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Mosso J, Briand G, Pierzchala K, Simicic D, Sierra A, Abdollahzadeh A, Jelescu IO, Cudalbu C. Diffusion of brain metabolites highlights altered brain microstructure in type C hepatic encephalopathy: a 9.4 T preliminary study. Front Neurosci 2024; 18:1344076. [PMID: 38572151 PMCID: PMC10987698 DOI: 10.3389/fnins.2024.1344076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Accepted: 02/19/2024] [Indexed: 04/05/2024] Open
Abstract
Introduction Type C hepatic encephalopathy (HE) is a decompensating event of chronic liver disease leading to severe motor and cognitive impairment. The progression of type C HE is associated with changes in brain metabolite concentrations measured by 1H magnetic resonance spectroscopy (MRS), most noticeably a strong increase in glutamine to detoxify brain ammonia. In addition, alterations of brain cellular architecture have been measured ex vivo by histology in a rat model of type C HE. The aim of this study was to assess the potential of diffusion-weighted MRS (dMRS) for probing these cellular shape alterations in vivo by monitoring the diffusion properties of the major brain metabolites. Methods The bile duct-ligated (BDL) rat model of type C HE was used. Five animals were scanned before surgery and 6- to 7-week post-BDL surgery, with each animal being used as its own control. 1H-MRS was performed in the hippocampus (SPECIAL, TE = 2.8 ms) and dMRS in a voxel encompassing the entire brain (DW-STEAM, TE = 15 ms, diffusion time = 120 ms, maximum b-value = 25 ms/μm2) on a 9.4 T scanner. The in vivo MRS acquisitions were further validated with histological measures (immunohistochemistry, Golgi-Cox, electron microscopy). Results The characteristic 1H-MRS pattern of type C HE, i.e., a gradual increase of brain glutamine and a decrease of the main organic osmolytes, was observed in the hippocampus of BDL rats. Overall increased metabolite diffusivities (apparent diffusion coefficient and intra-stick diffusivity-Callaghan's model, significant for glutamine, myo-inositol, and taurine) and decreased kurtosis coefficients were observed in BDL rats compared to control, highlighting the presence of osmotic stress and possibly of astrocytic and neuronal alterations. These results were consistent with the microstructure depicted by histology and represented by a decline in dendritic spines density in neurons, a shortening and decreased number of astrocytic processes, and extracellular edema. Discussion dMRS enables non-invasive and longitudinal monitoring of the diffusion behavior of brain metabolites, reflecting in the present study the globally altered brain microstructure in BDL rats, as confirmed ex vivo by histology. These findings give new insights into metabolic and microstructural abnormalities associated with high brain glutamine and its consequences in type C HE.
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Affiliation(s)
- Jessie Mosso
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Animal Imaging and Technology, École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Guillaume Briand
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Animal Imaging and Technology, École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Katarzyna Pierzchala
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Animal Imaging and Technology, École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Dunja Simicic
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Animal Imaging and Technology, École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Alejandra Sierra
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Ali Abdollahzadeh
- Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States
| | - Ileana O. Jelescu
- Department of Radiology, Lausanne University Hospital (CHUV), Lausanne, Switzerland
- Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Cristina Cudalbu
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Animal Imaging and Technology, École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland
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Ligneul C, Najac C, Döring A, Beaulieu C, Branzoli F, Clarke WT, Cudalbu C, Genovese G, Jbabdi S, Jelescu I, Karampinos D, Kreis R, Lundell H, Marjańska M, Möller HE, Mosso J, Mougel E, Posse S, Ruschke S, Simsek K, Szczepankiewicz F, Tal A, Tax C, Oeltzschner G, Palombo M, Ronen I, Valette J. Diffusion-weighted MR spectroscopy: Consensus, recommendations, and resources from acquisition to modeling. Magn Reson Med 2024; 91:860-885. [PMID: 37946584 DOI: 10.1002/mrm.29877] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 07/18/2023] [Accepted: 09/08/2023] [Indexed: 11/12/2023]
Abstract
Brain cell structure and function reflect neurodevelopment, plasticity, and aging; and changes can help flag pathological processes such as neurodegeneration and neuroinflammation. Accurate and quantitative methods to noninvasively disentangle cellular structural features are needed and are a substantial focus of brain research. Diffusion-weighted MRS (dMRS) gives access to diffusion properties of endogenous intracellular brain metabolites that are preferentially located inside specific brain cell populations. Despite its great potential, dMRS remains a challenging technique on all levels: from the data acquisition to the analysis, quantification, modeling, and interpretation of results. These challenges were the motivation behind the organization of the Lorentz Center workshop on "Best Practices & Tools for Diffusion MR Spectroscopy" held in Leiden, the Netherlands, in September 2021. During the workshop, the dMRS community established a set of recommendations to execute robust dMRS studies. This paper provides a description of the steps needed for acquiring, processing, fitting, and modeling dMRS data, and provides links to useful resources.
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Affiliation(s)
- Clémence Ligneul
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Chloé Najac
- C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - André Döring
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
| | - Christian Beaulieu
- Departments of Biomedical Engineering and Radiology, University of Alberta, Alberta, Edmonton, Canada
| | - Francesca Branzoli
- Paris Brain Institute-ICM, Sorbonne University, UMR S 1127, Inserm U 1127, CNRS UMR 7225, Paris, France
| | - William T Clarke
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Cristina Cudalbu
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Animal Imaging and Technology, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Guglielmo Genovese
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minnesota, Minneapolis, USA
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Ileana Jelescu
- Department of Radiology, Lausanne University Hospital, Lausanne, Switzerland
- Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Dimitrios Karampinos
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| | - Roland Kreis
- MR Methodology, Department for Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland
- Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
| | - Henrik Lundell
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital-Amager anf Hvidovre, Hvidovre, Denmark
- Department of Health Technology, Technical University of Denmark, Lyngby, Denmark
| | - Małgorzata Marjańska
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minnesota, Minneapolis, USA
| | - Harald E Möller
- NMR Methods & Development Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Jessie Mosso
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Animal Imaging and Technology, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- LIFMET, EPFL, Lausanne, Switzerland
| | - Eloïse Mougel
- Université Paris-Saclay, CEA, CNRS, MIRCen, Laboratoires des Maladies Neurodégénératives, Fontenay-aux-Roses, France
| | - Stefan Posse
- Department of Neurology, University of New Mexico School of Medicine, New Mexico, Albuquerque, USA
- Department of Physics and Astronomy, University of New Mexico School of Medicine, New Mexico, Albuquerque, USA
| | - Stefan Ruschke
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| | - Kadir Simsek
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
- School of Computer Science and Informatics, Cardiff University, Cardiff, UK
| | | | - Assaf Tal
- Department of Chemical and Biological Physics, The Weizmann Institute of Science, Rehovot, Israel
| | - Chantal Tax
- University Medical Center Utrecht, Utrecht, The Netherlands
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Physics and Astronomy, Cardiff University, Cardiff, United Kingdom
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Maryland, Baltimore, USA
- F. M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Maryland, Baltimore, USA
| | - Marco Palombo
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
- School of Computer Science and Informatics, Cardiff University, Cardiff, UK
| | - Itamar Ronen
- Clinical Imaging Sciences Centre, Brighton and Sussex Medical School, Brighton, UK
| | - Julien Valette
- Université Paris-Saclay, CEA, CNRS, MIRCen, Laboratoires des Maladies Neurodégénératives, Fontenay-aux-Roses, France
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Mosso J, Simicic D, Lanz B, Gruetter R, Cudalbu C. Diffusion-weighted SPECIAL improves the detection of J-coupled metabolites at ultrahigh magnetic field. Magn Reson Med 2024; 91:4-18. [PMID: 37771277 DOI: 10.1002/mrm.29805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Revised: 06/16/2023] [Accepted: 07/04/2023] [Indexed: 09/30/2023]
Abstract
PURPOSE To improve the detection and subsequent estimation of the diffusion properties of strongly J-coupled metabolites in diffusion-weighted MRS (DWS). METHODS A new sequence for single-voxel diffusion-weighted 1 H MR spectroscopy, named DW-SPECIAL, is proposed. It combines the semi-adiabatic SPECIAL sequence with a stimulated echo diffusion block. Acquisitions with DW-SPECIAL and STE-LASER, the current gold standard for rodent DWS experiments at high fields, were performed at 14.1T on phantoms and in vivo on the rat brain. The apparent diffusion coefficient and intra-stick diffusivity (Callaghan's model, randomly-oriented sticks) were fitted and compared between the sequences for glutamate, glutamine, myo-inositol, taurine, total NAA, total Cho, total Cr, and the macromolecules. RESULTS The shorter TE achieved with DW-SPECIAL (18 ms against 33 ms with STE-LASER) substantially limited the metabolites' signal loss caused by J-evolution. In addition, DW-SPECIAL preserved the main advantages of STE-LASER: absence of cross-terms, diffusion time during a stimulated echo, and limited sensitivity to B1 inhomogeneities. In vivo, compared to STE-LASER, DW-SPECIAL yielded the same spectral quality and reduced the Cramer Rao Lower Bounds for J-coupled metabolites, irrespective of the b-value. DW-SPECIAL also reduced the SD of the metabolites' diffusion estimates based on individual animal fitting without loss of accuracy compared to the fit on the averaged decay. CONCLUSION We conclude that due to its reduced TE, DW-SPECIAL can serve as an alternative to STE-LASER when strongly J-coupled metabolites like glutamine are investigated, thereby extending the range of accessible metabolites in the context of DWS acquisitions.
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Affiliation(s)
- Jessie Mosso
- LIFMET, EPFL, Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Animal Imaging and Technology, EPFL, Lausanne, Switzerland
| | - Dunja Simicic
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Animal Imaging and Technology, EPFL, Lausanne, Switzerland
| | - Bernard Lanz
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Animal Imaging and Technology, EPFL, Lausanne, Switzerland
| | | | - Cristina Cudalbu
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Animal Imaging and Technology, EPFL, Lausanne, Switzerland
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Zöllner HJ, Davies-Jenkins CW, Murali-Manohar S, Gong T, Hui SCN, Song Y, Chen W, Wang G, Edden RAE, Oeltzschner G. Feasibility and implications of using subject-specific macromolecular spectra to model short echo time magnetic resonance spectroscopy data. NMR IN BIOMEDICINE 2023; 36:e4854. [PMID: 36271899 PMCID: PMC9930668 DOI: 10.1002/nbm.4854] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 10/14/2022] [Accepted: 10/15/2022] [Indexed: 05/27/2023]
Abstract
Expert consensus recommends linear-combination modeling (LCM) of 1 H MR spectra with sequence-specific simulated metabolite basis function and experimentally derived macromolecular (MM) basis functions. Measured MM basis functions are usually derived from metabolite-nulled spectra averaged across a small cohort. The use of subject-specific instead of cohort-averaged measured MM basis functions has not been studied widely. Furthermore, measured MM basis functions are not widely available to non-expert users, who commonly rely on parameterized MM signals internally simulated by LCM software. To investigate the impact of the choice of MM modeling, this study, therefore, compares metabolite level estimates between different MM modeling strategies (cohort-mean measured; subject-specific measured; parameterized) in a lifespan cohort and characterizes its impact on metabolite-age associations. 100 conventional (TE = 30 ms) and metabolite-nulled (TI = 650 ms) PRESS datasets, acquired from the medial parietal lobe in a lifespan cohort (20-70 years of age), were analyzed in Osprey. Short-TE spectra were modeled in Osprey using six different strategies to consider the MM baseline. Fully tissue- and relaxation-corrected metabolite levels were compared between MM strategies. Model performance was evaluated by model residuals, the Akaike information criterion (AIC), and the impact on metabolite-age associations. The choice of MM strategy had a significant impact on the mean metabolite level estimates and no major impact on variance. Correlation analysis revealed moderate-to-strong agreement between different MM strategies (r > 0.6). The lowest relative model residuals and AIC values were found for the cohort-mean measured MM. Metabolite-age associations were consistently found for two major singlet signals (total creatine (tCr])and total choline (tCho)) for all MM strategies; however, findings for metabolites that are less distinguishable from the background signals associations depended on the MM strategy. A variance partition analysis indicated that up to 44% of the total variance was related to the choice of MM strategy. Additionally, the variance partition analysis reproduced the metabolite-age association for tCr and tCho found in the simpler correlation analysis. In summary, the inclusion of a single high signal-to-noise ratio MM basis function (cohort-mean) in the short-TE LCM leads to more lower model residuals and AIC values compared with MM strategies with more degrees of freedom (Gaussian parametrization) or subject-specific MM information. Integration of multiple LCM analyses into a single statistical model potentially allows to identify the robustness in the detection of underlying effects (e.g., metabolite vs. age), reduces algorithm-based bias, and estimates algorithm-related variance.
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Affiliation(s)
- Helge J. Zöllner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Christopher W. Davies-Jenkins
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Saipavitra Murali-Manohar
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Tao Gong
- Departments of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021,China
- Departments of Radiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Jinan, Shandong, 250021,China
| | - Steve C. N. Hui
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Yulu Song
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | | | - Guangbin Wang
- Departments of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021,China
- Departments of Radiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Jinan, Shandong, 250021,China
| | - Richard A. E. Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
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Mosso J, Simicic D, Şimşek K, Kreis R, Cudalbu C, Jelescu IO. MP-PCA denoising for diffusion MRS data: promises and pitfalls. Neuroimage 2022; 263:119634. [PMID: 36150605 DOI: 10.1016/j.neuroimage.2022.119634] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 09/07/2022] [Accepted: 09/14/2022] [Indexed: 10/31/2022] Open
Abstract
Diffusion-weighted (DW) magnetic resonance spectroscopy (MRS) suffers from a lower signal to noise ratio (SNR) compared to conventional MRS owing to the addition of diffusion attenuation. This technique can therefore strongly benefit from noise reduction strategies. In the present work, Marchenko-Pastur principal component analysis (MP-PCA) denoising is tested on Monte Carlo simulations and on in vivo DW-MRS data acquired at 9.4 T in rat brain and at 3 T in human brain. We provide a descriptive study of the effects observed following different MP-PCA denoising strategies (denoising the entire matrix versus using a sliding window), in terms of apparent SNR, rank selection, noise correlation within and across b-values and quantification of metabolite concentrations and fitted diffusion coefficients. MP-PCA denoising yielded an increased apparent SNR, a more accurate B0 drift correction between shots, and similar estimates of metabolite concentrations and diffusivities compared to the raw data. No spectral residuals on individual shots were observed but correlations in the noise level across shells were introduced, an effect which was mitigated using a sliding window, but which should be carefully considered.
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Affiliation(s)
- Jessie Mosso
- CIBM Center for Biomedical Imaging, Switzerland; Animal Imaging and Technology, EPFL, Lausanne, Switzerland; LIFMET, EPFL, Lausanne, Switzerland.
| | - Dunja Simicic
- CIBM Center for Biomedical Imaging, Switzerland; Animal Imaging and Technology, EPFL, Lausanne, Switzerland; LIFMET, EPFL, Lausanne, Switzerland
| | - Kadir Şimşek
- Magnetic Resonance Methodology, Institute of Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland; Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland; Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Roland Kreis
- Magnetic Resonance Methodology, Institute of Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland; Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
| | - Cristina Cudalbu
- CIBM Center for Biomedical Imaging, Switzerland; Animal Imaging and Technology, EPFL, Lausanne, Switzerland
| | - Ileana O Jelescu
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
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Şimşek K, Döring A, Pampel A, Möller HE, Kreis R. Macromolecular background signal and non-Gaussian metabolite diffusion determined in human brain using ultra-high diffusion weighting. Magn Reson Med 2022; 88:1962-1977. [PMID: 35803740 PMCID: PMC9545875 DOI: 10.1002/mrm.29367] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 05/08/2022] [Accepted: 05/31/2022] [Indexed: 12/14/2022]
Abstract
Purpose Definition of a macromolecular MR spectrum based on diffusion properties rather than relaxation time differences and characterization of non‐Gaussian diffusion of brain metabolites with strongly diffusion‐weighted MR spectroscopy. Methods Short echo time MRS with strong diffusion‐weighting with b‐values up to 25 ms/μm2 at two diffusion times was implemented on a Connectom system and applied in combination with simultaneous spectral and diffusion decay modeling. Motion‐compensation was performed with a combined method based on the simultaneously acquired water and a macromolecular signal. Results The motion compensation scheme prevented spurious signal decay reflected in very small apparent diffusion constants for macromolecular signal. Macromolecular background signal patterns were determined using multiple fit strategies. Signal decay corresponding to non‐Gaussian metabolite diffusion was represented by biexponential fit models yielding parameter estimates for human gray matter that are in line with published rodent data. The optimal fit strategies used constraints for the signal decay of metabolites with limited signal contributions to the overall spectrum. Conclusion The determined macromolecular spectrum based on diffusion properties deviates from the conventional one derived from longitudinal relaxation time differences calling for further investigation before use as experimental basis spectrum when fitting clinical MR spectra. The biexponential characterization of metabolite signal decay is the basis for investigations into pathologic alterations of microstructure. Click here for author‐reader discussions
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Affiliation(s)
- Kadir Şimşek
- Magnetic Resonance MethodologyInstitute of Diagnostic and Interventional Neuroradiology, University of BernBernSwitzerland
- Graduate School for Cellular and Biomedical SciencesUniversity of BernBernSwitzerland
- Translational Imaging Center (TIC)Swiss Institute for Translational and Entrepreneurial MedicineBernSwitzerland
| | - André Döring
- Cardiff University Brain Research Imaging Centre (CUBRIC)School of Psychology, Cardiff UniversityCardiffUK
| | - André Pampel
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Harald E. Möller
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Roland Kreis
- Magnetic Resonance MethodologyInstitute of Diagnostic and Interventional Neuroradiology, University of BernBernSwitzerland
- Translational Imaging Center (TIC)Swiss Institute for Translational and Entrepreneurial MedicineBernSwitzerland
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Simicic D, Rackayova V, Xin L, Tkáč I, Borbath T, Starcuk Z, Starcukova J, Lanz B, Cudalbu C. In vivo macromolecule signals in rat brain 1 H-MR spectra at 9.4T: Parametrization, spline baseline estimation, and T 2 relaxation times. Magn Reson Med 2021; 86:2384-2401. [PMID: 34268821 PMCID: PMC8596437 DOI: 10.1002/mrm.28910] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 05/25/2021] [Accepted: 06/11/2021] [Indexed: 12/24/2022]
Abstract
PURPOSE Reliable detection and fitting of macromolecules (MM) are crucial for accurate quantification of brain short-echo time (TE) 1 H-MR spectra. An experimentally acquired single MM spectrum is commonly used. Higher spectral resolution at ultra-high field (UHF) led to increased interest in using a parametrized MM spectrum together with flexible spline baselines to address unpredicted spectroscopic components. Herein, we aimed to: (1) implement an advanced methodological approach for post-processing, fitting, and parametrization of 9.4T rat brain MM spectra; (2) assess the concomitant impact of the LCModel baseline and MM model (ie, single vs parametrized); and (3) estimate the apparent T2 relaxation times for seven MM components. METHODS A single inversion recovery sequence combined with advanced AMARES prior knowledge was used to eliminate the metabolite residuals, fit, and parametrize 10 MM components directly from 9.4T rat brain in vivo 1 H-MR spectra at different TEs. Monte Carlo simulations were also used to assess the concomitant influence of parametrized MM and DKNTMN parameter in LCModel. RESULTS A very stiff baseline (DKNTMN ≥ 1 ppm) in combination with a single MM spectrum led to deviations in metabolite concentrations. For some metabolites the parametrized MM showed deviations from the ground truth for all DKNTMN values. Adding prior knowledge on parametrized MM improved MM and metabolite quantification. The apparent T2 ranged between 12 and 24 ms for seven MM peaks. CONCLUSION Moderate flexibility in the spline baseline was required for reliable quantification of real/experimental spectra based on in vivo and Monte Carlo data. Prior knowledge on parametrized MM improved MM and metabolite quantification.
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Affiliation(s)
- Dunja Simicic
- CIBM Center for Biomedical Imaging, Switzerland.,Animal Imaging and Technology, EPFL, Lausanne, Switzerland.,Laboratory for functional and metabolic imaging (LIFMET), EPFL, Lausanne, Switzerland
| | - Veronika Rackayova
- CIBM Center for Biomedical Imaging, Switzerland.,Animal Imaging and Technology, EPFL, Lausanne, Switzerland
| | - Lijing Xin
- CIBM Center for Biomedical Imaging, Switzerland.,Animal Imaging and Technology, EPFL, Lausanne, Switzerland
| | - Ivan Tkáč
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Tamas Borbath
- High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.,Faculty of Science, University of Tübingen, Tübingen, Germany
| | - Zenon Starcuk
- Institute of Scientific Instruments, Czech Academy of Sciences, Brno, Czech Republic
| | - Jana Starcukova
- Institute of Scientific Instruments, Czech Academy of Sciences, Brno, Czech Republic
| | - Bernard Lanz
- Laboratory for functional and metabolic imaging (LIFMET), EPFL, Lausanne, Switzerland
| | - Cristina Cudalbu
- CIBM Center for Biomedical Imaging, Switzerland.,Animal Imaging and Technology, EPFL, Lausanne, Switzerland
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8
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Cudalbu C, Behar KL, Bhattacharyya PK, Bogner W, Borbath T, de Graaf RA, Gruetter R, Henning A, Juchem C, Kreis R, Lee P, Lei H, Marjańska M, Mekle R, Murali-Manohar S, Považan M, Rackayová V, Simicic D, Slotboom J, Soher BJ, Starčuk Z, Starčuková J, Tkáč I, Williams S, Wilson M, Wright AM, Xin L, Mlynárik V. Contribution of macromolecules to brain 1 H MR spectra: Experts' consensus recommendations. NMR IN BIOMEDICINE 2021; 34:e4393. [PMID: 33236818 PMCID: PMC10072289 DOI: 10.1002/nbm.4393] [Citation(s) in RCA: 64] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Revised: 07/08/2020] [Accepted: 07/13/2020] [Indexed: 05/08/2023]
Abstract
Proton MR spectra of the brain, especially those measured at short and intermediate echo times, contain signals from mobile macromolecules (MM). A description of the main MM is provided in this consensus paper. These broad peaks of MM underlie the narrower peaks of metabolites and often complicate their quantification but they also may have potential importance as biomarkers in specific diseases. Thus, separation of broad MM signals from low molecular weight metabolites enables accurate determination of metabolite concentrations and is of primary interest in many studies. Other studies attempt to understand the origin of the MM spectrum, to decompose it into individual spectral regions or peaks and to use the components of the MM spectrum as markers of various physiological or pathological conditions in biomedical research or clinical practice. The aim of this consensus paper is to provide an overview and some recommendations on how to handle the MM signals in different types of studies together with a list of open issues in the field, which are all summarized at the end of the paper.
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Affiliation(s)
- Cristina Cudalbu
- Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Vaud, Switzerland
| | - Kevin L Behar
- Magnetic Resonance Research Center and Department of Psychiatry, Yale University, New Haven, Connecticut, USA
| | | | - Wolfgang Bogner
- High Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
- Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria
| | - Tamas Borbath
- High-Field Magnetic Resonance, Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany
- Faculty of Science, Eberhard-Karls Universität Tübingen, Tübingen, Germany
| | - Robin A de Graaf
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, Connecticut, USA
| | - Rolf Gruetter
- Laboratory for Functional and Metabolic Imaging, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Anke Henning
- High-Field Magnetic Resonance, Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, Germany
| | - Christoph Juchem
- Departments of Biomedical Engineering and Radiology, Columbia University, New York, USA
| | - Roland Kreis
- Departments of Radiology and Biomedical Research, University of Bern, Bern, Switzerland
| | - Phil Lee
- Department of Radiology, Hoglund Brain Imaging Center, University of Kansas Medical Center, Kansas City, Kansas, USA
| | - Hongxia Lei
- Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Vaud, Switzerland
| | - Małgorzata Marjańska
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Ralf Mekle
- Center for Stroke Research Berlin (CSB), Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Saipavitra Murali-Manohar
- High-Field Magnetic Resonance, Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany
- Faculty of Science, Eberhard-Karls Universität Tübingen, Tübingen, Germany
| | - Michal Považan
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Veronika Rackayová
- Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Vaud, Switzerland
- Laboratory for Functional and Metabolic Imaging, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Dunja Simicic
- Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Vaud, Switzerland
- Laboratory for Functional and Metabolic Imaging, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Johannes Slotboom
- University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern and Inselspital, Bern, Switzerland
| | - Brian J Soher
- Center for Advanced MR Development, Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA
| | - Zenon Starčuk
- Czech Academy of Sciences, Institute of Scientific Instruments, Brno, Czech Republic
| | - Jana Starčuková
- Czech Academy of Sciences, Institute of Scientific Instruments, Brno, Czech Republic
| | - Ivan Tkáč
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Stephen Williams
- Division of Informatics, Imaging and Data Science, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Martin Wilson
- Centre for Human Brain Health and School of Psychology, University of Birmingham, Birmingham, UK
| | - Andrew Martin Wright
- High-Field Magnetic Resonance, Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany
- IMPRS for Cognitive and Systems Neuroscience, Eberhard-Karls Universität Tübingen, Tübingen, Germany
| | - Lijing Xin
- Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Vaud, Switzerland
| | - Vladimír Mlynárik
- High Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
- Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria
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9
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Li Y, Wang Z, Sun R, Lam F. Separation of Metabolites and Macromolecules for Short-TE 1H-MRSI Using Learned Component-Specific Representations. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:1157-1167. [PMID: 33395390 PMCID: PMC8049099 DOI: 10.1109/tmi.2020.3048933] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Short-echo-time (TE) proton magnetic resonance spectroscopic imaging (MRSI) allows for simultaneously mapping a number of molecules in the brain, and has been recognized as an important tool for studying in vivo biochemistry in various neuroscience and disease applications. However, separation of the metabolite and macromolecule (MM) signals present in the short-TE data with significant spectral overlaps remains a major technical challenge. This work introduces a new approach to solve this problem by integrating imaging physics and representation learning. Specifically, a mixed unsupervised and supervised learning-based strategy was developed to learn the metabolite and MM-specific low-dimensional representations using deep autoencoders. A constrained reconstruction formulation is proposed to integrate the MRSI spatiospectral encoding model and the learned representations as effective constraints for signal separation. An efficient algorithm was developed to solve the resulting optimization problem with provable convergence. Simulation and experimental results have been obtained to demonstrate the component-specific representation power of the learned models and the capability of the proposed method in separating metabolite and MM signals for practical short-TE [Formula: see text]-MRSI data.
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10
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Cherix A, Donati G, Lizarbe B, Lanz B, Poitry-Yamate C, Lei H, Gruetter R. Excitatory/inhibitory neuronal metabolic balance in mouse hippocampus upon infusion of [U- 13C 6]glucose. J Cereb Blood Flow Metab 2021; 41:282-297. [PMID: 32151224 PMCID: PMC8370000 DOI: 10.1177/0271678x20910535] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Hippocampus plays a critical role in linking brain energetics and behavior typically associated to stress exposure. In this study, we aimed to simultaneously assess excitatory and inhibitory neuronal metabolism in mouse hippocampus in vivo by applying 18FDG-PET and indirect 13C magnetic resonance spectroscopy (1H-[13C]-MRS) at 14.1 T upon infusion of uniformly 13C-labeled glucose ([U-13C6]Glc). Improving the spectral fitting by taking into account variable decoupling efficiencies of [U-13C6]Glc and refining the compartmentalized model by including two γ-aminobutyric acid (GABA) pools permit us to evaluate the relative contributions of glutamatergic and GABAergic metabolism to total hippocampal neuroenergetics. We report that GABAergic activity accounts for ∼13% of total neurotransmission (VNT) and ∼27% of total neuronal TCA cycle (VTCA) in mouse hippocampus suggesting a higher VTCA/VNT ratio for inhibitory neurons compared to excitatory neurons. Finally, our results provide new strategies and tools for bringing forward the developments and applications of 13C-MRS in specific brain regions of small animals.
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Affiliation(s)
- Antoine Cherix
- Laboratory for Functional and Metabolic Imaging, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Guillaume Donati
- Laboratory for Functional and Metabolic Imaging, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Blanca Lizarbe
- Laboratory for Functional and Metabolic Imaging, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.,Instituto de Investigaciones Biomedicas "Alberto Sols", CSIC-UAM, Madrid, Spain
| | - Bernard Lanz
- Laboratory for Functional and Metabolic Imaging, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.,Sir Peter Mansfield Imaging Centre (SPMIC), School of Medicine, University of Nottingham, Nottingham, UK
| | - Carole Poitry-Yamate
- Laboratory for Functional and Metabolic Imaging, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Hongxia Lei
- Center for Biomedical Imaging (CIBM-AIT), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Rolf Gruetter
- Laboratory for Functional and Metabolic Imaging, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
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11
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Dehghani M, Kunz N, Lei H. Diffusion behavior of cerebral metabolites of congenital portal systemic shunt mice assessed noninvasively by diffusion-weighted 1 H magnetic resonance spectroscopy. NMR IN BIOMEDICINE 2020; 33:e4198. [PMID: 31765073 DOI: 10.1002/nbm.4198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2018] [Revised: 08/27/2019] [Accepted: 09/13/2019] [Indexed: 06/10/2023]
Abstract
Diffusion-weighted 1 H-MRS (DW-MRS) allows for noninvasive investigation of the cellular compartmentalization of cerebral metabolites. DW-MRS applied to the congenital portal systemic shunt (PSS) mouse brain may provide specific insight into alterations of cellular restrictions associated with PSS in humans. At 14.1 T, adult male PSS and their age-matched healthy (Ctrl) mice were studied using DW-MRS covering b-values ranging from 0 to 45 ms/μm2 to determine the diffusion behavior of abundant metabolites. The remarkable sensitivity and spectral resolution, in combination with very high diffusion weighting, allowed for precise measurement of the diffusion properties of endogenous N-acetyl-aspartate, total creatine, myo-inositol, total choline with extension to glutamine and glutamate in mouse brains, in vivo. Most metabolites had comparable diffusion properties in PSS and Ctrl mice, suggesting that intracellular distribution space for these metabolites was not affected in the model. The slightly different diffusivity of the slow decaying component of taurine (0.015 ± 0.003 μm2 /ms in PSS vs 0.021 ± 0.002 μm2 /ms in Ctrl, P < 0.05) might support a cellular redistribution of taurine in the PSS mouse brain.
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Affiliation(s)
- Masoumeh Dehghani
- Laboratory of Functional and Metabolic Imaging (LIFMET), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Department of Psychiatry, McGill University, Montreal, Canada
| | - Nicolas Kunz
- Center for Biomedical Imaging (CIBM), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Hongxia Lei
- Center for Biomedical Imaging (CIBM), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
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12
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Chen X, Tamang SM, Du F, Ongur D. Glutamate diffusion in the rat brain in vivo under light and deep anesthesia conditions. Magn Reson Med 2019; 82:84-94. [PMID: 30860289 DOI: 10.1002/mrm.27722] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2018] [Revised: 01/08/2019] [Accepted: 02/11/2019] [Indexed: 11/08/2022]
Abstract
PURPOSE Glutamate (Glu) is the most abundant neurotransmitter in the human central nervous system and glutamatergic neurotransmission has been implicated in many common and severe neuropsychiatric disorders. In vivo MRS techniques have been developed to measure brain Glu concentration to investigate the pathophysiology of various brain disorders. However, it is difficult to interpret Glu signal changes because Glu plays multiple roles in the brain and is found in multiple microenvironments including cytosolic, vesicular, and extracellular. METHODS In vivo diffusion-weighted MRS (DW-MRS) with low to very high b-values was performed on the rat prefrontal cortex at 9.4T under both light and deep anesthetic conditions to examine Glu diffusion properties. RESULTS Significant alterations in Glu diffusion as well as reduced Glu concentration were observed under deep anesthesia compared with superficial anesthesia in the absence of similar changes in NAA or creatine. CONCLUSION The modifications in Glu diffusion under deep anesthesia might reflect changes in Glu microenvironment. The present work shows that Glu DW-MRS could be an important tool to explore Glu physiology with changing levels of neuronal activity and synaptic function.
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Affiliation(s)
- Xi Chen
- McLean Imaging Center, McLean Hospital, Harvard Medical School, Belmont, Massachusetts.,Psychotic Disorders Division, McLean Hospital, Harvard Medical School, Belmont, Massachusetts
| | - Siddartha M Tamang
- Psychotic Disorders Division, McLean Hospital, Harvard Medical School, Belmont, Massachusetts
| | - Fei Du
- McLean Imaging Center, McLean Hospital, Harvard Medical School, Belmont, Massachusetts.,Psychotic Disorders Division, McLean Hospital, Harvard Medical School, Belmont, Massachusetts
| | - Dost Ongur
- Psychotic Disorders Division, McLean Hospital, Harvard Medical School, Belmont, Massachusetts
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13
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Semiblind Spectral Factorization Approach for Magnetic Resonance Spectroscopy Quantification. IEEE Trans Biomed Eng 2018; 65:1717-1724. [DOI: 10.1109/tbme.2017.2770088] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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14
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Lizarbe B, Lei H, Duarte JM, Lanz B, Cherix A, Gruetter R. Feasibility of in vivo measurement of glucose metabolism in the mouse hypothalamus by1H-[13C] MRS at 14.1T. Magn Reson Med 2018; 80:874-884. [DOI: 10.1002/mrm.27129] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2017] [Revised: 01/22/2018] [Accepted: 01/22/2018] [Indexed: 12/24/2022]
Affiliation(s)
- Blanca Lizarbe
- Laboratory of Functional and Metabolic Imaging (LIFMET), École Polytechnique Fédérale de Lausanne; Lausanne Switzerland
| | - Hongxia Lei
- Department of Radiology; University of Geneva, Geneva, Switzerland and Center for Biomedical Imaging (CIBM); Lausanne Switzerland
| | - Joao M.N. Duarte
- Laboratory of Functional and Metabolic Imaging (LIFMET), École Polytechnique Fédérale de Lausanne; Lausanne Switzerland
| | - Bernard Lanz
- Laboratory of Functional and Metabolic Imaging (LIFMET), École Polytechnique Fédérale de Lausanne; Lausanne Switzerland
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham; Nottingham United Kingdom
| | - Antoine Cherix
- Laboratory of Functional and Metabolic Imaging (LIFMET), École Polytechnique Fédérale de Lausanne; Lausanne Switzerland
| | - Rolf Gruetter
- Laboratory of Functional and Metabolic Imaging (LIFMET), École Polytechnique Fédérale de Lausanne; Lausanne Switzerland
- Department of Radiology; University of Geneva, Geneva, Switzerland and Center for Biomedical Imaging (CIBM); Lausanne Switzerland
- Department of Radiology; University of Lausanne; Lausanne Switzerland
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15
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Dehghani M, Kunz N, Lanz B, Yoshihara HAI, Gruetter R. Diffusion-weighted MRS of acetate in the rat brain. NMR IN BIOMEDICINE 2017; 30:e3768. [PMID: 28796319 DOI: 10.1002/nbm.3768] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2016] [Revised: 05/04/2017] [Accepted: 05/31/2017] [Indexed: 06/07/2023]
Abstract
Acetate has been proposed as an astrocyte-specific energy substrate for metabolic studies in the brain. The determination of the relative contribution of the intracellular and extracellular compartments to the acetate signal using diffusion-weighted magnetic resonance spectroscopy can provide an insight into the cellular environment and distribution volume of acetate in the brain. In the present study, localized 1 H nuclear magnetic resonance (NMR) spectroscopy employing a diffusion-weighted stimulated echo acquisition mode (STEAM) sequence at an ultra-high magnetic field (14.1 T) was used to investigate the diffusivity characteristics of acetate and N-acetylaspartate (NAA) in the rat brain in vivo during prolonged acetate infusion. The persistence of the acetate resonance in 1 H spectra acquired at very large diffusion weighting indicated restricted diffusion of acetate and was attributed to intracellular spaces. However, the significantly greater diffusion of acetate relative to NAA suggests that a substantial fraction of acetate is located in the extracellular space of the brain. Assuming an even distribution for acetate in intracellular and extracellular spaces, the diffusion properties of acetate yielded a smaller volume of distribution for acetate relative to water and glucose in the rat brain.
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Affiliation(s)
- Masoumeh Dehghani
- Laboratoire d'imagerie fonctionnelle et métabolique (LIFMET), École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Nicolas Kunz
- Centre d'Imagerie BioMédicale (CIBM)-AIT, École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Bernard Lanz
- Laboratoire d'imagerie fonctionnelle et métabolique (LIFMET), École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Hikari A I Yoshihara
- Service de Cardiologie, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
| | - Rolf Gruetter
- Laboratoire d'imagerie fonctionnelle et métabolique (LIFMET), École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Centre d'Imagerie BioMédicale (CIBM), École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Radiology, Université de Lausanne (UNIL), Lausanne, Switzerland
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16
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Adalid V, Döring A, Kyathanahally SP, Bolliger CS, Boesch C, Kreis R. Fitting interrelated datasets: metabolite diffusion and general lineshapes. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2017; 30:429-448. [DOI: 10.1007/s10334-017-0618-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2016] [Revised: 03/24/2017] [Accepted: 03/27/2017] [Indexed: 12/23/2022]
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17
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Xin L, Tkáč I. A practical guide to in vivo proton magnetic resonance spectroscopy at high magnetic fields. Anal Biochem 2016; 529:30-39. [PMID: 27773654 DOI: 10.1016/j.ab.2016.10.019] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2016] [Revised: 10/03/2016] [Accepted: 10/19/2016] [Indexed: 12/26/2022]
Abstract
Localized proton magnetic resonance spectroscopy (1H-MRS) is a noninvasive tool for measuring in vivo neurochemical information in animal and human brains. With the increase of magnetic field strength, whereas localized 1H-MRS benefits from higher sensitivity and spectral dispersion, it is challenged by increased spatial inhomogeneity of the B0 and B1 fields, larger chemical shift displacement error, and shortened T2 relaxation times of metabolites. Advanced localized 1H-MRS methodologies developed for high magnetic fields have shown promising results and allow the measurement of neurochemical profiles with up to 19 brain metabolites, including less-abundant metabolites, such as glutathione, glycine, γ-aminobutyric acid and ascorbate. To provide a practical guide for conducting in vivo1H-MRS studies at high magnetic field strength, we reviewed various essential technical aspects from data acquisition (hardware requirements, B1 and B0 inhomogeneity, water suppression, localization sequences and acquisition strategies) to data processing (frequency and phase correction, spectral quality control, spectral fitting and concentration referencing). Additionally, we proposed guidelines for choosing the most appropriate data acquisition and processing approaches to maximize the achievable neurochemical information.
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Affiliation(s)
- Lijing Xin
- Animal Imaging and Technology Core (AIT), Center for Biomedical Imaging (CIBM), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
| | - Ivan Tkáč
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA.
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18
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Ligneul C, Palombo M, Valette J. Metabolite diffusion up to very high b in the mouse brain in vivo: Revisiting the potential correlation between relaxation and diffusion properties. Magn Reson Med 2016; 77:1390-1398. [PMID: 27018415 PMCID: PMC5008464 DOI: 10.1002/mrm.26217] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2015] [Revised: 01/26/2016] [Accepted: 02/23/2016] [Indexed: 12/19/2022]
Abstract
PURPOSE To assess the potential correlation between metabolites diffusion and relaxation in the mouse brain, which is of importance for interpreting and modeling metabolite diffusion based on pure geometry, irrespective of relaxation properties (multicompartmental relaxation or surface relaxivity). METHODS A new diffusion-weighted magnetic resonance spectroscopy sequence is introduced, dubbed "STE-LASER," which presents several nice properties, in particular the absence of cross-terms with selection gradients and a very clean localization. Metabolite diffusion is then measured in a large voxel in the mouse brain at 11.7 Tesla using a cryoprobe, resulting in excellent signal-to-noise ratio, up to very high b-values under different echo time, mixing time, and diffusion time combinations. RESULTS Our results suggest that the correlation between relaxation and diffusion properties is extremely small or even nonexistent for metabolites in the mouse brain. CONCLUSION The present work strongly supports the interpretation and modeling of metabolite diffusion primarily based on geometry, irrespective of relaxation properties, at least under current experimental conditions. Magn Reson Med 77:1390-1398, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
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Affiliation(s)
- Clémence Ligneul
- Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), Direction des Sciences du Vivant (DSV), Institut d'Imagerie Biomédicale (I2BM), MIRCen, Fontenay-aux-Roses, France.,Centre National de la Recherche Scientifique (CNRS), Université Paris-Sud, Université Paris-Saclay, UMR 9199, Neurodegenerative Diseases Laboratory, Fontenay-aux-Roses, France
| | - Marco Palombo
- Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), Direction des Sciences du Vivant (DSV), Institut d'Imagerie Biomédicale (I2BM), MIRCen, Fontenay-aux-Roses, France.,Centre National de la Recherche Scientifique (CNRS), Université Paris-Sud, Université Paris-Saclay, UMR 9199, Neurodegenerative Diseases Laboratory, Fontenay-aux-Roses, France
| | - Julien Valette
- Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), Direction des Sciences du Vivant (DSV), Institut d'Imagerie Biomédicale (I2BM), MIRCen, Fontenay-aux-Roses, France.,Centre National de la Recherche Scientifique (CNRS), Université Paris-Sud, Université Paris-Saclay, UMR 9199, Neurodegenerative Diseases Laboratory, Fontenay-aux-Roses, France
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19
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Jiru F, Skoch A, Wagnerova D, Dezortova M, Viskova J, Profant O, Syka J, Hajek M. The age dependence of T2 relaxation times of N-acetyl aspartate, creatine and choline in the human brain at 3 and 4T. NMR IN BIOMEDICINE 2016; 29:284-292. [PMID: 26752593 DOI: 10.1002/nbm.3456] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2014] [Revised: 10/12/2015] [Accepted: 11/09/2015] [Indexed: 06/05/2023]
Abstract
Knowledge of the T2 age dependence is of importance for MRS clinical studies involving subject groups with a wide age range. A number of studies have focused on the age dependence of T2 values in the human brain, with rather conflicting results. The aim of this study was to analyze the age dependence of T2 values of N-acetyl aspartate (NAA), creatine (Cr) and choline (Cho) in the human brain using data acquired at 3T and 4T and to assess the influence of the macromolecule (MM) baseline handling on the obtained results. Two distinct groups of young and elderly controls have been measured at 3T (TE = 30-540 ms, 9 young and 11 elderly subjects) and 4T (TE = 10-180 ms, 18 young and 14 elderly subjects) using single-voxel spectroscopy. In addition, MM spectra were measured from two subjects using the inversion-recovery technique at 4T. All spectra were processed with LCModel using basis sets with different MM signals (measured or simulated) and also with MM signals included for a different TE range. Individual estimated T2 values were statistically analyzed using the R programming language for the age dependence of T2 values as well as the influence of the MM baseline handling. A significant decrease of T2 values of NAA and Cr in elderly subjects compared with young subjects was confirmed. The same trend was observed for Cho. Significantly higher T2 values calculated using the measured MM baseline for all studied metabolites at 4T were observed for both young and elderly subjects. To conclude, while the handling of MM and lipid signals may have a significant effect on estimated T2 values, we confirmed the age dependence of T2 values of NAA and Cr and the same trend for Cho in the human brain. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- F Jiru
- Institute for Clinical and Experimental Medicine, MR-Unit, Department of Diagnostic and Interventional Radiology, Prague, Czech Republic
| | - A Skoch
- Institute for Clinical and Experimental Medicine, MR-Unit, Department of Diagnostic and Interventional Radiology, Prague, Czech Republic
- International Clinical Research Center, Department of Imaging Methods, St Anne's University Hospital Brno, Brno, Czech Republic
| | - D Wagnerova
- Institute for Clinical and Experimental Medicine, MR-Unit, Department of Diagnostic and Interventional Radiology, Prague, Czech Republic
| | - M Dezortova
- Institute for Clinical and Experimental Medicine, MR-Unit, Department of Diagnostic and Interventional Radiology, Prague, Czech Republic
| | - J Viskova
- International Clinical Research Center, Department of Imaging Methods, St Anne's University Hospital Brno, Brno, Czech Republic
| | - O Profant
- Institute of Experimental Medicine, Academy of Sciences of the Czech Republic, Department of Auditory Neuroscience, Prague, Czech Republic
- First Faculty of Medicine, Charles University, Faculty Hospital Motol, Department of Otorhinolaryngology and Head and Neck Surgery, Prague, Czech Republic
| | - J Syka
- Institute of Experimental Medicine, Academy of Sciences of the Czech Republic, Department of Auditory Neuroscience, Prague, Czech Republic
| | - M Hajek
- Institute for Clinical and Experimental Medicine, MR-Unit, Department of Diagnostic and Interventional Radiology, Prague, Czech Republic
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20
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Diserens G, Vermathen M, Precht C, Broskey NT, Boesch C, Amati F, Dufour JF, Vermathen P. Separation of small metabolites and lipids in spectra from biopsies by diffusion-weighted HR-MAS NMR: a feasibility study. Analyst 2015; 140:272-9. [PMID: 25368873 DOI: 10.1039/c4an01663g] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
High Resolution Magic Angle Spinning (HR-MAS) NMR allows metabolic characterization of biopsies. HR-MAS spectra from tissues of most organs show strong lipid contributions that are overlapping metabolite regions, which hamper metabolite estimation. Metabolite quantification and analysis would benefit from a separation of lipids and small metabolites. Generally, a relaxation filter is used to reduce lipid contributions. However, the strong relaxation filter required to eliminate most of the lipids also reduces the signals for small metabolites. The aim of our study was therefore to investigate different diffusion editing techniques in order to employ diffusion differences for separating lipid and small metabolite contributions in the spectra from different organs for unbiased metabonomic analysis. Thus, 1D and 2D diffusion measurements were performed, and pure lipid spectra that were obtained at strong diffusion weighting (DW) were subtracted from those obtained at low DW, which include both small metabolites and lipids. This subtraction yielded almost lipid free small metabolite spectra from muscle tissue. Further improved separation was obtained by combining a 1D diffusion sequence with a T2-filter, with the subtraction method eliminating residual lipids from the spectra. Similar results obtained for biopsies of different organs suggest that this method is applicable in various tissue types. The elimination of lipids from HR-MAS spectra and the resulting less biased assessment of small metabolites have potential to remove ambiguities in the interpretation of metabonomic results. This is demonstrated in a reproducibility study on biopsies from human muscle.
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Affiliation(s)
- G Diserens
- Depts. Clinical Research and Radiology, University of Bern, Bern, Switzerland.
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21
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Xin L, Lanz B, Lei H, Gruetter R. Assessment of metabolic fluxes in the mouse brain in vivo using 1H-[13C] NMR spectroscopy at 14.1 Tesla. J Cereb Blood Flow Metab 2015; 35:759-65. [PMID: 25605294 PMCID: PMC4420852 DOI: 10.1038/jcbfm.2014.251] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2014] [Revised: 11/27/2014] [Accepted: 12/15/2014] [Indexed: 01/13/2023]
Abstract
(13)C magnetic resonance spectroscopy (MRS) combined with the administration of (13)C labeled substrates uniquely allows to measure metabolic fluxes in vivo in the brain of humans and rats. The extension to mouse models may provide exclusive prospect for the investigation of models of human diseases. In the present study, the short-echo-time (TE) full-sensitivity (1)H-[(13)C] MRS sequence combined with high magnetic field (14.1 T) and infusion of [U-(13)C6] glucose was used to enhance the experimental sensitivity in vivo in the mouse brain and the (13)C turnover curves of glutamate C4, glutamine C4, glutamate+glutamine C3, aspartate C2, lactate C3, alanine C3, γ-aminobutyric acid C2, C3 and C4 were obtained. A one-compartment model was used to fit (13)C turnover curves and resulted in values of metabolic fluxes including the tricarboxylic acid (TCA) cycle flux VTCA (1.05 ± 0.04 μmol/g per minute), the exchange flux between 2-oxoglutarate and glutamate Vx (0.48 ± 0.02 μmol/g per minute), the glutamate-glutamine exchange rate V(gln) (0.20 ± 0.02 μmol/g per minute), the pyruvate dilution factor K(dil) (0.82 ± 0.01), and the ratio for the lactate conversion rate and the alanine conversion rate V(Lac)/V(Ala) (10 ± 2). This study opens the prospect of studying transgenic mouse models of brain pathologies.
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Affiliation(s)
- Lijing Xin
- Laboratory of Functional and Metabolic Imaging (LIFMET), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Unit for Research in Schizophrenia, Department of Psychiatry, Center for Psychiatric Neuroscience, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Bernard Lanz
- Laboratory of Functional and Metabolic Imaging (LIFMET), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Hongxia Lei
- Department of Radiology, University of Geneva, Geneva, Switzerland
- Animal Imaging and Technology Core (AIT), Center for Biomedical Imaging (CIBM), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Rolf Gruetter
- Laboratory of Functional and Metabolic Imaging (LIFMET), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Department of Radiology, University of Geneva, Geneva, Switzerland
- Department of Radiology, University of Lausanne, Lausanne, Switzerland
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Craveiro M, Clément-Schatlo V, Marino D, Gruetter R, Cudalbu C. In vivobrain macromolecule signals in healthy and glioblastoma mouse models:1H magnetic resonance spectroscopy, post-processing and metabolite quantification at 14.1 T. J Neurochem 2014; 129:806-15. [DOI: 10.1111/jnc.12673] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2013] [Revised: 01/21/2014] [Accepted: 02/03/2014] [Indexed: 12/19/2022]
Affiliation(s)
- Mélanie Craveiro
- Laboratory for Functional and Metabolic Imaging; Ecole Polytechnique Fédérale de Lausanne; Lausanne Switzerland
| | | | - Denis Marino
- Department of Clinical Neurosciences; University of Geneva; Geneva Switzerland
| | - Rolf Gruetter
- Laboratory for Functional and Metabolic Imaging; Ecole Polytechnique Fédérale de Lausanne; Lausanne Switzerland
- Department of Radiology; University of Lausanne; Lausanne Switzerland
- Department of Radiology; University of Geneva; Geneva Switzerland
| | - Cristina Cudalbu
- Centre d'Imagerie Biomédicale; Ecole Polytechnique Fédérale de Lausanne; Lausanne Switzerland
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Schaller B, Xin L, Gruetter R. Is the macromolecule signal tissue-specific in healthy human brain? A (1)H MRS study at 7 Tesla in the occipital lobe. Magn Reson Med 2013; 72:934-40. [PMID: 24407736 DOI: 10.1002/mrm.24995] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2013] [Revised: 08/23/2013] [Accepted: 09/18/2013] [Indexed: 12/24/2022]
Abstract
PURPOSE The macromolecule signal plays a key role in the precision and the accuracy of the metabolite quantification in short-TE (1) H MR spectroscopy. Macromolecules have been reported at 1.5 Tesla (T) to depend on the cerebral studied region and to be age specific. As metabolite concentrations vary locally, information about the profile of the macromolecule signal in different tissues may be of crucial importance. METHODS The aim of this study was to investigate, at 7T for healthy subjects, the neurochemical profile differences provided by macromolecule signal measured in two different tissues in the occipital lobe, predominantly composed of white matter tissue or of grey matter tissue. RESULTS White matter-rich macromolecule signal was relatively lower than the gray matter-rich macromolecule signal from 1.5 to 1.8 ppm and from 2.3 to 2.5 ppm with mean difference over these regions of 7% and 12% (relative to the reference peak at 0.9 ppm), respectively. The neurochemical profiles, when using either of the two macromolecule signals, were similar for 11 reliably quantified metabolites (CRLB < 20%) with relatively small concentration differences (< 0.3 μmol/g), except Glu (± 0.8 μmol/g). CONCLUSION Given the small quantification differences, we conclude that a general macromolecule baseline provides a sufficiently accurate neurochemical profile in occipital lobe at 7T in healthy human brain.
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Affiliation(s)
- Benoît Schaller
- Laboratory of Functional and Metabolic Imaging, Ecole Polytechnique Fédèrale de Lausanne, Lausanne, Switzerland
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Quantification in magnetic resonance spectroscopy based on semi-parametric approaches. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2013; 27:113-30. [DOI: 10.1007/s10334-013-0393-4] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2013] [Revised: 07/08/2013] [Accepted: 07/08/2013] [Indexed: 10/26/2022]
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Schaller B, Xin L, Cudalbu C, Gruetter R. Quantification of the neurochemical profile using simulated macromolecule resonances at 3 T. NMR IN BIOMEDICINE 2013; 26:593-599. [PMID: 23413241 DOI: 10.1002/nbm.2896] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/12/2012] [Revised: 10/30/2012] [Accepted: 11/01/2012] [Indexed: 06/01/2023]
Abstract
The broad resonances underlying the entire (1) H NMR spectrum of the brain, ascribed to macromolecules, can influence metabolite quantification. At the intermediate field strength of 3 T, distinct approaches for the determination of the macromolecule signal, previously used at either 1.5 or 7 T and higher, may become equivalent. The aim of this study was to evaluate, at 3 T for healthy subjects using LCModel, the impact on the metabolite quantification of two different macromolecule approaches: (i) experimentally measured macromolecules; and (ii) mathematically estimated macromolecules. Although small, but significant, differences in metabolite quantification (up to 23% for glutamate) were noted for some metabolites, 10 metabolites were quantified reproducibly with both approaches with a Cramer-Rao lower bound below 20%, and the neurochemical profiles were therefore similar. We conclude that the mathematical approximation can provide sufficiently accurate and reproducible estimation of the macromolecule contribution to the (1) H spectrum at 3 T.
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Affiliation(s)
- Benoît Schaller
- Laboratory of Functional and Metabolic Imaging, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
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Hong ST, Pohmann R. Quantification issues of in vivo (1) H NMR spectroscopy of the rat brain investigated at 16.4 T. NMR IN BIOMEDICINE 2013; 26:74-82. [PMID: 22711580 DOI: 10.1002/nbm.2821] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2011] [Revised: 04/16/2012] [Accepted: 04/17/2012] [Indexed: 06/01/2023]
Abstract
The accuracy and precision of the quantification of metabolite concentrations in in vivo (1) H NMR spectroscopy are affected by linewidth and signal-to-noise ratio (SNR). To study the effect of both factors in in vivo (1) H NMR spectra acquired at ultrahigh field, a reference spectrum was generated by summing nine in vivo (1) H NMR spectra obtained in rat brain with a STEAM sequence at 16.4 T. By progressive deterioration of linewidth and SNR, 6400 single spectra were generated. In an accuracy study, the variation in the mean concentrations of five metabolites was mainly dependent on SNR, whereas 11 metabolites were predominantly susceptible to the linewidth. However, the standard deviations of the concentrations obtained were dependent almost exclusively on the SNR. An insignificant correlation was found between most of the heavily overlapping metabolite peaks, indicating independent and reliable quantification. Two different approaches for the consideration of macromolecular signals were evaluated. The use of prior knowledge derived by parameterization of a metabolite-nulled spectrum demonstrated improved fitting quality, with reduced Cramér-Rao lower bounds, compared to the calculation of a regularized spline baseline.
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Affiliation(s)
- Sung-Tak Hong
- High-Field Magnetic Resonance Center, Max-Planck Institute for Biological Cybernetics, Tübingen, Germany
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Cudalbu C, Lanz B, Duarte JMN, Morgenthaler FD, Pilloud Y, Mlynárik V, Gruetter R. Cerebral glutamine metabolism under hyperammonemia determined in vivo by localized (1)H and (15)N NMR spectroscopy. J Cereb Blood Flow Metab 2012; 32:696-708. [PMID: 22167234 PMCID: PMC3318147 DOI: 10.1038/jcbfm.2011.173] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Brain glutamine synthetase (GS) is an integral part of the glutamate-glutamine cycle and occurs in the glial compartment. In vivo Magnetic Resonance Spectroscopy (MRS) allows noninvasive measurements of the concentrations and synthesis rates of metabolites. (15)N MRS is an alternative approach to (13)C MRS. Incorporation of labeled (15)N from ammonia in cerebral glutamine allows to measure several metabolic reactions related to nitrogen metabolism, including the glutamate-glutamine cycle. To measure (15)N incorporation into the position 5N of glutamine and position 2N of glutamate and glutamine, we developed a novel (15)N pulse sequence to simultaneously detect, for the first time, [5-(15)N]Gln and [2-(15)N]Gln+Glu in vivo in the rat brain. In addition, we also measured for the first time in the same experiment localized (1)H spectra for a direct measurement of the net glutamine accumulation. Mathematical modeling of (1)H and (15)N MRS data allowed to reduce the number of assumptions and provided reliable determination of GS (0.30±0.050 μmol/g per minute), apparent neurotransmission (0.26±0.030 μmol/g per minute), glutamate dehydrogenase (0.029±0.002 μmol/g per minute), and net glutamine accumulation (0.033±0.001 μmol/g per minute). These results showed an increase of GS and net glutamine accumulation under hyperammonemia, supporting the concept of their implication in cerebral ammonia detoxification.
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Affiliation(s)
- Cristina Cudalbu
- Laboratory for Functional and Metabolic Imaging, Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
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Abstract
The purpose of this study was to develop a two-compartment metabolic model of brain metabolism to assess oxidative metabolism from [1-(11)C] acetate radiotracer experiments, using an approach previously applied in (13)C magnetic resonance spectroscopy (MRS), and compared with an one-tissue compartment model previously used in brain [1-(11)C] acetate studies. Compared with (13)C MRS studies, (11)C radiotracer measurements provide a single uptake curve representing the sum of all labeled metabolites, without chemical differentiation, but with higher temporal resolution. The reliability of the adjusted metabolic fluxes was analyzed with Monte-Carlo simulations using synthetic (11)C uptake curves, based on a typical arterial input function and previously published values of the neuroglial fluxes V(tca)(g), V(x), V(nt), and V(tca)(n) measured in dynamic (13)C MRS experiments. Assuming V(x)(g)=10 × V(tca)(g) and V(x)(n)=V(tca)(n), it was possible to assess the composite glial tricarboxylic acid (TCA) cycle flux V(gt)(g) (V(gt)(g)=V(x)(g) × V(tca)(g)/(V(x)(g)+V(tca)(g))) and the neurotransmission flux V(nt) from (11)C tissue-activity curves obtained within 30 minutes in the rat cortex with a beta-probe after a bolus infusion of [1-(11)C] acetate (n=9), resulting in V(gt)(g)=0.136±0.042 and V(nt)=0.170±0.103 μmol/g per minute (mean±s.d. of the group), in good agreement with (13)C MRS measurements.
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Xiao L, Wu EX. Diffusion-weighted magnetic resonance spectroscopy: A novel approach to investigate intramyocellular lipids. Magn Reson Med 2011; 66:937-44. [DOI: 10.1002/mrm.23121] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
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Chong DGQ, Kreis R, Bolliger CS, Boesch C, Slotboom J. Two-dimensional linear-combination model fitting of magnetic resonance spectra to define the macromolecule baseline using FiTAID, a Fitting Tool for Arrays of Interrelated Datasets. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2011; 24:147-64. [DOI: 10.1007/s10334-011-0246-y] [Citation(s) in RCA: 45] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2010] [Revised: 02/03/2011] [Accepted: 02/28/2011] [Indexed: 10/18/2022]
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