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Weng G, Radojewski P, Sheriff S, Kiefer C, Schucht P, Wiest R, Maudsley AA, Slotboom J. SLOW: A novel spectral editing method for whole-brain MRSI at ultra high magnetic field. Magn Reson Med 2022; 88:53-70. [PMID: 35344608 PMCID: PMC9212787 DOI: 10.1002/mrm.29220] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 01/28/2022] [Accepted: 02/16/2022] [Indexed: 11/11/2022]
Abstract
PURPOSE At ultra-high field (UHF), B1 + -inhomogeneities and high specific absorption rate (SAR) of adiabatic slice-selective RF-pulses make spatial resolved spectral-editing extremely challenging with the conventional MEGA-approach. The purpose of the study was to develop a whole-brain resolved spectral-editing MRSI at UHF (UHF, B0 ≥ 7T) within clinical acceptable measurement-time and minimal chemical-shift-displacement-artifacts (CSDA) allowing for simultaneous GABA/Glx-, 2HG-, and PE-editing on a clinical approved 7T-scanner. METHODS Slice-selective adiabatic refocusing RF-pulses (2π-SSAP) dominate the SAR to the patient in (semi)LASER based MEGA-editing sequences, causing large CSDA and long measurement times to fulfill SAR requirements, even using SAR-minimized GOIA-pulses. Therefore, a novel type of spectral-editing, called SLOW-editing, using two different pairs of phase-compensated chemical-shift selective adiabatic refocusing-pulses (2π-CSAP) with different refocusing bandwidths were investigated to overcome these problems. RESULTS Compared to conventional echo-planar spectroscopic imaging (EPSI) and MEGA-editing, SLOW-editing shows robust refocusing and editing performance despite to B1 + -inhomogeneity, and robustness to B0 -inhomogeneities (0.2 ppm ≥ ΔB0 ≥ -0.2 ppm). The narrow bandwidth (∼0.6-0.8 kHz) CSAP reduces the SAR by 92%, RF peak power by 84%, in-excitation slab CSDA by 77%, and has no in-plane CSDA. Furthermore, the CSAP implicitly dephases water, lipid and all the other signals outside of range (≥ 4.6 ppm and ≤1.4 ppm), resulting in additional water and lipid suppression (factors ≥ 1000s) at zero SAR-cost, and no spectral aliasing artifacts. CONCLUSION A new spectral-editing has been developed that is especially suitable for UHF, and was successfully applied for 2HG, GABA+, PE, and Glx-editing within 10 min clinical acceptable measurement time.
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Affiliation(s)
- Guodong Weng
- Institute for Diagnostic and Interventional Neuroradiology, Support Center for Advanced Neuroimaging (SCAN), University of Bern, Bern, Switzerland
| | - Piotr Radojewski
- Institute for Diagnostic and Interventional Neuroradiology, Support Center for Advanced Neuroimaging (SCAN), University of Bern, Bern, Switzerland
| | - Sulaiman Sheriff
- Department of Radiology, University of Miami School of Medicine, Miami, Florida, USA
| | - Claus Kiefer
- Institute for Diagnostic and Interventional Neuroradiology, Support Center for Advanced Neuroimaging (SCAN), University of Bern, Bern, Switzerland
| | - Philippe Schucht
- Department of Neurosurgery, Inselspital Bern and University Hospital, Bern, Switzerland
| | - Roland Wiest
- Institute for Diagnostic and Interventional Neuroradiology, Support Center for Advanced Neuroimaging (SCAN), University of Bern, Bern, Switzerland
| | - Andrew A Maudsley
- Department of Radiology, University of Miami School of Medicine, Miami, Florida, USA
| | - Johannes Slotboom
- Institute for Diagnostic and Interventional Neuroradiology, Support Center for Advanced Neuroimaging (SCAN), University of Bern, Bern, Switzerland
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Li H, Heise KF, Chalavi S, Puts NAJ, Edden RAE, Swinnen SP. The role of MRS-assessed GABA in human behavioral performance. Prog Neurobiol 2022; 212:102247. [PMID: 35149113 DOI: 10.1016/j.pneurobio.2022.102247] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Revised: 01/25/2022] [Accepted: 02/04/2022] [Indexed: 01/16/2023]
Abstract
Understanding the neurophysiological mechanisms that drive human behavior has been a long-standing focus of cognitive neuroscience. One well-known neuro-metabolite involved in the creation of optimal behavioral repertoires is GABA, the main inhibitory neurochemical in the human brain. Converging evidence from both animal and human studies indicates that individual variations in GABAergic function are associated with behavioral performance. In humans, one increasingly used in vivo approach to measuring GABA levels is through Magnetic Resonance Spectroscopy (MRS). However, the implications of MRS measures of GABA for behavior remain poorly understood. In this respect, it is yet to be determined how GABA levels within distinct task-related brain regions of interest account for differences in behavioral performance. This review summarizes findings from cross-sectional studies that determined baseline MRS-assessed GABA levels and examined their associations with performance on various behaviors representing the perceptual, motor and cognitive domains, with a particular focus on healthy participants across the lifespan. Overall, the results indicate that MRS-assessed GABA levels play a pivotal role in various domains of behavior. Even though some converging patterns emerge, it is challenging to draw comprehensive conclusions due to differences in behavioral task paradigms, targeted brain regions of interest, implemented MRS techniques and reference compounds used. Across all studies, the effects of GABA levels on behavioral performance point to generic and partially independent functions that refer to distinctiveness, interference suppression and cognitive flexibility. On one hand, higher baseline GABA levels may support the distinctiveness of neural representations during task performance and better coping with interference and suppression of preferred response tendencies. On the other hand, lower baseline GABA levels may support a reduction of inhibition, leading to higher cognitive flexibility. These effects are task-dependent and appear to be mediated by age. Nonetheless, additional studies using emerging advanced methods are required to further clarify the role of MRS-assessed GABA in behavioral performance.
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Affiliation(s)
- Hong Li
- Movement Control & Neuroplasticity Research Group, Group Biomedical Sciences, KU Leuven, Belgium; KU Leuven Brain Institute (LBI), KU Leuven, Belgium.
| | - Kirstin-Friederike Heise
- Movement Control & Neuroplasticity Research Group, Group Biomedical Sciences, KU Leuven, Belgium; KU Leuven Brain Institute (LBI), KU Leuven, Belgium; Department of Health Sciences and Research, Medical University of South Carolina, Charleston, SC, USA.
| | - Sima Chalavi
- Movement Control & Neuroplasticity Research Group, Group Biomedical Sciences, KU Leuven, Belgium; KU Leuven Brain Institute (LBI), KU Leuven, Belgium.
| | - Nicolaas A J Puts
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK; Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK; Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Stephan P Swinnen
- Movement Control & Neuroplasticity Research Group, Group Biomedical Sciences, KU Leuven, Belgium; KU Leuven Brain Institute (LBI), KU Leuven, Belgium.
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53
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Tapper S, Hui SC, Saleh MG, Zöllner HJ, Oeltzschner G, Near J, Soher BJ, Edden RAE. Influence of editing pulse flip angle on J-difference MR spectroscopy. Magn Reson Med 2022; 87:589-596. [PMID: 34520079 PMCID: PMC8627430 DOI: 10.1002/mrm.29008] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 08/02/2021] [Accepted: 08/27/2021] [Indexed: 02/03/2023]
Abstract
PURPOSE To investigate the editing-pulse flip angle (FA) dependence of editing efficiency and ultimately to maximize the edited signal of commonly edited MR spectroscopy (MRS) signals, such as gamma-aminobutyric acid (GABA) and lactate. METHODS Density-matrix simulations were performed for a range of spin systems to find the editing-pulse FA for maximal editing efficiency. Simulations were confirmed by phantom experiments and in vivo measurements in 10 healthy participants using a 3T Philips scanner. Four MEGA-PRESS in vivo measurements targeting GABA+ and lactate were performed, comparing the conventional editing-pulse FA (FA = 180°) to the optimal one suggested by simulations (FA = 210°). RESULTS Simulations and phantom experiments show that edited GABA and lactate signals are maximal at FA = 210°. Compared to conventional editing (FA = 180°), in vivo signals from GABA+ and lactate signals increase on average by 8.5% and 9.3%, respectively. CONCLUSION Increasing the FA of editing-pulses in the MEGA-PRESS experiment from 180° to 210° increases the edited signals from GABA+ and lactate by about 9% in vivo.
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Affiliation(s)
- Sofie Tapper
- Russell H. Morgan Department of Radiology and Radiological Science, 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
| | - Steve C.N. Hui
- Russell H. Morgan Department of Radiology and Radiological Science, 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
| | - Muhammad G. Saleh
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore 21201, MD, United States
| | - Helge J. Zöllner
- Russell H. Morgan Department of Radiology and Radiological Science, 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, 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
| | - Jamie Near
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Brian J. Soher
- Center for Advanced MR Development, Department of Radiology, Duke University Medical Center, Durham, NC, United States
| | - Richard A. E. Edden
- Russell H. Morgan Department of Radiology and Radiological Science, 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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Song Y, Lally PJ, Yanez Lopez M, Oeltzschner G, Nebel MB, Gagoski B, Kecskemeti S, Hui SCN, Zöllner HJ, Shukla D, Arichi T, De Vita E, Yedavalli V, Thayyil S, Fallin D, Dean DC, Grant PE, Wisnowski JL, Edden RAE. Edited magnetic resonance spectroscopy in the neonatal brain. Neuroradiology 2022; 64:217-232. [PMID: 34654960 PMCID: PMC8887832 DOI: 10.1007/s00234-021-02821-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 09/20/2021] [Indexed: 10/20/2022]
Abstract
J-difference-edited spectroscopy is a valuable approach for the detection of low-concentration metabolites with magnetic resonance spectroscopy (MRS). Currently, few edited MRS studies are performed in neonates due to suboptimal signal-to-noise ratio, relatively long acquisition times, and vulnerability to motion artifacts. Nonetheless, the technique presents an exciting opportunity in pediatric imaging research to study rapid maturational changes of neurotransmitter systems and other metabolic systems in early postnatal life. Studying these metabolic processes is vital to understanding the widespread and rapid structural and functional changes that occur in the first years of life. The overarching goal of this review is to provide an introduction to edited MRS for neonates, including the current state-of-the-art in editing methods and editable metabolites, as well as to review the current literature applying edited MRS to the neonatal brain. Existing challenges and future opportunities, including the lack of age-specific reference data, are also discussed.
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Affiliation(s)
- Yulu Song
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Peter J Lally
- Department of Brain Sciences, Imperial College London, London, UK
| | - Maria Yanez Lopez
- Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Mary Beth Nebel
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, 21205, USA.,Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Borjan Gagoski
- Department of Radiology, Division of Neuroradiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.,Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, USA
| | | | - Steve C N Hui
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Helge J Zöllner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Deepika Shukla
- Centre for Perinatal Neuroscience, Department of Brain Sciences, Imperial College London, London, UK
| | - Tomoki Arichi
- Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Department of Bioengineering, Imperial College London, South Kensington Campus, London, UK
| | - Enrico De Vita
- Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, St Thomas's Hospital, Westminster Bridge Road, Lambeth Wing, 3rd Floor, London, SE1 7EH, UK
| | - Vivek Yedavalli
- Division of Neuroradiology, Park 367G, The Johns Hopkins University School of Medicine, 600 N. Wolfe St. B-112 D, Baltimore, MD, 21287, USA
| | - Sudhin Thayyil
- Centre for Perinatal Neuroscience, Department of Brain Sciences, Imperial College London, London, UK
| | - Daniele Fallin
- Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins University, Baltimore, USA.,Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, USA
| | - Douglas C Dean
- Waisman Center, University of WI-Madison, Madison, WI, 53705, USA.,Department of Pediatrics, Division of Neonatology and Newborn Nursery, University of WI-Madison, School of Medicine and Public Health, Madison, WI, 53705, USA.,Department of Medical Physics, University of WI-Madison, School of Medicine and Public Health, Madison, WI, 53705, USA
| | - P Ellen Grant
- Department of Radiology, Division of Neuroradiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.,Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, USA.,Department of Medicine, Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jessica L Wisnowski
- Children's Hospital Los Angeles, Los Angeles, CA, 90027, USA.,Department of Radiology and Fetal and Neonatal Institute, CHLA Division of Neonatology, Department of Pediatrics, Children's Hospital of Los Angeles, University of Southern California, Los Angeles, CA, 90033, USA
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA. .,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA. .,Division of Neuroradiology, Park 367G, The Johns Hopkins University School of Medicine, 600 N. Wolfe St. B-112 D, Baltimore, MD, 21287, USA.
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Basu S, Pradhan S, Barnett S, Mikkelsen M, Kapse K, Murnick J, Quistorff J, Lopez C, du Plessis A, Limperopoulos C. Regional Differences in Gamma-Aminobutyric Acid and Glutamate Concentrations in the Healthy Newborn Brain. AJNR Am J Neuroradiol 2022; 43:125-131. [PMID: 34764083 PMCID: PMC8757541 DOI: 10.3174/ajnr.a7336] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 09/10/2021] [Indexed: 01/03/2023]
Abstract
BACKGROUND AND PURPOSE Gamma-aminobutyric acid and glutamate system disruptions may underlie neonatal brain injury. However, in vivo investigations are challenged by the need for special 1H-MR spectroscopy sequences for the reliable measurement of the neurotransmitters in this population. We used J-edited 1H-MR spectroscopy (Mescher-Garwood point-resolved spectroscopy) to quantify regional in vivo gamma-aminobutyric acid and glutamate concentrations during the early postnatal period in healthy neonates. MATERIALS AND METHODS We prospectively enrolled healthy neonates and acquired Mescher-Garwood point-resolved spectroscopy spectra on a 3T MR imaging scanner from voxels located in the cerebellum, the right basal ganglia, and the right frontal lobe. CSF-corrected metabolite concentrations were compared for regional variations and cross-sectional temporal trends with advancing age. RESULTS Fifty-eight neonates with acceptable spectra acquired at postmenstrual age of 39.1 (SD, 1.3) weeks were included for analysis. Gamma-aminobutyric acid (+ macromolecule) (2.56 [SD, 0.1]) i.u., glutamate (3.80 [SD, 0.2]), Cho, and mIns concentrations were highest in the cerebellum, whereas NAA (6.72 [SD, 0.2]), NAA/Cho, Cr/Cho, and Glx/Cho were highest in the basal ganglia. Frontal gamma-aminobutyric acid (1.63 [SD, 0.1]), Glx (4.33 [SD, 0.3]), Cr (3.64 [SD, 0.2]), and Cho concentrations were the lowest among the ROIs. Glx, NAA, and Cr demonstrated a significant adjusted increase with postmenstrual age (β = 0.2-0.35), whereas gamma-aminobutyric acid and Cho did not. CONCLUSIONS We report normative regional variations and temporal trends of in vivo gamma-aminobutyric acid and glutamate concentrations reflecting the functional and maturational status of 3 distinct brain regions of the neonate. These measures will serve as important normative values to allow early detection of subtle neurometabolic alterations in high-risk neonates.
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Affiliation(s)
- S.K. Basu
- From the Department of Neonatology (S.K.B.),Developing Brain Institute (S.K.B., S.P., S.D.B., K.J.K., J.L.Q., C.A.L., C.L.),George Washington University School of Medicine (S.K.B. S.P., S.D.B., J.M., A.J.d.P., C.L.), Washington, DC
| | - S. Pradhan
- Developing Brain Institute (S.K.B., S.P., S.D.B., K.J.K., J.L.Q., C.A.L., C.L.),George Washington University School of Medicine (S.K.B. S.P., S.D.B., J.M., A.J.d.P., C.L.), Washington, DC
| | - S.D. Barnett
- Developing Brain Institute (S.K.B., S.P., S.D.B., K.J.K., J.L.Q., C.A.L., C.L.),George Washington University School of Medicine (S.K.B. S.P., S.D.B., J.M., A.J.d.P., C.L.), Washington, DC
| | - M. Mikkelsen
- Department of Radiology (M.M., J.M.), Weill Cornell Medicine, New York, New York
| | - K.J. Kapse
- Developing Brain Institute (S.K.B., S.P., S.D.B., K.J.K., J.L.Q., C.A.L., C.L.)
| | - J. Murnick
- George Washington University School of Medicine (S.K.B. S.P., S.D.B., J.M., A.J.d.P., C.L.), Washington, DC,Department of Radiology (M.M., J.M.), Weill Cornell Medicine, New York, New York
| | - J.L. Quistorff
- Developing Brain Institute (S.K.B., S.P., S.D.B., K.J.K., J.L.Q., C.A.L., C.L.)
| | - C.A. Lopez
- Developing Brain Institute (S.K.B., S.P., S.D.B., K.J.K., J.L.Q., C.A.L., C.L.)
| | - A.J. du Plessis
- Fetal Medicine Institute (A.J.d.P.), Children’s National Hospital, Washington, DC,George Washington University School of Medicine (S.K.B. S.P., S.D.B., J.M., A.J.d.P., C.L.), Washington, DC
| | - C. Limperopoulos
- Developing Brain Institute (S.K.B., S.P., S.D.B., K.J.K., J.L.Q., C.A.L., C.L.),Division of Diagnostic Imaging and Radiology (C.L.),George Washington University School of Medicine (S.K.B. S.P., S.D.B., J.M., A.J.d.P., C.L.), Washington, DC
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Otaduy MCG. Editorial: Magnetic Resonance Spectroscopy of GABA and Glutamate in Mental Health. Front Psychiatry 2022; 13:866356. [PMID: 35360128 PMCID: PMC8963709 DOI: 10.3389/fpsyt.2022.866356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 02/03/2022] [Indexed: 11/25/2022] Open
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Lavigne KM, Kanagasabai K, Palaniyappan L. Ultra-high field neuroimaging in psychosis: A narrative review. Front Psychiatry 2022; 13:994372. [PMID: 36506432 PMCID: PMC9730890 DOI: 10.3389/fpsyt.2022.994372] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 11/08/2022] [Indexed: 11/27/2022] Open
Abstract
Schizophrenia and related psychoses are complex neuropsychiatric diseases representing dysconnectivity across multiple scales, through the micro (cellular), meso (brain network), manifest (behavioral), and social (interpersonal) levels. In vivo human neuroimaging, particularly at ultra-high field (UHF), offers unprecedented opportunity to examine multiscale dysconnectivity in psychosis. In this review, we provide an overview of the literature to date on UHF in psychosis, focusing on microscale findings from magnetic resonance spectroscopy (MRS), mesoscale studies on structural and functional magnetic resonance imaging (fMRI), and multiscale studies assessing multiple neuroimaging modalities and relating UHF findings to behavior. We highlight key insights and considerations from multiscale and longitudinal studies and provide recommendations for future research on UHF neuroimaging in psychosis.
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Affiliation(s)
- Katie M Lavigne
- Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada.,Montreal Neurological Institute-Hospital, McGill University, Montreal, QC, Canada.,Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Kesavi Kanagasabai
- Robarts Research Institute, Western University, London, ON, Canada.,Department of Medical Biophysics, Western University, London, ON, Canada
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada.,Department of Psychiatry, McGill University, Montreal, QC, Canada.,Robarts Research Institute, Western University, London, ON, Canada.,Department of Medical Biophysics, Western University, London, ON, Canada
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Zöllner HJ, Tapper S, Hui SCN, Barker PB, Edden RAE, Oeltzschner G. Comparison of linear combination modeling strategies for edited magnetic resonance spectroscopy at 3 T. NMR IN BIOMEDICINE 2022; 35:e4618. [PMID: 34558129 PMCID: PMC8935346 DOI: 10.1002/nbm.4618] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 08/24/2021] [Accepted: 08/29/2021] [Indexed: 06/01/2023]
Abstract
J-difference-edited spectroscopy is a valuable approach for the in vivo detection of γ-aminobutyric-acid (GABA) with magnetic resonance spectroscopy (MRS). A recent expert consensus article recommends linear combination modeling (LCM) of edited MRS but does not give specific details regarding implementation. This study explores different modeling strategies to adapt LCM for GABA-edited MRS. Sixty-one medial parietal lobe GABA-edited MEGA-PRESS spectra from a recent 3-T multisite study were modeled using 102 different strategies combining six different approaches to account for co-edited macromolecules (MMs), three modeling ranges, three baseline knot spacings, and the use of basis sets with or without homocarnosine. The resulting GABA and GABA+ estimates (quantified relative to total creatine), the residuals at different ranges, standard deviations and coefficients of variation (CVs), and Akaike information criteria, were used to evaluate the models' performance. Significantly different GABA+ and GABA estimates were found when a well-parameterized MM3co basis function was included in the model. The mean GABA estimates were significantly lower when modeling MM3co , while the CVs were similar. A sparser spline knot spacing led to lower variation in the GABA and GABA+ estimates, and a narrower modeling range-only including the signals of interest-did not substantially improve or degrade modeling performance. Additionally, the results suggest that LCM can separate GABA and the underlying co-edited MM3co . Incorporating homocarnosine into the modeling did not significantly improve variance in GABA+ estimates. In conclusion, GABA-edited MRS is most appropriately quantified by LCM with a well-parameterized co-edited MM3co basis function with a constraint to the nonoverlapped MM0.93 , in combination with a sparse spline knot spacing (0.55 ppm) and a modeling range of 0.5-4 ppm.
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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, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Sofie Tapper
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Steve C. N. Hui
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Peter B. Barker
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Richard A. E. Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
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Finkelman T, Furman-Haran E, Paz R, Tal A. Quantifying the excitatory-inhibitory balance: A comparison of SemiLASER and MEGA-SemiLASER for simultaneously measuring GABA and glutamate at 7T. Neuroimage 2021; 247:118810. [PMID: 34906716 DOI: 10.1016/j.neuroimage.2021.118810] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Revised: 12/08/2021] [Accepted: 12/10/2021] [Indexed: 10/19/2022] Open
Abstract
The importance of the excitatory-inhibitory (E/I) balance in a wide range of cognitive and behavioral processes has prompted a commensurate interest in methods for reliably quantifying it. Proton Magnetic Resonance Spectroscopy (1H-MRS) remains the only method capable of safely and non-invasively measuring the concentrations of the brain's major excitatory (glutamate) and inhibitory (γ-aminobutyric-acid, GABA) neurotransmitters in-vivo. MRS relies on spectral Mescher-Garwood (MEGA) editing techniques at 3T to distinguish GABA from its overlapping resonances. However, with the increased spectral resolution at ultrahigh field strengths of 7T and above, non-edited spectroscopic techniques become potential viable alternatives to MEGA based approaches, and also address some of their shortcomings, such as signal loss, sensitivity to transmitter inhomogeneities and temporal resolution. We present a comprehensive comparison of both edited and non-edited strategies at 7T for simultaneously quantifying glutamate and GABA from the dorsal anterior cingulate cortex (dACC), and evaluate their reproducibility and relative bias. The combined root-mean-square test-retest reproducibility of Glu and GABA (CVE/I) was as low as 13.3% for unedited MRS at TE=80 ms using SemiLASER localization, while edited MRS at TE=80 ms yielded CVE/I=20% and 21% for asymmetric and symmetric MEGA editing, respectively. An unedited SemiLASER acquisition using a shorter echo time of TE=42 ms yielded CVE/I as low as 24.9%. Our results show that non-edited sequences at an echo time of 80 ms provide better reproducibility than either edited sequences at the same TE, or non-edited sequences at a shorter TE of 42 ms. This is supported by numerical simulations and is driven in part by a pseudo-singlet appearance of the GABA multiplets at TE=80 ms, and the excellent spectral resolution at 7T. Our results uphold a transition to non-edited MRS for monitoring the E/I balance at ultrahigh fields, and stress the importance of using a properly-optimized echo time.
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Affiliation(s)
- Tal Finkelman
- Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel; Department of Chemical and Biological Physics, Weizmann Institute of Science, 234 Herzel St., Rehovot 7610001, Israel
| | - Edna Furman-Haran
- Life Sciences Core Facilities, Weizmann Institute of Science, Rehovot, Israel
| | - Rony Paz
- Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel
| | - Assaf Tal
- Department of Chemical and Biological Physics, Weizmann Institute of Science, 234 Herzel St., Rehovot 7610001, Israel.
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60
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Cognitive control affects motor learning through local variations in GABA within the primary motor cortex. Sci Rep 2021; 11:18566. [PMID: 34535725 PMCID: PMC8448760 DOI: 10.1038/s41598-021-97974-1] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Accepted: 08/27/2021] [Indexed: 02/08/2023] Open
Abstract
The primary motor cortex (M1) is crucial for motor learning; however, its interaction with other brain areas during motor learning remains unclear. We hypothesized that the fronto-parietal execution network (FPN) provides learning-related information critical for the flexible cognitive control that is required for practice. We assessed network-level changes during sequential finger tapping learning under speed pressure by combining magnetic resonance spectroscopy and task and resting-state functional magnetic resonance imaging. There was a motor learning-related increase in preparatory activity in the fronto-parietal regions, including the right M1, overlapping the FPN and sensorimotor network (SMN). Learning-related increases in M1-seeded functional connectivity with the FPN, but not the SMN, were associated with decreased GABA/glutamate ratio in the M1, which were more prominent in the parietal than the frontal region. A decrease in the GABA/glutamate ratio in the right M1 was positively correlated with improvements in task performance (p = 0.042). Our findings indicate that motor learning driven by cognitive control is associated with local variations in the GABA/glutamate ratio in the M1 that reflects remote connectivity with the FPN, representing network-level motor sequence learning formations.
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61
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Caldwell S, Rothman DL. 1H Magnetic Resonance Spectroscopy to Understand the Biological Basis of ALS, Diagnose Patients Earlier, and Monitor Disease Progression. Front Neurol 2021; 12:701170. [PMID: 34512519 PMCID: PMC8429815 DOI: 10.3389/fneur.2021.701170] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 08/03/2021] [Indexed: 11/13/2022] Open
Abstract
At present, limited biomarkers exist to reliably understand, diagnose, and monitor the progression of amyotrophic lateral sclerosis (ALS), a fatal neurological disease characterized by motor neuron death. Standard MRI technology can only be used to exclude a diagnosis of ALS, but 1H-MRS technology, which measures neurochemical composition, may provide the unique ability to reveal biomarkers that are specific to ALS and sensitive enough to diagnose patients at early stages in disease progression. In this review, we present a summary of current theories of how mitochondrial energetics and an altered glutamate/GABA neurotransmitter flux balance play a role in the pathogenesis of ALS. The theories are synthesized into a model that predicts how pathogenesis impacts glutamate and GABA concentrations. When compared with the results of all MRS studies published to date that measure the absolute concentrations of these neurochemicals in ALS patients, results were variable. However, when normalized for neuronal volume using the MRS biomarker N-acetyl aspartate (NAA), there is clear evidence for an elevation of neuronal glutamate in nine out of thirteen studies reviewed, an observation consistent with the predictions of the model of increased activity of glutamatergic neurons and excitotoxicity. We propose that this increase in neuronal glutamate concentration, in combination with decreased neuronal volume, is specific to the pathology of ALS. In addition, when normalized to glutamate levels, there is clear evidence for a decrease in neuronal GABA in three out of four possible studies reviewed, a finding consistent with a loss of inhibitory regulation contributing to excessive neuronal excitability. The combination of a decreased GABA/Glx ratio with an elevated Glx/NAA ratio may enhance the specificity for 1H-MRS detection of ALS and ability to monitor glutamatergic and GABAergic targeted therapeutics. Additional longitudinal studies calculating the exact value of these ratios are needed to test these hypotheses and understand how ratios may change over the course of disease progression. Proposed modifications to the experimental design of the reviewed 1H MRS studies may also increase the sensitivity of the technology to changes in these neurochemicals, particularly in early stages of disease progression.
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Affiliation(s)
- Sarah Caldwell
- Departments of Radiology and Biomedical Engineering, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, CT, United States
| | - Douglas L Rothman
- Departments of Radiology and Biomedical Engineering, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, CT, United States
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62
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Maria YL, Price AN, Puts NAJ, Hughes EJ, Edden RAE, McAlonan GM, Arichi T, De Vita E. Simultaneous quantification of GABA, Glx and GSH in the neonatal human brain using magnetic resonance spectroscopy. Neuroimage 2021; 233:117930. [PMID: 33711485 PMCID: PMC8204265 DOI: 10.1016/j.neuroimage.2021.117930] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 02/25/2021] [Accepted: 02/28/2021] [Indexed: 11/23/2022] Open
Abstract
Balance between inhibitory and excitatory neurotransmitter systems and the protective role of the major antioxidant glutathione (GSH) are central to early healthy brain development. Disruption has been implicated in the early life pathophysiology of psychiatric disorders and neurodevelopmental conditions including Autism Spectrum Disorder. Edited magnetic resonance spectroscopy (MRS) methods such as HERMES have great potential for providing important new non-invasive insights into these crucial processes in human infancy. In this work, we describe a systematic approach to minimise the impact of specific technical challenges inherent to acquiring MRS data in a neonatal population, including automatic segmentation, full tissue-correction and optimised GABA+ fitting and consider the minimum requirements for a robust edited-MRS acquisition. With this approach we report for the first time simultaneous GABA+, Glx (glutamate + glutamine) and GSH concentrations in the neonatal brain (n = 18) in two distinct regions (thalamus and anterior cingulate cortex (ACC)) using edited MRS at 3T. The improved sensitivity provided by our method allows specific regional neurochemical differences to be identified including: significantly lower Glx and GSH ratios to total creatine in the thalamus compared to the ACC (p < 0.001 for both), and significantly higher GSH levels in the ACC following tissue-correction (p < 0.01). Furthermore, in contrast to adult GABA+ which can typically be accurately fitted with a single peak, all neonate spectra displayed a characteristic doublet GABA+ peak at 3 ppm, indicating a lower macromolecule (MM) contribution to the 3 ppm signal in neonates. Relatively high group-level variance shows the need to maximise voxel size/acquisition time in edited neonatal MRS acquisitions for robust estimation of metabolites. Application of this method to study how these levels and balance are altered by early-life brain injury or genetic risk can provide important new knowledge about the pathophysiology underlying neurodevelopmental disorders.
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Affiliation(s)
- Yanez Lopez Maria
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Anthony N Price
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Nicolaas A J Puts
- Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Emer J Hughes
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - 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, Maryland, United States
| | - Grainne M McAlonan
- Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom; MRC Centre for Neurodevelopmental Disorders, King's College London, London, United Kingdom; NIHR-Maudsley Biomedical Research, King's College London, United Kingdom
| | - Tomoki Arichi
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; Department of Bioengineering, Imperial College London, South Kensington Campus, London, United Kingdom
| | - Enrico De Vita
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, St Thomas' Hospital, Westminster Bridge Road, Lambeth Wing, 3rd Floor, London SE1 7EH, United Kingdom.
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63
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Porges EC, Jensen G, Foster B, Edden RAE, Puts NAJ. The trajectory of cortical GABA across the lifespan, an individual participant data meta-analysis of edited MRS studies. eLife 2021; 10:e62575. [PMID: 34061022 PMCID: PMC8225386 DOI: 10.7554/elife.62575] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 05/30/2021] [Indexed: 01/18/2023] Open
Abstract
γ-Aminobutyric acid (GABA) is the principal inhibitory neurotransmitter in the human brain and can be measured with magnetic resonance spectroscopy (MRS). Conflicting accounts report decreases and increases in cortical GABA levels across the lifespan. This incompatibility may be an artifact of the size and age range of the samples utilized in these studies. No single study to date has included the entire lifespan. In this study, eight suitable datasets were integrated to generate a model of the trajectory of frontal GABA estimates (as reported through edited MRS; both expressed as ratios and in institutional units) across the lifespan. Data were fit using both a log-normal curve and a nonparametric spline as regression models using a multi-level Bayesian model utilizing the Stan language. Integrated data show that an asymmetric lifespan trajectory of frontal GABA measures involves an early period of increase, followed by a period of stability during early adulthood, with a gradual decrease during adulthood and aging that is described well by both spline and log-normal models. The information gained will provide a general framework to inform expectations of future studies based on the age of the population being studied.
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Affiliation(s)
- Eric C Porges
- Center for Cognitive Aging and Memory, University of FloridaGainesvilleUnited States
- McKnight Brain Research Foundation, University of FloridaUnited StatesUnited States
- Department of Clinical and Health Psychology, University of FloridaGainesvilleUnited States
| | - Greg Jensen
- Department of Neuroscience, Columbia University Medical CenterNew YorkUnited States
- Zuckerman Mind Brain Behavior Institute, Columbia UniversityNew YorkUnited States
| | - Brent Foster
- Center for Cognitive Aging and Memory, University of FloridaGainesvilleUnited States
- McKnight Brain Research Foundation, University of FloridaUnited StatesUnited States
- Department of Clinical and Health Psychology, University of FloridaGainesvilleUnited States
| | - Richard AE Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of MedicineBaltimoreUnited States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger InstituteBaltimoreUnited States
| | - Nicolaas AJ Puts
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of MedicineBaltimoreUnited States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger InstituteBaltimoreUnited States
- Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology, and Neuroscience, King’s College LondonLondonUnited Kingdom
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64
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Basu SK, Pradhan S, du Plessis AJ, Ben-Ari Y, Limperopoulos C. GABA and glutamate in the preterm neonatal brain: In-vivo measurement by magnetic resonance spectroscopy. Neuroimage 2021; 238:118215. [PMID: 34058332 PMCID: PMC8404144 DOI: 10.1016/j.neuroimage.2021.118215] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 04/30/2021] [Accepted: 05/25/2021] [Indexed: 12/11/2022] Open
Abstract
Cognitive and behavioral disabilities in preterm infants, even without obvious brain injury on conventional neuroimaging, underscores a critical need to identify the subtle underlying microstructural and biochemical derangements. The gamma-aminobutyric acid (GABA) and glutamatergic neurotransmitter systems undergo rapid maturation during the crucial late gestation and early postnatal life, and are at-risk of disruption after preterm birth. Animal and human autopsy studies provide the bulk of current understanding since non-invasive specialized proton magnetic resonance spectroscopy (1H-MRS) to measure GABA and glutamate are not routinely available for this vulnerable population due to logistical and technical challenges. We review the specialized 1H-MRS techniques including MEscher-GArwood Point Resolved Spectroscopy (MEGA-PRESS), special challenges and considerations needed for interpretation of acquired data from the developing brain of preterm infants. We summarize the limited in-vivo preterm data, highlight the gaps in knowledge, and discuss future directions for optimal integration of available in-vivo approaches to understand the influence of GABA and glutamate on neurodevelopmental outcomes after preterm birth.
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Affiliation(s)
- Sudeepta K Basu
- Neonatology, Children's National Hospital, Washington, D.C., United States; Center for the Developing Brain, Children's National Hospital, Washington, D.C., United States; Division of Neurology, Children's National Hospital, Washington, D.C., United States; The George Washington University School of Medicine, Washington, D.C., United States
| | - Subechhya Pradhan
- Center for the Developing Brain, Children's National Hospital, Washington, D.C., United States; Division of Neurology, Children's National Hospital, Washington, D.C., United States; The George Washington University School of Medicine, Washington, D.C., United States
| | - Adre J du Plessis
- Fetal Medicine institute, Children's National Hospital, Washington, D.C., United States; Division of Neurology, Children's National Hospital, Washington, D.C., United States; The George Washington University School of Medicine, Washington, D.C., United States
| | - Yehezkel Ben-Ari
- Division of Neurology, Children's National Hospital, Washington, D.C., United States; Neurochlore, Marseille, France
| | - Catherine Limperopoulos
- Center for the Developing Brain, Children's National Hospital, Washington, D.C., United States; Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, D.C., United States; Division of Neurology, Children's National Hospital, Washington, D.C., United States; The George Washington University School of Medicine, Washington, D.C., United States.
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65
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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: 80] [Impact Index Per Article: 26.7] [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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66
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Krššák M, Lindeboom L, Schrauwen‐Hinderling V, Szczepaniak LS, Derave W, Lundbom J, Befroy D, Schick F, Machann J, Kreis R, Boesch C. Proton magnetic resonance spectroscopy in skeletal muscle: Experts' consensus recommendations. NMR IN BIOMEDICINE 2021; 34:e4266. [PMID: 32022964 PMCID: PMC8244035 DOI: 10.1002/nbm.4266] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 12/21/2019] [Accepted: 01/15/2020] [Indexed: 05/02/2023]
Abstract
1 H-MR spectroscopy of skeletal muscle provides insight into metabolism that is not available noninvasively by other methods. The recommendations given in this article are intended to guide those who have basic experience in general MRS to the special application of 1 H-MRS in skeletal muscle. The highly organized structure of skeletal muscle leads to effects that change spectral features far beyond simple peak heights, depending on the type and orientation of the muscle. Specific recommendations are given for the acquisition of three particular metabolites (intramyocellular lipids, carnosine and acetylcarnitine) and for preconditioning of experiments and instructions to study volunteers.
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Affiliation(s)
- Martin Krššák
- Division of Endocrinology and Metabolism, Department of Internal Medicine III & High Field MR Centre, Department of Biomedical Imaging and Image guided TherapyMedical University of ViennaViennaAustria
| | - Lucas Lindeboom
- Department of Radiology and Nuclear Medicine and Department of Nutrition and Movement ScienceMaastricht University Medical CenterMaastrichtThe Netherlands
| | - Vera Schrauwen‐Hinderling
- Department of Radiology and Nuclear Medicine and Department of Nutrition and Movement ScienceMaastricht University Medical CenterMaastrichtThe Netherlands
| | - Lidia S. Szczepaniak
- Biomedical Research Consulting in Magnetic Resonance SpectroscopyAlbuquerqueNew Mexico
| | - Wim Derave
- Department of Movement and Sports SciencesGhent UniversityGhentBelgium
| | - Jesper Lundbom
- Department of Diagnostics and TherapeuticsUniversity of HelsinkiHelsinkiFinland
| | | | - Fritz Schick
- Section on Experimental Radiology, Department of Diagnostic and Interventional RadiologyUniversity Hospital TübingenTübingenGermany
| | - Jürgen Machann
- Section on Experimental Radiology, Department of Diagnostic and Interventional RadiologyUniversity Hospital TübingenTübingenGermany
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich at the University of TübingenTübingenGermany
- German Center for Diabetes Research (DZD)TübingenGermany
| | - Roland Kreis
- Departments of Radiology and Biomedical ResearchUniversity and InselspitalBernSwitzerland
| | - Chris Boesch
- Departments of Radiology and Biomedical ResearchUniversity and InselspitalBernSwitzerland
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67
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Near J, Harris AD, Juchem C, Kreis R, Marjańska M, Öz G, Slotboom J, Wilson M, Gasparovic C. Preprocessing, analysis and quantification in single-voxel magnetic resonance spectroscopy: experts' consensus recommendations. NMR IN BIOMEDICINE 2021; 34:e4257. [PMID: 32084297 PMCID: PMC7442593 DOI: 10.1002/nbm.4257] [Citation(s) in RCA: 172] [Impact Index Per Article: 57.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 12/21/2019] [Accepted: 12/22/2019] [Indexed: 05/05/2023]
Abstract
Once an MRS dataset has been acquired, several important steps must be taken to obtain the desired metabolite concentration measures. First, the data must be preprocessed to prepare them for analysis. Next, the intensity of the metabolite signal(s) of interest must be estimated. Finally, the measured metabolite signal intensities must be converted into scaled concentration units employing a quantitative reference signal to allow meaningful interpretation. In this paper, we review these three main steps in the post-acquisition workflow of a single-voxel MRS experiment (preprocessing, analysis and quantification) and provide recommendations for best practices at each step.
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Affiliation(s)
- Jamie Near
- Douglas Mental Health University Institute and Department of Psychiatry, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
| | - Ashley D. Harris
- Department of Radiology, University of Calgary, Calgary, Canada
- Alberta Children’s Hospital Research Institute, Calgary, Canada
- Hotchkiss Brain Institute, Calgary, Canada
| | - Christoph Juchem
- Department of Biomedical Engineering, Columbia University, New York NY, USA
| | - Roland Kreis
- Departments of Radiology and Biomedical Research, University Bern, Switzerland
| | - Małgorzata Marjańska
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis MN, USA
| | - Gülin Öz
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis MN, USA
| | - Johannes Slotboom
- Support Center for Advanced Neuroimaging (SCAN), Neuroradiology, University Hospital Inselspital, Bern, Switzerland
| | - Martin Wilson
- Centre for Human Brain Health and School of Psychology, University of Birmingham, Birmingham, England
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68
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Lin A, Andronesi O, Bogner W, Choi I, Coello E, Cudalbu C, Juchem C, Kemp GJ, Kreis R, Krššák M, Lee P, Maudsley AA, Meyerspeer M, Mlynarik V, Near J, Öz G, Peek AL, Puts NA, Ratai E, Tkáč I, Mullins PG. Minimum Reporting Standards for in vivo Magnetic Resonance Spectroscopy (MRSinMRS): Experts' consensus recommendations. NMR IN BIOMEDICINE 2021; 34:e4484. [PMID: 33559967 PMCID: PMC8647919 DOI: 10.1002/nbm.4484] [Citation(s) in RCA: 134] [Impact Index Per Article: 44.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 11/24/2020] [Accepted: 01/12/2021] [Indexed: 05/08/2023]
Abstract
The translation of MRS to clinical practice has been impeded by the lack of technical standardization. There are multiple methods of acquisition, post-processing, and analysis whose details greatly impact the interpretation of the results. These details are often not fully reported, making it difficult to assess MRS studies on a standardized basis. This hampers the reviewing of manuscripts, limits the reproducibility of study results, and complicates meta-analysis of the literature. In this paper a consensus group of MRS experts provides minimum guidelines for the reporting of MRS methods and results, including the standardized description of MRS hardware, data acquisition, analysis, and quality assessment. This consensus statement describes each of these requirements in detail and includes a checklist to assist authors and journal reviewers and to provide a practical way for journal editors to ensure that MRS studies are reported in full.
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Affiliation(s)
- Alexander Lin
- Center for Clinical Spectroscopy, Department of Radiology, Brigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Ovidiu Andronesi
- Department of RadiologyMassachusetts General HospitalBostonMassachusettsUSA
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - In‐Young Choi
- Department of Neurology, Hoglund Biomedical Imaging CenterUniversity of Kansas Medical CenterKansas CityKansasUSA
| | - Eduardo Coello
- Center for Clinical Spectroscopy, Department of Radiology, Brigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Cristina Cudalbu
- Center for Biomedical Imaging (CIBM), Ecole Polytechnique Fédérale de LausanneLausanneSwitzerland
| | - Christoph Juchem
- Departments of Biomedical Engineering and RadiologyColumbia UniversityNew YorkNew YorkUSA
| | - Graham J. Kemp
- Department of Musculoskeletal and Ageing Science and Liverpool Magnetic Resonance Imaging Centre (LiMRIC)University of LiverpoolLiverpoolUK
| | - Roland Kreis
- Departments of Radiology and Biomedical ResearchUniversity of BernBernSwitzerland
| | - Martin Krššák
- Department of Medicine III and Department of Biomedical Imaging and Image guided TherapyMedical University of ViennaViennaAustria
| | - Phil Lee
- Department of Radiology, Hoglund Biomedical Imaging CenterUniversity of Kansas Medical CenterKansas CityKansasUSA
| | | | - Martin Meyerspeer
- High Field MR Center, Center for Medical Physics and Biomedical EngineeringMedical University of ViennaViennaAustria
| | - Vladamir Mlynarik
- Magnetic Resonance Centre of Excellence. Medical University of ViennaViennaAustria
| | - Jamie Near
- Brain Imaging Centre, Douglas Research Centre, Department of PsychiatryMcGill UniversityMontrealQuebecCanada
| | - Gülin Öz
- Center for Magnetic Resonance Research, Department of RadiologyUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Aimie L. Peek
- Faculty of Health SciencesUniversity of SydneySydneyAustralia
| | - Nicolaas A. Puts
- Department of Forensic and Neurodevelopmental SciencesSackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology, and Neuroscience, King's College LondonLondonUK
| | - Eva‐Maria Ratai
- A.A. Martinos Center for Biomedical Imaging, Neuroradiology Division, Department of RadiologyMassachusetts General HospitalBostonMassachusettsUSA
| | - Ivan Tkáč
- Faculty of Health SciencesUniversity of SydneySydneyAustralia
| | - Paul G. Mullins
- Bangor Imaging Unit, School of PsychologyBangor UniversityBangorGwyneddUK
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Abstract
Brain tumors, especially glioblastoma, remain the most aggressive form of all the cancers because of inefficient diagnosis and profiling. Nanostructures, such as metallic nanostructures, silica nano-vehicles, quantum dots, lipid nanoparticles (NPs) and polymeric NPs, with high specificity have made it possible to permeate the blood–brain barrier (BBB). NPs possess optical, magnetic and photodynamic properties that can be exploited by surface modification, bio composition, contrast agents’ encapsulation and coating by tumor-derived cells. Hence, nanotechnology has brought on a revolution in the field of diagnosis and imaging of brain tumors and cancers. Recently, nanomaterials with biomimetic functions have been introduced to efficiently cross the BBB to be engulfed by deep skin tumors and cancer malignancies for imaging. The review focuses on nanotechnology-based diagnostic and imaging approaches for exploration in brain tumors and cancers. Moreover, the review also summarizes a few strategies to image glioblastoma and cancers by multimodal functional nanocomposites for more precise and accurate clinical diagnosis. Their unique physicochemical attributes, including nanoscale sizes, larger surface area, explicit structural features and ability to encapsulate diverse molecules on their surface, render nanostructured materials as excellent nano-vehicles to cross the blood–brain barrier and convey drug molecules to their target region. This review sheds light on the current progress of various kinds of nanomaterials, such as liposomes, nano-micelles, dendrimers, carbon nanotubes, carbon dots and NPs (gold, silver and zinc oxide NPs), for efficient drug delivery in the treatment and diagnosis of brain cancer.
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70
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Lanz B, Abaei A, Braissant O, Choi IY, Cudalbu C, Henry PG, Gruetter R, Kara F, Kantarci K, Lee P, Lutz NW, Marjańska M, Mlynárik V, Rasche V, Xin L, Valette J. Magnetic resonance spectroscopy in the rodent brain: Experts' consensus recommendations. NMR IN BIOMEDICINE 2020; 34:e4325. [PMID: 33565219 PMCID: PMC9429976 DOI: 10.1002/nbm.4325] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Revised: 03/29/2020] [Accepted: 04/30/2020] [Indexed: 05/21/2023]
Abstract
In vivo MRS is a non-invasive measurement technique used not only in humans, but also in animal models using high-field magnets. MRS enables the measurement of metabolite concentrations as well as metabolic rates and their modifications in healthy animals and disease models. Such data open the way to a deeper understanding of the underlying biochemistry, related disturbances and mechanisms taking place during or prior to symptoms and tissue changes. In this work, we focus on the main preclinical 1H, 31P and 13C MRS approaches to study brain metabolism in rodent models, with the aim of providing general experts' consensus recommendations (animal models, anesthesia, data acquisition protocols). An overview of the main practical differences in preclinical compared with clinical MRS studies is presented, as well as the additional biochemical information that can be obtained in animal models in terms of metabolite concentrations and metabolic flux measurements. The properties of high-field preclinical MRS and the technical limitations are also described.
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Affiliation(s)
- Bernard Lanz
- Laboratory for Functional and Metabolic Imaging (LIFMET), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - Alireza Abaei
- Core Facility Small Animal Imaging, Ulm University, Ulm, Germany
| | - Olivier Braissant
- Service of Clinical Chemistry, University of Lausanne and University Hospital of Lausanne, Lausanne, Switzerland
| | - In-Young Choi
- Department of Neurology, University of Kansas Medical Center, Kansas City, Kansas, US
| | - Cristina Cudalbu
- Centre d'Imagerie Biomedicale (CIBM), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Pierre-Gilles Henry
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, US
| | - Rolf Gruetter
- Laboratory for Functional and Metabolic Imaging (LIFMET), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Firat Kara
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, US
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, US
| | - Phil Lee
- Department of Radiology, University of Kansas Medical Center, Kansas City, Kansas, US
| | - Norbert W Lutz
- CNRS, CRMBM, Aix-Marseille University, Marseille, France
| | - Małgorzata Marjańska
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, US
| | - Vladimír Mlynárik
- High Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Volker Rasche
- Core Facility Small Animal Imaging, Ulm University, Ulm, Germany
| | - Lijing Xin
- Centre d'Imagerie Biomedicale (CIBM), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Julien Valette
- Commissariat à l'Energie Atomique et aux Energies Alternatives, MIRCen, Fontenay-aux-Roses, France
- Neurodegenerative Diseases Laboratory, Centre National de la Recherche Scientifique, Université Paris-Sud, Université Paris-Saclay, UMR 9199, Fontenay-aux-Roses, France
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71
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Kreis R, Boer V, Choi I, Cudalbu C, de Graaf RA, Gasparovic C, Heerschap A, Krššák M, Lanz B, Maudsley AA, Meyerspeer M, Near J, Öz G, Posse S, Slotboom J, Terpstra M, Tkáč I, Wilson M, Bogner W. Terminology and concepts for the characterization of in vivo MR spectroscopy methods and MR spectra: Background and experts' consensus recommendations. NMR IN BIOMEDICINE 2020; 34:e4347. [PMID: 32808407 PMCID: PMC7887137 DOI: 10.1002/nbm.4347] [Citation(s) in RCA: 64] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Revised: 05/20/2020] [Accepted: 05/21/2020] [Indexed: 05/04/2023]
Abstract
With a 40-year history of use for in vivo studies, the terminology used to describe the methodology and results of magnetic resonance spectroscopy (MRS) has grown substantially and is not consistent in many aspects. Given the platform offered by this special issue on advanced MRS methodology, the authors decided to describe many of the implicated terms, to pinpoint differences in their meanings and to suggest specific uses or definitions. This work covers terms used to describe all aspects of MRS, starting from the description of the MR signal and its theoretical basis to acquisition methods, processing and to quantification procedures, as well as terms involved in describing results, for example, those used with regard to aspects of quality, reproducibility or indications of error. The descriptions of the meanings of such terms emerge from the descriptions of the basic concepts involved in MRS methods and examinations. This paper also includes specific suggestions for future use of terms where multiple conventions have emerged or coexisted in the past.
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Affiliation(s)
- Roland Kreis
- Department of Radiology, Neuroradiology, and Nuclear Medicine and Department of Biomedical ResearchUniversity BernBernSwitzerland
| | - Vincent Boer
- Danish Research Centre for Magnetic Resonance, Funktions‐ og Billeddiagnostisk EnhedCopenhagen University Hospital HvidovreHvidovreDenmark
| | - In‐Young Choi
- Department of Neurology, Hoglund Brain Imaging CenterUniversity of Kansas Medical CenterKansas CityKansasUSA
| | - Cristina Cudalbu
- Centre d'Imagerie Biomedicale (CIBM)Ecole Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland
| | - Robin A. de Graaf
- Department of Radiology and Biomedical Imaging & Department of Biomedical EngineeringYale UniversityNew HavenConnecticutUSA
| | | | - Arend Heerschap
- Department of Radiology and Nuclear MedicineRadboud University Medical CenterNijmegenThe Netherlands
| | - Martin Krššák
- Division of Endocrinology and Metabolism, Department of Internal Medicine III & High Field MR Centre, Department of Biomedical Imaging and Image guided TherapyMedical University of ViennaViennaAustria
| | - Bernard Lanz
- Laboratory of Functional and Metabolic Imaging (LIFMET)Ecole Polytechnique Fédérale de LausanneLausanneSwitzerland
- Sir Peter Mansfield Imaging Centre, School of MedicineUniversity of NottinghamNottinghamUK
| | - Andrew A. Maudsley
- Department of Radiology, Miller School of MedicineUniversity of MiamiMiamiFloridaUSA
| | - Martin Meyerspeer
- Center for Medical Physics and Biomedical EngineeringMedical University of ViennaViennaAustria
- High Field MR CenterMedical University of ViennaViennaAustria
| | - Jamie Near
- Douglas Mental Health University Institute and Department of PsychiatryMcGill UniversityMontrealCanada
| | - Gülin Öz
- Center for Magnetic Resonance Research, Department of RadiologyUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Stefan Posse
- Department of NeurologyUniversity of New Mexico School of MedicineAlbuquerqueNew MexicoUSA
| | - Johannes Slotboom
- Department of Radiology, Neuroradiology, and Nuclear MedicineUniversity Hospital BernBernSwitzerland
| | - Melissa Terpstra
- Center for Magnetic Resonance Research, Department of RadiologyUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Ivan Tkáč
- Center for Magnetic Resonance Research, Department of RadiologyUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Martin Wilson
- Centre for Human Brain Health and School of PsychologyUniversity of BirminghamBirminghamUK
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
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72
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Öz G, Deelchand DK, Wijnen JP, Mlynárik V, Xin L, Mekle R, Noeske R, Scheenen TWJ, Tkáč I. Advanced single voxel 1 H magnetic resonance spectroscopy techniques in humans: Experts' consensus recommendations. NMR IN BIOMEDICINE 2020; 34:e4236. [PMID: 31922301 PMCID: PMC7347431 DOI: 10.1002/nbm.4236] [Citation(s) in RCA: 86] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Revised: 10/29/2019] [Accepted: 11/07/2019] [Indexed: 05/06/2023]
Abstract
Conventional proton MRS has been successfully utilized to noninvasively assess tissue biochemistry in conditions that result in large changes in metabolite levels. For more challenging applications, namely, in conditions which result in subtle metabolite changes, the limitations of vendor-provided MRS protocols are increasingly recognized, especially when used at high fields (≥3 T) where chemical shift displacement errors, B0 and B1 inhomogeneities and limitations in the transmit B1 field become prominent. To overcome the limitations of conventional MRS protocols at 3 and 7 T, the use of advanced MRS methodology, including pulse sequences and adjustment procedures, is recommended. Specifically, the semiadiabatic LASER sequence is recommended when TE values of 25-30 ms are acceptable, and the semiadiabatic SPECIAL sequence is suggested as an alternative when shorter TE values are critical. The magnetic field B0 homogeneity should be optimized and RF pulses should be calibrated for each voxel. Unsuppressed water signal should be acquired for eddy current correction and preferably also for metabolite quantification. Metabolite and water data should be saved in single shots to facilitate phase and frequency alignment and to exclude motion-corrupted shots. Final averaged spectra should be evaluated for SNR, linewidth, water suppression efficiency and the presence of unwanted coherences. Spectra that do not fit predefined quality criteria should be excluded from further analysis. Commercially available tools to acquire all data in consistent anatomical locations are recommended for voxel prescriptions, in particular in longitudinal studies. To enable the larger MRS community to take advantage of these advanced methods, a list of resources for these advanced protocols on the major clinical platforms is provided. Finally, a set of recommendations are provided for vendors to enable development of advanced MRS on standard platforms, including implementation of advanced localization sequences, tools for quality assurance on the scanner, and tools for prospective volume tracking and dynamic linear shim corrections.
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Affiliation(s)
- Gülin Öz
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
| | - Dinesh K. Deelchand
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
| | - Jannie P. Wijnen
- High field MR Research group, Department of Radiology, University Medical Centre Utrecht, Utrecht, the Netherlands
| | - Vladimír Mlynárik
- High Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Lijing Xin
- Animal Imaging and Technology Core (AIT), Center for Biomedical Imaging (CIBM), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Ralf Mekle
- Center for Stroke Research Berlin (CSB), Charité Universitätsmedizin Berlin, Berlin, Germany
| | | | - Tom W. J. Scheenen
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
- Erwin L Hahn Institute for Magnetic Resonance Imaging, UNESCO World Cultural Heritage Zollverein, Essen, Germany
| | - Ivan Tkáč
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
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