Thalamic metabolic abnormalities in patients with Huntington's disease measured by magnetic resonance spectroscopy

Huntington's disease (HD) is a neurologic disorder that is not completely understood; its fundamental physiological mechanisms and chemical effects remain somewhat unclear. Among these uncertainties, we can highlight information about the concentrations of brain metabolites, which have been widely discussed. Concentration differences in affected, compared to healthy, individuals could lead to the development of useful tools for evaluating the progression of disease, or to the advance of investigations of different/alternative treatments. The aim of this study was to compare the thalamic concentration of metabolites in HD patients and healthy individuals using magnetic resonance spectroscopy. We used a 2.0-Tesla magnetic field, repetition time of 1500 ms, and echo time of 135 ms. Spectra from 40 adult HD patients and 26 control subjects were compared. Quantitative analysis was performed using the LCModel method. There were statistically significant differences between HD patients and controls in the concentrations of N-acetylaspartate+N-acetylaspartylglutamate (NAA+NAAG; t-test, P<0.001), and glycerophosphocholine+phosphocholine (GPC+PCh; t-test, P=0.001) relative to creatine+phosphocreatine (Cr+PCr). The NAA+NAAG/Cr+PCr ratio was decreased by 9% and GPC+PCh/Cr+PCr increased by 17% in patients compared with controls. There were no correlations between the concentration ratios and clinical features. Although these results could be caused by T1 and T2 changes, rather than variations in metabolite concentrations given the short repetition time and long echo time values used, our findings point to thalamic dysfunction, corroborating prior evidence.

Effect of scanner acoustic background noise on strict resting-state fMRI

Functional MRI (fMRI) resting-state experiments are aimed at identifying brain networks that support basal brain function. Although most investigators consider a 'resting-state' fMRI experiment with no specific external stimulation, subjects are unavoidably under heavy acoustic noise produced by the equipment. In the present study, we evaluated the influence of auditory input on the resting-state networks (RSNs). Twenty-two healthy subjects were scanned using two similar echo-planar imaging sequences in the same 3T MRI scanner: a default pulse sequence and a reduced "silent" pulse sequence. Experimental sessions consisted of two consecutive 7-min runs with noise conditions (default or silent) counterbalanced across subjects. A self-organizing group independent component analysis was applied to fMRI data in order to recognize the RSNs. The insula, left middle frontal gyrus and right precentral and left inferior parietal lobules showed significant differences in the voxel-wise comparison between RSNs depending on noise condition. In the presence of low-level noise, these areas Granger-cause oscillations in RSNs with cognitive implications (dorsal attention and entorhinal), while during high noise acquisition, these connectivities are reduced or inverted. Applying low noise MR acquisitions in research may allow the detection of subtle differences of the RSNs, with implications in experimental planning for resting-state studies, data analysis, and ergonomic factors.

Manual and semi-automatic quantification of in vivo ¹H-MRS data for the classification of human primary brain tumors

In vivo proton magnetic resonance spectroscopy (¹H-MRS) is a technique capable of assessing biochemical content and pathways in normal and pathological tissue. In the brain, ¹H-MRS complements the information given by magnetic resonance images. The main goal of the present study was to assess the accuracy of ¹H-MRS for the classification of brain tumors in a pilot study comparing results obtained by manual and semi-automatic quantification of metabolites. In vivo single-voxel ¹H-MRS was performed in 24 control subjects and 26 patients with brain neoplasms that included meningiomas, high-grade neuroglial tumors and pilocytic astrocytomas. Seven metabolite groups (lactate, lipids, N-acetyl-aspartate, glutamate and glutamine group, total creatine, total choline, myo-inositol) were evaluated in all spectra by two methods: a manual one consisting of integration of manually defined peak areas, and the advanced method for accurate, robust and efficient spectral fitting (AMARES), a semi-automatic quantification method implemented in the jMRUI software. Statistical methods included discriminant analysis and the leave-one-out cross-validation method. Both manual and semi-automatic analyses detected differences in metabolite content between tumor groups and controls (P < 0.005). The classification accuracy obtained with the manual method was 75% for high-grade neuroglial tumors, 55% for meningiomas and 56% for pilocytic astrocytomas, while for the semi-automatic method it was 78, 70, and 98%, respectively. Both methods classified all control subjects correctly. The study demonstrated that ¹H-MRS accurately differentiated normal from tumoral brain tissue and confirmed the superiority of the semi-automatic quantification method.

MR imaging texture analysis of the corpus callosum and thalamus in amnestic mild cognitive impairment and mild Alzheimer disease

BACKGROUND AND PURPOSE

TA is a branch of image processing that seeks to reduce image information by extracting texture descriptors from the image. TA of MR images of anatomic structures in mild AD and aMCI is not well-studied. Our objective was to attempt to find differences among patients with aMCI and mild AD and normal-aging subjects, by using TA applied to the MR images of the CC and the thalami of these groups of subjects.

MATERIALS AND METHODS

TA was applied to the MR images of 17 patients with aMCI, 16 patients with mild AD, and 16 normal-aging subjects. The TA approach was based on the GLCM. MR images were T1-weighted and were obtained in the sagittal and axial planes. The CC and thalami were manually segmented for each subject, and 44 texture parameters were computed for each of these structures.

RESULTS

TA parameters showed differences among the 3 groups for the CC and thalamus. A pair-wise comparison among groups showed differences for AD-control and aMCI-AD for the CC; and for AD-control, aMCI-AD, and aMCI-control for the thalamus.

CONCLUSIONS

TA is a useful technique to aid in the detection of tissue alterations in MR images of mild AD and aMCI and has the potential to become a helpful tool in the diagnosis and understanding of these pathologies.

Antiepileptic drug response in temporal lobe epilepsy: a clinical and MRI morphometry study

OBJECTIVE

To investigate the relationship between brain MRI and clinical characteristics and patterns of antiepileptic drug (AED) response in patients with mesial temporal lobe epilepsy (MTLE).

METHODS

A total of 165 MTLE patients were divided into seizure-free with AED (AED responders, n = 50), pharmacoresistant (n = 87), and remitting-relapsing seizure control group (n = 28). All groups were evaluated regarding age, frequency of seizures, and age at epilepsy onset, duration of epilepsy, febrile seizures, presence and side of hippocampal atrophy (HA), and initial precipitating injuries. For gray matter (GM) MRI voxel-based morphometry (VBM) we selected only patients with unilateral HA on visual MRI analysis (n = 100). Comparisons were made between all groups and 75 healthy controls.

RESULTS

Age at epilepsy onset was lower (p = 0.005) and initial frequency of seizures was higher in the pharmacoresistant compared with the other 2 groups (p = 0.018). All groups showed GM atrophy compared to controls in ipsilateral hippocampus, bilateral parahippocampal gyri, frontal, occipital, parietal, and cerebellar areas. In the AED responders group, such findings were more restricted to areas ipsilateral to the epileptic focus and more widespread in the pharmacoresistant and remitting-relapsing groups. VBM pairwise comparisons showed areas with GM volume reduction in the pharmacoresistant and remitting-relapsing groups compared with AED responders in bilateral periorbital frontal (p < 0.01), cingulum (p < 0.05), and temporal lobe contralateral to the epileptic focus (p < 0.05).

CONCLUSIONS

Pharmacoresistant and remitting-relapsing groups presented a similar pattern of GM atrophy, which was more widespread compared with AED responders. Conversely, age at epilepsy onset was lower and initial seizure frequency was higher in pharmacoresistant patients.