Simultaneous frequency and phase corrections of single-shot MRS data using cross-correlation.

PURPOSE: The objective of this study was to propose a novel preprocessing approach to simultaneously correct for the frequency and phase drifts in MRS data using cross-correlation technique. METHODS: The performance of the proposed method was first investigated at different SNR levels using simulation. Random frequency and phase offsets were added to a previously acquired STEAM human data at 7 T, simulating two different noise levels with and without baseline artifacts. Alongside the proposed spectral cross-correlation (SC) method, three other simultaneous alignment approaches were evaluated. Validation was performed on human brain data at 3 T and mouse brain data at 16.4 T. RESULTS: The results showed that the SC technique effectively corrects for both small and large frequency and phase drifts, even at low SNR levels. Furthermore, the mean square measurement error of the SC algorithm was comparable to the other three methods used, with much faster processing time. The efficacy of the proposed technique was successfully demonstrated in both human brain MRS data and in a noisy MRS dataset acquired from a small volume-of-interest in the mouse brain. CONCLUSION: The study demonstrated the availability of a fast and robust technique that accurately corrects for both small and large frequency and phase shifts in MRS.

Diffusion-weighted MR spectroscopy of the prostate.

PURPOSE: Prostate tissue has a complex microstructure, mainly composed of epithelial and stromal cells, and of extracellular (acinar-luminal) spaces. Diffusion-weighted MR spectroscopy (DW-MRS) is ideally suited to explore complex microstructure in vivo with metabolites selectively distributed in different subspaces. To date, this technique has been applied to brain and muscle. This study presents the development and pioneering utilization of 1H-DW-MRS in the prostate, accompanied by in vitro studies to support interpretations of in vivo findings. METHODS: Nine healthy volunteers underwent a prostate MR examination (mean age, 56 years; range, 31-66). Metabolic complexation was studied in vitro using solutions with major compounds found in prostatic fluid of the lumen. DW-MRS was performed at 3 T with a non-water-suppressed single-voxel sequence with metabolite-cycling to concurrently measure metabolite and water signals. The water signal was used in postprocessing as a reference in a motion-compensation scheme. The spectra were fitted simultaneously in the spectral and diffusion-weighting dimensions. Apparent diffusion coefficients (ADCs) were derived by fitting signal decays that were assumed to be mono-exponential for metabolites and biexponential for water. RESULTS: DW-MRS of the prostate revealed relatively low ADCs for Cho and Cr compounds, aligning with their intracellular location and higher ADCs for citrate and spermine supporting their luminal origin. In vitro assessments of the ADCs of citrate and spermine demonstrated their complex formation and protein binding. Tissue concentrations of MRS-detectable metabolites were as expected for the voxel location. CONCLUSIONS: This work successfully demonstrates the feasibility of 1H-DW-MRS of the prostate and its potential for providing valuable microstructural information.

Metabolic fingerprinting by nuclear magnetic resonance of hepatocellular carcinoma cells during p53 reactivation-induced senescence.

Cellular senescence is characterized by stable cell cycle arrest. Senescent cells exhibit a senescence-associated secretory phenotype that can promote tumor progression. The aim of our study was to identify specific nuclear magnetic resonance (NMR) spectroscopy-based markers of cancer cell senescence. For metabolic studies, we employed murine liver carcinoma Harvey Rat Sarcoma Virus (H-Ras) cells, in which reactivation of p53 expression induces senescence. Senescent and nonsenescent cell extracts were subjected to high-resolution proton (1H)-NMR spectroscopy-based metabolomics, and dynamic metabolic changes during senescence were analyzed using a magnetic resonance spectroscopy (MRS)-compatible cell perfusion system. Additionally, the ability of intact senescent cells to degrade the extracellular matrix (ECM) was quantified in the cell perfusion system. Analysis of senescent H-Ras cell extracts revealed elevated sn-glycero-3-phosphocholine, myoinositol, taurine, and creatine levels, with decreases in glycine, o-phosphocholine, threonine, and valine. These metabolic findings were accompanied by a greater degradation index of the ECM in senescent H-Ras cells than in control H-Ras cells. MRS studies with the cell perfusion system revealed elevated creatine levels in senescent cells on Day 4, confirming the 1H-NMR results. These senescence-associated changes in metabolism and ECM degradation strongly impact growth and redox metabolism and reveal potential MRS signals for detecting senescent cancer cells in vivo.

Brain metabolism after therapeutic hypothermia for murine hypoxia-ischemia using hyperpolarized [1-13C] pyruvate magnetic resonance spectroscopy.

Hypoxic-ischemic encephalopathy (HIE) is a common neurological syndrome in newborns with high mortality and morbidity. Therapeutic hypothermia (TH), which is standard of care for HIE, mitigates brain injury by suppressing anaerobic metabolism. However, more than 40% of HIE neonates have a poor outcome, even after TH. This study aims to provide metabolic biomarkers for predicting the outcomes of hypoxia-ischemia (HI) after TH using hyperpolarized [1-13C] pyruvate magnetic resonance spectroscopy. Postnatal day 10 (P10) mice with HI underwent TH at 1 h and were scanned at 6-8 h (P10), 24 h (P11), 7 days (P17), and 21 days (P31) post-HI on a 14.1-T NMR spectrometer. The metabolic images were collected, and the conversion rate from pyruvate to lactate and the ratio of lactate to pyruvate in the injured left hemisphere (kPL(L) and Lac/Pyr(L), respectively) were calculated at each timepoint. The outcomes of TH were determined by the assessments of brain injury on T2-weighted images and behavioral tests at later timepoint. kPL(L) and Lac/Pyr(L) over time between the good-outcome and poor-outcome groups and across timepoints within groups were analyzed. We found significant differences in temporal trends of kPL(L) and Lac/Pyr(L) between groups. In the good-outcome group, kPL(L) increased until P31 with a significantly higher value at P31 compared with that at P10, while the level of Lac/Pyr(L) at P31 was notably higher than those at all other timepoints. In the poor-outcome group, kPL(L) and Lac/Pyr(L) increased within 24 h. The kPL(L) value at P11 was considerably higher compared with P10. Discrete temporal changes of kPL(L) and Lac/Pyr(L) after TH between the good-outcome and poor-outcome groups were seen as early as 24 h after HI, reflecting various TH effects on brain anaerobic metabolism, which may provide insights for early screening for response to TH.

Repeatability of alkaline inorganic phosphate quantification in the skeletal muscle using 31P-magnetic resonance spectroscopy at 3 T.

The detection of a secondary inorganic phosphate (Pi) resonance, a possible marker of mitochondrial content in vivo, using phosphorus magnetic resonance spectroscopy (31P-MRS), poses technical challenges at 3 Tesla (T). Overcoming these challenges is imperative for the integration of this biomarker into clinical research. To evaluate the repeatability and reliability of measuring resting skeletal muscle alkaline Pi (Pialk) using with 31P-MRS at 3 T. After an initial set of experiments on five subjects to optimize the sequence, resting 31P-MRS of the quadriceps muscles were acquired on two visits (~4 days apart) using an intra-subjects design, from 13 sedentary to moderately active young male and female adults (22 ± 3 years old) within a whole-body 3 T MR system. Measurement variability attributed to changes in coil position, shimming procedure, and spectral analysis were quantified. 31P-MRS data were acquired with a 31P/-proton (1H) dual-tuned surface coil positioned on the quadriceps using a pulse-acquire sequence. Test-retest absolute and relative repeatability was analyzed using the coefficient of variation (CV) and intra-class correlation coefficients (ICC), respectively. After sequence parameter optimization, Pialk demonstrated high intra-subject repeatability (CV: 10.6 ± 5.4%, ICC: 0.80). Proximo-distal change in coil position along the length of the quadriceps introduced Pialk quantitation variability (CV: 28 ± 5%), due to magnetic field inhomogeneity with more distal coil locations. In contrast, Pialk measurement variability due to repeated shims from the same muscle volume (0.40 ± 0.09mM; CV: 6.6%), and automated spectral processing (0.37 ± 0.01mM; CV: 2.3%), was minor. The quantification of Pialk in skeletal muscle via surface coil 31P-MRS at 3 T demonstrated excellent reproducibility. However, caution is advised against placing the coil at the distal part of the quadriceps to mitigate shimming inhomogeneity.

A multivariate curve resolution analysis of multicenter proton spectroscopic imaging of the prostate for cancer localization and assessment of aggressiveness.

In this study, we investigated the potential of the multivariate curve resolution alternating least squares (MCR-ALS) algorithm for analyzing three-dimensional (3D) 1 H-MRSI data of the prostate in prostate cancer (PCa) patients. MCR-ALS generates relative intensities of components representing spectral profiles derived from a large training set of patients, providing an interpretable model. Our objectives were to classify magnetic resonance (MR) spectra, differentiating tumor lesions from benign tissue, and to assess PCa aggressiveness. We included multicenter 3D 1 H-MRSI data from 106 PCa patients across eight centers. The patient cohort was divided into a training set (N = 63) and an independent test set (N = 43). Singular value decomposition determined that MR spectra were optimally represented by five components. The profiles of these components were extracted from the training set by MCR-ALS and assigned to specific tissue types. Using these components, MCR-ALS was applied to the test set for a quantitative analysis to discriminate tumor lesions from benign tissue and to assess tumor aggressiveness. Relative intensity maps of the components were reconstructed and compared with histopathology reports. The quantitative analysis demonstrated a significant separation between tumor and benign voxels (t-test, p < 0.001). This result was achieved including voxels with low-quality MR spectra. A receiver operating characteristic analysis of the relative intensity of the tumor component revealed that low- and high-risk tumor lesions could be distinguished with an area under the curve of 0.88. Maps of this component properly identified the extent of tumor lesions. Our study demonstrated that MCR-ALS analysis of 1 H-MRSI of the prostate can reliably identify tumor lesions and assess their aggressiveness. It handled multicenter data with minimal preprocessing and without using prior knowledge or quality control. These findings indicate that MCR-ALS can serve as an automated tool to assess the presence, extent, and aggressiveness of tumor lesions in the prostate, enhancing diagnostic capabilities and treatment planning of PCa patients.

Associations Between Brain Metabolites Measured With MR Spectroscopy and Head Impacts in High School American Football Athletes.

BACKGROUND: While changes in brain metabolites after injury have been reported, relationships between metabolite changes and head impacts are less characterized. PURPOSE: To investigate alterations in neurochemistry in high school athletes as a function of head impacts, concussion, and the use of a jugular vein compression (JVC) collar. STUDY TYPE: Prospective controlled trial. SUBJECTS: A total of 284 male American football players, divided into JVC collar and noncollar groups; 215 included in final analysis (age = 15.9 ± 1.0 years; 114 in collar group). FIELD STRENGTH/SEQUENCE: 3 Tesla/T1-weighted gradient echo, 1H point resolved spectroscopy, acquired between August and November 2018. ASSESSMENT: Head impacts were quantified using accelerometers. Concussion was diagnosed by medical professionals for each team. Pre- to postseason differences in total N-acetylaspartate (tNAA), total choline (tCho), myo-inositol (myoI), and glutamate + glutamine (Glx), in primary motor cortex (M1) and anterior cingulate cortex (ACC), relative to total creatine (tCr), were determined. STATISTICAL TESTS: Group-wise comparisons were performed using Wilcoxon signed-rank, Friedman's, and Mann-Whitney U tests. Relationships between ∆metabolite/tCr and mean g-force were analyzed using linear regressions accounting for concussion and JVC collar. Significance was set at P ≤ 0.05. RESULTS: In participants without concussion, a significant decrease in tCho/tCr (0.233 ± 1.40 × 10-3 to 0.227 ± 1.47 × 10-7) and increase in Glx/tCr (1.60 ± 8.75 × 10-3 to 1.63 ± 1.08 × 10-2) in ACC were observed pre- to postseason. The relationship between ∆tCho/tCr in M1 and ACC and mean g-force from >80 g to >140 g differed significantly between participants with and without concussion (M1 ß ranged from 3.9 × 10-3 to 2.1 × 10-3; ACC ß ranged from 2.7 × 10-3 to 2.1 × 10-3). Posthoc analyses revealed increased tCho/tCr in M1 was positively associated with mean g-force >100 g (ß = 3.6 × 10-3) and >110 g (ß = 2.9 × 10-3) in participants with concussion. Significant associations between ∆ myoI / tCr $$ \Delta \mathrm{myoI}/\mathrm{tCr} $$ in ACC and mean g-force >110 g (ß = -1.1 × 10-3) and >120 g (ß = -1.1 × 10-3) were observed in the collar group only. DATA CONCLUSION: Diagnosed concussion and the use of a JVC collar result in distinct neurochemical trends after repeated head impacts. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 3.

2D 1H sLASER Long-TE and 3D 31P Chemical Shift Imaging at 3 T for Monitoring Fasting-Induced Changes in Brain Tumor Tissue.

BACKGROUND: Emerging evidence suggests that fasting could play a key role in cancer treatment. Its metabolic effects on gliomas require further investigation. PURPOSE: To design a multi-voxel 1H/31P MR-spectroscopic imaging (MRSI) protocol for noninvasive metabolic monitoring of cerebral, fasting-induced changes on an individual patient/tumor level, and to assess its technical reliability/reproducibility. STUDY TYPE: Prospective. POPULATION: MRS phantom. Twenty-two patients (mean age = 61, 6 female) with suspected WHO grade II-IV glioma examined before and after 72-hour-fasting prior to biopsy/resection. FIELD STRENGTH/SEQUENCE: 3-T, 1H decoupled 3D 31P MRSI, 2D 1H sLASER MRSI at an echo time of 144 msec, 2D 1H MRSI (as water reference), T1-weighted, T1-weighted contrast-enhanced, T2-weighted, and FLAIR. sLASER and PRESS sequences were used for phantom measurements. ASSESSMENT: Phantom measurements and spectral simulations were performed with various echo-times for protocol optimization. In vivo spectral analyses were conducted using LCModel and AMARES, obtaining quality/fitting parameters (linewidth, signal-to-noise-ratio, and uncertainty measures of fitting) and metabolite intensities. The volume of glioma sub-regions was calculated and correlated with MRS findings. Ex-vivo spectra of necrotic tumor tissues were obtained using high-resolution magic-angle spinning (HR-MAS) technique. STATISTICAL TESTS: Wilcoxon signed-rank test, Bland-Altman plots, and coefficient of variation were used for repeatability analysis of quality/fitting parameters and metabolite concentrations. Spearman ρ correlation for the concentration of ketone bodies with volumes of glioma sub-regions was determined. A P-value <0.05 was considered statistically significant. RESULTS: 1H and 31P repeatability measures were highly consistent between the two sessions. ß-hydroxybutyrate and acetoacetate were detectable (fitting-uncertainty <50%) in glioma sub-regions of all patients who completed the 72-hour-fasting cycle. ß-hydroxybutyrate accumulation was significantly correlated with the necrotic/non-enhancing tumor core volume (ρ = 0.81) and validated using ex-vivo 1H HR-MAS. DATA CONCLUSION: We propose a comprehensive MRS protocol that may be used for monitoring cerebral, fasting-induced changes in patients with glioma. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 4.

31 P MR Spectroscopy in the Pancreas: Repeatability, Comparison With Liver, and Pilot Pancreatic Cancer Data.

BACKGROUND: Non-invasive evaluation of phosphomonoesters (PMEs) and phosphodiesters (PDEs) by 31-phosphorus MR spectroscopy (31 P MRS) may have potential for early therapy (non-)response assessment in cancer. However, 31 P MRS has not yet been applied to investigate the human pancreas in vivo. PURPOSE: To assess the technical feasibility and repeatability of 31 P MR spectroscopic imaging (MRSI) of the pancreas, compare 31 P metabolite levels between pancreas and liver, and determine the feasibility of 31 P MRSI in pancreatic cancer. STUDY TYPE: Prospective cohort study. POPULATION: 10 healthy subjects (age 34 ± 12 years, four females) and one patient (73-year-old female) with pancreatic ductal adenocarcinoma. FIELD STRENGTH/SEQUENCE: 7-T, 31 P FID-MRSI, 1 H gradient-echo MRI. ASSESSMENT: 31 P FID-MRSI of the abdomen (including the pancreas and liver) was performed with a nominal voxel size of 20 mm (isotropic). For repeatability measurements, healthy subjects were scanned twice on the same day. The patient was only scanned once. Test-retest 31 P MRSI data of pancreas and liver voxels (segmented on 1 H MRI) of healthy subjects were quantified by fitting in the time domain and signal amplitudes were normalized to γ-adenosine triphosphate. In addition, the PME/PDE ratio was calculated. Metabolite levels were averaged over all voxels within the pancreas, right liver lobe and left liver lobe, respectively. STATISTICAL TESTS: Repeatability of test-retest data from healthy pancreas was assessed by paired t-tests, Bland-Altman analyses, and calculation of the intrasubject coefficients of variation (CoVs). Significant differences between healthy pancreas and right and left liver lobes were assessed with a two-way analysis of variance (ANOVA) for repeated measures. A P-value <0.05 was considered statistically significant. RESULTS: The intrasubject CoVs for PME, PDE, and PME/PDE in healthy pancreas were below 20%. Furthermore, PME and PME/PDE were significantly higher in pancreas compared to liver. In the patient with pancreatic cancer, qualitatively, elevated relative PME signals were observed in comparison with healthy pancreas. DATA CONCLUSION: In vivo 31 P MRSI of the human healthy pancreas and in pancreatic cancer may be feasible at 7 T. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Prenatal molecular diagnosis of pyruvate dehydrogenase complex deficiency enables rapid initiation of ketogenic diet.

Pyruvate dehydrogenase complex deficiency (PDCD) is a mitochondrial disorder of carbohydrate oxidation characterized by lactic acidosis and central nervous system involvement. Knowledge of the affected metabolic pathways and clinical observations suggest that early initiation of the ketogenic diet may ameliorate the metabolic and neurologic course of the disease. We present a case in which first trimester ultrasound identified structural brain abnormalities prompting a prenatal molecular diagnosis of PDCD. Ketogenic diet, thiamine, and N-acetylcysteine were initiated in the perinatal period with good response, including sustained developmental progress. This case highlights the importance of a robust neurometabolic differential diagnosis for prenatally diagnosed structural anomalies and the use of prenatal molecular testing to facilitate rapid, genetically tailored intervention.

Higher striatal glutamate in male youth with internet gaming disorder.

Internet gaming disorder (IGD) was included in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) as a research diagnosis, but little is known about its pathophysiology. Alterations in frontostriatal circuits appear to play a critical role in the development of addiction. Glutamate is considered an essential excitatory neurotransmitter in addictive disorders. This study's aim was to investigate striatal glutamate in youth with IGD compared to healthy controls (HC). Using a cross-sectional design, 25 adolescent male subjects fulfilling DSM-5 criteria for IGD and 26 HC, matched in age, education, handedness and smoking, were included in the analysis. A structural MPRAGE T1 sequence followed by a single-voxel magnetic resonance spectroscopy MEGA-PRESS sequence (TR = 1500 ms, TE = 68 ms, 208 averages) with a voxel size of 20 mm3 were recorded on 3 T Siemens Magnetom Prisma scanner. The voxel was placed in the left striatum. Group comparison of the relative glutamate and glutamine (Glx) was calculated using regression analysis. IGD subjects met an average of 6.5 of 9 DSM-5 IGD criteria and reported an average of 29 h of weekly gaming. Regression analysis showed a significant group effect for Glx, with higher Glx levels in IGD as compared to HC (coef. = .086, t (50) = 2.17, p = .035). Our study is the first to show higher levels of Glx in the striatum in youth with IGD. The elevation of Glx in the striatum may indicate hyperactivation of the reward system in IGD. Thus, results confirm that neurochemical alterations can be identified in early stages of behavioral addictions.

Severity of prematurity and age impact early postnatal development of GABA and glutamate systems.

Gamma-aminobutyric acid (GABA) and glutamatergic system perturbations following premature birth may explain neurodevelopmental deficits in the absence of structural brain injury. Using GABA-edited spectroscopy (MEscher-GArwood Point Resolved Spectroscopy [MEGA-PRESS] on 3 T MRI), we have described in-vivo brain GABA+ (+macromolecules) and Glx (glutamate + glutamine) concentrations in term-born infants. We report previously unavailable comparative data on in-vivo GABA+ and Glx concentrations in the cerebellum, the right basal ganglia, and the right frontal lobe of preterm-born infants without structural brain injury. Seventy-five preterm-born (gestational age 27.8 ± 2.9 weeks) and 48 term-born (39.6 ± 0.9 weeks) infants yielded reliable MEGA-PRESS spectra acquired at post-menstrual age (PMA) of 40.2 ± 2.3 and 43.0 ± 2 weeks, respectively. GABA+ (median 2.44 institutional units [i.u.]) concentrations were highest in the cerebellum and Glx higher in the cerebellum (5.73 i.u.) and basal ganglia (5.16 i.u.), with lowest concentrations in the frontal lobe. Metabolite concentrations correlated positively with advancing PMA and postnatal age at MRI (Spearman's rho 0.2-0.6). Basal ganglia Glx and NAA, and frontal GABA+ and NAA concentrations were lower in preterm compared with term infants. Moderate preterm infants had lower metabolite concentrations than term and extreme preterm infants. Our findings emphasize the impact of premature extra-uterine stimuli on GABA-glutamate system development and may serve as early biomarkers of neurodevelopmental deficits.

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.

SLIPMAT: A pipeline for extracting tissue-specific spectral profiles from 1H MR spectroscopic imaging data.

1H Magnetic Resonance Spectroscopy (MRS) is an important non-invasive tool for measuring brain metabolism, with numerous applications in the neuroscientific and clinical domains. In this work we present a new analysis pipeline (SLIPMAT), designed to extract high-quality, tissue-specific, spectral profiles from MR spectroscopic imaging data (MRSI). Spectral decomposition is combined with spatially dependant frequency and phase correction to yield high SNR white and grey matter spectra without partial-volume contamination. A subsequent series of spectral processing steps are applied to reduce unwanted spectral variation, such as baseline correction and linewidth matching, before direct spectral analysis with machine learning and traditional statistical methods. The method is validated using a 2D semi-LASER MRSI sequence, with a 5-minute duration, from data acquired in triplicate across 8 healthy participants. Reliable spectral profiles are confirmed with principal component analysis, revealing the importance of total-choline and scyllo-inositol levels in distinguishing between individuals - in good agreement with our previous work. Furthermore, since the method allows the simultaneous measurement of metabolites in grey and white matter, we show the strong discriminative value of these metabolites in both tissue types for the first time. In conclusion, we present a novel and time efficient MRSI acquisition and processing pipeline, capable of detecting reliable neuro-metabolic differences between healthy individuals, and suitable for the sensitive neurometabolic profiling of in-vivo brain tissue.

The psychosis human connectome project: Design and rationale for studies of visual neurophysiology.

Visual perception is abnormal in psychotic disorders such as schizophrenia. In addition to hallucinations, laboratory tests show differences in fundamental visual processes including contrast sensitivity, center-surround interactions, and perceptual organization. A number of hypotheses have been proposed to explain visual dysfunction in psychotic disorders, including an imbalance between excitation and inhibition. However, the precise neural basis of abnormal visual perception in people with psychotic psychopathology (PwPP) remains unknown. Here, we describe the behavioral and 7 tesla MRI methods we used to interrogate visual neurophysiology in PwPP as part of the Psychosis Human Connectome Project (HCP). In addition to PwPP (n = 66) and healthy controls (n = 43), we also recruited first-degree biological relatives (n = 44) in order to examine the role of genetic liability for psychosis in visual perception. Our visual tasks were designed to assess fundamental visual processes in PwPP, whereas MR spectroscopy enabled us to examine neurochemistry, including excitatory and inhibitory markers. We show that it is feasible to collect high-quality data across multiple psychophysical, functional MRI, and MR spectroscopy experiments with a sizable number of participants at a single research site. These data, in addition to those from our previously described 3 tesla experiments, will be made publicly available in order to facilitate further investigations by other research groups. By combining visual neuroscience techniques and HCP brain imaging methods, our experiments offer new opportunities to investigate the neural basis of abnormal visual perception in PwPP.

Reproducibility of 3D MRSI for imaging human brain glucose metabolism using direct (2H) and indirect (1H) detection of deuterium labeled compounds at 7T and clinical 3T.

INTRODUCTION: Deuterium metabolic imaging (DMI) and quantitative exchange label turnover (QELT) are novel MR spectroscopy techniques for non-invasive imaging of human brain glucose and neurotransmitter metabolism with high clinical potential. Following oral or intravenous administration of non-ionizing [6,6'-2H2]-glucose, its uptake and synthesis of downstream metabolites can be mapped via direct or indirect detection of deuterium resonances using 2H MRSI (DMI) and 1H MRSI (QELT), respectively. The purpose of this study was to compare the dynamics of spatially resolved brain glucose metabolism, i.e., estimated concentration enrichment of deuterium labeled Glx (glutamate+glutamine) and Glc (glucose) acquired repeatedly in the same cohort of subjects using DMI at 7T and QELT at clinical 3T. METHODS: Five volunteers (4 m/1f) were scanned in repeated sessions for 60 min after overnight fasting and 0.8 g/kg oral [6,6'-2H2]-glucose administration using time-resolved 3D 2H FID-MRSI with elliptical phase encoding at 7T and 3D 1H FID-MRSI with a non-Cartesian concentric ring trajectory readout at clinical 3T. RESULTS: One hour after oral tracer administration regionally averaged deuterium labeled Glx4 concentrations and the dynamics were not significantly different over all participants between 7T 2H DMI and 3T 1H QELT data for GM (1.29±0.15 vs. 1.38±0.26 mM, p=0.65 & 21±3 vs. 26±3 µM/min, p=0.22) and WM (1.10±0.13 vs. 0.91±0.24 mM, p=0.34 & 19±2 vs. 17±3 µM/min, p=0.48). Also, the observed time constants of dynamic Glc6 data in GM (24±14 vs. 19±7 min, p=0.65) and WM (28±19 vs. 18±9 min, p=0.43) dominated regions showed no significant differences. Between individual 2H and 1H data points a weak to moderate negative correlation was observed for Glx4 concentrations in GM (r=-0.52, p<0.001), and WM (r=-0.3, p<0.001) dominated regions, while a strong negative correlation was observed for Glc6 data GM (r=-0.61, p<0.001) and WM (r=-0.70, p<0.001). CONCLUSION: This study demonstrates that indirect detection of deuterium labeled compounds using 1H QELT MRSI at widely available clinical 3T without additional hardware is able to reproduce absolute concentration estimates of downstream glucose metabolites and the dynamics of glucose uptake compared to 2H DMI data acquired at 7T. This suggests significant potential for widespread application in clinical settings especially in environments with limited access to ultra-high field scanners and dedicated RF hardware.

A review of machine learning applications for the proton MR spectroscopy workflow.

This literature review presents a comprehensive overview of machine learning (ML) applications in proton MR spectroscopy (MRS). As the use of ML techniques in MRS continues to grow, this review aims to provide the MRS community with a structured overview of the state-of-the-art methods. Specifically, we examine and summarize studies published between 2017 and 2023 from major journals in the MR field. We categorize these studies based on a typical MRS workflow, including data acquisition, processing, analysis, and artificial data generation. Our review reveals that ML in MRS is still in its early stages, with a primary focus on processing and analysis techniques, and less attention given to data acquisition. We also found that many studies use similar model architectures, with little comparison to alternative architectures. Additionally, the generation of artificial data is a crucial topic, with no consistent method for its generation. Furthermore, many studies demonstrate that artificial data suffers from generalization issues when tested on in vivo data. We also conclude that risks related to ML models should be addressed, particularly for clinical applications. Therefore, output uncertainty measures and model biases are critical to investigate. Nonetheless, the rapid development of ML in MRS and the promising results from the reviewed studies justify further research in this field.

Denoising single MR spectra by deep learning: Miracle or mirage?

PURPOSE: The inherently poor SNR of MRS measurements presents a significant hurdle to its clinical application. Denoising by machine or deep learning (DL) was proposed as a remedy. It is investigated whether such denoising leads to lower estimate uncertainties or whether it essentially reduces noise in signal-free areas only. METHODS: Noise removal based on supervised DL with U-nets was implemented using simulated 1 H MR spectra of human brain in two approaches: (1) via time-frequency domain spectrograms and (2) using 1D spectra as input. Quality of denoising was evaluated in three ways: (1) by an adapted fit quality score, (2) by traditional model fitting, and (3) by quantification via neural networks. RESULTS: Visually appealing spectra were obtained; hinting that denoising is well-suited for MRS. However, an adapted denoising score showed that noise removal is inhomogeneous and more efficient for signal-free areas. This was confirmed by quantitative analysis of traditional fit results as well as DL quantitation following DL denoising. DL denoising, although apparently successful as judged by mean squared errors, led to substantially biased estimates in both implementations. CONCLUSION: The implemented DL-based denoising techniques may be useful for display purposes, but do not help quantitative evaluations, confirming expectations based on estimation theory: Cramér Rao lower bounds defined by the original data and the appropriate fitting model cannot be circumvented in an unbiased way for single data sets, unless additional prior knowledge can be incurred in the form of parameter restrictions/relations or applicable substates.

Model-informed unsupervised deep learning approaches to frequency and phase correction of MRS signals.

PURPOSE: A supervised deep learning (DL) approach for frequency and phase correction (FPC) of MRS data recently showed encouraging results, but obtaining transients with labels for supervised learning is challenging. This work investigates the feasibility and efficiency of unsupervised deep learning-based FPC. METHODS: Two novel deep learning-based FPC methods (deep learning-based Cr referencing and deep learning-based spectral registration), which use a priori physics domain knowledge, are presented. The proposed networks were trained, validated, and evaluated using simulated, phantom, and publicly accessible in vivo MEGA-edited MRS data. The performance of our proposed FPC methods was compared with other generally used FPC methods, in terms of precision and time efficiency. A new measure was proposed in this study to evaluate the FPC method performance. The ability of each of our methods to carry out FPC at varying SNR levels was evaluated. A Monte Carlo study was carried out to investigate the performance of our proposed methods. RESULTS: The validation using low-SNR manipulated simulated data demonstrated that the proposed methods could perform FPC comparably with other methods. The evaluation showed that the deep learning-based spectral registration over a limited frequency range method achieved the highest performance in phantom data. The applicability of the proposed method for FPC of GABA-edited in vivo MRS data was demonstrated. Our proposed networks have the potential to reduce computation time significantly. CONCLUSIONS: The proposed physics-informed deep neural networks trained in an unsupervised manner with complex data can offer efficient FPC of large MRS data in a shorter time.

A Double-Blind, Randomized, Placebo-Controlled Trial of Ursodeoxycholic Acid (UDCA) in Parkinson's Disease.

BACKGROUND: Rescue of mitochondrial function is a promising neuroprotective strategy for Parkinson's disease (PD). Ursodeoxycholic acid (UDCA) has shown considerable promise as a mitochondrial rescue agent across a range of preclinical in vitro and in vivo models of PD. OBJECTIVES: To investigate the safety and tolerability of high-dose UDCA in PD and determine midbrain target engagement. METHODS: The UP (UDCA in PD) study was a phase II, randomized, double-blind, placebo-controlled trial of UDCA (30 mg/kg daily, 2:1 randomization UDCA vs. placebo) in 30 participants with PD for 48 weeks. The primary outcome was safety and tolerability. Secondary outcomes included 31-phosphorus magnetic resonance spectroscopy (31 P-MRS) to explore target engagement of UDCA in PD midbrain and assessment of motor progression, applying both the Movement Disorder Society Unified Parkinson's Disease Rating Scale Part III (MDS-UPDRS-III) and objective, motion sensor-based quantification of gait impairment. RESULTS: UDCA was safe and well tolerated, and only mild transient gastrointestinal adverse events were more frequent in the UDCA treatment group. Midbrain 31 P-MRS demonstrated an increase in both Gibbs free energy and inorganic phosphate levels in the UDCA treatment group compared to placebo, reflecting improved ATP hydrolysis. Sensor-based gait analysis indicated a possible improvement of cadence (steps per minute) and other gait parameters in the UDCA group compared to placebo. In contrast, subjective assessment applying the MDS-UPDRS-III failed to detect a difference between treatment groups. CONCLUSIONS: High-dose UDCA is safe and well tolerated in early PD. Larger trials are needed to further evaluate the disease-modifying effect of UDCA in PD. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.