The age dependence of T2 relaxation times of N-acetyl aspartate, creatine and choline in the human brain at 3 and 4T.

Knowledge of the T2 age dependence is of importance for MRS clinical studies involving subject groups with a wide age range. A number of studies have focused on the age dependence of T2 values in the human brain, with rather conflicting results. The aim of this study was to analyze the age dependence of T2 values of N-acetyl aspartate (NAA), creatine (Cr) and choline (Cho) in the human brain using data acquired at 3T and 4T and to assess the influence of the macromolecule (MM) baseline handling on the obtained results. Two distinct groups of young and elderly controls have been measured at 3T (TE = 30-540 ms, 9 young and 11 elderly subjects) and 4T (TE = 10-180 ms, 18 young and 14 elderly subjects) using single-voxel spectroscopy. In addition, MM spectra were measured from two subjects using the inversion-recovery technique at 4T. All spectra were processed with LCModel using basis sets with different MM signals (measured or simulated) and also with MM signals included for a different TE range. Individual estimated T2 values were statistically analyzed using the R programming language for the age dependence of T2 values as well as the influence of the MM baseline handling. A significant decrease of T2 values of NAA and Cr in elderly subjects compared with young subjects was confirmed. The same trend was observed for Cho. Significantly higher T2 values calculated using the measured MM baseline for all studied metabolites at 4T were observed for both young and elderly subjects. To conclude, while the handling of MM and lipid signals may have a significant effect on estimated T2 values, we confirmed the age dependence of T2 values of NAA and Cr and the same trend for Cho in the human brain. Copyright © 2016 John Wiley & Sons, Ltd.

Connectivity of the anterior insula differentiates participants with first-episode schizophrenia spectrum disorders from controls: a machine-learning study.

BACKGROUND: Early diagnosis of schizophrenia could improve the outcomes and limit the negative effects of untreated illness. Although participants with schizophrenia show aberrant functional connectivity in brain networks, these between-group differences have a limited diagnostic utility. Novel methods of magnetic resonance imaging (MRI) analyses, such as machine learning (ML), may help bring neuroimaging from the bench to the bedside. Here, we used ML to differentiate participants with a first episode of schizophrenia-spectrum disorder (FES) from healthy controls based on resting-state functional connectivity (rsFC). METHOD: We acquired resting-state functional MRI data from 63 patients with FES who were individually matched by age and sex to 63 healthy controls. We applied linear kernel support vector machines (SVM) to rsFC within the default mode network, the salience network and the central executive network. RESULTS: The SVM applied to the rsFC within the salience network distinguished the FES from the control participants with an accuracy of 73.0% (p = 0.001), specificity of 71.4% and sensitivity of 74.6%. The classification accuracy was not significantly affected by medication dose, or by the presence of psychotic symptoms. The functional connectivity within the default mode or the central executive networks did not yield classification accuracies above chance level. CONCLUSIONS: Seed-based functional connectivity maps can be utilized for diagnostic classification, even early in the course of schizophrenia. The classification was probably based on trait rather than state markers, as symptoms or medications were not significantly associated with classification accuracy. Our results support the role of the anterior insula/salience network in the pathophysiology of FES.

Vegetarian diet improves insulin resistance and oxidative stress markers more than conventional diet in subjects with Type 2 diabetes.

AIMS: The aim of this study was to compare the effects of calorie-restricted vegetarian and conventional diabetic diets alone and in combination with exercise on insulin resistance, visceral fat and oxidative stress markers in subjects with Type 2 diabetes. METHODS: A 24-week, randomized, open, parallel design was used. Seventy-four patients with Type 2 diabetes were randomly assigned to either the experimental group (n = 37), which received a vegetarian diet, or the control group (n = 37), which received a conventional diabetic diet. Both diets were isocaloric, calorie restricted (-500 kcal/day). All meals during the study were provided. The second 12 weeks of the diet were combined with aerobic exercise. Participants were examined at baseline, 12 weeks and 24 weeks. Primary outcomes were: insulin sensitivity measured by hyperinsulinaemic isoglycaemic clamp; volume of visceral and subcutaneous fat measured by magnetic resonance imaging; and oxidative stress measured by thiobarbituric acid reactive substances. Analyses were by intention to treat. RESULTS: Forty-three per cent of participants in the experimental group and 5% of participants in the control group reduced diabetes medication (P < 0.001). Body weight decreased more in the experimental group than in the control group [-6.2 kg (95% CI -6.6 to -5.3) vs. -3.2 kg (95% CI -3.7 to -2.5); interaction group × time P = 0.001]. An increase in insulin sensitivity was significantly greater in the experimental group than in the control group [30% (95% CI 24.5-39) vs. 20% (95% CI 14-25), P = 0.04]. A reduction in both visceral and subcutaneous fat was greater in the experimental group than in the control group (P = 0.007 and P = 0.02, respectively). Plasma adiponectin increased (P = 0.02) and leptin decreased (P = 0.02) in the experimental group, with no change in the control group. Vitamin C, superoxide dismutase and reduced glutathione increased in the experimental group (P = 0.002, P < 0.001 and P = 0.02, respectively). Differences between groups were greater after the addition of exercise training. Changes in insulin sensitivity and enzymatic oxidative stress markers correlated with changes in visceral fat. CONCLUSIONS: A calorie-restricted vegetarian diet had greater capacity to improve insulin sensitivity compared with a conventional diabetic diet over 24 weeks. The greater loss of visceral fat and improvements in plasma concentrations of adipokines and oxidative stress markers with this diet may be responsible for the reduction of insulin resistance. The addition of exercise training further augmented the improved outcomes with the vegetarian diet.

The relationships between quantitative MR parameters in hippocampus in healthy subjects and patients with temporal lobe epilepsy.

We introduce a new magnetic resonance (MR) method based on a pixel-by-pixel image processing to examine relationships between metabolic and structural processes in the pathologic hippocampus. The method was tested for lateralization of the epileptogenic zone in patients with temporal lobe epilepsy (TLE). Twenty patients with drug-resistant TLE and fifteen healthy controls were examined at 3T. The measurement protocol contained T2-weighted MR images, spectroscopic imaging, diffusion tensor imaging and T2 relaxometry. Correlations between quantitative MR parameters were calculated on a pixel-by-pixel basis using the CORIMA program which enables automated pixel identification in the normal tissue according to control data. All MR parameters changed in the anteroposterior direction in the hippocampus and correlation patterns and their slopes differed between patients and controls. Combinations of T2 relaxation times with metabolite values represent the best biomarkers of the epileptogenic zone. Correlations with mean diffusivity did not provide sufficiently accurate results due to diffusion image distortions. Quantitative MR analysis non-invasively provides a detailed description of hippocampal pathology and may represent complementary tool to the standard clinical protocol. However, the automated processing should be carefully monitored in order to avoid possible errors caused by MR artifacts.

Diffusion tensor imaging and MR morphometry of the central auditory pathway and auditory cortex in aging.

Age-related hearing loss (presbycusis) is caused mainly by the hypofunction of the inner ear, but recent findings point also toward a central component of presbycusis. We used MR morphometry and diffusion tensor imaging (DTI) with a 3T MR system with the aim to study the state of the central auditory system in a group of elderly subjects (>65years) with mild presbycusis, in a group of elderly subjects with expressed presbycusis and in young controls. Cortical reconstruction, volumetric segmentation and auditory pathway tractography were performed. Three parameters were evaluated by morphometry: the volume of the gray matter, the surface area of the gyrus and the thickness of the cortex. In all experimental groups the surface area and gray matter volume were larger on the left side in Heschl's gyrus and planum temporale and slightly larger in the gyrus frontalis superior, whereas they were larger on the right side in the primary visual cortex. Almost all of the measured parameters were significantly smaller in the elderly subjects in Heschl's gyrus, planum temporale and gyrus frontalis superior. Aging did not change the side asymmetry (laterality) of the gyri. In the central part of the auditory pathway above the inferior colliculus, a trend toward an effect of aging was present in the axial vector of the diffusion (L1) variable of DTI, with increased values observed in elderly subjects. A trend toward a decrease of L1 on the left side, which was more pronounced in the elderly groups, was observed. The effect of hearing loss was present in subjects with expressed presbycusis as a trend toward an increase of the radial vectors (L2L3) in the white matter under Heschl's gyrus. These results suggest that in addition to peripheral changes, changes in the central part of the auditory system in elderly subjects are also present; however, the extent of hearing loss does not play a significant role in the central changes.

Effect of acute hyperinsulinemia on brain metabolism evaluated by 1H MR spectroscopy--a pilot study.

To determine whether acutely-induced supraphysiological hyperinsulinemia influences brain metabolism in patients with type 1 diabetes (D) and healthy controls (C) as detected by MR Spectroscopy. Group D consisted of 4 patients with the average duration of diabetes for 7 years. They were matched according to age, sex and BMI to 4 healthy controls. 1H MR Spectroscopy was performed with a 1.5 Tesla. Spectra were obtained from parietooccipital white matter repeatedly during a 3-h hyperinsulinemic euglycemic clamp with 2 mU.kg(-1).min(-1). In group D, significantly lower basal concentrations of N-acetylaspartate (p=0.02), choline (p=0.03), creatine (p=0.002) and inositol (p=0.007) were detected compared to C. After the induction of hyperinsulinemia, concentrations of choline, creatine, GABA, inositol, lactate, NAA and composite signal glutamate + glutamine (Glx) stayed stable. The detection of glucose signal is less realiable at 1.5 Tesla but we registered the alteration in glucose concentration (p=0.003) in the whole group. Originally sightly elevated glucose concentration in D decreased on the contrary to the increase of originally lower glucose level in C. In conclusions, brain metabolism was altered in D. Short term supraphysiological euglycemic hyperinsulinemia induced changes in the concentration of brain glucose in both C and D.

Error images for spectroscopic imaging by LCModel using Cramer-Rao bounds.

The results of spectroscopic imaging (SI) measurements are often presented as metabolic images. If the spectra quality is not sufficient, the calculated concentrations are biased and the metabolic images show an incorrect metabolite distribution. To simplify the quality analysis of spectra measured by SI, an error image, reflecting the accuracy of the computed concentrations, can be displayed along with the metabolite image. In this paper the relevance of Cramer-Rao bounds (CRBs) calculated by the LCModel program to describe errors in estimated concentrations is validated using spectra simulations. The relation between the average CRBs and standard deviations (STD) of metabolite concentrations from 100 simulated spectra for various signal to noise ratio and line broadening conditions is evaluated. A parameter for calculating error images for metabolite ratios is proposed and an effective way to display error images is shown. The results suggest that the average CRBs are strongly correlated with the standard deviations and hence that CRB values reflect the relative uncertainty of the calculated concentrations. The error information can be integrated directly into a metabolite image by displaying only those areas of the metabolite image with corresponding CRBs below a selected threshold or by mapping CRBs as a transparency of the metabolite image. The concept of error images avoids extensive examination of each SI spectrum and helps to reject low quality spectra.

Classification of calf muscle MR images by texture analysis.

AIM: To evaluate a method of texture analysis (TA) for the description of magnetic resonance (MR) images of healthy and diseased calf muscles and to compare this method with standard radiological evaluation. METHODS: A total of 93 subjects (20 controls, seven healthy children of hypertonic parents, five diabetic patients and 61 subjects with muscle malfunction of various origin) underwent MR imaging of the calf muscle and texture analysis of images was performed. The results of TA were analysed by t-statistics and principal component analysis. Images of subjects were divided into four groups according to the assessment of three radiologists and this categorization of subjects was compared with the results from TA. RESULTS: We extracted seven features (from a total number of 282) which were successfully used for the description of the texture of T1w MR images of calf muscles. The results of classification by TA are in 80% agreement with the categorization made by the radiologists. In some cases, TA is able to describe changes not apparent by visual inspection. CONCLUSION: The TA of MR images of calf muscles can be used for the objective description of changes in muscles and could help radiologists to distinguish between healthy and diseased tissue.