Irritable bowel syndrome in women: Association between decreased insular subregion volumes and gastrointestinal symptoms.

OBJECTIVE: Irritable bowel syndrome (IBS) is a chronic pain disorder characterized by disturbed interactions between the gut and the brain with depression as a common comorbidity. In both IBS and depression, structural brain alterations of the insular cortices, key structures for pain processing and interoception, have been demonstrated but the specificity of these findings remains unclear. We compared the gray matter volume (GMV) of insular cortex (IC) subregions in IBS women and healthy controls (HC) and examined relations to gastrointestinal (GI) symptoms and glutamate + glutamine (Glx) concentrations. We further analyzed GMV of IC subregions in women with major depression (MDD) compared to HC and addressed possible differences between depression, IBS, IBS with depression and HC. DESIGN: Women with IBS (n = 75), MDD (n = 41) and their respective HC (n = 39 and n = 43) underwent structural brain MRI. IC subregion volumes were estimated using statistical parametric mapping software. General linear model approaches were applied to IC volumetric data and FDR-corrected partial correlation analyses assessed relations between GMV, GI symptoms and Glx concentrations. RESULTS: IBS patients had significantly smaller IC subregions than HC in both hemispheres but there was no significant difference between MDD compared with IBS and HC for any insular subregion. In IBS, the dorsal anterior insular volumes were negatively correlated with symptoms of nausea and pain, and the left ventral subregion showed a positive correlation with straining to defecate, while the posterior subregion volumes showed no relation to symptoms. In the anterior insula, concentration of Glx showed positive correlations with GMV bilaterally in HC and with GMV of the right anterior insula in IBS. CONCLUSION: As the interoceptive cortex, the insula shows substantial and disease-specific structural differences in patients with chronic interoceptive visceral pain. Particularly changes in the anterior proportions might be related to chronic exposure to or enhanced salience towards adverse interoceptive visceral signals and could be linked to biochemical changes, calling for further multimodal and longitudinal work.

Comparison of linear combination modeling strategies for edited magnetic resonance spectroscopy at 3 T.

J-difference-edited spectroscopy is a valuable approach for the in vivo detection of γ-aminobutyric-acid (GABA) with magnetic resonance spectroscopy (MRS). A recent expert consensus article recommends linear combination modeling (LCM) of edited MRS but does not give specific details regarding implementation. This study explores different modeling strategies to adapt LCM for GABA-edited MRS. Sixty-one medial parietal lobe GABA-edited MEGA-PRESS spectra from a recent 3-T multisite study were modeled using 102 different strategies combining six different approaches to account for co-edited macromolecules (MMs), three modeling ranges, three baseline knot spacings, and the use of basis sets with or without homocarnosine. The resulting GABA and GABA+ estimates (quantified relative to total creatine), the residuals at different ranges, standard deviations and coefficients of variation (CVs), and Akaike information criteria, were used to evaluate the models' performance. Significantly different GABA+ and GABA estimates were found when a well-parameterized MM3co basis function was included in the model. The mean GABA estimates were significantly lower when modeling MM3co , while the CVs were similar. A sparser spline knot spacing led to lower variation in the GABA and GABA+ estimates, and a narrower modeling range-only including the signals of interest-did not substantially improve or degrade modeling performance. Additionally, the results suggest that LCM can separate GABA and the underlying co-edited MM3co . Incorporating homocarnosine into the modeling did not significantly improve variance in GABA+ estimates. In conclusion, GABA-edited MRS is most appropriately quantified by LCM with a well-parameterized co-edited MM3co basis function with a constraint to the nonoverlapped MM0.93 , in combination with a sparse spline knot spacing (0.55 ppm) and a modeling range of 0.5-4 ppm.

Influence of editing pulse flip angle on J-difference MR spectroscopy.

PURPOSE: To investigate the editing-pulse flip angle (FA) dependence of editing efficiency and ultimately to maximize the edited signal of commonly edited MR spectroscopy (MRS) signals, such as gamma-aminobutyric acid (GABA) and lactate. METHODS: Density-matrix simulations were performed for a range of spin systems to find the editing-pulse FA for maximal editing efficiency. Simulations were confirmed by phantom experiments and in vivo measurements in 10 healthy participants using a 3T Philips scanner. Four MEGA-PRESS in vivo measurements targeting GABA+ and lactate were performed, comparing the conventional editing-pulse FA (FA = 180°) to the optimal one suggested by simulations (FA = 210°). RESULTS: Simulations and phantom experiments show that edited GABA and lactate signals are maximal at FA = 210°. Compared to conventional editing (FA = 180°), in vivo signals from GABA+ and lactate signals increase on average by 8.5% and 9.3%, respectively. CONCLUSION: Increasing the FA of editing-pulses in the MEGA-PRESS experiment from 180° to 210° increases the edited signals from GABA+ and lactate by about 9% in vivo.

The macromolecular MR spectrum does not change with healthy aging.

PURPOSE: To acquire the mobile macromolecule (MM) spectrum from healthy participants, and to investigate changes in the signals with age and sex. METHODS: 102 volunteers (49 M/53 F) between 20 and 69 years were recruited for in vivo data acquisition in the centrum semiovale (CSO) and posterior cingulate cortex (PCC). Spectral data were acquired at 3T using PRESS localization with a voxel size of 30 × 26 × 26 mm3 , pre-inversion (TR/TI 2000/600 ms) and CHESS water suppression. Metabolite-nulled spectra were modeled to eliminate residual metabolite signals, which were then subtracted out to yield a "clean" MM spectrum using the Osprey software. Pearson's correlation coefficient was calculated between integrals and age for the 14 MM signals. One-way ANOVA was performed to determine differences between age groups. An independent t-test was carried out to determine differences between sexes. RESULTS: MM spectra were successfully acquired in 99 (CSO) and 96 (PCC) of 102 subjects. No significant correlations were seen between age and MM signals. One-way ANOVA also suggested no age-group differences for any MM peak (all p > .004). No differences were observed between sex groups. WM and GM voxel fractions showed a significant (p < .05) negative linear association with age in the WM-predominant CSO (R = -0.29) and GM-predominant PCC regions (R = -0.57) respectively while CSF increased significantly with age in both regions. CONCLUSION: Our findings suggest that a pre-defined MM basis function can be used for linear combination modeling of metabolite data from different age and sex groups.

Comparison of different linear-combination modeling algorithms for short-TE proton spectra.

Short-TE proton MRS is used to study metabolism in the human brain. Common analysis methods model the data as a linear combination of metabolite basis spectra. This large-scale multi-site study compares the levels of the four major metabolite complexes in short-TE spectra estimated by three linear-combination modeling (LCM) algorithms. 277 medial parietal lobe short-TE PRESS spectra (TE = 35 ms) from a recent 3 T multi-site study were preprocessed with the Osprey software. The resulting spectra were modeled with Osprey, Tarquin and LCModel, using the same three vendor-specific basis sets (GE, Philips and Siemens) for each algorithm. Levels of total N-acetylaspartate (tNAA), total choline (tCho), myo-inositol (mI) and glutamate + glutamine (Glx) were quantified with respect to total creatine (tCr). Group means and coefficient of variations of metabolite estimates agreed well for tNAA and tCho across vendors and algorithms, but substantially less so for Glx and mI, with mI systematically estimated as lower by Tarquin. The cohort mean coefficient of determination for all pairs of LCM algorithms across all datasets and metabolites was R2¯ = 0.39, indicating generally only moderate agreement of individual metabolite estimates between algorithms. There was a significant correlation between local baseline amplitude and metabolite estimates (cohort mean R2¯ = 0.10). While mean estimates of major metabolite complexes broadly agree between linear-combination modeling algorithms at group level, correlations between algorithms are only weak-to-moderate, despite standardized preprocessing, a large sample of young, healthy and cooperative subjects, and high spectral quality. These findings raise concerns about the comparability of MRS studies, which typically use one LCM software and much smaller sample sizes.

Frequency and phase correction of J-difference edited MR spectra using deep learning.

PURPOSE: To investigate whether a deep learning-based (DL) approach can be used for frequency-and-phase correction (FPC) of MEGA-edited MRS data. METHODS: Two neural networks (1 for frequency, 1 for phase) consisting of fully connected layers were trained and validated using simulated MEGA-edited MRS data. This DL-FPC was subsequently tested and compared to a conventional approach (spectral registration [SR]) and to a model-based SR implementation (mSR) using in vivo MEGA-edited MRS datasets. Additional artificial offsets were added to these datasets to further investigate performance. RESULTS: The validation showed that DL-based FPC was capable of correcting within 0.03 Hz of frequency and 0.4°of phase offset for unseen simulated data. DL-based FPC performed similarly to SR for the unmanipulated in vivo test datasets. When additional offsets were added to these datasets, the networks still performed well. However, although SR accurately corrected for smaller offsets, it often failed for larger offsets. The mSR algorithm performed well for larger offsets, which was because the model was generated from the in vivo datasets. In addition, the computation times were much shorter using DL-based FPC or mSR compared to SR for heavily distorted spectra. CONCLUSION: These results represent a proof of principle for the use of DL for preprocessing MRS data.

Correcting frequency and phase offsets in MRS data using robust spectral registration.

An algorithm for retrospective correction of frequency and phase offsets in MRS data is presented. The algorithm, termed robust spectral registration (rSR), contains a set of subroutines designed to robustly align individual transients in a given dataset even in cases of significant frequency and phase offsets or unstable lipid contamination and residual water signals. Data acquired by complex multiplexed editing approaches with distinct subspectral profiles are also accurately aligned. Automated removal of unstable lipid contamination and residual water signals is applied first, when needed. Frequency and phase offsets are corrected in the time domain by aligning each transient to a weighted average reference in a statistically optimal order using nonlinear least-squares optimization. The alignment of subspectra in edited datasets is performed using an approach that specifically targets subtraction artifacts in the frequency domain. Weighted averaging is then used for signal averaging to down-weight poorer-quality transients. Algorithm performance was assessed on one simulated and 67 in vivo pediatric GABA-/GSH-edited HERMES datasets and compared with the performance of a multistep correction method previously developed for aligning HERMES data. The performance of the novel approach was quantitatively assessed by comparing the estimated frequency/phase offsets against the known values for the simulated dataset or by examining the presence of subtraction artifacts in the in vivo data. Spectral quality was improved following robust alignment, especially in cases of significant spectral distortion. rSR reduced more subtraction artifacts than the multistep method in 64% of the GABA difference spectra and 75% of the GSH difference spectra. rSR overcomes the major challenges of frequency and phase correction.

A pilot study of essential tremor: cerebellar GABA+/Glx ratio is correlated with tremor severity.

OBJECTIVE: Essential tremor is a common movement disorder with an unclear origin. Emerging evidence suggests the role of the cerebellum and the thalamus in tremor pathophysiology. We examined the two main neurotransmitters acting inhibitory (GABA+) and excitatory (Glx) respectively, in the thalamus and cerebellum, in patients diagnosed with severe essential tremor. Furthermore, we also investigated the relationship between determined neurotransmitter concentrations and tremor severity in the essential tremor patients. METHODS: Ten essential tremor patients (prior to deep brain stimulation surgery) and six healthy controls, were scanned using a 3 T MR system. GABA+ and Glx concentrations were measured using magnetic resonance spectroscopy (MRS) performed using single voxel MEGA-PRESS. For the purpose of assessing the tremor severity, the essential tremor rating scale (ETRS) was used in accordance with Fahn, Tolosa, and Marin. RESULTS: We demonstrated that the cerebellar GABA+/Glx ratio was positively correlated to the ETRS (r = 0.70, p = 0.03) in essential tremor. Cerebellar and thalamic GABA+ and Glx concentrations did not show any significant difference when comparing essential tremor patients with healthy controls, at the group level. CONCLUSION: We demonstrated a positive correlation between increasing tremor disability and the ratio of GABA+/ Glx in the cerebellum of essential tremor patients. This highlights the impact of an altered balance of the excitatory and inhibitory neurotransmitters in tremor severity. Rather than a change in GABA+, which was constant, we attribute this finding to an overall decrease of Glx.

Osprey: Open-source processing, reconstruction & estimation of magnetic resonance spectroscopy data.

BACKGROUND: Processing and quantitative analysis of magnetic resonance spectroscopy (MRS) data are far from standardized and require interfacing with third-party software. Here, we present Osprey, a fully integrated open-source data analysis pipeline for MRS data, with seamless integration of pre-processing, linear-combination modelling, quantification, and data visualization. NEW METHOD: Osprey loads multiple common MRS data formats, performs phased-array coil combination, frequency-and phase-correction of individual transients, signal averaging and Fourier transformation. Linear combination modelling of the processed spectrum is carried out using simulated basis sets and a spline baseline. The MRS voxel is coregistered to an anatomical image, which is segmented for tissue correction and quantification is performed based upon modelling parameters and tissue segmentation. The results of each analysis step are visualized in the Osprey GUI. The analysis pipeline is demonstrated in 12 PRESS, 11 MEGA-PRESS, and 8 HERMES datasets acquired in healthy subjects. RESULTS: Osprey successfully loads, processes, models, and quantifies MRS data acquired with a variety of conventional and spectral editing techniques. COMPARISON WITH EXISTING METHOD(S): Osprey is the first MRS software to combine uniform pre-processing, linear-combination modelling, tissue correction and quantification into a coherent ecosystem. Compared to existing compiled, often closed-source modelling software, Osprey's open-source code philosophy allows researchers to integrate state-of-the-art data processing and modelling routines, and potentially converge towards standardization of analysis. CONCLUSIONS: Osprey combines robust, peer-reviewed data processing methods into a modular workflow that is easily augmented by community developers, allowing the rapid implementation of new methods.

Elucidating the putative link between prefrontal neurotransmission, functional connectivity, and affective symptoms in irritable bowel syndrome.

Altered neural mechanisms are well-acknowledged in irritable bowel syndrome (IBS), a disorder of brain-gut-communication highly comorbid with anxiety and depression. As a key hub in corticolimbic inhibition, medial prefrontal cortex (mPFC) may be involved in disturbed emotion regulation in IBS. However, aberrant mPFC excitatory and inhibitory neurotransmission potentially contributing to psychological symptoms in IBS remains unknown. Using quantitative magnetic resonance spectroscopy (qMRS), we compared mPFC glutamate + glutamine (Glx) and γ-aminobutyric acid (GABA+) concentrations in 64 women with IBS and 32 age-matched healthy women (HCs) and investigated their association with anxiety and depression in correlational and subgroup analyses. Applying functional magnetic resonance imaging (fMRI), we explored whether altered neurotransmission was paralleled by aberrant mPFC resting-state functional connectivity (FC). IBS patients did not differ from HCs with respect to mPFC GABA+ or Glx levels. Anxiety was positively associated with mPFC GABA+ concentrations in IBS, whereas Glx was unrelated to psychological or gastrointestinal symptoms. Subgroup comparisons of patients with high or low anxiety symptom severity and HCs revealed increased GABA+ in patients with high symptom severity, and lower mPFC FC with adjacent anterior cingulate cortex (ACC), a crucial region of emotion modulation. Our findings provide novel evidence that altered prefrontal inhibitory neurotransmission may be linked to anxiety in IBS.

Reduced excitatory neurotransmitter levels in anterior insulae are associated with abdominal pain in irritable bowel syndrome.

Irritable bowel syndrome (IBS) is a visceral pain condition with psychological comorbidity. Brain imaging studies in IBS demonstrate altered function in anterior insula (aINS), a key hub for integration of interoceptive, affective, and cognitive processes. However, alterations in aINS excitatory and inhibitory neurotransmission as putative biochemical underpinnings of these functional changes remain elusive. Using quantitative magnetic resonance spectroscopy, we compared women with IBS and healthy women (healthy controls [HC]) with respect to aINS glutamate + glutamine (Glx) and γ-aminobutyric acid (GABA+) concentrations and addressed possible associations with symptoms. Thirty-nine women with IBS and 21 HC underwent quantitative magnetic resonance spectroscopy of bilateral aINS to assess Glx and GABA+ concentrations. Questionnaire data from all participants and prospective symptom-diary data from patients were obtained for regression analyses of neurotransmitter concentrations with IBS-related and psychological parameters. Concentrations of Glx were lower in IBS compared with HC (left aINS P < 0.05, right aINS P < 0.001), whereas no group differences were detected for GABA+ concentrations. Lower right-lateralized Glx concentrations in patients were substantially predicted by longer pain duration, while less frequent use of adaptive pain-coping predicted lower Glx in left aINS. Our findings provide first evidence for reduced excitatory but unaltered inhibitory neurotransmitter levels in aINS in IBS. The results also indicate a functional lateralization of aINS with a stronger involvement of the right hemisphere in perception of abdominal pain and of the left aINS in cognitive pain regulation. Our findings suggest that glutaminergic deficiency may play a role in pain processing in IBS.

Retrospective artifact elimination in MEGA-PRESS using a correlation approach.

PURPOSE: To develop a method for retrospective artifact elimination of MRS data. This retrospective method was based on an approach that combines jackknife analyses with the correlation of spectral windows, and therefore termed "JKC." METHODS: Twelve healthy volunteers performed 3 separate measurement protocols using a 3T MR system. One protocol consisted of 2 cerebellar MEGA-PRESS measurements: 1 reference and 1 measurement including head movements. One-third of the artifact-influenced datasets were treated as training data for the implementation the JKC method, and the rest were used for validation. RESULTS: The implemented JKC method correctly characterized most of the validation data. Additionally, after elimination of the detected artifacts, the resulting concentrations were much closer to those computed for the reference datasets. Moreover, when the JKC method was applied to the reference data, the estimated concentrations were not affected, compared with standard averaging. CONCLUSION: The implemented JKC method can be applied without any extra cost to MRS data, regardless of whether the dataset has been contaminated by artifacts. Furthermore, the results indicate that the JKC method could be used as a quality control of a dataset, or as an indication of whether a shift in voxel placement has occurred during the measurement.

Evidence for cognitive resource imbalance in adolescents with narcolepsy.

The study investigated brain activity changes during performance of a verbal working memory task in a population of adolescents with narcolepsy. Seventeen narcolepsy patients and twenty healthy controls performed a verbal working memory task during simultaneous fMRI and EEG acquisition. All subjects also underwent MRS to measure GABA and Glutamate concentrations in the medial prefrontal cortex. Activation levels in the default mode network and left middle frontal gyrus were examined to investigate whether narcolepsy is characterized by an imbalance in cognitive resources. Significantly increased deactivation within the default mode network during task performance was observed for the narcolepsy patients for both the encoding and recognition phases of the task. No evidence for task performance deficits or reduced activation within the left middle frontal gyrus was noted for the narcolepsy patients. Correlation analyses between the spectroscopy and fMRI data indicated that deactivation of the anterior aspect of the default mode in narcolepsy patients correlated more with increased concentrations of Glutamate and decreased concentrations of GABA. In contrast, deactivation in the default mode was correlated with increased concentrations of GABA and decreased concentrations of Glutamate in controls. The results suggested that narcolepsy is not characterized by a deficit in working memory but rather an imbalance of cognitive resources in favor of monitoring and maintaining attention over actual task performance. This points towards dysregulation within the sustained attention system being the origin behind self-reported cognitive difficulties in narcolepsy.

How does motion affect GABA-measurements? Order statistic filtering compared to conventional analysis of MEGA-PRESS MRS.

PURPOSE: The aim of this study was to evaluate two post-processing techniques applied to MRS MEGA-PRESS data influenced by motion-induced artifacts. In contrast to the conventional averaging technique, order statistic filtering (OSF) is a known method for artifact reduction. Therefore, this method may be suitable to incorporate in the GABA quantification. METHODS: Twelve healthy volunteers were scanned three times using a 3 T MR system. One measurement protocol consisted of two MEGA-PRESS measurements, one reference measurement and one measurement including head motions. The resulting datasets were analyzed with the standard averaging technique and with the OSF-technique in two schemes; filtering phase cycles 'RAW PC' and filtering dynamics 'RAW Dyn'. RESULTS: The datasets containing artifacts resulted in an underestimation of the concentrations. There was a trend for the OSF-technique to compensate for this reduction when quantifying SNR-intense signals. However, there was no indication that OSF improved the estimated GABA concentrations. Moreover, when only considering the reference measurements, the OSF technique was equally as effective as averaging, which suggests that the techniques are interchangeable. CONCLUSION: OSF performed equally well as the conventional averaging technique for low-SNR signals. For high-SNR signals, OSF performed better and thus could be considered for routine usage.