UNASSIGNED: Evidence from animal and human studies suggests glutamatergic dysfunction in posttraumatic stress disorder (PTSD). The purpose of this study was to investigate glutamate abnormalities in the dorsolateral prefrontal cortex (DLFPC) of individuals with PTSD using 7T MRS, which has better spectral resolution and signal-to-noise ratio than lower field strengths, thus allowing for better spectral quality and higher sensitivity. We hypothesized that individuals with PTSD would have lower glutamate levels compared to trauma-exposed individuals without PTSD and individuals without trauma exposure. Additionally, we explored potential alterations in other neurometabolites and the relationship between glutamate and psychiatric symptoms.
UNASSIGNED: Individuals with PTSD (n = 27), trauma-exposed individuals without PTSD (n = 27), and individuals without trauma exposure (n = 26) underwent 7T MRS to measure glutamate and other neurometabolites in the left DLPFC. The severities of PTSD, depression, anxiety, and dissociation symptoms were assessed.
UNASSIGNED: We found that glutamate was lower in the PTSD and trauma-exposed groups compared to the group without trauma exposure. Furthermore, N-acetylaspartate (NAA) was lower and lactate was higher in the PTSD group compared to the group without trauma exposure. Glutamate was negatively correlated with depression symptom severity in the PTSD group. Glutamate was not correlated with PTSD symptom severity.
UNASSIGNED: In this first 7T MRS study of PTSD, we observed altered concentrations of glutamate, NAA, and lactate. Our findings provide evidence for multiple possible pathological processes in individuals with PTSD. High-field MRS offers insight into the neurometabolic alterations associated with PTSD and is a powerful tool to probe trauma- and stress-related neurotransmission and metabolism in vivo.

Gamma-aminobutyric acid (GABA), the most important inhibitory neurotransmitter in the human brain, has long been considered essential in human behavior in general and learning in particular. GABA concentration can be quantified using magnetic resonance spectroscopy (MRS). Using this technique, numerous studies have reported associations between baseline GABA levels and various human behaviors. However, regional GABA concentration is not fixed and may exhibit rapid modulation as a function of environmental factors. Hence, quantification of GABA levels at several time points during the performance of tasks can provide insights into the dynamics of GABA levels in distinct brain regions. This review reports on findings from studies using repeated measures (n = 41) examining the dynamic modulation of GABA levels in humans in response to various interventions in the perceptual, motor, and cognitive domains to explore associations between GABA modulation and human behavior. GABA levels in a specific brain area may increase or decrease during task performance or as a function of learning, depending on its precise involvement in the process under investigation. Here, we summarize the available evidence and derive two overarching hypotheses regarding the role of GABA modulation in performance and learning. Firstly, training-induced increases in GABA levels appear to be associated with an improved ability to differentiate minor perceptual differences during perceptual learning. This observation gives rise to the \'GABA increase for better neural distinctiveness hypothesis\'. Secondly, converging evidence suggests that reducing GABA levels may play a beneficial role in effectively filtering perceptual noise, enhancing motor learning, and improving performance in visuomotor tasks. Additionally, some studies suggest that the reduction of GABA levels is related to better working memory and successful reinforcement learning. These observations inspire the \'GABA decrease to boost learning hypothesis\', which states that decreasing neural inhibition through a reduction of GABA in dedicated brain areas facilitates human learning. Additionally, modulation of GABA levels is also observed after short-term physical exercise. Future work should elucidate which specific circumstances induce robust GABA modulation to enhance neuroplasticity and boost performance.

Cognitive flexibility represents the capacity to switch among different mental schemes, providing an adaptive advantage to a changing environment. The neural underpinnings of this executive function have been deeply studied in humans through fMRI, showing that the left inferior frontal cortex (IFC) and the left inferior parietal lobule (IPL) are crucial. Here, we investigated the inhibitory-excitatory balance in these regions by means of γ-aminobutyric acid (GABA+) and glutamate + glutamine (Glx), measured with magnetic resonance spectroscopy, during a cognitive flexibility task and its relationship with the performance level and the local task-induced blood oxygenation level-dependent (BOLD) response in 40 young (18-35 years; 26 female) and 40 older (18-35 years; 21 female) human adults. As the IFC and the IPL are richly connected regions, we also examined whole-brain effects associated with their local metabolic activity. Results did not show absolute metabolic modulations associated with flexibility performance, but the performance level was related to the direction of metabolic modulation in the IPL with opposite patterns in young and older individuals. The individual inhibitory-excitatory balance modulation showed an inverse relationship with the local BOLD response in the IPL. Finally, the modulation of inhibitory-excitatory balance in IPL was related to whole-brain effects only in older individuals. These findings show disparities in the metabolic mechanisms underlying cognitive flexibility in young and older adults and their association with the performance level and BOLD response. Such metabolic differences are likely to play a role in executive functioning during aging and specifically in cognitive flexibility.

BACKGROUND: Acute ischemic stroke causes irreversible damage to the brain parenchyma surrounded by salvageable tissue known as the ischemic penumbra. Magnetic resonance imaging (MRI), particularly the mismatch between abnormal diffusion-weighted imaging (DWI) signals and normal fluid-attenuated inversion recovery (FLAIR) signals, plays a critical role in detecting ischemic penumbra. It also allows for the identification of patients who may benefit from reperfusion therapy. Hence, this prospective cohort study aimed to explore the correlation between DWI-FLAIR mismatch and clinical outcomes in acute ischemic stroke patients, specifically those with delayed or uncertain symptom onset, offering potential insights into reperfusion therapy.
METHODS: A total of 38 thrombotic stroke patients aged above 18 were included in this prospective cohort study. Baseline data, including demographics, lifestyle factors, and medical history, were recorded. DWI-FLAIR mismatch was evaluated through brain MRI within 4.5 hours to 12 hours of symptom onset.
RESULTS:  Of the cohort, 63.2% were males, predominantly in the 61-70 age group. Smoking and alcohol consumption were reported by 15.79% each. DWI-FLAIR mismatch was present in 20 out of 38 subjects. No statistically significant differences were noted in the mean National Institutes of Health Stroke Scale (NIHSS) and Modified Rankin Scale (MRS) scores between subjects with and without DWI-FLAIR mismatch. Thrombolysis in wake-up stroke subjects demonstrated a substantial reduction in mean MRS at discharge (1.29±0.95) and at six to eight weeks (1.71±1.11), suggesting potential benefits on functional outcomes.
CONCLUSIONS:  The prevalence of DWI-FLAIR mismatch was seen in the majority of patients beyond their window period and also showed beneficiary outcomes with a mean reduction in NHISS and MRS scores following thrombolysis.

暂无摘要。

OBJECTIVE: This study aimed to determine the risk factors and stroke subtypes for young ischemic stroke patients and their outcomes at the time of discharge.
METHODS: This is a retrospective cross-sectional study of ischemic stroke patients (n = 264) between the age groups of 18 and 45. The study population was divided into two broad age groups: 18 to 35 years and 36 to 45 years; and compared based on demographics, risk factors, the Trial of Org 10172 in Acute Stroke Treatment (TOAST) classification, and outcomes. The outcomes were compared based on the National Institutes of Health Stroke Scale (NIHSS) and Modified Rankin Scale (MRS) systems at the time of admission and discharge.
RESULTS: The mean age of patients was 37.84±6.19 years. The male-to-female ratio was 2.5:1. The most common vascular risk factors identified were diabetes (29.16%), hypertension (49.62%), dyslipidaemia (DLP, 44.4%), and smoking (10.9%). The most common TOAST subtype was large vessel disease (38.63%), followed by the undetermined category (35.6%). The elderly group showed a high proportion of strokes secondary to small vessel disease (14.13%; p = 0.03), while cardioembolic strokes were common in the female subgroup (p = 0.05). The majority of strokes were in the anterior circulation (66.6%) as compared to the posterior (25.75%), and nearly 50% of the patients had intracranial disease. Overall, there was a favourable MRS outcome at discharge.
CONCLUSIONS: Conventional vascular risk factors are equally prevalent, even among young stroke patients. The benchmark for young stroke age is showing a downward shift as more stroke patients above the age of 35 are showing similar risk factor trends as those of their older counterparts. The majority of stroke burden still falls under the undermined category, which requires aggressive risk factor identification and management.

We aim to assess a straightforward technique to enhance spectral quality in the brain, particularly in the cerebellum, during 7 T MRI scans. This is achieved through a wireless RF array insert designed to mitigate signal dropouts caused by the limited transmit field efficiency in the inferior part of the brain. We recently developed a wireless RF array to improve MRI and 1H-MRS at 7 T by augmenting signal via inductive coupling between the wireless RF array and the MRI coil. In vivo experiments on a Siemens 7 T whole-body human scanner with a Nova 1Tx/32Rx head coil quantified the impact of the dorsal cervical array in improving signal in the posterior fossa, including the cerebellum, where the transmit efficiency of the coil is inherently low. The 1H-MRS experimental protocol consisted of paired acquisition of data sets, both with and without the RF array, using the semi-LASER and SASSI sequences. The overall results indicate that the localized 1H-MRS is improved significantly in the presence of the array. Comparison of in vivo 1H-MRS plots in the presence versus absence of the array demonstrated an average SNR enhancement of a factor of 2.2. LCModel analysis reported reduced Cramér-Rao lower bounds, indicating more confident fits. This wireless RF array can significantly increase detection sensitivity. It may reduce the RF transmission power and data acquisition time for 1H-MRS and MRI applications, specifically at 7 T, where 1H-MRS requires a high-power RF pulse. The array could provide a cost-effective and efficient solution to improve detection sensitivity for human 1H-MRS and MRI in the regions with lower transmit efficiency.

UNASSIGNED: Evidence from animal and human studies suggests glutamatergic dysfunction in posttraumatic stress disorder (PTSD). The purpose of this study was to investigate glutamate abnormalities in the dorsolateral prefrontal cortex (DLFPC) of individuals with PTSD using 7T MRS, which has better spectral resolution and signal-to-noise ratio than lower field strengths, thus allowing for better spectral quality and higher sensitivity. We hypothesized that individuals with PTSD would have lower glutamate levels compared to trauma-exposed individuals without PTSD and individuals without trauma exposure. Additionally, we explored potential alterations in other neurometabolites and the relationship between glutamate and psychiatric symptoms.
UNASSIGNED: Individuals with PTSD (n=27), trauma-exposed individuals without PTSD (n=27), and individuals without trauma exposure (n=26) underwent 7T MRS to measure glutamate and other neurometabolites in the left DLPFC. The severities of PTSD, depression, anxiety, and dissociation symptoms were assessed.
UNASSIGNED: We found that glutamate was lower in the PTSD and trauma-exposed groups compared to the group without trauma exposure. Furthermore, N-acetylaspartate (NAA) was lower and lactate was higher in the PTSD group compared to the group without trauma exposure. Glutamate was negatively correlated with depression symptom severity in the PTSD group. Glutamate was not correlated with PTSD symptom severity.
UNASSIGNED: In this first 7T MRS study of PTSD, we observed altered concentrations of glutamate, NAA, and lactate. Our findings provide evidence for multiple possible pathological processes in individuals with PTSD. High-field MRS offers insight into the neurometabolic alterations associated with PTSD and is a powerful tool to probe trauma- and stress-related neurotransmission and metabolism in vivo.

暂无摘要。

Proton MRS is used clinically to collect localized, quantitative metabolic data from living tissues. However, the presence of baselines in the spectra complicates accurate MRS data quantification. The occurrence of baselines is not specific to short-echo-time MRS data. In short-echo-time MRS, the baseline consists typically of a dominating macromolecular (MM) part, and can, depending on B0 shimming, poor voxel placement, and/or localization sequences, also contain broad water and lipid resonance components, indicated by broad components (BCs). In long-echo-time MRS, the MM part is usually much smaller, but BCs may still be present. The sum of MM and BCs is denoted by the baseline. Many algorithms have been proposed over the years to tackle these artefacts. A first approach is to identify the baseline itself in a preprocessing step, and a second approach is to model the baseline in the quantification of the MRS data themselves. This paper gives an overview of baseline handling algorithms and also proposes a new algorithm for baseline correction. A subset of suitable baseline removal algorithms were tested on in vivo MRSI data (semi-LASER at TE = 40 ms) and compared with the new algorithm. The baselines in all datasets were removed using the different methods and subsequently fitted using spectrIm-QMRS with a TDFDFit fitting model that contained only a metabolite basis set and lacked a baseline model. The same spectra were also fitted using a spectrIm-QMRS model that explicitly models the metabolites and the baseline of the spectrum. The quantification results of the latter quantification were regarded as ground truth. The fit quality number (FQN) was used to assess baseline removal effectiveness, and correlations between metabolite peak areas and ground truth models were also examined. The results show a competitive performance of our new proposed algorithm, underscoring its automatic approach and efficiency. Nevertheless, none of the tested baseline correction methods achieved FQNs as good as the ground truth model. All separately applied baseline correction methods introduce a bias in the observed metabolite peak areas. We conclude that all baseline correction methods tested, when applied as a separate preprocessing step, yield poorer FQNs and biased quantification results. While they may enhance visual display, they are not advisable for use before spectral fitting.