Lineshape of Magnetic Resonance and its Effects on Free Induction Decay and Steady-State Free Precession Signal FormationRead the full article
Concepts in Magnetic Resonance Part A publishes research concerning the applications of magnetic resonance techniques, including magnetic resonance imaging (MRI), nuclear magnetic resonance (NMR) and electron paramagnetic resonance (EPR).
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Brain and Hepatic Glucose Utilization in Malarial Infection Does Not Depend on Cerebral Symptoms of the Disease
Cerebral malaria causes several deaths every year. Global metabolic alteration, specifically hypoglycemia and lactic acidosis are hallmarks of severe malaria. Glucose being the major fuel source for the brain, it is important to understand cerebral glucose utilization in the host during cerebral complications of the disease that may have a significant role in cerebral pathogenesis. We have used 13C NMR spectroscopy to understand glucose utilization in the brain and liver of mice with cerebral malaria (CM), noncerebral malaria (NCM), and in control mice. Animals were challenged with intravenous glucose bolus followed by metabolic profiling of brain and liver extracts. Our result suggests a differential glucose utilization in the malaria group with respect to that of controls, while no difference between CM and NCM.
Magic Angle Spinning and Truncated Field Concept in NMR
In order to thoroughly comprehend and adequtely interpret NMR data, it is necessary to perceive the complex structure of spin Hamiltonian. Although NMR principles have been extensively discussed in a number of distinguished introductory publications, it still remains difficult to find illustrative graphical models revealing the tensorial nature of spin interaction. Exposure of the structure standing behind mathematical formulas can clarify intangible concepts and provide a coherent image of basic phenomena. This approach is essential when it comes to hard to manage, time-dependent processes such as Magic Angle Spinning (MAS), where the anisotropic character of the spin system interactions couple with experimentally introduced time evolution processes. The presented work concerns fundamental aspects of solid state NMR namely: the uniqueness of the tetrahedral angle and evolution of both dipolar D and chemical shield σ coupling tensors under MAS conditions.
Quantitative Susceptibility Mapping of Magnetic Quadrupole Moments
We modeled the magnetic field up to the quadrupole term to investigate not only the average susceptibility (dipole), but also the susceptibility distribution (quadrupole) contribution. Expanding the magnetic field up to the order provides the quadrupole (: monopole, : dipole). Numerical simulations were performed to investigate the quadrupole contribution with subvoxel nonuniformity. Conventional dipole and our dipole + quadrupole models were compared in the simulation, the phantom and human brain. Furthermore, the quadrupole field was compared with the anisotropic susceptibility field in the dipole tensor model. In a nonuniformity case, numerical simulations showed a nonnegligible quadrupole field contribution. Our study showed a difference between the two methods in the susceptibility map at the edges; both the phantom and human studies showed sharper structural edges with the dipole + quadrupole model. Quadrupole moments showed contrast mainly at the structural boundaries. The quadrupole moment field contribution was smaller but nonnegligible compared to the anisotropic susceptibility contribution. Nonuniform and uniform source distributions can be separately considered by quadrupole expansion, which were mixed together in the dipole model. In the presence of nonuniformity, the susceptibility maps may be different between the two models. For a comprehensive field model, the quadrupole might need to be considered along with susceptibility anisotropy and microstructure effects.
Evaluation of the Impact of Magnetic Resonance Imaging (MRI) on Gross Tumor Volume (GTV) Definition for Radiation Treatment Planning (RTP) of Inoperable High Grade Gliomas (HGGs)
Aim and Background. Inoperable high-grade gliomas (HGGs) comprise a specific group of brain tumors portending a very poor prognosis. In the absence of surgical management, radiation therapy (RT) offers the primary local treatment modality for inoperable HGGs. Optimal target definition for radiation treatment planning (RTP) of HGGs is a difficult task given the diffusely infiltrative nature of the disease. In this context, detailed multimodality imaging information may add to the accuracy of target definition in HGGs. We evaluated the impact of Magnetic Resonance Imaging (MRI) on Gross Tumor Volume (GTV) definition for RTP of inoperable HGGs in this study. Materials and Methods. Twenty-five inoperable patients with a clinical diagnosis of HGG were included in the study. GTV definition was based on Computed Tomography- (CT-) simulation images only or both CT-simulation and MR images, and a comparative assessment was performed to investigate the incorporation of MRI into RTP of HGGs. Results. Median volume of GTV acquired by using CT-simulation images only and by use of CT and MR images was 65.3 (39.6-94.3) cc and 76.1 (46.8-108.9) cc, respectively. Incorporation of MRI into GTV definition has resulted in a median increase of 12.61% (6%-19%) in the volume of GTV defined by using the CT-simulation images only, which was statistically significant (p < 0.05). Conclusion. Incorporation of MRI into RTP of inoperable HGGs may improve GTV definition and may have implications for dose escalation/intensification strategies despite the need for further supporting evidence.
Dual-Echo Arterial Spin Labeling for Brain Perfusion Quantification and Functional Analysis
Arterial Spin Labeling (ASL) is a noninvasive MRI-based method to measure cerebral blood flow (CBF). Recently, the study of ASL as a functional tool has emerged once CBF fluctuation comes from capillaries in brain tissue, giving a more spatially specific response when compared to the standard functional MRI method, based on the blood oxygenation level-dependent (BOLD) contrast. Although the BOLD effect could be desirable to study brain function, if one aims to quantify CBF, such effect is considered contamination that can be more attenuated if short TE value is used in the image acquisition. An approach that provides both CBF and function information in a simultaneous acquisition is the use of a dual-echo ASL (DE-ASL) readout. Our purpose was to evaluate the information provided by DE-ASL regarding CBF quantification and functional connectivity with a motor task. Pseudocontinuous ASL of twenty healthy subjects (age: 32.4 ± 10.2 years, 13 male) was acquired at a 3T scanner. We analyzed the influence of TE on CBF values and brain connectivity provided by CBF and concurrent BOLD (cc-BOLD) time series. Brain networks were obtained by the general linear model and independent component analysis. Connectivity matrices were generated using a bivariate correlation (Fisher Z values). No effect of the sequence readout, but significant effect of the TE value, was observed on gray matter CBF values. Motor networks with reduced extension and more connections with important regions for brain integration were observed for CBF data acquired with short TE, proving its higher spatial specificity. Therefore, it was possible to use a dual-echo readout provided by a standard commercial ASL pulse sequence to obtain reliable quantitative CBF values and functional information simultaneously.
Full-Range Liver Fat Fraction Estimation in Magnitude MRI Using a Signal Shape Descriptor
Current methods for estimation of proton density fat fraction (PDFF) of the liver using magnitude magnetic resonance (MR) imaging face the challenge of correctly estimating it when fat is the dominant molecule; i.e., PDFF is more than 50%. Therefore, the accuracy of the methods is limited to half-range operation. We introduce a method based on neural networks for regression capable of estimating over the full range of fat fractions. We built a neural network based on the angles and distances between the data in the discrete MR signal (ADALIFE), using these as features associated with different PDFFs and as input for the network. Tests were performed using ADALIFE and Multi-interference, a state-of-the-art method to estimate PDFFs, with simulated signals at various signal-to-noise (SNR) values. Results were compared in order to verify repeatability and agreement using Bland-Altman and REC curves. Results for Multi-interference were similar to its in vivo literature, showing the relevance of a simulation. ADALIFE was able to correctly estimate fat fractions up to 100%, breaking the current paradigm for full-range estimation using only offline postprocessing. Within half range, our method outperformed Multi-interference in repeatability and agreement, with narrower limits of agreement and lower expected error at any SNR.