Early detection of secondary damage in ipsilateral thalamus after acute infarction at unilateral corona radiata by diffusion tensor imaging and magnetic resonance spectroscopy

Background  

Traditional magnetic resonance (MR) imaging can identify abnormal changes in ipsilateral thalamus in patients with unilateral middle cerebral artery (MCA) infarcts. However, it is difficult to demonstrate these early changes quantitatively. Diffusion tensor imaging (DTI) and proton magnetic resonance spectroscopy (MRS) are potentially sensitive and quantitative methods of detection in examining changes of tissue microstructure and metabolism. In this study, We used both DTI and MRS to examine possible secondary damage of thalamus in patients with corona radiata infarction.     

Is MR Spectroscopy Really the Best MR-Based Method for the Evaluation of Fatty Liver in Diabetic Patients in Clinical Practice?

Objective

To investigate if magnetic resonance spectroscopy (MRS) is the best Magnetic Resonance (MR)-based method when compared to gradient-echo magnetic resonance imaging (MRI) for the detection and quantification of liver steatosis in diabetic patients in the clinical practice using liver biopsy as the reference standard, and to assess the influence of steatohepatitis and fibrosis on liver fat quantification.

Methods

Institutional approval and patient consent were obtained for this prospective study. Seventy-three patients with type 2 diabetes (60 women and 13 men; mean age, 54±9 years) underwent MRI and MRS at 3.0 T. The liver fat fraction was calculated from triple- and multi-echo gradient-echo sequences, and MRS data. Liver specimens were obtained in all patients. The accuracy for liver fat detection was estimated by receiver operator characteristic (ROC) analysis, and the correlation between fat quantification by imaging and histolopathology was analyzed by Spearman''s correlation coefficients.

Results

The prevalence of hepatic steatosis was 92%. All gradient-echo MRI and MRS findings strongly correlated with biopsy findings (triple-echo, rho = 0.819; multi-echo, rho = 0.773; MRS, rho = 0.767). Areas under the ROC curves to detect mild, moderate, and severe steatosis were: triple-echo sequences, 0.961, 0.975, and 0.962; multi-echo sequences, 0.878, 0.979, and 0.961; and MRS, 0.981, 0.980, and 0.954. The thresholds for mild, moderate, and severe steatosis were: triple-echo sequences, 4.09, 9.34, and 12.34, multi-echo sequences, 7.53, 11.75, and 15.08, and MRS, 1.71, 11.69, and 14.91. Quantification was not significantly influenced by steatohepatitis or fibrosis.

Conclusions

Liver fat quantification by MR methods strongly correlates with histopathology. Due to the wide availability and easier post-processing, gradient-echo sequences may represent the best imaging method for the detection and quantification of liver fat fraction in diabetic patients in the clinical practice.     

Comparison of 3T MR scanners in regional cartilage-thickness analysis in osteoarthritis: a cross-sectional multicenter,multivendor study

Introduction  

Cartilage thickness from MR images has been identified as a possible biomarker in knee osteoarthritis (OA) research. The ability to acquire MR data at multiple centers by using different vendors' scanners would facilitate patient recruitment and shorten the duration of OA trials. Several vendors manufacture 3T MR scanners, including Siemens, Philips Medical Systems, and GE Healthcare. This study investigates whether quantitative MR assessments of cartilage morphology are comparable between scanners of three different vendors.     

Prevalence of abnormal findings on brain magnetic resonance (MR) examinations in adult participants of brain docking

Background  

To determine the prevalence of abnormal findings on brain magnetic resonance (MR) examinations in adult participants of brain docking in order to assess its usefulness.     

The cerebro-morphological fingerprint of a progeroid syndrome: white matter changes correlate with neurological symptoms in xeroderma pigmentosum

Background

Xeroderma pigmentosum (XP) is a rare autosomal recessive progeroid syndrome. It has recently been shown that the underlying DNA repair defect plays a central role in the aging process. In addition to skin symptoms, various premature neurological abnormalities have been reported.

Methodology/Principal Findings

We present the clinical neurological phenotype in 14 XP patients (seven subtypes), in seven of these patients together with conventional and multiparametric advanced MRI data to assess the macrostructural and microstructural cerebral morphology in comparison to controls, including volumetric measurements, MR spectroscopy (¹H MRS), and diffusion tensor imaging (DTI). Clinical hallmarks were spinocerebellar ataxia, pyramidal tract signs, and mild cognitive deficits. DTI demonstrated significantly reduced WM directionality in all regions investigated, i.e. the thalamus, the corticospinal tracts and the dorsal corpus callosum. Single patients showed a marked relative hippocampal volume reduction, but the patients were not different from controls in the volumetric measurements of hippocampal and whole brain volumes at group level. However, ¹H MRS demonstrated that the hippocampal formation was metabolically altered.

Conclusions

The most prominent feature was the white matter affectation, as assessed by DTI, with volume and directionality reductions of the fiber projections involving both the craniocaudal fibers and the interhemispheric connections. These findings, although heterogeneous among the study sample, could be correlated with the clinico-neurological symptoms. The imaging findings support the position that myelin structures degrade prematurely in the brain of XP patients.     

Metabolic heterogeneity of the normal human brain: multivariate analysis of <Superscript>1</Superscript>H MRS in vivo spectra acquired at 3T

Introduction

In recent years multivariate projection techniques of data analysis (PCA, PLS-DA) have been increasingly used for detection of complex ¹H MRS derived metabolic signatures in pathologic conditions. However, these techniques have not been applied in the studies of metabolic heterogeneity of the normal human brain.

Objective

In this work we extended current knowledge about regional distribution of metabolites by multivariate analysis of metabolite levels obtained from various cortical and subcortical regions.

Methods

The studied group consisted of 71 volunteers with no neurological disorders. The metabolite levels obtained from short echo time ¹H MRS in vivo spectra were subjected to univariate and multivariate analysis.

Results

The major variance direction in the dataset was dominated by glutamine?+?glutamate, creatine, myo-inositol and was successful in differentiation of the cortical grey matter and cerebellar vermis from the cortical white matter, pons, basal ganglia, hippocampus and thalamus. The projection plane formed by the second and third variance directions was dominated by N-acetylaspartate?+?N-acetylaspartylglutamate, choline and glutamine?+?glutamate variation not explained by the first direction. This plane revealed a huge metabolic contrast between the pons and basal ganglia, differentiation between the cortical grey matter regions and cerebellar vermis as well as biochemical heterogeneity between the regions such as: thalamus, basal ganglia and hippocampus.

Conclusion

Multivariate approach to ¹H MRS data analysis provides an insight into the normal brain biochemistry and is helpful in understanding the regional heterogeneity of the normal brain. Such knowledge is crucial for a proper interpretation of altered metabolic pathways in diseases.

     

Convex Non-Negative Matrix Factorization for Brain Tumor Delimitation from MRSI Data

Background

Pattern Recognition techniques can provide invaluable insights in the field of neuro-oncology. This is because the clinical analysis of brain tumors requires the use of non-invasive methods that generate complex data in electronic format. Magnetic Resonance (MR), in the modalities of spectroscopy (MRS) and spectroscopic imaging (MRSI), has been widely applied to this purpose. The heterogeneity of the tissue in the brain volumes analyzed by MR remains a challenge in terms of pathological area delimitation.

Methodology/Principal Findings

A pre-clinical study was carried out using seven brain tumor-bearing mice. Imaging and spectroscopy information was acquired from the brain tissue. A methodology is proposed to extract tissue type-specific sources from these signals by applying Convex Non-negative Matrix Factorization (Convex-NMF). Its suitability for the delimitation of pathological brain area from MRSI is experimentally confirmed by comparing the images obtained with its application to selected target regions, and to the gold standard of registered histopathology data. The former showed good accuracy for the solid tumor region (proliferation index (PI)>30%). The latter yielded (i) high sensitivity and specificity in most cases, (ii) acquisition conditions for safe thresholds in tumor and non-tumor regions (PI>30% for solid tumoral region; ≤5% for non-tumor), and (iii) fairly good results when borderline pixels were considered.

Conclusions/Significance

The unsupervised nature of Convex-NMF, which does not use prior information regarding the tumor area for its delimitation, places this approach one step ahead of classical label-requiring supervised methods for discrimination between tissue types, minimizing the negative effect of using mislabeled voxels. Convex-NMF also relaxes the non-negativity constraints on the observed data, which allows for a natural representation of the MRSI signal. This should help radiologists to accurately tackle one of the main sources of uncertainty in the clinical management of brain tumors, which is the difficulty of appropriately delimiting the pathological area.     

Localized 1H-NMR spectroscopy in patients with fibromyalgia: a controlled study of changes in cerebral glutamate/glutamine, inositol, choline, and N-acetylaspartate

Introduction  

The purpose of this study was to investigate whether single-voxel (SV) proton magnetic resonance spectroscopy (MRS), diffusion-weighted imaging (DWI), and diffusion tensor imaging (DTI) detected differences between fibromyalgia (FM) patients and healthy controls. We also searched for correlations between neuroimaging abnormalities and neuropsychological variables.     

A decision tree--based method for the differential diagnosis of Aortic Stenosis from Mitral Regurgitation using heart sounds

Background  

New technologies like echocardiography, color Doppler, CT, and MRI provide more direct and accurate evidence of heart disease than heart auscultation. However, these modalities are costly, large in size and operationally complex and therefore are not suitable for use in rural areas, in homecare and generally in primary healthcare set-ups. Furthermore the majority of internal medicine and cardiology training programs underestimate the value of cardiac auscultation and junior clinicians are not adequately trained in this field. Therefore efficient decision support systems would be very useful for supporting clinicians to make better heart sound diagnosis. In this study a rule-based method, based on decision trees, has been developed for differential diagnosis between "clear" Aortic Stenosis (AS) and "clear" Mitral Regurgitation (MR) using heart sounds.     

Hyperpolarized MRI,functional MRI,MR spectroscopy and CEST to provide metabolic information in vivo

Access to metabolic information in vivo using magnetic resonance (MR) technologies has generally been the niche of MR spectroscopy (MRS) and spectroscopic imaging (MRSI). Metabolic fluxes can be studied using the infusion of substrates labeled with magnetic isotopes, with the use of hyperpolarization especially powerful. Unfortunately, these promising methods are not yet accepted clinically, where fast, simple, and reliable measurement and diagnosis are key. Recent advances in functional MRI and chemical exchange saturation transfer (CEST) MRI allow the use of water imaging to study oxygen metabolism and tissue metabolite levels. These, together with the use of novel data analysis approaches such as machine learning for all of these metabolic MR approaches, are increasing the likelihood of their clinical translation.     

Quantification of ethanol methyl 1H magnetic resonance signal intensity following intravenous ethanol administration in primate brain

In vivo ¹H magnetic resonance spectroscopy (MRS) can be used to directly monitor brain ethanol. Previously, studies of human subjects have lead to the suggestion that the ethanol methyl ¹H MRS signal intensity relates to tolerance to ethanol’s intoxicating effects. More recently, the ethanol ¹H MRS signal intensity has been recognized to vary between brain gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) due to differences in T₂ within these environments. The methods presented here extend ethanol MRS techniques to non-human primate subjects. Twelve monkeys were administered ethanol while sedated and positioned within a 3T MRI system. Chemical shift imaging (CSI) measurements were performed following intravenous infusion of 1 g/kg ethanol. Magnetic resonance imaging (MRI) data were also recorded for each monkey to provide volume fractions of GM, WM, and CSF for each CSI spectrum. To estimate co-variance of ethanol MRS intensity with GM, WM, and CSF volume fractions, the relative contribution of each tissue subtype was determined following corrections for radiofrequency pulse profile non-uniformity, chemical shift artifacts, and differences between the point spread function in the CSI data and the imaging data. The ethanol MRS intensity per unit blood ethanol concentration was found to differ between GM, WM, and CSF. Individual differences in MRS intensity were larger in GM than WM. This methodology demonstrates the feasibility of ethanol MRS experiments and analysis in non-human primate subjects, and suggests GM may be a site of significant variation in ethanol MRS intensity between individuals.     

A comprehensive re-analysis of the Golden Spike data: Towards a benchmark for differential expression methods

Background  

The Golden Spike data set has been used to validate a number of methods for summarizing Affymetrix data sets, sometimes with seemingly contradictory results. Much less use has been made of this data set to evaluate differential expression methods. It has been suggested that this data set should not be used for method comparison due to a number of inherent flaws.     

Immunohistochemical localization of mu opioid receptor in the marginal division with comparison to patches in the neostriatum of the rat brain

Background  

Mu opioid receptor (MOR), which plays key roles in analgesia and also has effects on learning and memory, was reported to distribute abundantly in the patches of the neostriatum. The marginal division (MrD) of the neostriatum, which located at the caudomedial border of the neostriatum, was found to stain for enkephalin and substance P immunoreactivities and this region was found to be involved in learning and memory in our previous study. However, whether MOR also exists in the MrD has not yet been determined.     

Utility of the Rio Score and Modified Rio Score in Korean Patients with Multiple Sclerosis

Objectives

Early identification of suboptimal responders to multiple sclerosis (MS) treatment is critical for optimizing therapeutic decisions. The Rio score (RS) and modified Rio score (MRS) were developed to discriminate the responses to interferon-beta (IFNB) treatment in MS patients. This study was performed to evaluate the utility of RS and MRS in daily clinical practice in Korea.

Methods

This was a real-world setting, multicenter, retrospective study of MS patients treated with IFNB from 10 hospitals in Korea. We investigated whether the RS and MRS at the early stage of IFNB therapy could predict treatment responses over 3 years. Suboptimal treatment responses at 3 years were defined as the presence of clinical relapse and/or EDSS progression and/or patients who had been treated with INFB for at least for 1 year and therapy was switched due to perceived treatment failure during the 2 years of follow-up.

Results

Seventy patients (50 females and 20 males) were enrolled; 92% (12/13) of patients with high RS and 86% (12/14) of patients with high MRS (score 2 or 3) were suboptimal responders, whereas 93% (53/57) of patients with low RS and 93% (52/56) patients with low MRS (score 0 or 1) showed optimal responses. New active lesions on MRI with clinical relapse in high RS and MRS were the most common combination in suboptimal responders.

Conclusions

We confirmed that RS and MRS at 6–15 months of IFNB therapy were useful for predicting poor responders over 3 years.     

Structural analysis of the evolution of steroid specificity in the mineralocorticoid and glucocorticoid receptors

Background  

The glucocorticoid receptor (GR) and mineralocorticoid receptor (MR) evolved from a common ancestor. Still not completely understood is how specificity for glucocorticoids (e.g. cortisol) and mineralocorticoids (e.g. aldosterone) evolved in these receptors.     

Noninvasive In Vivo Small Animal MRI and MRS: Basic Experimental Procedures

Small animal Magnetic Resonance (MR) research has emerged as an important element of modern biomedical research due to its non-invasive nature and the richness of biological information it provides. MR does not require any ionizing radiation and can noninvasively provide higher resolution and better signal-to-noise ratio in comparison to other tomographic or spectroscopic modalities. In this protocol, we will focus on small animal MR imaging and MR spectroscopy (MRI/MRS) to noninvasively acquire relaxation weighted ¹H images of mouse and to obtain ³¹P spectra of mouse muscle. This work does not attempt to cover every aspect of small animal MRI/MRS but rather introduces basic procedures of mouse MRI/MRS experiments. The main goal of this work is to inform researchers of the basic procedures for in vivo MR experiments on small animals. The goal is to provide a better understanding of basic experimental procedures to allow researchers new to the MR field to better plan for non-MR components of their studies so that both MR and non-MR procedures are seamlessly integrated.Download video file.^{(143M, mp4)}     

Evaluation of the Diagnostic Performance of Magnetic Resonance Spectroscopy in Brain Tumors: A Systematic Review and Meta-Analysis

Object

The aim of this study was to determine the suitability of magnetic resonance spectroscopy (MRS) for screening brain tumors, based on a systematic review and meta-analysis of published data on the diagnostic performance of MRS.

Methods

The PubMed and PHMC databases were systematically searched for relevant studies up to December 2013. The sensitivities and specificities of MRS in individual studies were calculated and the pooled diagnostic accuracies, with 95% confidence intervals (CI), were assessed under a fixed-effects model.

Results

Twenty-four studies were included, comprising a total of 1013 participants. Overall, no heterogeneity of diagnostic effects was observed between studies. The pooled sensitivity and specificity of MRS were 80.05% (95% CI = 75.97%–83.59%) and 78.46% (95% CI: 73.40%–82.78%), respectively. The area under the summary receiver operating characteristic curve was 0.78. Stratified meta analysis showed higher sensitivity and specificity in child than adult. CSI had higher sensitivity and SV had higher specificity. Higher sensitivity and specificity were obtained in short TE value.

Conclusion

Although the qualities of the studies included in the meta-analysis were moderate, current evidence suggests that MRS may be a valuable adjunct to magnetic resonance imaging for diagnosing brain tumors, but requires selection of suitable technique and TE value.