Short TE downfield magnetic resonance spectroscopy in a mouse model of brain glioma.

PURPOSE: Enhanced cell proliferation in tumors can be associated with altered metabolic profiles and dramatic microenvironmental changes. Downfield magnetic resonance spectroscopy (MRS) has received increasing attention due to its ability to report on labile resonances of molecules not easily detected in upfield 1 H MRS. Image-selected-in-vivo-spectroscopy-relaxation enhanced MRS (iRE-MRS) was recently introduced for acquiring short echo-time (TE) spectra. Here, iRE-MRS was used to investigate in-vivo downfield spectra in glioma-bearing mice. METHODS: Experiments were performed in vivo in an immunocompetent glioma mouse model at 9.4 T using a cryogenic coil. iRE-MRS spectra were acquired in N = 6 glioma-bearing mice (voxel size = 2.23 mm3 ) and N = 6 control mice. Spectra were modeled by a sum of Lorentzian peaks simulating known downfield resonances, and differences between controls and tumors were quantified using relative peak areas. RESULTS: Short TE tumor spectra exhibited large qualitative differences compared to control spectra. Most peaks appeared modulated, with strong attenuation of NAA (∼7.82, 7.86 ppm) and changes in relative peak areas between 6.75 and 8.49 ppm. Peak areas tended to be smaller for DF6.83 , DF7.60 , DF8.18 and NAA; and larger for DF7.95 and DF8.24 . Differences were also detected in signals resonating above 8.5 ppm, assumed to arise from NAD+. CONCLUSIONS: In-vivo downfield 1 H iRE-MRS of mouse glioma revealed differences between controls and tumor bearing mice, including in metabolites which are not easily detectable in the more commonly investigated upfield spectrum. These findings motivate future downfield MRS investigations exploring pH and exchange contributions to these differences.

A whole brain longitudinal study in the YAC128 mouse model of Huntington's disease shows distinct trajectories of neurochemical, structural connectivity and volumetric changes.

Huntington's disease (HD) is a neurodegenerative disorder causing cognitive and motor impairments, evolving to death within 15-20 years after symptom onset. We previously established a mouse model with the entire human HD gene containing 128 CAG repeats (YAC128) which accurately recapitulates the natural history of the human disease. Defined time points in this natural history enable the understanding of longitudinal trajectories from the neurochemical and structural points of view using non-invasive high-resolution multi-modal imaging. Accordingly, we designed a longitudinal structural imaging (MRI and DTI) and spectroscopy (1H-MRS) study in YAC128, at 3, 6, 9 and 12 months of age, at 9.4 T. Structural analysis (MRI/DTI), confirmed that the striatum is the earliest affected brain region, but other regions were also identified through connectivity analysis (pre-frontal cortex, hippocampus, globus pallidus and thalamus), suggesting a striking homology with the human disease. Importantly, we found for the first time, a negative correlation between striatal and hippocampal changes only in YAC128. In fact, the striatum showed accelerated volumetric decay in HD, as opposed to the hippocampus. Neurochemical analysis of the HD striatum suggested early neurometabolic alterations in neurotransmission and metabolism, with a significant increase in striatal GABA levels, and specifically anticorrelated levels of N-acetyl aspartate and taurine, suggesting that the later is homeostatically adjusted for neuroprotection, as neural loss, indicated by the former, is progressing. These results provide novel insights into the natural history of HD and prove a valuable role for longitudinal multi-modal panels of structural and metabolite/neurotransmission in the YAC128 model.

Short echo time relaxation-enhanced MR spectroscopy reveals broad downfield resonances.

PURPOSE: Most MR spectroscopy (MRS) pulse sequences rely on broadband excitation with water saturation and typically focus on upfield signals. By contrast, the downfield spectrum, which contains many potentially useful resonances, is typically not targeted because conventional water-suppressed techniques indirectly saturate the labile protons through exchange. Relaxation-enhanced MRS (RE-MRS) uses frequency-selective excitation while actively avoiding bulk water perturbation, thereby enabling high-quality downfield spectroscopy. However, RE-MRS typically requires very long (typically >40 ms) echo times (TEs) due to its localization module, which inevitably decreases sensitivity and filters shorter T2 components. Here, we overcome this limitation by combining RE-MRS and image selected in vivo spectroscopy (ISIS) localization, abbreviated iRE-MRS, which in turn allows very short TEs (5 ms using our hardware). METHODS: Experiments were performed in vitro for validation as well as and in in vivo rat brains at 9.4T. RESULTS: The new iRE-MRS methodology was validated in phantoms where good performance was noted. When the downfield spectrum was investigated at short TEs in in vivo rat brains, iRE-MRS provided very high sensitivity; the ensuing downfield spectra encompassed numerous broad peaks, as well as a broad baseline. All downfield spectral peaks were highly attenuated by increasing TEs as well as by applying water saturation, although to different extent. The signal ratios also varied between TEs, suggesting that exchange rates are different among the downfield signals. CONCLUSIONS: Short-TE iRE 1 H downfield MRS opens new directions in the investigation of in vivo downfield metabolites and their role on healthy and disease processes.

Novel artefact removal algorithms for co-registered EEG/fMRI based on selective averaging and subtraction.

Co-registered EEG and functional MRI (EEG/fMRI) is a potential clinical tool for planning invasive EEG in patients with epilepsy. In addition, the analysis of EEG/fMRI data provides a fundamental insight into the precise physiological meaning of both fMRI and EEG data. Routine application of EEG/fMRI for localization of epileptic sources is hampered by large artefacts in the EEG, caused by switching of scanner gradients and heartbeat effects. Residuals of the ballistocardiogram (BCG) artefacts are similarly shaped as epileptic spikes, and may therefore cause false identification of spikes. In this study, new ideas and methods are presented to remove gradient artefacts and to reduce BCG artefacts of different shapes that mutually overlap in time. Gradient artefacts can be removed efficiently by subtracting an average artefact template when the EEG sampling frequency and EEG low-pass filtering are sufficient in relation to MR gradient switching (Gonçalves et al., 2007). When this is not the case, the gradient artefacts repeat themselves at time intervals that depend on the remainder between the fMRI repetition time and the closest multiple of the EEG acquisition time. These repetitions are deterministic, but difficult to predict due to the limited precision by which these timings are known. Therefore, we propose to estimate gradient artefact repetitions using a clustering algorithm, combined with selective averaging. Clustering of the gradient artefacts yields cleaner EEG for data recorded during scanning of a 3T scanner when using a sampling frequency of 2048 Hz. It even gives clean EEG when the EEG is sampled with only 256 Hz. Current BCG artefacts-reduction algorithms based on average template subtraction have the intrinsic limitation that they fail to deal properly with artefacts that overlap in time. To eliminate this constraint, the precise timings of artefact overlaps were modelled and represented in a sparse matrix. Next, the artefacts were disentangled with a least squares procedure. The relevance of this approach is illustrated by determining the BCG artefacts in a data set consisting of 29 healthy subjects recorded in a 1.5 T scanner and 15 patients with epilepsy recorded in a 3 T scanner. Analysis of the relationship between artefact amplitude, duration and heartbeat interval shows that in 22% (1.5T data) to 30% (3T data) of the cases BCG artefacts show an overlap. The BCG artefacts of the EEG/fMRI data recorded on the 1.5T scanner show a small negative correlation between HBI and BCG amplitude. In conclusion, the proposed methodology provides a substantial improvement of the quality of the EEG signal without excessive computer power or additional hardware than standard EEG-compatible equipment.

Revisiting the Potential of Alternating Repetition Time Balanced Steady-State Free Precession Imaging of the Abdomen at 3 T.

OBJECTIVE: The aim was to investigate the value of optimized 3-dimensional alternating repetition time balanced steady-state free precession (ATR-SSFP), as an alternative to conventional segmented balanced steady-state free precession (bSSFP) with fat suppression prepulse (FS-bSSFP), in single breath-hold abdominal magnetic resonance imaging at 3 T. METHODS: Bloch simulations were performed to determine the optimal flip angle (FA = 1-90 degrees) and τ (1-3) with respect to signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) between abdominal organs for ATR-SSFP. These were corroborated by phantom measurements for different T1/T2 values (5-47) as well as in a healthy volunteer. In addition, fat suppression efficiency was studied using phantom and volunteer measurements. The effect of resolution on image quality was studied in a healthy volunteer. Using the optimal settings, ATR-SSFP images as well as FS-bSSFP images were obtained in 15 pancreatic cancer patients. For 10 structures of interest, the signal ratio with respect to the pancreas was computed and compared between both sequences. Finally, 10 items on image quality (fat suppression, artifacts, and sharpness) and tissue conspicuity (ducts, vessels, and duodenum) were scored by 2 abdominal radiologists for both image sequences. RESULTS: The results of simulations, phantom measurements, and volunteer measurements showed that, considering scan time, fat suppression, and clinical relevance, the ideal settings for ATR-SSFP were as follows: τ = 3; TR1 = 3.46 milliseconds; radiofrequency phase cycling 0, 180, 180, 0 degrees; and FA = 13-16 degrees (highest SNR) and 24-26 degrees (highest CNR). The optimized feasible additional settings implemented for patient scans were FA = 18 degrees and resolution = 1.4 × 1.4 × 1.4 mm. In patients, the signal ratios of both ATR-SSFP and FS-bSSFP were comparable and had a T2-like contrast behavior, although more accentuated in ATR-SSFP. The ATR-SSFP scored significantly higher than FS-bSSFP for 9 of 10 items scored. CONCLUSIONS: For single breath-hold abdominal imaging at 3 T, ATR-SSFP performs best with τ = 3 and an FA between 13 degrees (highest SNR) and 26 degrees (highest CNR). The scoring of both abdominal radiologists indicated that, at τ = 3, FA = 18 degrees, and 1.4 × 1.4 × 1.4 mm resolution, ATR-SSFP was preferred over conventional FS-bSSFP with similar settings.

Dynamics of epileptic activity in a peculiar case of childhood absence epilepsy and correlation with thalamic levels of GABA.

OBJECTIVES: Childhood absence epilepsy (CAE) is a syndrome with well-defined electroclinical features but unknown pathological basis. An increased thalamic tonic GABA inhibition has recently been discovered on animal models (Cope et al., 2009), but its relevance for human CAE is unproven. METHODS: We studied an 11-year-old boy, presenting the typical clinical features of CAE, but spike-wave discharges (SWD) restricted to one hemisphere. RESULTS: High-resolution EEG failed to demonstrate independent contralateral hemisphere epileptic activity. Consistently, simultaneous EEG-fMRI revealed the typical thalamic BOLD activation, associated with caudate and default mode network deactivation, but restricted to the hemisphere with SWD. Cortical BOLD activations were localized on the ipsilateral pars transverse. Magnetic resonance spectroscopy, using MEGA-PRESS, showed that the GABA/creatine ratio was 2.6 times higher in the hemisphere with SWD than in the unaffected one, reflecting a higher GABA concentration. Similar comparisons for the patient's occipital cortex and thalamus of a healthy volunteer yielded asymmetries below 25%. SIGNIFICANCE: In a clinical case of CAE with EEG and fMRI-BOLD manifestations restricted to one hemisphere, we found an associated increase in thalamic GABA concentration consistent with a role for this abnormality in human CAE.

Differences in MEG/EEG epileptic spike yields explained by regional differences in signal-to-noise ratios.

Controversy remains regarding the preferred modality, magnetoencephalography (MEG) or EEG, for the presurgical evaluation of patients with epilepsy. In general, it appears that the spike yields for MEG and EEG are similar in patients with temporal lobe epilepsy, and that for neocortical epilepsy the MEG spike yields may be larger than for EEG. In general, MEG/EEG spike yields depend on factors such as (1) the number of sensors, (2) the source depth and orientation, (3) the background activity, and (4) the smearing of the potential fields due to variations in skull resistivity in EEG. Because the contribution of all these factors are of the same order of magnitude, the authors took them all into account to predict the signal-to-noise ratio (SNR) of hypothetical spikes in different brain areas. In this study, it was assumed that spike sensitivity (and therefore the spike yield) increases with SNR. The estimated SNR values at temporal areas were comparable for MEG and EEG, which is in agreement with clinical findings that spike yields in temporal lobe epilepsy are similar. Furthermore, the SNR of MEG was substantially higher in the frontal area, indicating that in frontal lobe epilepsy MEG may be highly relevant to prescreening of epilepsy patients. This model-based approach indicates that SNR mapping clarifies differences between MEG and EEG findings that are difficult to understand on the basis of patient studies only.

In vivo measurement of the brain and skull resistivities using an EIT-based method and realistic models for the head.

In vivo measurements of equivalent resistivities of skull (rho(skull)) and brain (rho(brain)) are performed for six subjects using an electric impedance tomography (EIT)-based method and realistic models for the head. The classical boundary element method (BEM) formulation for EIT is very time consuming. However, the application of the Sherman-Morrison formula reduces the computation time by a factor of 5. Using an optimal point distribution in the BEM model to optimize its accuracy, decreasing systematic errors of numerical origin, is important because cost functions are shallow. Results demonstrate that rho(skull)/rho(brain) is more likely to be within 20 and 50 rather than equal to the commonly accepted value of 80. The variation in rho(brain)(average = 301 omega x cm, SD = 13%) and rho(skull)(average = 12230 omega x cm, SD = 18%) is decreased by half, when compared with the results using the sphere model, showing that the correction for geometry errors is essential to obtain realistic estimations. However, a factor of 2.4 may still exist between values of rho(skull)/rho(brain) corresponding to different subjects. Earlier results show the necessity of calibrating rho(brain) and rho(skull) by measuring them in vivo for each subject, in order to decrease errors associated with the electroencephalogram inverse problem. We show that the proposed method is suited to this goal.

MR fat fraction mapping: a simple biomarker for liver steatosis quantification in nonalcoholic fatty liver disease patients.

RATIONALE AND OBJECTIVES: To assess the performance, postprocessing time, and intra- and interobserver agreement of a simple magnetic resonance-based mapping technique to quantify liver fat. MATERIALS AND METHODS: This prospective, single-center study included 26 patients who were overweight with type 2 diabetes and at risk for nonalcoholic fatty liver disease. Mapping of the liver was based on a triple echo gradient-echo sequence, and (1)H magnetic resonance spectroscopy was used as the reference standard. The nonparametric Spearman correlation coefficient and the Wilcoxon test were used for comparisons between mapping and spectroscopy. The mapping was assessed for its predictive performance using the area under the curve of a receiver operating characteristic curve. Intraclass correlation coefficients were used to calculate intra- and interobserver's agreement for mapping measurements. RESULTS: Patients had a mean fat percentage of 11.7% (range, 2-35.4%). A strong correlation was seen between mapping and spectroscopy (r = 0.89, P < .0001). A cutoff of 6.9% for fat fraction mapping was found to diagnose steatosis with 93% sensitivity and 100% specificity with an area under the curve of 0.99. Mapping of the liver had shorter acquisition and post-processing times than spectroscopy (5 min vs. 38 min; P < .0001). Mapping measurements had an intra- and interobserver agreement of 0.98 and 0.99, respectively. CONCLUSIONS: The magnetic resonance-based liver mapping can accurately quantify liver fat with a cutoff value of 6.9% and excellent intra- and interobserver agreement. This mapping technique, with its simple methodology and short postprocessing time, has the potential to be included in routine abdominal protocols.

Correction for desynchronization of EEG and fMRI clocks through data interpolation optimizes artifact reduction.

Co-registration of EEG (Electroencephalogram)- and fMRI (functional magnetic resonance imaging) remains a challenge due to the large artifacts induced on the EEG by the MR (magnetic resonance) sequence gradient and RF pulses. We present an algorithm, based on the average-subtraction method, which is able to correct EEG data for gradient and RF pulse artifacts. We optimized artifact reduction by correcting the misalignment of EEG and fMRI data samples, resulting from the asynchronous sampling of EEG and fMRI data, through interpolation of EEG data. A clustering algorithm is proposed to account for the variability of the pulse artifact. Results show that the algorithm was able to keep the spontaneous brain activity while removing gradient and pulse artifacts with only a subtraction of selectively averaged data. Pulse artifact clustering showed that most of the variability was due to the time jitter of the pulse artifact markers. We show that artifact reduction by average-subtraction is optimized by interpolating the EEG data to correct for asynchronously sampled EEG and fMRI data.