scholarly journals Sleep Dependent Changes of Lactate Concentration in Human Brain

2021 ◽  
Author(s):  
Selda Yildiz ◽  
Miranda M. Lim ◽  
Manoj K. Sammi ◽  
Katherine Powers ◽  
Charles F. Murchison ◽  
...  
Keyword(s):  
Human Brain ◽  
Rem Sleep ◽  
Animal Studies ◽  
Sleep Stage ◽  
Lactate Concentration ◽  
Small Animal ◽  
Resonance Spectroscopy ◽  
Non Invasive ◽  
Brain Lactate

AbstractLactate is an important cellular metabolite that is present at high concentrations in the brain, both within cells and in the extracellular space between cells. Small animal studies demonstrated high extracellular concentrations of lactate during wakefulness with reductions during sleep and/or anesthesia with a recent study suggesting the glymphatic activity as the mechanism for the reduction of lactate concentrations. We have recently developed a rigorous non-invasive imaging approach combining simultaneous magnetic resonance spectroscopy (MRS) and polysomnography (PSG) measurements, and here, we present the first in-vivo evaluation of brain lactate levels during sleep-wake cycles in young healthy humans. First, we collected single voxel proton MRS (1H-MRS) data at the posterior cingulate with high temporal resolution (every 7.5 sec), and simultaneously recorded PSG data while temporally registering with 1H-MRS time-series. Second, we evaluated PSG data in 30 s epochs, and classified into four stages Wake (W), Non-REM sleep stage 1 (N1), Non-REM sleep stage 2 (N2), and Non-REM sleep stage 3 (N3). Third, we determined lactate signal intensity from each 7.5-s spectrum, normalized to corresponding water signal, and averaged over 30-s for each PSG epoch. In examinations of nine healthy participants (four females, five males; mean age 24.2 (±2; SD) years; age range: 21-27 years) undergoing up to 3-hour simultaneous MRS/PSG recordings, we observed a group mean reduction of [4.9 ± 4.9] % in N1, [10.4 ± 5.2] % in N2, and [24.0 ± 5.8] % in N3 when compared to W. Our finding is consistent with more than 70 years of invasive lactate measurements from small animal studies. In addition, reduced brain lactate was accompanied by a significant reduction the apparent diffusion coefficient of brain lactate. Taken together, these findings are consistent with the loss of lactate from the extracellular space during sleep while suggesting lactate metabolism is altered and/or lactate clearance via glymphatic exchange is increased during sleep.Significance StatementThis study describes a non-invasive magnetic resonance spectroscopy/polysomnography technique that allows rigorous measurement of brain metabolite levels together with simultaneous characterization of brain arousal state as either wakeful or one of the several sleep states. The results provide the first in-vivo demonstration of reductions in brain lactate concentration and diffusivity during sleep versus wakefulness in young healthy human brain. These findings are consistent with invasive small-animal studies showing the loss of extracellular lactate during sleep, and support the notion of altered lactate metabolism and/or increased glymphatic activity in sleeping human brain.

252 Non-Invasive Quantification of Human Brain Lactate Concentrations Across Sleep-Wake Cycles

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A101-A102
Author(s):  
Selda Yildiz ◽  
Miranda Lim ◽  
Manoj Sammi ◽  
Katherine Powers ◽  
Charles Murchison ◽  
...  
Keyword(s):  
Human Brain ◽  
Sleep Stage ◽  
Small Animal ◽  
Sleep Stages ◽  
1H Mrs ◽  
Animal Brain ◽  
Non Invasive ◽  
Water Signal ◽  
Lactate Levels ◽  
Brain Lactate

Abstract Introduction Cellular mechanisms underlying changes in small animal brain lactate concentrations have been investigated for more than 70 years and report sharp reductions in lactate (12-35%) during sleep or anesthesia relative to wakefulness. The goal of this study was to investigate alterations in human cerebral lactate concentrations across sleep-wake cycles. Toward this goal, we developed a novel non-invasive methodology, quantified changes in human cerebral lactate during sleep stages, and investigated potential mechanisms associated with changes in lactate. Methods Nine subjects (four females, five males; 21-27 y-o, mean age 24.2 ±2) were sleep deprived overnight, and underwent (5:45~11:00 am) experiments combining simultaneous MR-spectroscopy (MRS) and polysomnography (PSG) in a 3 T MR instrument using a 64-channel head/neck coil. A single voxel MRS (1H-MRS) acquired signals from a volume of interest (12~24 cm3) for every 7.5-s for 88~180-min. Lactate signal intensity was determined from each 7.5-s spectrum, normalized to corresponding water signal, and averaged over 30-s for each PSG epochs. Artifact corrected PSG data were scored for each 30-s epoch using the standard criteria and classified into one of four stages: W, N1, N2 and N3. Group mean lactate levels were quantified using LCModel. Three subjects returned for lactate diffusivity measurements using diffusion-sensitized PRESS MRS sequence. Results Compared to W, group mean lactate levels within each sleep stage showed a reduction of [4.9 ± 4.9] % in N1, [10.4 ± 5.2] % in N2, and [24.0 ± 5.8] % in N3. We observed a significant decrease in lactate apparent diffusion coefficient (ADC) accompanied by reduced brain lactate in sleep compared to wake (P<0.002). There were no differences in ADC values between wake and sleep for H2O, NAA, tCr, or Cho. Conclusion This is the first in-vivo report of alterations in human brain lactate concentrations across sleep-wake cycles. Observed decline in lactate levels during sleep compared to wakefulness is consistent with, and extends results from invasive small animal brain studies first reported more than 70 years ago, and support the notion of altered lactate metabolism and/or increased glymphatic activity in sleeping human brain. Support (if any) The Paul. G. Allen Family Foundation funded the study.

scholarly journals BIMG-08. DEUTERIUM MAGNETIC RESONANCE SPECTROSCOPY USING 2H-PYRUVATE ALLOWS NON-INVASIVE IN VIVO IMAGING OF TERT EXPRESSION IN BRAIN TUMORS

2021 ◽  
Vol 3 (Supplement_1) ◽  
pp. i2-i2
Author(s):  
Georgios Batsios ◽  
Celine Taglang ◽  
Meryssa Tran ◽  
Anne Marie Gillespie ◽  
Joseph Costello ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Magnetic Resonance Spectroscopy ◽  
In Vivo Imaging ◽  
Lactate Production ◽  
Telomere Maintenance ◽  
Resonance Spectroscopy ◽  
Low Grade ◽  
Non Invasive ◽  
Tert Expression

Abstract Telomere shortening constitutes a natural barrier to uncontrolled proliferation and all tumors must find a mechanism of maintaining telomere length. Most human tumors, including high-grade primary glioblastomas (GBMs) and low-grade oligodendrogliomas (LGOGs) achieve telomere maintenance via reactivation of the expression of telomerase reverse transcriptase (TERT), which is silenced in normal somatic cells. TERT expression is, therefore, a driver of tumor proliferation and, due to this essential role, TERT is also a therapeutic target. However, non-invasive methods of imaging TERT are lacking. The goal of this study was to identify magnetic resonance spectroscopy (MRS)-detectable metabolic biomarkers of TERT expression that will enable non-invasive visualization of tumor burden in LGOGs and GBMs. First, we silenced TERT expression by RNA interference in patient-derived LGOG (SF10417, BT88) and GBM (GS2) models. Our results linked TERT silencing to significant reductions in steady-state levels of NADH in all models. NADH is essential for the conversion of pyruvate to lactate, suggesting that measuring pyruvate flux to lactate could be useful for imaging TERT status. Recently, deuterium (2H)-MRS has emerged as a novel, clinically translatable method of monitoring metabolic fluxes in vivo. However, to date, studies have solely examined 2H-glucose and the use of [U-2H]pyruvate for non-invasive 2H-MRS has not been tested. Following intravenous injection of a bolus of [U-2H]pyruvate, lactate production was higher in mice bearing orthotopic LGOG (BT88 and SF10417) and GBM (GS2) tumor xenografts relative to tumor-free mice, suggesting that [U-2H]pyruvate has the potential to monitor TERT expression in vivo. In summary, our study, for the first time, shows the feasibility and utility of [U-2H]pyruvate for in vivo imaging. Importantly, since 2H-MRS can be implemented on clinical scanners, our results provide a novel, non-invasive method of integrating information regarding a fundamental cancer hallmark, i.e. TERT, into glioma patient management.

scholarly journals Metabolic Maturation of the Human Brain From Birth Through Adolescence: Insights From In Vivo Magnetic Resonance Spectroscopy

2012 ◽  
Vol 23 (12) ◽  
pp. 2944-2955 ◽  
Author(s):  
S. Bluml ◽  
J. L. Wisnowski ◽  
M. D. Nelson ◽  
L. Paquette ◽  
F. H. Gilles ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Magnetic Resonance Spectroscopy ◽  
Human Brain ◽  
Resonance Spectroscopy

scholarly journals Introduction to in vivo31P magnetic resonance spectroscopy of (human) skeletal muscle

1999 ◽  
Vol 58 (4) ◽  
pp. 861-870 ◽  
Author(s):  
A. Heerschap ◽  
C. Houtman ◽  
H. J. A. in 't Zandt ◽  
A. J. van den Bergh ◽  
B. Wieringa
Keyword(s):  
Skeletal Muscle ◽  
Magnetic Resonance ◽  
Magnetic Resonance Spectroscopy ◽  
Current Status ◽  
Resonance Spectroscopy ◽  
Biochemical Processes ◽  
Non Invasive ◽  
Introductory Overview ◽  
Muscle Biochemistry

31P magnetic resonance spectroscopy (MRS) offers a unique non-invasive window on energy metabolism in skeletal muscle, with possibilities for longitudinal studies and of obtaining important bioenergetic data continuously and with sufficient time resolution during muscle exercise. The present paper provides an introductory overview of the current status of in vivo31P MRS of skeletal muscle, focusing on human applications, but with some illustrative examples from studies on transgenic mice. Topics which are described in the present paper are the information content of the 31P magnetic resonance spectrum of skeletal muscle, some practical issues in the performance of this MRS methodology, related muscle biochemistry and the validity of interpreting results in terms of biochemical processes, the possibility of investigating reaction kinetics in vivo and some indications for fibre-type heterogeneity as seen in spectra obtained during exercise.

scholarly journals Diffuse Correlation Spectroscopy at Short Source-Detector Separations: Simulations, Experiments and Theoretical Modeling

2019 ◽  
Vol 9 (15) ◽  
pp. 3047 ◽  
Author(s):  
Karthik Vishwanath ◽  
Sara Zanfardino
Keyword(s):  
Diffusion Theory ◽  
Small Animal ◽  
Tissue Perfusion ◽  
Flow Channel ◽  
Correlation Spectroscopy ◽  
Diffuse Correlation Spectroscopy ◽  
Non Invasive ◽  
Yield Information ◽  
Theoretical Analyses

Diffuse correlation spectroscopy (DCS) has widely been used as a non-invasive optical technique to measure tissue perfusion in vivo. DCS measurements are quantified to yield information about moving scatterers using photon diffusion theory and are therefore obtained at long source-detector separations (SDS). However, short SDS DCS could be used for measuring perfusion in small animal models or endoscopically in clinical studies. Here, we investigate the errors in analytically retrieved flow coefficients from simulated and experimental data acquired at short SDS. Monte Carlo (MC) simulations of photon correlation transport was programmed to simulate DCS measurements and used to (a) examine the accuracy and validity of theoretical analyses, and (b) model experimental measurements made on phantoms at short SDS. Experiments consisted of measurements from a series of optical phantoms containing an embedded flow channel. Both the fluid flow rate and depth of the flow channel from the liquid surface were varied. Inputs to MC simulations required to model experiments were obtained from corrected theoretical analyses. Results show that the widely used theoretical DCS model is robust for quantifying relative changes in flow. We also show that retrieved flow coefficients at short SDS can be scaled to retrieve absolute values via MC simulations.

scholarly journals Non-Invasive Prediction of IDH Mutation in Patients with Glioma WHO II/III/IV Based on F-18-FET PET-Guided In Vivo 1H-Magnetic Resonance Spectroscopy and Machine Learning

Cancers ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3406
Author(s):  
Elisabeth Bumes ◽  
Fro-Philip Wirtz ◽  
Claudia Fellner ◽  
Jirka Grosse ◽  
Dirk Hellwig ◽  
...  
Keyword(s):  
Machine Learning ◽  
Magnetic Resonance ◽  
Magnetic Resonance Spectroscopy ◽  
Support Vector ◽  
Resonance Spectroscopy ◽  
Idh Mutation ◽  
1H Mrs ◽  
1H Magnetic Resonance Spectroscopy ◽  
Non Invasive

Isocitrate dehydrogenase (IDH)-1 mutation is an important prognostic factor and a potential therapeutic target in glioma. Immunohistological and molecular diagnosis of IDH mutation status is invasive. To avoid tumor biopsy, dedicated spectroscopic techniques have been proposed to detect D-2-hydroxyglutarate (2-HG), the main metabolite of IDH, directly in vivo. However, these methods are technically challenging and not broadly available. Therefore, we explored the use of machine learning for the non-invasive, inexpensive and fast diagnosis of IDH status in standard 1H-magnetic resonance spectroscopy (1H-MRS). To this end, 30 of 34 consecutive patients with known or suspected glioma WHO grade II-IV were subjected to metabolic positron emission tomography (PET) imaging with O-(2-18F-fluoroethyl)-L-tyrosine (18F-FET) for optimized voxel placement in 1H-MRS. Routine 1H-magnetic resonance (1H-MR) spectra of tumor and contralateral healthy brain regions were acquired on a 3 Tesla magnetic resonance (3T-MR) scanner, prior to surgical tumor resection and molecular analysis of IDH status. Since 2-HG spectral signals were too overlapped for reliable discrimination of IDH mutated (IDHmut) and IDH wild-type (IDHwt) glioma, we used a nested cross-validation approach, whereby we trained a linear support vector machine (SVM) on the complete spectral information of the 1H-MRS data to predict IDH status. Using this approach, we predicted IDH status with an accuracy of 88.2%, a sensitivity of 95.5% (95% CI, 77.2–99.9%) and a specificity of 75.0% (95% CI, 42.9–94.5%), respectively. The area under the curve (AUC) amounted to 0.83. Subsequent ex vivo 1H-nuclear magnetic resonance (1H-NMR) measurements performed on metabolite extracts of resected tumor material (eight specimens) revealed myo-inositol (M-ins) and glycine (Gly) to be the major discriminators of IDH status. We conclude that our approach allows a reliable, non-invasive, fast and cost-effective prediction of IDH status in a standard clinical setting.

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