, g-ratio, free and bound water transverse relaxation and magnetic susceptibility. Finally, the network was trained to recover these micro-structural parameters from an ex vivo dataset acquired in 9 orientations with respect to the magnetic field and 12 echo times. We demonstrate that this is an overdetermined problem and that as few as 3 orientations can already provide comparable results for some of the decoded metrics.

Myelin water imaging techniques based on multi-compartment relaxometry have been developed as an important tool to measure myelin concentration in vivo, but are limited by the long scan time of multi-contrast multi-echo acquisition. In this work, a fast imaging technique, termed variable flip angle Echo Planar Time-Resolved Imaging (vFA-EPTI), is developed to acquire multi-echo and multi-flip-angle gradient-echo data with significantly reduced acquisition time, providing rich information for multi-compartment analysis of gradient-echo myelin water imaging (GRE-MWI). The proposed vFA-EPTI method achieved 26 folds acceleration with good accuracy by utilizing an efficient continuous readout, optimized spatiotemporal encoding across echoes and flip angles, as well as a joint subspace reconstruction. An approach to estimate off-resonance field changes between different flip-angle acquisitions was also developed to ensure high-quality joint reconstruction across flip angles. The accuracy of myelin water fraction (MWF) estimate under high acceleration was first validated by a retrospective undersampling experiment using a lengthy fully-sampled data as reference. Prospective experiments were then performed where whole-brain MWF and multi-compartment quantitative maps were obtained in 5 min at 1.5 mm isotropic resolution and 24 min at 1 mm isotropic resolution at 3T. Additionally, ultra-high resolution data at 600 µm isotropic resolution were acquired at 7T, which show detailed structures within the cortex such as the line of Gennari, demonstrating the ability of the proposed method for submillimeter GRE-MWI that can be used to study cortical myeloarchitecture in vivo.

Quantitative susceptibility mapping (QSM) is a physics-driven computational technique that has a high sensitivity in quantifying iron deposition based on MRI phase images. Furthermore, it has a unique ability to distinguish paramagnetic and diamagnetic contributions such as haemorrhage and calcification based on image contrast. These properties have contributed to a growing interest to use QSM not only in research but also in clinical applications. However, it is challenging to obtain high quality susceptibility map because of its ill-posed nature, especially for researchers who have less experience with QSM and the optimisation of its pipeline. In this paper, we present an open-source processing pipeline tool called SuscEptibility mapping PIpeline tool for phAse images (SEPIA) dedicated to the post-processing of MRI phase images and QSM. SEPIA connects various QSM toolboxes freely available in the field to offer greater flexibility in QSM processing. It also provides an interactive graphical user interface to construct and execute a QSM processing pipeline, simplifying the workflow in QSM research. The extendable design of SEPIA also allows developers to deploy their methods in the framework, providing a platform for developers and researchers to share and utilise the state-of-the-art methods in QSM.

The endeavor to understand the human brain has seen more progress in the last few decades than in the previous two millennia. Still, our understanding of how the human brain relates to behavior in the real world and how this link is modulated by biological, social, and environmental factors is limited. To address this, we designed the Healthy Brain Study (HBS), an interdisciplinary, longitudinal, cohort study based on multidimensional, dynamic assessments in both the laboratory and the real world. Here, we describe the rationale and design of the currently ongoing HBS. The HBS is examining a population-based sample of 1,000 healthy participants (age 30-39) who are thoroughly studied across an entire year. Data are collected through cognitive, affective, behavioral, and physiological testing, neuroimaging, bio-sampling, questionnaires, ecological momentary assessment, and real-world assessments using wearable devices. These data will become an accessible resource for the scientific community enabling the next step in understanding the human brain and how it dynamically and individually operates in its bio-social context. An access procedure to the collected data and bio-samples is in place and published on https://www.healthybrainstudy.nl/en/data-and-methods/access. Trail registration: https://www.trialregister.nl/trial/7955.

Myelin water fraction (MWF) mapping based on data fitting of a 3-pool exponential model of multi-echo gradient echo (mGRE) data using MRI shows great promises for in vivo myelin quantification. However, this multi-exponential fitting is ill-conditioned because of the similar relaxation times and frequency shifts of the various compartments. Additionally, the bound water residing in the myelin sheath of white matter is expected to have a faster longitudinal magnetisation recovery than that of the free water in the intra-axonal and extra-axonal space. When the Ernst angle is used to achieve maximum SNR and improve fitting, this will introduce a T1-weighting effect to the derived MWF. In this study, we first demonstrate that diffusion-weighted imaging can be used to infer the compartmental signal properties using an analytical fibre model to achieve a robust MWF estimation. Second, we show that by incorporating a variable flip angle scheme to the mGRE acquisition with a multi-compartment relaxometry model, not only the MWF is corrected from the T1 dependency but also the fitting procedure becomes less ill-conditioned and more SNR efficient. Finally, we demonstrate these two approaches can be combined to allow higher spatial resolution MWF maps than what has been reported to date with robust MWF estimation on a small cohort.

The detection of gravitational waves and electromagnetic signals from the neutron star merger GW170817 has provided evidence that these astrophysical events are sites where the r-process nucleosynthesis operates. The electromagnetic signal, commonly known as kilonova, is powered by the radioactive decay of freshly synthesized nuclei. However, its luminosity, colour and spectra depend on the atomic opacities of the produced elements. In particular, opacities of lanthanides and actinides elements, due to their large density of bound–bound transitions, are fundamental. The current work focuses on atomic structure calculations for lanthanide and actinide ions, which are important in kilonovae modelling of ejecta spectra. Calculations for Nd III and U III, two representative rare-earth ions, were achieved. Our aim is to provide valuable insights for future opacity calculations for all heavy elements. We noticed that the opacity of U III is about an order of magnitude greater than the opacity of Nd III due to a higher density of levels in the case of the actinide.

These imaging data are examples of sub-millimeter resolution T1-weighted EPI (Echo Planar Imaging) acquired using the T123DEPI (T1-imaging with 2 3D-EPIs) sequence [1]; functional MRI data with matching resolution and distortion, and MP2RAGE (Magnetization Prepared 2 Rapid Acquisition Gradient Echoes) anatomical images [2], from the same subjects. Data from two protocols and subjects presented in the paper describing the sequence [1] are made available here: 1) 0.8 mm protocol: whole brain, axial T123DEPI T1-weighted images; a 5-minute fMRI run with the same orientation and 27 mm coverage in the slice selection direction, covering the primary visual cortex. fMRI data were acquired while the volunteer viewed a flashing checkerboard stimulus; the unsmoothed GLM results of the fMRI and a 0.64 mm resolution MP2RAGE from the same subject. These data are from Experiment 3 in [1] 2) 0.7 mm protocol: partial brain T123DEPI T1-weighted images with longer or shorter readouts; matching coronal echo planar images again acquired while viewing a flashing checkerboard stimulus and a 0.64 mm whole brain MP2RAGE from the same subject. These data are from Experiment 1 in [1]

We present relativistic ab initio calculations of fundamental parameters for atomic selenium, based on the Multiconfiguration Dirac-Fock method. In detail, fluorescence yields and subshell linewidths, both of K shell, as well as Kβ to Kα intensity ratio are provided, showing overall agreement with previous theoretical calculations and experimental values. Relative intensities were evaluated assuming the same ionization cross-section for the K-shell hole states, leading to a statistical distribution of these initial states. A method for estimating theoretical linewidths of X-ray lines, where the lines are composed by a multiplet of fine-structure levels that are spread in energy, is proposed. This method provides results that are closer to Kα1,2 experimental width values than the usual method, although slightly higher discrepancies occur for the Kβ1,3 lines. This indicates some inaccuracies in the calculation of Auger rates that have a higher contribution for partial linewidths of the subshells involved in the Kβ1,3 profile. Apart from this, the calculated value of Kβ to Kα intensity ratio, which is less sensitive to Auger rates issues, is in excellent agreement with recommended values.

ObjectiveQuantitative and semi-quantitative MRI (qMRI) metrics provide complementary specificity and differential sensitivity to pathological brain changes compatible with brain inflammation, degeneration, and repair. Moreover, advanced magnetic resonance imaging (MRI) metrics with overlapping elements amplify the true tissue-related information and limit measurement noise. In this work, we combined multiple advanced MRI parameters to assess focal and diffuse brain changes over 2 years in a group of early-stage relapsing-remitting MS patients.MethodsThirty relapsing-remitting MS patients with less than 5 years disease duration and nine healthy subjects underwent 3T MRI at baseline and after 2 years including T1, T2, T2* relaxometry, and magnetization transfer imaging. To assess longitudinal changes in normal-appearing (NA) tissue and lesions, we used analyses of variance and Bonferroni correction for multiple comparisons. Multivariate linear regression was used to assess the correlation between clinical outcome and multiparametric MRI changes in lesions and NA tissue.ResultsIn patients, we measured a significant longitudinal decrease of mean T2 relaxation times in NA white matter (p = 0.005) and a decrease of T1 relaxation times in the pallidum (p 0.4, p

COVID-19 pandemic impacted the world dramatically and how communities and societies behaved. The purpose of this study was to explore lecturers' perspectives on emergency remote teaching, not only from technology-prone lecturers but encompassing contributions from disparate academic fields, which brought assorted experiences into the data. The qualitative study analyses the perspectives of 344 lecturers from 35 higher education institutions in Portugal instigated by the COVID-19 outbreak. The thematic analysis revealed three themes related to the advantages and disadvantages: the lecturing process, learning process, and life and society. Regarding the concerns, four themes emerged: learning process, self-regulation and compromising the future, resources, the assessment process, and well-being. Finally, solutions encompass three themes: pedagogy and innovation, normative framework, and digital literacy. With a special focus on the solutions, all these themes contribute to designing the structure of a training program for the 21st-century higher education lecturer, emphasizing the digital domain. The themes cluster in digital-based innovative pedagogies (mastering digital education software, active pedagogies for digital environments, lecturer posture in digital environments, "for-digital" studying material production, e-proctoring, and transferable competences besides the digital), and digital competences (transgenerational digital-base communication, webcam behavior, well-being in digital settings, and general digital competences).

This article investigates the applicability of Augmented Reality (AR) and Spatial Computing in hospital environments, exploring how these technologies can enhance interaction between patients and healthcare professionals as well as the efficiency of medical procedures. Through a systematic literature review using the PRISMA methodology, relevant articles highlighting the potential of these technologies in the hospital setting were selected and analysed. The results suggest a growing adoption of AR and Spatial Computing, driven by the advancement of 5G technology, with the potential to improve diagnostic accuracy, the effectiveness of surgical procedures, and the educational experience of healthcare professionals. The study concludes that the integration of these emerging technologies promises to transform hospital environments, emphasising the need to overcome technical, ethical, and privacy challenges to maximise their positive impact on health. [ABSTRACT FROM AUTHOR]