Comparison of direct 13C and indirect 1H-[13C] MR detection methods for the study of dynamic metabolic turnover in the human brain

A wide range of direct ¹³C and indirect ¹H-[¹³C] MR detection methods exist to probe dynamic metabolic pathways in the human brain. Choosing an optimal detection method is difficult as sequence-specific features regarding spatial localization, broadband decoupling, spectral resolution, power requirements and sensitivity complicate a straightforward comparison. Here we combine density matrix simulations with experimentally determined values for intrinsic ¹H and ¹³C sensitivity, T₁ and T₂ relaxation and transmit efficiency to allow selection of an optimal ¹³C MR detection method for a given application and magnetic field. The indirect proton-observed, carbon-edited (POCE) detection method provides the highest accuracy at reasonable RF power deposition both at 4T and 7T. The various polarization transfer methods all have comparable performances, but may become infeasible at 7T due to the high RF power deposition. 2D MR methods have limited value for the metabolites considered (primarily glutamate, glutamine and γ-amino butyric acid (GABA)), but may prove valuable when additional information can be extracted, such as isotopomers or lipid composition. While providing the lowest accuracy, the detection of non-protonated carbons is the simplest to implement with the lowest RF power deposition. The magnetic field homogeneity is one of the most important parameters affecting the detection accuracy for all metabolites and all acquisition methods.

Contributions of glycogen to astrocytic energetics during brain activation

Glycogen is the major store of glucose in brain and is mainly in astrocytes. Brain glycogen levels in unstimulated, carefully-handled rats are 10-12 μmol/g, and assuming that astrocytes account for half the brain mass, astrocytic glycogen content is twice as high. Glycogen turnover is slow under basal conditions, but it is mobilized during activation. There is no net increase in incorporation of label from glucose during activation, whereas label release from pre-labeled glycogen exceeds net glycogen consumption, which increases during stronger stimuli. Because glycogen level is restored by non-oxidative metabolism, astrocytes can influence the global ratio of oxygen to glucose utilization. Compensatory increases in utilization of blood glucose during inhibition of glycogen phosphorylase are large and approximate glycogenolysis rates during sensory stimulation. In contrast, glycogenolysis rates during hypoglycemia are low due to continued glucose delivery and oxidation of endogenous substrates; rates that preserve neuronal function in the absence of glucose are also low, probably due to metabolite oxidation. Modeling studies predict that glycogenolysis maintains a high level of glucose-6-phosphate in astrocytes to maintain feedback inhibition of hexokinase, thereby diverting glucose for use by neurons. The fate of glycogen carbon in vivo is not known, but lactate efflux from brain best accounts for the major metabolic characteristics during activation of living brain. Substantial shuttling coupled with oxidation of glycogen-derived lactate is inconsistent with available evidence. Glycogen has important roles in astrocytic energetics, including glucose sparing, control of extracellular K(+) level, oxidative stress management, and memory consolidation; it is a multi-functional compound.

In vivo Magnetic Resonance Spectroscopy of cerebral glycogen metabolism in animals and humans

Glycogen serves as an important energy reservoir in the human body. Despite the abundance of glycogen in the liver and skeletal muscles, its concentration in the brain is relatively low, hence its significance has been questioned. A major challenge in studying brain glycogen metabolism has been the lack of availability of non-invasive techniques for quantification of brain glycogen in vivo. Invasive methods for brain glycogen quantification such as post mortem extraction following high energy microwave irradiation are not applicable in the human brain. With the advent of (13)C Magnetic Resonance Spectroscopy (MRS), it has been possible to measure brain glycogen concentrations and turnover in physiological conditions, as well as under the influence of stressors such as hypoglycemia and visual stimulation. This review presents an overview of the principles of the (13)C MRS methodology and its applications in both animals and humans to further our understanding of glycogen metabolism under normal physiological and pathophysiological conditions such as hypoglycemia unawareness.

Imaging liver and brain glycogen metabolism at the nanometer scale

In mammals, glycogen synthesis and degradation are dynamic processes regulating blood and cerebral glucose-levels within a well-defined physiological range. Despite the essential role of glycogen in hepatic and cerebral metabolism, its spatiotemporal distribution at the molecular and cellular level is unclear. By correlating electron microscopy and ultra-high resolution ion microprobe (NanoSIMS) imaging of tissue from fasted mice injected with (13)C-labeled glucose, we demonstrate that liver glycogenesis initiates in the hepatocyte perinuclear region before spreading toward the cell membrane. In the mouse brain, we observe that (13)C is inhomogeneously incorporated into astrocytic glycogen at a rate ~25 times slower than in the liver, in agreement with prior bulk studies. This experiment, using temporally resolved, nanometer-scale imaging of glycogen synthesis and degradation, provides greater insight into glucose metabolism in mammalian organs and shows how this technique can be used to explore biochemical pathways in healthy and diseased states.

Effect of insulin-induced hypoglycaemia on the peripheral nervous system: focus on adaptive mechanisms, pathogenesis and histopathological changes

Insulin-induced hypoglycaemia (IIH) is a common acute side effect in type 1 and type 2 diabetic patients, especially during intensive insulin therapy. The peripheral nervous system (PNS) depends on glucose as its primary energy source during normoglycaemia and, consequently, it may be particularly susceptible to IIH damage. Possible mechanisms for adaption of the PNS to IIH include increased glucose uptake, utilisation of alternative energy substrates and the use of Schwann cell glycogen as a local glucose reserve. However, these potential adaptive mechanisms become insufficient when the hypoglycaemic state exceeds a certain level of severity and duration, resulting in a sensory-motor neuropathy with associated skeletal muscle atrophy. Large myelinated motor fibres appear to be particularly vulnerable. Thus, although the PNS is not an obligate glucose consumer, as is the brain, it appears to be more prone to IIH than the central nervous system when hypoglycaemia is not severe (blood glucose level ≤ 2 mm), possibly reflecting a preferential protection of the brain during periods of inadequate glucose availability. With a primary focus on evidence from experimental animal studies investigating nondiabetic IIH, the present review discusses the effect of IIH on the PNS with a focus on adaptive mechanisms, pathogenesis and histological changes.

Effect of insulin-induced hypoglycaemia on the central nervous system: evidence from experimental studies

Insulin-induced hypoglycaemia (IIH) is a major acute complication in type 1 as well as in type 2 diabetes, particularly during intensive insulin therapy. The brain plays a central role in the counter-regulatory response by eliciting parasympathetic and sympathetic hormone responses to restore normoglycaemia. Brain glucose concentrations, being approximately 15-20% of the blood glucose concentration in humans, are rigorously maintained during hypoglycaemia through adaptions such as increased cerebral glucose transport, decreased cerebral glucose utilisation and, possibly, by using central nervous system glycogen as a glucose reserve. However, during sustained hypoglycaemia, the brain cannot maintain a sufficient glucose influx and, as the cerebral hypoglycaemia becomes severe, electroencephalogram changes, oxidative stress and regional neuronal death ensues. With particular focus on evidence from experimental studies on nondiabetic IIH, this review outlines the central mechanisms behind the counter-regulatory response to IIH, as well as cerebral adaption to avoid sequelae of cerebral neuroglycopaenia, including seizures and coma.

Investigation of field and diffusion time dependence of the diffusion-weighted signal at ultrahigh magnetic fields

Over the last decade, there has been a significant increase in the number of high-magnetic-field MRI magnets. However, the exact effect of a high magnetic field strength (B0 ) on diffusion-weighted MR signals is not yet fully understood. The goal of this study was to investigate the influence of different high magnetic field strengths (9.4 T and 14.1 T) and diffusion times (9, 11, 13, 15, 17 and 24 ms) on the diffusion-weighted signal in rat brain white matter. At a short diffusion time (9 ms), fractional anisotropy values were found to be lower at 14.1 T than at 9.4 T, but this difference disappeared at longer diffusion times. A simple two-pool model was used to explain these findings. The model describes the white matter as a first hindered compartment (often associated with the extra-axonal space), characterized by a faster orthogonal diffusion and a lower fractional anisotropy, and a second restricted compartment (often associated with the intra-axonal space), characterized by a slower orthogonal diffusion (i.e. orthogonal to the axon direction) and a higher fractional anisotropy. Apparent T2 relaxation time measurements of the hindered and restricted pools were performed. The shortening of the pseudo-T2 value from the restricted compartment with B0 is likely to be more pronounced than the apparent T2 changes in the hindered compartment. This study suggests that the observed differences in diffusion tensor imaging parameters between the two magnetic field strengths at short diffusion time may be related to differences in the apparent T2 values between the pools.