Identification of a by-product of nitric oxide synthase activity in human acute brain injury with in vivo proton magnetic resonance spectroscopy

BACKGROUND AND PURPOSE: Laboratory studies have been used to identify nitric oxide as a notable mediator in neuronal death after acute brain injury. To our knowledge, this has not previously been confirmed with in vivo study in humans. Our purpose was to seek in vivo evidence for the induction of nitric oxide synthase (NOS) in human acute brain injury by using proton MR spectroscopy.

METHODS: In vitro proton MR spectra were obtained in neural extracts from 30 human cadavers, and in vivo spectra were obtained in 20 patients with acute brain injury and in a similar number of control subjects.

RESULTS: We identified a unique peak at 3.15 ppm by using in vivo proton MR spectroscopy in eight of 20 patients with acute brain injury but not in 20 healthy volunteers (P < .002). On the basis of in vitro data, we have tentatively assigned this peak to citrulline, a NOS by-product.

CONCLUSION: To our knowledge, our findings suggest, for the first time, that excitotoxicity may occur in human acute brain injury. Confirmation with the acquisition of spectra in very early acute cerebral injury would provide a rationale for the use of neuroprotective agents in these conditions, as well as a new noninvasive method for quantification.

Analysis of dynamic strains in tibia during human locomotion based on flexible multibody approach integrated with magnetic resonance imaging technique

Bone is known to adapt to the prevalent strain environment while the variation in strains, e.g., due to mechanical loading, modulates bone remodeling, and modeling. Dynamic strains rather than static strains provide the primary stimulus of bone functional adaptation. The finite element method can be generally used for estimating bone strains, but it may be limited to the static analysis of bone strains since the dynamic analysis requires expensive computation. Direct in vivo strain measurement, in turn, is an invasive procedure, limited to certain superficial bone sites, and requires surgical implementation of strain gauges and thus involves risks (e.g., infection). Therefore, to overcome difficulties associated with the finite element method and the in vivo strain measurements, the flexible multibody simulation approach has been recently introduced as a feasible method to estimate dynamic bone strains during physical activity. The purpose of the present study is to further strengthen the idea of using the flexible multibody approach for the analysis of dynamic bone strains. Besides discussing the background theory, magnetic resonance imaging is integrated into the flexible multibody approach framework so that the actual bone geometry could be better accounted for and the accuracy of prediction improved.

Computer-aided detection of depression from magnetic resonance images

Magnetic resonance imaging (MRI) of the brain is used to detect depression disorder. However, a large number of MRI scans needs to be analyzed for such detection. Manual segmentation of the biomarkers in MRI scans by clinical experts can become time consuming and sometimes erroneous. This paper presents a study on computer-aided detection of depression from MRI scans. These systems have not yet been identified, categorized and compared in the literature. The paper covers fully automated to semi-automated detection systems. It also presents performance comparison for the considered systems.

Towards automated detection of depression from brain structural magnetic resonance images

Introduction : Depression is a major issue worldwide and is seen as a significant health problem. Stigma and patient denial, clinical experience, time limitations, and reliability of psychometrics are barriers to the clinical diagnoses of depression. Thus, the establishment of an automated system that could detect such abnormalities would assist medical experts in their decision-making process. This paper reviews existing methods for the automated detection of depression from brain structural magnetic resonance images (sMRI).Methods : Relevant sources were identified from various databases and online sites using a combination of keywords and terms including depression, major depressive disorder, detection, classification, and MRI databases. Reference lists of chosen articles were further reviewed for associated publications.Results : The paper introduces a generic structure for representing and describing the methods developed for the detection of depression from sMRI of the brain. It consists of a number of components including acquisition and preprocessing, feature extraction, feature selection, and classification.Conclusion : Automated sMRI-based detection methods have the potential to provide an objective measure of depression, hence improving the confidence level in the diagnosis and prognosis of depression.

Measuring miscible fluid displacement in porous media with magnetic resonance imaging

The development of new quantitative magnetic resonance imaging (MRI) technologies open new opportunities for measurements of mass transport in porous media. The current work examines a simple miscible displacement process of H2O and D2O in porous media samples. Laboratory measurements of dispersion in porous media traditionally monitor the effluent intensity of an injected tracer. We employ MRI to obtain quantitative water saturation profiles, and to measure dispersion in rock core plugs. The saturation profiles are modeled with PHREEQC, a fluid transport modeling program. We demonstrate how independent magnetic resonance measurements can be employed to estimate three important input parameters for PHREEQC, mobile porosity, immobile porosity, and dispersivity. Bulk Carr Purcell Meiboom Gill (CPMG) T2 distribution measurements were undertaken to estimate mobile and immobile porosity. Bulk alternating-pulsed-gradient-stimulated-echo (APGSTE) measurements were undertaken to measure dispersivity. The imaging method employed, T2 mapping Spin Echo Single Point Imaging (SE-SPI), also provides information about the pore size distributions in the rock cores, and how the fluid occupancy of the pores changes during the displacement process.

Probing ion exchange in the triflic acid-guanidinium triflate system: a solid-state nuclear magnetic resonance study

Knowledge of ion exchange and transport behavior in electrolyte materials is crucial for designing and developing novel electrolytes for electrochemical device applications such as fuel cells or batteries. In the present study, we show that, upon the addition of triflic acid (HTf) to the guanidinium triflate (GTf) solid-state matrix, several orders of magnitude enhancement in the proton conductivity can be achieved. The static 1H and 19F solid-state NMR results show that the addition of HTf has no apparent effect on local molecular mobility of the GTf matrix at room temperature. At higher temperatures, however, the HTf exhibits fast ion exchange with the GTf matrix. The exchange rate, as quantified by our continuum T2 fitting analysis, increases with increasing temperature. The activation energy for the chemical exchange process was estimated to be 58.4 kJ/mol. It is anticipated that the solid-state NMR techniques used in this study may be also applied to other organic solid-state electrolyte systems to investigate their ion-exchange processes.

New insights into the thermal behaviour of organic ionic plastic crystals: magnetic resonance imaging of polycrystalline morphology alterations induced by solid-solid phase transitions

Organic ionic plastic crystals (OIPCs) show strong potential as solid-state electrolytes for lithium battery applications, demonstrating promising electrochemical performance and eliminating the need for a volatile and flammable liquid electrolyte. The ionic conductivity (σ) in these systems has recently been shown to depend strongly on polycrystalline morphology, which is largely determined by the sample's thermal history. [K. Romanenko et al., J. Am. Chem. Soc., 2014, 136, 15638]. Tailoring this morphology could lead to conductivities sufficiently high for battery applications, so a more complete understanding of how phenomena such as solid-solid phase transitions can affect the sample morphology is of significant interest. Anisotropic relaxation of nuclear spin magnetisation provides a new MRI based approach for studies of polycrystalline materials at both a macroscopic and molecular level. In this contribution, morphology alterations induced by solid-solid phase transitions in triisobutyl(methyl)phosphonium bis(fluorosulfonyl)imide (P1444FSI) and diethyl(methyl)(isobutyl)phosphonium hexafluorophosphate (P1224PF6) are examined using magnetic resonance imaging (MRI), alongside nuclear magnetic resonance (NMR) spectroscopy, diffusion measurements and conductivity data. These observations are linked to molecular dynamics and structural behaviour crucial for the conductive properties of OIPCs. A distinct correlation is established between the conductivity at a given temperature, σ(T), and the intensity of the narrow NMR signal that is attributed to a mobile fraction, fm(T), of ions in the OIPC. To explain these findings we propose an analogy with the well-studied relationship between permeability (k) and void fraction (θ) in porous media, with k(θ) commonly quantified by a power-law dependence that can also be employed to describe σ(fm).

Automated detection of depression from brain structural magnetic resonance imaging (sMRI) scans

 Automated sMRI-based depression detection system is developed whose components include acquisition and preprocessing, feature extraction, feature selection, and classification. The core focus of the research is on the establishment of a new feature selection algorithm that quantifies the most relevant brain volumetric feature for depression detection at an individual level.