Metabolic changes assessed by 1H MR spectroscopy in the corpus callosum of post-COVID patients.

OBJECTIVE: Many patients with long COVID experience neurological and psychological symptoms. Signal abnormalities on MR images in the corpus callosum have been reported. Knowledge about the metabolic profile in the splenium of the corpus callosum (CCS) may contribute to a better understanding of the pathophysiology of long COVID. MATERIALS AND METHODS: Eighty-one subjects underwent proton MR spectroscopy examination. The metabolic concentrations of total N-acetylaspartate (NAA), choline-containing compounds (Cho), total creatine (Cr), myo-inositol (mI), and NAA/Cho in the CCS were statistically compared in the group of patients containing 58 subjects with positive IgG COVID-19 antibodies or positive SARS-CoV-2 qPCR test at least two months before the MR and the group of healthy controls containing 23 subjects with negative IgG antibodies. RESULTS: An age-dependent effect of SARS-CoV-2 on Cho concentrations in the CCS has been observed. Considering the subjective threshold of age = 40 years, older patients showed significantly increased Cho concentrations in the CCS than older healthy controls (p = 0.02). NAA, Cr, and mI were unchanged. All metabolite concentrations in the CCS of younger post-COVID-19 patients remained unaffected by SARS-CoV-2. Cho did not show any difference between symptomatic and asymptomatic patients (p = 0.91). DISCUSSION: Our results suggest that SARS-CoV-2 disproportionately increases Cho concentration in the CCS among older post-COVID-19 patients compared to younger ones. The observed changes in Cho may be related to the microstructural reorganization in the CCS also reported in diffusion measurements rather than increased membrane turnover. These changes do not seem to be related to neuropsychological problems of the post-COVID-19 patients. Further metabolic studies are recommended to confirm these observations.

Spectroscopic abnormalities in the pregenual anterior cingulate cortex in obsessive-compulsive disorder using proton magnetic resonance spectroscopy: a controlled study.

BACKGROUND: The main aim of the present study is to determine the role of metabolites observed using proton magnetic resonance spectroscopy (1H-MRS) in obsessive-compulsive disorder (OCD). As the literature describing biochemical changes in OCD yields conflicting results, we focused on accurate metabolite quantification of total N-acetyl aspartate (tNAA), total creatine (tCr), total choline-containing compounds (tCh), and myo-inositol (mI) in the anterior cingulate cortex (ACC) to capture the small metabolic changes between OCD patients and controls and between OCD patients with and without medication. METHODS: In total 46 patients with OCD and 46 healthy controls (HC) matched for age and sex were included in the study. The severity of symptoms in the OCD was evaluated on the day of magnetic resonance imaging (MRI) using the Yale-Brown Obsessive-Compulsive Scale (YBOCS). Subjects underwent 1H-MRS from the pregenual ACC (pgACC) region to calculate concentrations of tNAA, tCr, tCho, and mI. Twenty-eight OCD and 28 HC subjects were included in the statistical analysis. We compared differences between groups for all selected metabolites and in OCD patients we analyzed the relationship between metabolite levels and symptom severity, medication status, age, and the duration of illness. RESULTS: Significant decreases in tCr (U = 253.00, p = 0.022) and mI (U = 197.00, p = 0.001) in the pgACC were observed in the OCD group. No statistically significant differences were found in tNAA and tCho levels; however, tCho revealed a trend towards lower concentrations in OCD patients (U = 278.00, p = 0.062). Metabolic concentrations showed no significant correlations with the age and duration of illness. The correlation statistics found a significant negative correlation between tCr levels and YBOCS compulsions subscale (cor = -0.380, p = 0.046). tCho and YBOCS compulsions subscale showed a trend towards a negative correlation (cor = -0.351, p = 0.067). Analysis of subgroups with or without medication showed no differences. CONCLUSIONS: Patients with OCD present metabolic disruption in the pgACC. The decrease in tCr shows an important relationship with OCD symptomatology. tCr as a marker of cerebral bioenergetics may also be considered as a biomarker of the severity of compulsions. The study failed to prove that metabolic changes correlate with the medication status or the duration of illness. It seems that a disruption in the balance between these metabolites and their transmission may play a role in the pathophysiology of OCD.

Glutamatergic abnormalities in the pregenual anterior cingulate cortex in obsessive-compulsive disorder using magnetic resonance spectroscopy: A controlled study.

In this study, we utilized proton magnetic resonance spectroscopy (MRS) to understand the role of glutamate (Glu), glutamine (Gln), and gamma-aminobutyric acid (GABA) of OCD patients in the pregenual anterior cingulate cortex (pgACC). In total, 54 patients with OCD and 54 healthy controls (HC) matched for age and sex were included in the study. They underwent MRS in the pgACC region to calculate the concentrations of Glu, Gln, GABA, and Glu + Gln (Glx). After quality control of the MRS data, 21 OCD and 21 HC were statistically analyzed. The severity of symptoms were evaluated using the Yale-Brown Obsessive-Compulsive Scale (YBOCS). In the statistical analysis, we compared differences between groups for the metabolites; in the OCD we analyzed the correlations with symptom severity, medication status, age, and duration of illness. A significant decrease in Glx, in Glu, and in Gln in the pgACC were observed in the OCD compared to HC. The correlation statistics showed a significant positive correlation between Glu levels and the YBOCS compulsions subscale. The results indicate that patients with OCD present a disturbance in glutamatergic metabolism in the pgACC. The results also demonstrate that these changes correlate with the severity of compulsions.

Technical note: MR-compatible pedal ergometer with electromechanical pedal resistance and exercise triggering enhanced by visual feedback via video display.

BACKGROUND: During and after exercise, dynamic 31 P MR parameters are typically measured using an MR-compatible ergometer. Self-built equipment for local condition can be constructed where possible. PURPOSE: To develop a pedal resistance ergometer with rocker arm based on a system that combines electric weight displacement, visual self-monitoring, and exercise triggering. The repeatability and reproducibility were tested. METHODS: The hardware and software for the ergometer were constructed from commercial components in a home laboratory. Twelve volunteers participated in the testing of the ergometer. RESULTS: A fully automated ergometer system was developed, allowing the pedal resistance to be adjusted during the examination. The system includes a self-monitoring and triggering mechanism that enables both the operator and subject to monitor pedal frequency and force. The operator can modify the pedal resistance as desired during the exercise. This self-monitoring solution is simple and cost-effective, requiring only a commercial potentiometer, an Arduino converter, and a conventional video projector with a personal computer (PC). Additionally, all system components are located outside the magnetic resonance (MR) room, avoiding interference with the MR system. Results of several test of the reproducibility/repeatability of power at three pedal resistance values (15%, 24%, 25% maximal voluntary force) were expressed both as a coefficient of variation ranging from 6% to 3.1% and as an intraclass correlation of coefficient ranging from 0.96 to 0.99. Similar values were also found for other dynamic parameters of 31 P MR spectroscopy. These findings are similar to published data obtained on different types of ergometers. CONCLUSIONS: Based on more than 1 year of usage, the ergometer proved successful in handling stationary and variable loads, and can be easily operated by a single user.