Quantitative T1-relaxation corrected metabolite mapping of 12 metabolites in the human brain at 9.4 T

Magnetic resonance spectroscopic imaging (MRSI) is a non-invasive imaging modality that enables observation of metabolites. Applications of MRSI for neuroimaging applications has shown promise for monitoring and detecting various diseases. This study builds off previously developed techniques of short TR, 1H FID MRSI by correcting for T1-weighting of the metabolites and utilizing an internal water reference to produce quantitative (mmol kg-1) metabolite maps. This work reports and shows quantitative metabolite maps for 12 metabolites for a single slice. Voxel-specific T1-corrections for water are common in MRSI studies; however, most studies use either averaged T1-relaxation times to correct for T1-weighting of metabolites or omit this correction step entirely. This work employs the use of voxel-specific T1-corrections for metabolites in addition to water. Utilizing averaged T1-relaxation times for metabolites can bias metabolite maps for metabolites that have strong differences between T1-relaxation for GM and WM (i.e. Glu). This work systematically compares quantitative metabolite maps to single voxel quantitative results and qualitatively compares metabolite maps to previous works.

Cerebellar GABA change during visuomotor adaptation relates to adaptation performance and cerebellar network connectivity: A Magnetic Resonance Spectroscopic Imaging study.

Motor adaptation is crucial for performing accurate movements in a changing environment and relies on the cerebellum. Although cerebellar involvement has been well characterized, the neurochemical changes in the cerebellum that underpin human motor adaptation remain unknown. We used a novel Magnetic Resonance Spectroscopic Imaging (MRSI) technique to measure changes in the major inhibitory neurotransmitter γ-aminobutyric acid (GABA) in the human cerebellum during visuomotor adaptation. Participants used their right hand to adapt to a rotated cursor in the scanner, compared with a control task requiring no adaptation. We were able to spatially resolve adaptation-driven GABA changes at the cerebellar nuclei and in the cerebellar cortex in the left and the right cerebellar hemisphere independently and found that simple movement of the right hand increases GABA in the right cerebellar nuclei and decreases GABA in the left. When isolating adaptation-driven GABA changes, we found an increase in GABA in the left cerebellar nuclei and a decrease in GABA in the right cerebellar nuclei during adaptation. Early adaptation-driven GABA change in the right cerebellar nuclei correlated with adaptation performance: Participants showing greater GABA decrease adapted better, suggesting that this early GABA change is behaviourally relevant. Early GABA change also correlated with functional connectivity change in a cerebellar network: Participants showing a greater decrease in GABA also showed greater strength increase in cerebellar network connectivity. These results were specific to GABA, specific to adaptation and specific to the cerebellar network. This study provides the first evidence for plastic changes in cerebellar neurochemistry during a motor adaptation task. Characterising these naturally occurring neurochemical changes may provide a basis for developing therapeutic interventions to facilitate neurochemical changes in the cerebellum that can improve human motor adaptation.

ORYX-MRSI: A Fully-Automated Open-Source Software for Three-Dimensional Proton Magnetic Resonance Spectroscopic Imaging Data Analysis

Proton magnetic resonance spectroscopic imaging (1H-MRSI) provides noninvasive evaluation of brain metabolism. However, there are some limitations of 1H-MRSI preventing its wider use in the clinics, including the spectral quality issues, partial volume effect and chemical shift artifact. Additionally, it is necessary to create metabolite maps for analyzing spectral data along with other MRI modalities. In this study, a MATLAB-based open-source data analysis software for 3D 1H-MRSI, called Oryx-MRSI, which includes modules for visualization of raw 1H-MRSI data and LCModel outputs, chemical shift correction, tissue fraction calculation, metabolite map production, and registration onto standard MNI152 brain atlas while providing automatic spectral quality control, is presented. Oryx-MRSI implements region of interest analysis at brain parcellations defined on MNI152 brain atlas. All generated metabolite maps are stored in NIfTI format. Oryx-MRSI is publicly available at https://github.com/sevimcengiz/Oryx-MRSI along with six example datasets.

Enhancing Metabolic Imaging of Energy Metabolism in Traumatic Brain Injury Using Hyperpolarized [1-13C]Pyruvate and Dichloroacetate

Hyperpolarized magnetic resonance spectroscopic imaging (MRSI) of [1-13C]pyruvate metabolism has previously been used to assess the effects of traumatic brain injury (TBI) in rats. Here, we show that MRSI can be used in conjunction with dichloroacetate to measure the phosphorylation state of pyruvate dehydrogenase (PDH) following mild-to-moderate TBI, and that measurements can be repeated in a longitudinal study to monitor the course of injury progression and recovery. We found that the level of 13C-bicarbonate and the bicarbonate-to-lactate ratio decreased on the injured side of the brain four hours after injury and continued to decrease through day 7. Levels recovered to normal by day 28. Measurements following dichloroacetate administration showed that PDH was inhibited equally by PDH kinase (PDK) on both sides of the brain. Therefore, the decrease in aerobic metabolism is not due to inhibition by PDK.

Hyperpolarized 13C Magnetic Resonance Spectroscopic Imaging of Pyruvate Metabolism in Murine Breast Cancer Models of Different Metastatic Potential

This study uses dynamic hyperpolarized [1-13C]pyruvate magnetic resonance spectroscopic imaging (MRSI) to estimate differences in glycolytic metabolism between highly metastatic (4T1, n = 7) and metastatically dormant (4T07, n = 7) murine breast cancer models. The apparent conversion rate of pyruvate-to-lactate (kPL) and lactate-to-pyruvate area-under-the-curve ratio (AUCL/P) were estimated from the metabolite images and compared with biochemical metabolic measures and immunohistochemistry (IHC). A non-significant trend of increasing kPL (p = 0.17) and AUCL/P (p = 0.11) from 4T07 to 4T1 tumors was observed. No significant differences in tumor IHC lactate dehydrogenase-A (LDHA), monocarboxylate transporter-1 (MCT1), cluster of differentiation 31 (CD31), and hypoxia inducible factor-α (HIF-1α), tumor lactate-dehydrogenase (LDH) activity, or blood lactate or glucose levels were found between the two tumor lines. However, AUCL/P was significantly correlated with tumor LDH activity (ρspearman = 0.621, p = 0.027) and blood glucose levels (ρspearman = −0.474, p = 0.042). kPL displayed a similar, non-significant trend for LDH activity (ρspearman = 0.480, p = 0.114) and blood glucose levels (ρspearman = −0.414, p = 0.088). Neither kPL nor AUCL/P were significantly correlated with blood lactate levels or tumor LDHA or MCT1. The significant positive correlation between AUCL/P and tumor LDH activity indicates the potential of AUCL/P as a biomarker of glycolytic metabolism in breast cancer models. However, the lack of a significant difference between in vivo tumor metabolism for the two models suggest similar pyruvate-to-lactate conversion despite differing metastatic potential.