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Weingärtner S, Desmond KL, Obuchowski NA, Baessler B, Zhang Y, Biondetti E, Ma D, Golay X, Boss MA, Gunter JL, Keenan KE, Hernando D. Development, validation, qualification, and dissemination of quantitative MR methods: Overview and recommendations by the ISMRM quantitative MR study group. Magn Reson Med 2021; 87:1184-1206. [PMID: 34825741 DOI: 10.1002/mrm.29084] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 10/20/2021] [Accepted: 10/27/2021] [Indexed: 12/26/2022]
Abstract
On behalf of the International Society for Magnetic Resonance in Medicine (ISMRM) Quantitative MR Study Group, this article provides an overview of considerations for the development, validation, qualification, and dissemination of quantitative MR (qMR) methods. This process is framed in terms of two central technical performance properties, i.e., bias and precision. Although qMR is confounded by undesired effects, methods with low bias and high precision can be iteratively developed and validated. For illustration, two distinct qMR methods are discussed throughout the manuscript: quantification of liver proton-density fat fraction, and cardiac T1 . These examples demonstrate the expansion of qMR methods from research centers toward widespread clinical dissemination. The overall goal of this article is to provide trainees, researchers, and clinicians with essential guidelines for the development and validation of qMR methods, as well as an understanding of necessary steps and potential pitfalls for the dissemination of quantitative MR in research and in the clinic.
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Affiliation(s)
- Sebastian Weingärtner
- Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands
| | - Kimberly L Desmond
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Nancy A Obuchowski
- Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio, USA
| | - Bettina Baessler
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
| | - Yuxin Zhang
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Emma Biondetti
- Department of Neuroscience, Imaging and Clinical Sciences, D'Annunzio University of Chieti and Pescara, Chieti, Italy
| | - Dan Ma
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Xavier Golay
- Brain Repair & Rehabilitation, Institute of Neurology, University College London, United Kingdom.,Gold Standard Phantoms Limited, Rochester, United Kingdom
| | - Michael A Boss
- Center for Research and Innovation, American College of Radiology, Philadelphia, Pennsylvania, USA
| | | | - Kathryn E Keenan
- National Institute of Standards and Technology, Boulder, Colorado, USA
| | - Diego Hernando
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
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202
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Tensaouti F, Desmoulin F, Gilhodes J, Martin E, Ken S, Lotterie JA, Noël G, Truc G, Sunyach MP, Charissoux M, Magné N, Lubrano V, Péran P, Cohen-Jonathan Moyal E, Laprie A. Quality control of 3D MRSI data in glioblastoma: Can we do without the experts? Magn Reson Med 2021; 87:1688-1699. [PMID: 34825724 DOI: 10.1002/mrm.29098] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 11/05/2021] [Accepted: 11/05/2021] [Indexed: 12/23/2022]
Abstract
PURPOSE Proton magnetic resonance spectroscopic imaging (1H MRSI) is a noninvasive technique for assessing tumor metabolism. Manual inspection is still the gold standard for quality control (QC) of spectra, but it is both time-consuming and subjective. The aim of the present study was to assess automatic QC of glioblastoma MRSI data using random forest analysis. METHODS Data for 25 patients, acquired prospectively in a preradiotherapy examination, were submitted to postprocessing with syngo.MR Spectro (VB40A; Siemens) or Java-based magnetic resonance user interface (jMRUI) software. A total of 28 features were extracted from each spectrum for the automatic QC. Three spectroscopists also performed manual inspections, labeling each spectrum as good or poor quality. All statistical analyses, with addressing unbalanced data, were conducted with R 3.6.1 (R Foundation for Statistical Computing; https://www.r-project.org). RESULTS The random forest method classified the spectra with an area under the curve of 95.5%, sensitivity of 95.8%, and specificity of 81.7%. The most important feature for the classification was Residuum_Lipids_Versus_Fit, obtained with syngo.MR Spectro. CONCLUSION The automatic QC method was able to distinguish between good- and poor-quality spectra, and can be used by radiation oncologists who are not spectroscopy experts. This study revealed a novel set of MRSI signal features that are closely correlated with spectral quality.
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Affiliation(s)
- Fatima Tensaouti
- Department of Radiation Oncology, Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse-Oncopôle, Toulouse, France.,ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France
| | - Franck Desmoulin
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France
| | - Julia Gilhodes
- Department of Biostatistics, Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse-Oncopôle, Toulouse, France
| | - Elodie Martin
- Department of Biostatistics, Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse-Oncopôle, Toulouse, France
| | - Soleakhena Ken
- Department of Engineering and Medical Physics, Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse-Oncopôle, Toulouse, France
| | - Jean-Albert Lotterie
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France.,Department of Nuclear Medicine, CHU Toulouse, Toulouse, France
| | - Georges Noël
- ICANS-Radiation Oncology Strasbourg, Strasbourg, France
| | - Gilles Truc
- Department of Radiation Oncology, Centre Georges-François Leclerc, Dijon, France
| | | | - Marie Charissoux
- Department of Radiation Oncology, Institut du Cancer de Montpellier, Montpellier, France
| | - Nicolas Magné
- Department of Radiation Oncology, Institut de Cancérologie de la Loire Lucien Neuwirth, Saint-Priest-en-Jarez, France
| | - Vincent Lubrano
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France
| | - Patrice Péran
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France
| | - Elizabeth Cohen-Jonathan Moyal
- Department of Radiation Oncology, Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse-Oncopôle, Toulouse, France.,Inserm U1037-Centre de Recherches Contre le Cancer de Toulouse, Toulouse, France
| | - Anne Laprie
- Department of Radiation Oncology, Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse-Oncopôle, Toulouse, France.,ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France
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203
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MacKinnon N, Alinaghian M, Silva P, Gloge T, Luy B, Jouda M, Korvink J. Selective excitation enables encoding and measurement of multiple diffusion parameters in a single experiment. MAGNETIC RESONANCE (GOTTINGEN, GERMANY) 2021; 2:835-842. [PMID: 37905219 PMCID: PMC10539772 DOI: 10.5194/mr-2-835-2021] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 10/31/2021] [Indexed: 11/01/2023]
Abstract
Band selectivity to address specific resonances in a spectrum enables one to encode individual settings for diffusion experiments. In a single experiment, this could include different gradient strengths (enabling coverage of a larger range of diffusion constants), different diffusion delays, or different gradient directions (enabling anisotropic diffusion measurement). In this report, a selective variant of the bipolar pulsed gradient eddy current delay (BPP-LED) experiment, enabling selective encoding of three resonances, was implemented. As proof of principle, the diffusion encoding gradient amplitude was assigned a range dependent on the selected signal, thereby allowing the extraction of the diffusion coefficient for water and a tripeptide (Met-Ala-Ser) with optimal settings in a single experiment.
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Affiliation(s)
- Neil MacKinnon
- Institute of Microstructure Technology (IMT), Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
| | - Mehrdad Alinaghian
- Institute of Microstructure Technology (IMT), Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
| | - Pedro Silva
- Institute of Microstructure Technology (IMT), Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
- DeepSpin GmbH, Kurfürstenstraße 56, 10785 Berlin, Germany
| | - Thomas Gloge
- Institute of Biological Interfaces (IBG-4), Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
| | - Burkhard Luy
- Institute of Biological Interfaces (IBG-4), Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
| | - Mazin Jouda
- Institute of Microstructure Technology (IMT), Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
| | - Jan G. Korvink
- Institute of Microstructure Technology (IMT), Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
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204
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Riemann LT, Aigner CS, Ellison SLR, Brühl R, Mekle R, Schmitter S, Speck O, Rose G, Ittermann B, Fillmer A. Assessment of measurement precision in single-voxel spectroscopy at 7 T: Toward minimal detectable changes of metabolite concentrations in the human brain in vivo. Magn Reson Med 2021; 87:1119-1135. [PMID: 34783376 DOI: 10.1002/mrm.29034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2021] [Revised: 09/14/2021] [Accepted: 09/16/2021] [Indexed: 12/13/2022]
Abstract
PURPOSE To introduce a study design and statistical analysis framework to assess the repeatability, reproducibility, and minimal detectable changes (MDCs) of metabolite concentrations determined by in vivo MRS. METHODS An unbalanced nested study design was chosen to acquire in vivo MRS data within different repeatability and reproducibility scenarios. A spin-echo, full-intensity acquired localized (SPECIAL) sequence was employed at 7 T utlizing three different inversion pulses: a hyperbolic secant (HS), a gradient offset independent adiabaticity (GOIA), and a wideband, uniform rate, smooth truncation (WURST) pulse. Metabolite concentrations, Cramér-Rao lower bounds (CRLBs) and coefficients of variation (CVs) were calculated. Both Bland-Altman analysis and a restricted maximum-likelihood estimation (REML) analysis were performed to estimate the different variance contributions of the repeatability and reproducibility of the measured concentration. A Bland-Altmann analysis of the spectral shape was performed to assess the variance of the spectral shape, independent of quantification model influences. RESULTS For the used setup, minimal detectable changes of brain metabolite concentrations were found to be between 0.40 µmol/g and 2.23 µmol/g. CRLBs account for only 16 % to 74 % of the total variance of the metabolite concentrations. The application of gradient-modulated inversion pulses in SPECIAL led to slightly improved repeatability, but overall reproducibility appeared to be limited by differences in positioning, calibration, and other day-to-day variations throughout different sessions. CONCLUSION A framework is introduced to estimate the precision of metabolite concentrations obtained by MRS in vivo, and the minimal detectable changes for 13 metabolite concentrations measured at 7 T using SPECIAL are obtained.
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Affiliation(s)
| | | | | | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt, Braunschweig und Berlin, Germany
| | - Ralf Mekle
- Center for Stroke Research Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | | | - Oliver Speck
- Biomedical Magnetic Resonance, Otto-von-Guericke University, Magdeburg, Germany.,Research Campus STIMULATE, Magdeburg, Germany
| | - Georg Rose
- Research Campus STIMULATE, Magdeburg, Germany.,Institut für Medizintechnik, Otto-von-Guericke University, Magdeburg, Germany
| | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt, Braunschweig und Berlin, Germany
| | - Ariane Fillmer
- Physikalisch-Technische Bundesanstalt, Braunschweig und Berlin, Germany
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205
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Swanberg KM, Prinsen H, DeStefano K, Bailey M, Kurada AV, Pitt D, Fulbright RK, Juchem C. In vivo evidence of differential frontal cortex metabolic abnormalities in progressive and relapsing-remitting multiple sclerosis. NMR IN BIOMEDICINE 2021; 34:e4590. [PMID: 34318959 DOI: 10.1002/nbm.4590] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 06/11/2021] [Accepted: 07/04/2021] [Indexed: 06/13/2023]
Abstract
The pathophysiology of progressive multiple sclerosis remains elusive, significantly limiting available disease-modifying therapies. Proton MRS (1 H-MRS) enables in vivo measurement of small molecules implicated in multiple sclerosis, but its application to key metabolites glutamate, γ-aminobutyric acid (GABA), and glutathione has been sparse. We employed, at 7 T, a previously validated 1 H-MRS protocol to measure glutamate, GABA, and glutathione, as well as glutamine, N-acetyl aspartate, choline, and myoinositol, in the frontal cortex of individuals with relapsing-remitting (N = 26) or progressive (N = 21) multiple sclerosis or healthy control adults (N = 25) in a cross-sectional analysis. Only individuals with progressive multiple sclerosis demonstrated reduced glutamate (F2,65 = 3.424, p = 0.04; 12.40 ± 0.62 mM versus control 13.17 ± 0.95 mM, p = 0.03) but not glutamine (F2,65 = 0.352, p = 0.7; 4.71 ± 0.35 mM versus control 4.84 ± 0.42 mM), reduced GABA (F2,65 = 3.89, p = 0.03; 1.29 ± 0.23 mM versus control 1.47 ± 0.25 mM, p = 0.05), and possibly reduced glutathione (F2,65 = 0.352, p = 0.056; 2.23 ± 0.46 mM versus control 2.51 ± 0.48 mM, p < 0.1). As a group, multiple sclerosis patients demonstrated significant negative correlations between disease duration and glutamate or GABA (ρ = -0.4, p = 0.02) but not glutamine or glutathione. Alone, only relapsing-remitting multiple sclerosis patients exhibited a significant negative correlation between disease duration and GABA (ρ = -0.5, p = 0.03). Taken together, these results indicate that frontal cortex metabolism is differentially disturbed in progressive and relapsing-remitting multiple sclerosis.
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Affiliation(s)
- Kelley M Swanberg
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut
- Department of Biomedical Engineering, Columbia University School of Engineering and Applied Science, New York, New York
| | - Hetty Prinsen
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut
| | - Katherine DeStefano
- Department of Neurology, Yale University School of Medicine, New Haven, Connecticut
| | - Mary Bailey
- Department of Neurology, Yale University School of Medicine, New Haven, Connecticut
| | - Abhinav V Kurada
- Department of Biomedical Engineering, Columbia University School of Engineering and Applied Science, New York, New York
| | - David Pitt
- Department of Neurology, Yale University School of Medicine, New Haven, Connecticut
| | - Robert K Fulbright
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut
| | - Christoph Juchem
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut
- Department of Biomedical Engineering, Columbia University School of Engineering and Applied Science, New York, New York
- Department of Neurology, Yale University School of Medicine, New Haven, Connecticut
- Department of Radiology, Columbia University Medical Center, New York, New York
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206
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Kubota M, Kimura Y, Shimojo M, Takado Y, Duarte JMN, Takuwa H, Seki C, Shimada H, Shinotoh H, Takahata K, Kitamura S, Moriguchi S, Tagai K, Obata T, Nakahara J, Tomita Y, Tokunaga M, Maeda J, Kawamura K, Zhang MR, Ichise M, Suhara T, Higuchi M. Dynamic alterations in the central glutamatergic status following food and glucose intake: in vivo multimodal assessments in humans and animal models. J Cereb Blood Flow Metab 2021; 41:2928-2943. [PMID: 34039039 PMCID: PMC8545038 DOI: 10.1177/0271678x211004150] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 02/24/2021] [Accepted: 02/28/2021] [Indexed: 11/17/2022]
Abstract
Fluctuations of neuronal activities in the brain may underlie relatively slow components of neurofunctional alterations, which can be modulated by food intake and related systemic metabolic statuses. Glutamatergic neurotransmission plays a major role in the regulation of excitatory tones in the central nervous system, although just how dietary elements contribute to the tuning of this system remains elusive. Here, we provide the first demonstration by bimodal positron emission tomography (PET) and magnetic resonance spectroscopy (MRS) that metabotropic glutamate receptor subtype 5 (mGluR5) ligand binding and glutamate levels in human brains are dynamically altered in a manner dependent on food intake and consequent changes in plasma glucose levels. The brain-wide modulations of central mGluR5 ligand binding and glutamate levels and profound neuronal activations following systemic glucose administration were further proven by PET, MRS, and intravital two-photon microscopy, respectively, in living rodents. The present findings consistently support the notion that food-associated glucose intake is mechanistically linked to glutamatergic tones in the brain, which are translationally accessible in vivo by bimodal PET and MRS measurements in both clinical and non-clinical settings.
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Affiliation(s)
- Manabu Kubota
- Department of Functional Brain Imaging, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
- Department of Psychiatry, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Yasuyuki Kimura
- Department of Functional Brain Imaging, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
- Department of Clinical and Experimental Neuroimaging, Center for Development of Advanced Medicine for Dementia, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Masafumi Shimojo
- Department of Functional Brain Imaging, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Yuhei Takado
- Department of Functional Brain Imaging, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Joao MN Duarte
- Department of Experimental Medical Science, Faculty of Medicine, Lund University, Lund, Sweden
- Wallenberg Centre for Molecular Medicine, Lund University, Lund, Sweden
| | - Hiroyuki Takuwa
- Department of Functional Brain Imaging, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Chie Seki
- Department of Functional Brain Imaging, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Hitoshi Shimada
- Department of Functional Brain Imaging, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Hitoshi Shinotoh
- Department of Functional Brain Imaging, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Keisuke Takahata
- Department of Functional Brain Imaging, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Soichiro Kitamura
- Department of Functional Brain Imaging, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
- Department of Psychiatry, Nara Medical University, Nara, Japan
| | - Sho Moriguchi
- Department of Functional Brain Imaging, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Kenji Tagai
- Department of Functional Brain Imaging, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Takayuki Obata
- Department of Molecular Imaging and Theranostics, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Jin Nakahara
- Department of Neurology, Keio University School of Medicine, Tokyo, Japan
| | - Yutaka Tomita
- Department of Neurology, Keio University School of Medicine, Tokyo, Japan
- Tomita Hospital, Aichi, Japan
| | - Masaki Tokunaga
- Department of Functional Brain Imaging, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Jun Maeda
- Department of Functional Brain Imaging, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Kazunori Kawamura
- Department of Radiopharmaceutics Development, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Ming-Rong Zhang
- Department of Radiopharmaceutics Development, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Masanori Ichise
- Department of Functional Brain Imaging, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Tetsuya Suhara
- Department of Functional Brain Imaging, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Makoto Higuchi
- Department of Functional Brain Imaging, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
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207
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Hui SCN, Mikkelsen M, Zöllner HJ, Ahluwalia V, Alcauter S, Baltusis L, Barany DA, Barlow LR, Becker R, Berman JI, Berrington A, Bhattacharyya PK, Blicher JU, Bogner W, Brown MS, Calhoun VD, Castillo R, Cecil KM, Choi YB, Chu WCW, Clarke WT, Craven AR, Cuypers K, Dacko M, de la Fuente-Sandoval C, Desmond P, Domagalik A, Dumont J, Duncan NW, Dydak U, Dyke K, Edmondson DA, Ende G, Ersland L, Evans CJ, Fermin ASR, Ferretti A, Fillmer A, Gong T, Greenhouse I, Grist JT, Gu M, Harris AD, Hat K, Heba S, Heckova E, Hegarty JP, Heise KF, Honda S, Jacobson A, Jansen JFA, Jenkins CW, Johnston SJ, Juchem C, Kangarlu A, Kerr AB, Landheer K, Lange T, Lee P, Levendovszky SR, Limperopoulos C, Liu F, Lloyd W, Lythgoe DJ, Machizawa MG, MacMillan EL, Maddock RJ, Manzhurtsev AV, Martinez-Gudino ML, Miller JJ, Mirzakhanian H, Moreno-Ortega M, Mullins PG, Nakajima S, Near J, Noeske R, Nordhøy W, Oeltzschner G, Osorio-Duran R, Otaduy MCG, Pasaye EH, Peeters R, Peltier SJ, Pilatus U, Polomac N, Porges EC, Pradhan S, Prisciandaro JJ, Puts NA, Rae CD, Reyes-Madrigal F, Roberts TPL, Robertson CE, Rosenberg JT, Rotaru DG, O'Gorman Tuura RL, Saleh MG, Sandberg K, Sangill R, Schembri K, et alHui SCN, Mikkelsen M, Zöllner HJ, Ahluwalia V, Alcauter S, Baltusis L, Barany DA, Barlow LR, Becker R, Berman JI, Berrington A, Bhattacharyya PK, Blicher JU, Bogner W, Brown MS, Calhoun VD, Castillo R, Cecil KM, Choi YB, Chu WCW, Clarke WT, Craven AR, Cuypers K, Dacko M, de la Fuente-Sandoval C, Desmond P, Domagalik A, Dumont J, Duncan NW, Dydak U, Dyke K, Edmondson DA, Ende G, Ersland L, Evans CJ, Fermin ASR, Ferretti A, Fillmer A, Gong T, Greenhouse I, Grist JT, Gu M, Harris AD, Hat K, Heba S, Heckova E, Hegarty JP, Heise KF, Honda S, Jacobson A, Jansen JFA, Jenkins CW, Johnston SJ, Juchem C, Kangarlu A, Kerr AB, Landheer K, Lange T, Lee P, Levendovszky SR, Limperopoulos C, Liu F, Lloyd W, Lythgoe DJ, Machizawa MG, MacMillan EL, Maddock RJ, Manzhurtsev AV, Martinez-Gudino ML, Miller JJ, Mirzakhanian H, Moreno-Ortega M, Mullins PG, Nakajima S, Near J, Noeske R, Nordhøy W, Oeltzschner G, Osorio-Duran R, Otaduy MCG, Pasaye EH, Peeters R, Peltier SJ, Pilatus U, Polomac N, Porges EC, Pradhan S, Prisciandaro JJ, Puts NA, Rae CD, Reyes-Madrigal F, Roberts TPL, Robertson CE, Rosenberg JT, Rotaru DG, O'Gorman Tuura RL, Saleh MG, Sandberg K, Sangill R, Schembri K, Schrantee A, Semenova NA, Singel D, Sitnikov R, Smith J, Song Y, Stark C, Stoffers D, Swinnen SP, Tain R, Tanase C, Tapper S, Tegenthoff M, Thiel T, Thioux M, Truong P, van Dijk P, Vella N, Vidyasagar R, Vovk A, Wang G, Westlye LT, Wilbur TK, Willoughby WR, Wilson M, Wittsack HJ, Woods AJ, Wu YC, Xu J, Lopez MY, Yeung DKW, Zhao Q, Zhou X, Zupan G, Edden RAE. Frequency drift in MR spectroscopy at 3T. Neuroimage 2021; 241:118430. [PMID: 34314848 PMCID: PMC8456751 DOI: 10.1016/j.neuroimage.2021.118430] [Show More Authors] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 06/18/2021] [Accepted: 07/22/2021] [Indexed: 11/17/2022] Open
Abstract
PURPOSE Heating of gradient coils and passive shim components is a common cause of instability in the B0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites. METHOD A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC). RESULTS Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p < 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI. DISCUSSION This study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed.
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Affiliation(s)
- 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
| | - Mark Mikkelsen
- 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
| | - Vishwadeep Ahluwalia
- GSU/GT Center for Advanced Brain Imaging, Georgia Institute of Technology, Atlanta, GA USA
| | - Sarael Alcauter
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Queretaro, Mexico
| | - Laima Baltusis
- Center for Cognitive and Neurobiological Imaging, Stanford University, Stanford, CA USA
| | - Deborah A Barany
- Department of Kinesiology, University of Georgia, and Augusta University/University of Georgia Medical Partnership, Athens, GA USA
| | - Laura R Barlow
- Department of Radiology, Faculty of Medicine, The University of British Columbia, Vancouver, Canada
| | - Robert Becker
- Center for Innovative Psychiatry and Psychotherapy Research, Department Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Jeffrey I Berman
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA USA
| | - Adam Berrington
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | | | - Jakob Udby Blicher
- Center of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark
| | - Wolfgang Bogner
- Department of Biomedical Imaging and Image-guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
| | - Mark S Brown
- Department of Radiology, Medical Physics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA USA
| | - Ryan Castillo
- NeuRA Imaging, Neuroscience Research Australia, Randwick, Australia
| | - Kim M Cecil
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH USA
| | - Yeo Bi Choi
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH USA
| | - Winnie C W Chu
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong, China
| | - William T Clarke
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Alexander R Craven
- Department of Biological and Medical Psychology, University of Bergen, Haukeland University Hospital, Bergen, Norway
| | - Koen Cuypers
- REVAL Rehabilitation Research Institute (REVAL), Hasselt University, Diepenbeek, Belgium; Department of Movement Sciences, KU Leuven, Leuven, Belgium
| | - Michael Dacko
- Department of Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Camilo de la Fuente-Sandoval
- Laboratory of Experimental Psychiatry & Neuropsychiatry Department, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico
| | - Patricia Desmond
- Department of Radiology, University of Melbourne/ Royal Melbourne Hospital, Melbourne, Australia
| | - Aleksandra Domagalik
- Brain Imaging Core Facility, Malopolska Centre of Biotechnology, Jagiellonian University, Kraków, Poland
| | - Julien Dumont
- Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, US 41 - UMS 2014 - PLBS, F-59000 Lille, France
| | - Niall W Duncan
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan
| | - Ulrike Dydak
- School of Health Sciences, Purdue University, West Lafayette, IN USA
| | - Katherine Dyke
- School of Psychology, University of Nottingham, Nottingham, UK
| | - David A Edmondson
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH USA
| | - Gabriele Ende
- Center for Innovative Psychiatry and Psychotherapy Research, Department Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Lars Ersland
- Department of Clinical Engineering, University of Bergen, Haukeland University Hospital, Bergen, Norway
| | | | - Alan S R Fermin
- Center for Brain, Mind and KANSEI Sciences Research, Hiroshima University, Hiroshima, Japan
| | - Antonio Ferretti
- Department of Neuroscience, Imaging and Clinical Sciences, University "G. d'Annunzio" of Chieti-Pescara, Chieti, Italy
| | - Ariane Fillmer
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig und Berlin, Germany
| | - Tao Gong
- Department of Imaging and Nuclear Medicine, Shandong Medical Imaging Research Institute, Shandong University, Jinan, China
| | - Ian Greenhouse
- Department of Human Physiology, University of Oregon, Eugene, OR USA
| | - James T Grist
- Department of Physiology, Anatomy, and Genetics, Oxford Centre for Magnetic Resonance / Department of Radiology, The Churchill Hospital, The University of Oxford, Oxford, UK
| | - Meng Gu
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Ashley D Harris
- Department of Radiology, University of Calgary, Calgary, Canada
| | - Katarzyna Hat
- Consciousness Lab, Institute of Psychology, Jagiellonian University, Kraków, Poland
| | - Stefanie Heba
- Department of Neurology, BG University Hospital Bergmannsheil, Bochum, Germany
| | - Eva Heckova
- Department of Biomedical Imaging and Image-guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
| | - John P Hegarty
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA
| | | | - Shiori Honda
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Aaron Jacobson
- Department of Radiology / Psychiatry, University of California San Diego, San Diego, CA USA
| | - Jacobus F A Jansen
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
| | | | - Stephen J Johnston
- Psychology Department / Clinical Imaging Facility, Swansea University, Swansea, UK
| | - Christoph Juchem
- Departments of Biomedical Engineering and Radiology, Columbia University, New York, NY USA
| | - Alayar Kangarlu
- Department of Psychiatry, Columbia University Irving Medical Center/New York State Psychiatric Institute, New York, NY USA
| | - Adam B Kerr
- Center for Cognitive and Neurobiological Imaging, Stanford University, Stanford, CA USA
| | - Karl Landheer
- Departments of Biomedical Engineering and Radiology, Columbia University, New York, NY USA
| | - Thomas Lange
- Department of Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Phil Lee
- Department of Radiology / Hoglund Biomedical Imaging Center, University of Kansas Medical Center, Kansas City, KS USA
| | | | - Catherine Limperopoulos
- Developing Brain Institute, Diagnostic Imaging and Radiology, Children's National Hospital, Washington, DC USA
| | - Feng Liu
- Department of Psychiatry, Columbia University Irving Medical Center/New York State Psychiatric Institute, New York, NY USA
| | - William Lloyd
- Division of Informatics, Imaging & Data Sciences, University of Manchester, Manchester, UK
| | - David J Lythgoe
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Maro G Machizawa
- Center for Brain, Mind and KANSEI Sciences Research, Hiroshima University, Hiroshima, Japan
| | - Erin L MacMillan
- Department of Radiology, Faculty of Medicine, The University of British Columbia, Vancouver, Canada; Philips Canada, Markham, ON, Canada
| | - Richard J Maddock
- Department of Psychiatry and Behavioral Sciences, University of California Davis, Imaging Research Center, Davis, CA USA
| | - Andrei V Manzhurtsev
- Department of Radiology, Clinical and Research Institute of Emergency Pediatric Surgery and Trauma, Moscow, Russia; Emanuel Institute of Biochemical Physics of the Russian Academy of Sciences, Moscow, Russia
| | - María L Martinez-Gudino
- Departamento de Imágenes Cerebrales, Instituto Nacional de Psiquiatría Ramón de la Fuente Muñiz, Mexico City, Mexico
| | - Jack J Miller
- Department of Physics, University of Oxford, Oxford, UK; The MR Research Centre & The PET Research Centre, Aarhus University, Aarhus, DK
| | - Heline Mirzakhanian
- Department of Radiology / Psychiatry, University of California San Diego, San Diego, CA USA
| | - Marta Moreno-Ortega
- Department of Psychiatry, Columbia University Irving Medical Center/New York State Psychiatric Institute, New York, NY USA
| | - Paul G Mullins
- Bangor Imaging Unit, Department of Psychology, Bangor University, Bangor, Wales, UK
| | - Shinichiro Nakajima
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Jamie Near
- Douglas Mental Health University Institute and Department of Psychiatry, McGill University, Montreal, Canada
| | | | - Wibeke Nordhøy
- NORMENT, Division of Mental Health and Addiction and Department of Diagnostic Physics, Division of Radiology and Nuclear Medicine, Oslo University Hospital / Department of Psychology, University of Oslo, Oslo, Norway
| | - 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
| | - Raul Osorio-Duran
- Departamento de Imágenes Cerebrales, Instituto Nacional de Psiquiatría Ramón de la Fuente Muñiz, Mexico City, Mexico
| | - Maria C G Otaduy
- LIM44, Instituto e Departamento de Radiologia, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Erick H Pasaye
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Queretaro, Mexico
| | - Ronald Peeters
- Department of Imaging & Pathology, Department of Radiology, University Hospitals Leuven, KU Leuven, Leuven, Belgium
| | - Scott J Peltier
- Functional MRI Laboratory, University of Michigan, Ann Arbor, MI USA
| | - Ulrich Pilatus
- Institute of Neuroradiology, Goethe-University Frankfurt, Frankfurt, Germany
| | - Nenad Polomac
- Institute of Neuroradiology, Goethe-University Frankfurt, Frankfurt, Germany
| | - Eric C Porges
- Center for Cognitive Aging and Memory, McKnight Brain Institute, Department of Clinical and Health Psychology, College of Public Health and Health Professions. Department of Neuroscience, College of Medicine, University of Florida, Gainesville, USA
| | - Subechhya Pradhan
- Developing Brain Institute, Diagnostic Imaging and Radiology, Children's National Hospital, Washington, DC USA
| | - James Joseph Prisciandaro
- Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC USA
| | - Nicolaas A Puts
- Department of Forensic & Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, King's College London, London, UK
| | - Caroline D Rae
- NeuRA Imaging, Neuroscience Research Australia, Randwick, Australia
| | - Francisco Reyes-Madrigal
- Laboratory of Experimental Psychiatry & Neuropsychiatry Department, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico
| | - Timothy P L Roberts
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA USA
| | - Caroline E Robertson
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH USA
| | - Jens T Rosenberg
- McKnight Brain Institute, AMRIS, University of Florida, Gainesville, FL USA
| | - Diana-Georgiana Rotaru
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Ruth L O'Gorman Tuura
- Center for MR Research, University Children's Hospital, Zurich, University of Zurich, Switzerland
| | - Muhammad G Saleh
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, USA
| | - Kristian Sandberg
- Center of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark
| | - Ryan Sangill
- Center of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark
| | | | - Anouk Schrantee
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Natalia A Semenova
- Department of Radiology, Clinical and Research Institute of Emergency Pediatric Surgery and Trauma, Moscow, Russia; Emanuel Institute of Biochemical Physics of the Russian Academy of Sciences, Moscow, Russia
| | - Debra Singel
- Department of Psychiatry, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Rouslan Sitnikov
- Clinical Neuroscience, MRI Centre, Karolinska Institute, Stockholm, Sweden
| | - Jolinda Smith
- Lewis Center for Neuroimaging, University of Oregon, Eugene, OR USA
| | - Yulu Song
- Department of Imaging and Nuclear Medicine, Shandong Medical Imaging Research Institute, Shandong University, Jinan, China
| | - Craig Stark
- Department of Neurobiology and Behavior, Facility for Imaging and Brain Research (FIBRE) & Campus Center for Neuroimaging (CCNI), School of Biological Sciences, University of California, Irvine, Irvine, CA USA
| | - Diederick Stoffers
- Spinoza Centre for Neuroimaging, Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
| | | | - Rongwen Tain
- Department of Neurobiology and Behavior, Facility for Imaging and Brain Research (FIBRE) & Campus Center for Neuroimaging (CCNI), School of Biological Sciences, University of California, Irvine, Irvine, CA USA
| | - Costin Tanase
- Department of Psychiatry and Behavioral Sciences, University of California Davis, Imaging Research Center, Davis, CA USA
| | - Sofie Tapper
- 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
| | - Martin Tegenthoff
- Department of Neurology, BG University Hospital Bergmannsheil, Bochum, Germany
| | - Thomas Thiel
- Institute of Clinical Neuroscience and Medical Psychology, University Dusseldorf, Medical Faculty, Düsseldorf, Germany
| | - Marc Thioux
- Department of Otorhinolaryngology, Head and Neck Surgery, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Peter Truong
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, Canada
| | - Pim van Dijk
- Department of Otorhinolaryngology, Head and Neck Surgery, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Nolan Vella
- Medical Physics, Mater Dei Hospital, Imsida, Malta
| | - Rishma Vidyasagar
- Melbourne Dementia Research Centre, Florey Institute of Neurosciences and Mental Health, Melbourne, Australia
| | - Andrej Vovk
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Guangbin Wang
- Department of Imaging and Nuclear Medicine, Shandong Medical Imaging Research Institute, Shandong University, Jinan, China
| | - Lars T Westlye
- NORMENT, Division of Mental Health and Addiction and Department of Diagnostic Physics, Division of Radiology and Nuclear Medicine, Oslo University Hospital / Department of Psychology, University of Oslo, Oslo, Norway
| | - Timothy K Wilbur
- Department of Radiology, University of Washington, Seattle, WA USA
| | - William R Willoughby
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL USA
| | - Martin Wilson
- Centre for Human Brain Health and School of Psychology, University of Birmingham, Birmingham, UK
| | - Hans-Jörg Wittsack
- Department of Diagnostic and Interventional Radiology, University Düsseldorf, Medical Faculty, Düsseldorf, Germany
| | - Adam J Woods
- Center for Cognitive Aging and Memory, McKnight Brain Institute, Department of Clinical and Health Psychology, College of Public Health and Health Professions. Department of Neuroscience, College of Medicine, University of Florida, Gainesville, USA
| | - Yen-Chien Wu
- Department of Radiology, TMU-Shuang Ho Hospital, New Taipei City, Taiwan
| | - Junqian Xu
- Department of Radiology and Psychiatry, Baylor College of Medicine, Houston, USA
| | | | - David K W Yeung
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong, China
| | - Qun Zhao
- Bioimaging Research Center, Department of Physics and Astronomy, University of Georgia, Athens, GA USA
| | - Xiaopeng Zhou
- School of Health Sciences, Purdue University, West Lafayette, IN USA
| | - Gasper Zupan
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - 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.
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Radbruch A, Paech D, Gassenmaier S, Luetkens J, Isaak A, Herrmann J, Othman A, Schäfer J, Nikolaou K. 1.5 vs 3 Tesla Magnetic Resonance Imaging: A Review of Favorite Clinical Applications for Both Field Strengths-Part 2. Invest Radiol 2021; 56:692-704. [PMID: 34417406 DOI: 10.1097/rli.0000000000000818] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
ABSTRACT The second part of this review deals with experiences in neuroradiological and pediatric examinations using modern magnetic resonance imaging systems with 1.5 T and 3 T, with special attention paid to experiences in pediatric cardiac imaging. In addition, whole-body examinations, which are widely used for diagnostic purposes in systemic diseases, are compared with respect to the image quality obtained in different body parts at both field strengths. A systematic overview of the technical differences at 1.5 T and 3 T has been presented in part 1 of this review, as well as several organ-based magnetic resonance imaging applications including musculoskeletal imaging, abdominal imaging, and prostate diagnostics.
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Affiliation(s)
- Alexander Radbruch
- From the Clinic for Diagnostic and Interventional Neuroradiology, University Hospital Bonn, Bonn
| | - Daniel Paech
- From the Clinic for Diagnostic and Interventional Neuroradiology, University Hospital Bonn, Bonn
| | - Sebastian Gassenmaier
- Department of Radiology, Diagnostic and Interventional Radiology, University of Tübingen, Tübingen
| | - Julian Luetkens
- Clinic for Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn
| | - Alexander Isaak
- Clinic for Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn
| | - Judith Herrmann
- Department of Radiology, Diagnostic and Interventional Radiology, University of Tübingen, Tübingen
| | | | - Jürgen Schäfer
- Department of Radiology, Diagnostic and Interventional Radiology, University of Tübingen, Tübingen
| | - Konstantin Nikolaou
- Department of Radiology, Diagnostic and Interventional Radiology, University of Tübingen, Tübingen
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Whitehead MT, Bluml S. Proton and Multinuclear Spectroscopy of the Pediatric Brain. Magn Reson Imaging Clin N Am 2021; 29:543-555. [PMID: 34717844 DOI: 10.1016/j.mric.2021.06.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Magnetic resonance spectroscopy (MRS) is a valuable adjunct to structural brain imaging. State-of-the-art MRS has benefited greatly from recent technical advancements. Neurometabolic alterations in pediatric brain diseases have implications for diagnosis, prognosis, and therapy. Herein, the authors discuss MRS technical considerations and applications in the setting of various pediatric disease processes including tumors, metabolic diseases, hypoxic/ischemic encephalopathy/stroke, epilepsy, demyelinating disease, and infection.
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Affiliation(s)
- Matthew T Whitehead
- Department of Radiology, Children's National Hospital, 111 Michigan Avenue NW, Washington, DC 20010, USA; Prenatal Pediatrics Institute, Children's National Hospital, Washington, DC, USA; The George Washington University School of Medicine and Health Sciences, Washington, DC, USA.
| | - Stefan Bluml
- Department of Radiology, Children's Hospital Los Angeles, Keck School of Medicine, University of Southern California, 450 Sunset Boulevard, Los Angeles, CA 90027, USA; Rudi Schulte Research Institute, Santa Barbara, CA, USA
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210
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Maximo JO, Briend F, Armstrong WP, Kraguljac NV, Lahti AC. Salience network glutamate and brain connectivity in medication-naïve first episode patients - A multimodal magnetic resonance spectroscopy and resting state functional connectivity MRI study. Neuroimage Clin 2021; 32:102845. [PMID: 34662778 PMCID: PMC8526757 DOI: 10.1016/j.nicl.2021.102845] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Revised: 09/08/2021] [Accepted: 09/25/2021] [Indexed: 11/25/2022]
Abstract
BACKGROUND Salience network (SN) connectivity is altered in schizophrenia, but the pathophysiological origin remains poorly understood. The goal of this multimodal neuroimaging study was to investigate the role of glutamatergic metabolism as putative mechanism underlying SN dysconnectivity in first episode psychosis (FEP) subjects. METHODS We measured glutamate + glutamine (Glx) in the dorsal anterior cingulate cortex (dACC) from 70 antipsychotic-naïve FEP subjects and 52 healthy controls (HC). The dACC was then used as seed to define positive and negative resting state functional connectivity (FC) of the SN. We used multiple regression analyses to test main effects and group interactions of Glx and FC associations. RESULTS dACC Glx levels did not differ between groups. Positive FC was significantly reduced in FEP compared to HC, and no group differences were found in negative FC. Group interactions of Glx-FC associations were found within the SN for positive FC, and in parietal cortices for negative FC. In HC, higher Glx levels predicted greater positive FC in the dACC and insula, and greater negative FC of the lateral parietal cortex. These relationships were weaker or absent in FEP. CONCLUSIONS Here, we found that positive FC in the SN is already altered in medication-naïve FEP, underscoring the importance of considering both correlations and anticorrelations for characterization of pathology. Our data demonstrate that Glx and functional connectivity work differently in FEP than in HC, pointing to a possible mechanism underlying dysconnectivity in psychosis.
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Affiliation(s)
- Jose O Maximo
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Frederic Briend
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA; UMR1253, iBrain, Université de Tours, Inserm, Tours, France
| | - William P Armstrong
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Nina V Kraguljac
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Adrienne C Lahti
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA.
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211
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Piersson AD, Ibrahim B, Suppiah S, Mohamad M, Hassan HA, Omar NF, Ibrahim MI, Yusoff AN, Ibrahim N, Saripan MI, Razali RM. Multiparametric MRI for the improved diagnostic accuracy of Alzheimer's disease and mild cognitive impairment: Research protocol of a case-control study design. PLoS One 2021; 16:e0252883. [PMID: 34547018 PMCID: PMC8454976 DOI: 10.1371/journal.pone.0252883] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Accepted: 05/18/2021] [Indexed: 11/19/2022] Open
Abstract
Background Alzheimer’s disease (AD) is a major neurocognitive disorder identified by memory loss and a significant cognitive decline based on previous level of performance in one or more cognitive domains that interferes in the independence of everyday activities. The accuracy of imaging helps to identify the neuropathological features that differentiate AD from its common precursor, mild cognitive impairment (MCI). Identification of early signs will aid in risk stratification of disease and ensures proper management is instituted to reduce the morbidity and mortality associated with AD. Magnetic resonance imaging (MRI) using structural MRI (sMRI), functional MRI (fMRI), diffusion tensor imaging (DTI), and magnetic resonance spectroscopy (1H-MRS) performed alone is inadequate. Thus, the combination of multiparametric MRI is proposed to increase the accuracy of diagnosing MCI and AD when compared to elderly healthy controls. Methods This protocol describes a non-interventional case control study. The AD and MCI patients and the healthy elderly controls will undergo multi-parametric MRI. The protocol consists of sMRI, fMRI, DTI, and single-voxel proton MRS sequences. An eco-planar imaging (EPI) will be used to perform resting-state fMRI sequence. The structural images will be analysed using Computational Anatomy Toolbox-12, functional images will be analysed using Statistical Parametric Mapping-12, DPABI (Data Processing & Analysis for Brain Imaging), and Conn software, while DTI and 1H-MRS will be analysed using the FSL (FMRIB’s Software Library) and Tarquin respectively. Correlation of the MRI results and the data acquired from the APOE genotyping, neuropsychological evaluations (i.e. Montreal Cognitive Assessment [MoCA], and Mini–Mental State Examination [MMSE] scores) will be performed. The imaging results will also be correlated with the sociodemographic factors. The diagnosis of AD and MCI will be standardized and based on the DSM-5 criteria and the neuropsychological scores. Discussion The combination of sMRI, fMRI, DTI, and MRS sequences can provide information on the anatomical and functional changes in the brain such as regional grey matter volume atrophy, impaired functional connectivity among brain regions, and decreased metabolite levels specifically at the posterior cingulate cortex/precuneus. The combination of multiparametric MRI sequences can be used to stratify the management of MCI and AD patients. Accurate imaging can decide on the frequency of follow-up at memory clinics and select classifiers for machine learning that may aid in the disease identification and prognostication. Reliable and consistent quantification, using standardised protocols, are crucial to establish an optimal diagnostic capability in the early detection of Alzheimer’s disease.
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Affiliation(s)
- Albert Dayor Piersson
- Diagnostic Imaging and Radiotherapy Programme, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
- Department of Imaging Technology & Sonography, School of Allied Health Sciences, University of Cape Coast, Cape Coast, Ghana
| | - Buhari Ibrahim
- Faculty of Medicine and Health Sciences, Department of Radiology, Universiti Putra Malaysia, Seri Kembangan, Malaysia
- Faculty of Medicine and Health Sciences, Neuroscience Laboratory for Cognitive Function and Behavioural Imaging (NeuroCoB), Universiti Putra Malaysia, Seri Kembangan, Malaysia
- Faculty of Basic Medical Sciences, Department of Physiology, Bauchi State University PMB 65, Gadau, Nigeria
| | - Subapriya Suppiah
- Faculty of Medicine and Health Sciences, Department of Radiology, Universiti Putra Malaysia, Seri Kembangan, Malaysia
- Faculty of Medicine and Health Sciences, Neuroscience Laboratory for Cognitive Function and Behavioural Imaging (NeuroCoB), Universiti Putra Malaysia, Seri Kembangan, Malaysia
- * E-mail:
| | - Mazlyfarina Mohamad
- Diagnostic Imaging and Radiotherapy Programme, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - Hasyma Abu Hassan
- Faculty of Medicine and Health Sciences, Department of Radiology, Universiti Putra Malaysia, Seri Kembangan, Malaysia
| | - Nur Farhayu Omar
- Faculty of Medicine and Health Sciences, Department of Radiology, Universiti Putra Malaysia, Seri Kembangan, Malaysia
| | - Mohd Izuan Ibrahim
- Diagnostic Imaging and Radiotherapy Programme, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - Ahmad Nazlim Yusoff
- Diagnostic Imaging and Radiotherapy Programme, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - Normala Ibrahim
- Faculty of Medicine and Health Sciences, Department of Psychiatry, Universiti Putra Malaysia, Seri Kembangan, Malaysia
| | - M. Iqbal Saripan
- Faculty of Engineering, Department of Computer & Communication Systems, University Putra Malaysia, Seri Kembangan, Malaysia
| | - Rizah Mazzuin Razali
- Gerontology Unit, Department of Medicine, Hospital Kuala Lumpur, Kuala Lumpur, Malaysia
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212
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Vakulin A, Green MA, D'Rozario AL, Stevens D, Openshaw H, Bartlett D, Wong K, McEvoy RD, Grunstein RR, Rae CD. Brain mitochondrial dysfunction and driving simulator performance in untreated obstructive sleep apnea. J Sleep Res 2021; 31:e13482. [PMID: 34528315 DOI: 10.1111/jsr.13482] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 08/29/2021] [Accepted: 08/30/2021] [Indexed: 11/30/2022]
Abstract
It is challenging to determine which patients with obstructive sleep apnea (OSA) have impaired driving ability. Vulnerability to this neurobehavioral impairment may be explained by lower brain metabolites levels involved in mitochondrial metabolism. This study compared markers of brain energy metabolism in OSA patients identified as vulnerable vs resistant to driving impairment following extended wakefulness. 44 patients with moderate-severe OSA underwent 28hr extended wakefulness with three 90min driving simulation assessments. Using a two-step cluster analysis, objective driving data (steering deviation and crashes) from the 2nd driving assessment (22.5 h awake) was used to categorise patients into vulnerable (poor driving, n = 21) or resistant groups (good driving, n = 23). 1 H magnetic resonance spectra were acquired at baseline using two scan sequences (short echo PRESS and longer echo-time asymmetric PRESS), focusing on key metabolites, creatine, glutamate, N-acetylaspartate (NAA) in the hippocampus, anterior cingulate cortex and left orbito-frontal cortex. Based on cluster analysis, the vulnerable group had impaired driving performance compared with the resistant group and had lower levels of creatine (PRESS p = ns, APRESS p = 0.039), glutamate, (PRESS p < 0.01, APRESS p < 0.01), NAA (PRESS p = 0.038, APRESS p = 0.035) exclusively in the left orbito-frontal cortex. Adjusted analysis, higher glutamate was associated with a 21% (PRESS) and 36% (APRESS) reduced risk of vulnerable classification. Brain mitochondrial bioenergetics in the frontal brain regions are impaired in OSA patients who are vulnerable to driving impairment following sleep loss. These findings provide a potential way to identify at risk OSA phenotype when assessing fitness to drive, but this requires confirmation in larger future studies.
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Affiliation(s)
- Andrew Vakulin
- Adelaide Institute for Sleep Health/FHMRI Sleep Health, College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia.,Centre for Sleep and Chronobiology, Woolcock Institute of Medical Research, Sydney, New South Wales, Australia
| | - Michael A Green
- Neuroscience Research Australia, Sydney, New South Wales, Australia.,School of Medical Sciences, The University of New South Wales, Sydney, New South Wales, Australia
| | - Angela L D'Rozario
- Centre for Sleep and Chronobiology, Woolcock Institute of Medical Research, Sydney, New South Wales, Australia.,School of Psychology, Faculty of Science, Brain and Mind Centre and Charles Perkins Centre, University of Sydney, Sydney, New South Wales, Australia
| | - David Stevens
- Adelaide Institute for Sleep Health/FHMRI Sleep Health, College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia.,Centre for Nutritional and Gastrointestinal Diseases, SAHMRI, Adelaide, South Australia, Australia
| | - Hannah Openshaw
- Centre for Sleep and Chronobiology, Woolcock Institute of Medical Research, Sydney, New South Wales, Australia
| | - Delwyn Bartlett
- Centre for Sleep and Chronobiology, Woolcock Institute of Medical Research, Sydney, New South Wales, Australia.,Sydney Medical School, The University of Sydney, Sydney, New South Wales, Australia
| | - Keith Wong
- Centre for Sleep and Chronobiology, Woolcock Institute of Medical Research, Sydney, New South Wales, Australia.,Sydney Medical School, The University of Sydney, Sydney, New South Wales, Australia.,Royal Prince Alfred Hospital, Sydney Health Partners, Sydney, New South Wales, Australia
| | - R Doug McEvoy
- Adelaide Institute for Sleep Health/FHMRI Sleep Health, College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia
| | - Ronald R Grunstein
- Centre for Sleep and Chronobiology, Woolcock Institute of Medical Research, Sydney, New South Wales, Australia.,Sydney Medical School, The University of Sydney, Sydney, New South Wales, Australia.,Royal Prince Alfred Hospital, Sydney Health Partners, Sydney, New South Wales, Australia
| | - Caroline D Rae
- Neuroscience Research Australia, Sydney, New South Wales, Australia.,School of Medical Sciences, The University of New South Wales, Sydney, New South Wales, Australia
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213
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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: 3.0] [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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214
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Chang CK, Shih TTF, Tien YW, Chang MC, Chang YT, Yang SH, Cheng MF, Chen BB. Metabolic Alterations in Pancreatic Cancer Detected by In Vivo 1H-MR Spectroscopy: Correlation with Normal Pancreas, PET Metabolic Activity, Clinical Stages, and Survival Outcome. Diagnostics (Basel) 2021; 11:1541. [PMID: 34573881 PMCID: PMC8472373 DOI: 10.3390/diagnostics11091541] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 08/12/2021] [Accepted: 08/23/2021] [Indexed: 12/16/2022] Open
Abstract
OBJECTIVE To compare the metabolites of in vivo 1H- MRS in pancreatic cancer with normal pancreas, and correlate these metabolites with Positron Emission Tomography (PET) metabolic activity, clinical stages, and survival outcomes. METHODS The prospective study included 58 patients (mean age 62.7 ± 12.1 years, range 34-81 years; 36 men, 22 women) with pathological proof of pancreatic adenocarcinoma, and all of them received 18F-fluorodeoxyglucose (FDG) PET/MRI before treatment. The single-voxel MRS with a point-resolved selective spectroscopy sequence was used to measure metabolites (creatine, Glx (glutamine and glutamate), N-acetylaspartate (NAA), and lipid) of pancreatic cancer and adjacent normal parenchyma, respectively. FDG-PET parameters included SUVmax, metabolic tumor volume (MTV), and total lesion glycolysis (TLG). Non-parametric tests were used to evaluate the differences of MRS metabolites between pancreatic cancer and those in normal pancreas, and their correlation with PET parameters and clinical stages. The correlation with progression-free survival (PFS) and overall survival (OS) was measured using the Kaplan-Meier and Cox proportional hazard models. RESULTS When compared with normal pancreas, the Glx, NAA, and lipid levels were significantly decreased in pancreatic cancer (all p < 0.05). Creatine, Glx, and lipid levels were all inversely correlated with both MTV (rho = -0.405~-0.454) and TLG (rho = -0.331~-0.441). For correlation with clinical stages, lower lipid levels were found in patients with T4 (vs. CONCLUSIONS Decreased MRS metabolites in pancreatic cancer were associated with poor survival outcome, and may be used as prognostic image biomarkers for these patients.
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Affiliation(s)
- Chih-Kai Chang
- Department of Medical Imaging, National Taiwan University Hospital, Taipei 100, Taiwan; (C.-K.C.); (T.T.-F.S.)
| | - Tiffany Ting-Fang Shih
- Department of Medical Imaging, National Taiwan University Hospital, Taipei 100, Taiwan; (C.-K.C.); (T.T.-F.S.)
- Department of Radiology, College of Medicine, National Taiwan University, Taipei 100, Taiwan
| | - Yu-Wen Tien
- Department of Surgery, National Taiwan University Hospital, Taipei 100, Taiwan;
| | - Ming-Chu Chang
- Department of Internal Medicine, National Taiwan University Hospital, Taipei 100, Taiwan; (M.-C.C.); (Y.-T.C.)
| | - Yu-Ting Chang
- Department of Internal Medicine, National Taiwan University Hospital, Taipei 100, Taiwan; (M.-C.C.); (Y.-T.C.)
| | - Shih-Hung Yang
- Department of Oncology, National Taiwan University Hospital, Taipei 100, Taiwan;
| | - Mei-Fang Cheng
- Department of Nuclear Medicine, National Taiwan University Hospital, Taipei 100, Taiwan;
| | - Bang-Bin Chen
- Department of Medical Imaging, National Taiwan University Hospital, Taipei 100, Taiwan; (C.-K.C.); (T.T.-F.S.)
- Department of Radiology, College of Medicine, National Taiwan University, Taipei 100, Taiwan
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215
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Kantrowitz JT, Dong Z, Milak MS, Rashid R, Kegeles LS, Javitt DC, Lieberman JA, John Mann J. Ventromedial prefrontal cortex/anterior cingulate cortex Glx, glutamate, and GABA levels in medication-free major depressive disorder. Transl Psychiatry 2021; 11:419. [PMID: 34354048 PMCID: PMC8342485 DOI: 10.1038/s41398-021-01541-1] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 07/12/2021] [Accepted: 07/23/2021] [Indexed: 02/07/2023] Open
Abstract
Glutamate (Glu) and gamma-aminobutyric acid (GABA) are implicated in the pathophysiology of major depressive disorder (MDD). GABA levels or GABAergic interneuron numbers are generally low in MDD, potentially disinhibiting Glu release. It is unclear whether Glu release or turnover is increased in depression. Conversely, a meta-analysis of prefrontal proton magnetic resonance spectroscopy (1H MRS) studies in MDD finds low Glx (combination of glutamate and glutamine) in medicated MDD. We hypothesize that elevated Glx or Glu may be a marker of more severe, untreated MDD. We examined ventromedial prefrontal cortex/anterior cingulate cortex (vmPFC/ACC) Glx and glutamate levels using 1H MRS in 34 medication-free, symptomatic, chronically ill MDD patients and 32 healthy volunteers, and GABA levels in a subsample. Elevated Glx and Glu were observed in MDD compared with healthy volunteers, with the highest levels seen in males with MDD. vmPFC/ACC GABA was low in MDD. Higher Glx levels correlated with more severe depression and lower GABA. MDD severity and diagnosis were both linked to higher Glx in vmPFC/ACC. Low GABA in a subset of these patients is consistent with our hypothesized model of low GABA leading to glutamate disinhibition in MDD. This finding and model are consistent with our previously reported findings that the NMDAR-antagonist antidepressant effect is proportional to the reduction of vmPFC/ACC Glx or Glu levels.
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Affiliation(s)
- Joshua T. Kantrowitz
- grid.21729.3f0000000419368729Department of Psychiatry, Columbia University, College of Physicians and Surgeons, New York, NY USA ,grid.413734.60000 0000 8499 1112New York State Psychiatric Institute, New York, NY USA ,grid.250263.00000 0001 2189 4777Nathan Kline Institute, 140 Old Orangeburg Road, Orangeburg, NY USA
| | - Zhengchao Dong
- grid.21729.3f0000000419368729Department of Psychiatry, Columbia University, College of Physicians and Surgeons, New York, NY USA ,grid.413734.60000 0000 8499 1112New York State Psychiatric Institute, New York, NY USA
| | - Matthew S. Milak
- grid.21729.3f0000000419368729Department of Psychiatry, Columbia University, College of Physicians and Surgeons, New York, NY USA ,grid.413734.60000 0000 8499 1112New York State Psychiatric Institute, New York, NY USA
| | - Rain Rashid
- grid.21729.3f0000000419368729Department of Psychiatry, Columbia University, College of Physicians and Surgeons, New York, NY USA ,grid.413734.60000 0000 8499 1112New York State Psychiatric Institute, New York, NY USA
| | - Lawrence S. Kegeles
- grid.21729.3f0000000419368729Department of Psychiatry, Columbia University, College of Physicians and Surgeons, New York, NY USA ,grid.413734.60000 0000 8499 1112New York State Psychiatric Institute, New York, NY USA ,grid.21729.3f0000000419368729Department of Radiology, Columbia University, College of Physicians and Surgeons, New York, NY USA
| | - Daniel C. Javitt
- grid.21729.3f0000000419368729Department of Psychiatry, Columbia University, College of Physicians and Surgeons, New York, NY USA ,grid.413734.60000 0000 8499 1112New York State Psychiatric Institute, New York, NY USA ,grid.250263.00000 0001 2189 4777Nathan Kline Institute, 140 Old Orangeburg Road, Orangeburg, NY USA
| | - Jeffrey A. Lieberman
- grid.21729.3f0000000419368729Department of Psychiatry, Columbia University, College of Physicians and Surgeons, New York, NY USA ,grid.413734.60000 0000 8499 1112New York State Psychiatric Institute, New York, NY USA
| | - J. John Mann
- grid.21729.3f0000000419368729Department of Psychiatry, Columbia University, College of Physicians and Surgeons, New York, NY USA ,grid.413734.60000 0000 8499 1112New York State Psychiatric Institute, New York, NY USA ,grid.21729.3f0000000419368729Department of Radiology, Columbia University, College of Physicians and Surgeons, New York, NY USA
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Schnider B, Disselhoff V, Latal B, Wehrle F, Hagmann C, Tuura R. Reply to comment: "Brain creatine alteration and executive function deficits in children born very preterm". Pediatr Res 2021; 90:256-258. [PMID: 33214676 DOI: 10.1038/s41390-020-01281-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Accepted: 09/23/2020] [Indexed: 11/10/2022]
Affiliation(s)
- Barbara Schnider
- Department of Neonatology and Pediatric Intensive Care, University Children's Hospital Zurich, Zurich, Switzerland.,Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland
| | - Vera Disselhoff
- Department of Neonatology and Pediatric Intensive Care, University Children's Hospital Zurich, Zurich, Switzerland.,Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland
| | - Beatrice Latal
- Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland.,Child Development Center, University Children's Hospital Zurich, Zurich, Switzerland
| | - Flavia Wehrle
- Department of Neonatology and Pediatric Intensive Care, University Children's Hospital Zurich, Zurich, Switzerland.,Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland.,Child Development Center, University Children's Hospital Zurich, Zurich, Switzerland
| | - Cornelia Hagmann
- Department of Neonatology and Pediatric Intensive Care, University Children's Hospital Zurich, Zurich, Switzerland.,Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland
| | - Ruth Tuura
- Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland. .,Centre for MR Research, University Children's Hospital Zurich, Zurich, Switzerland.
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217
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Avula S, Peet A, Morana G, Morgan P, Warmuth-Metz M, Jaspan T. European Society for Paediatric Oncology (SIOPE) MRI guidelines for imaging patients with central nervous system tumours. Childs Nerv Syst 2021; 37:2497-2508. [PMID: 33973057 DOI: 10.1007/s00381-021-05199-4] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Accepted: 05/03/2021] [Indexed: 12/15/2022]
Abstract
INTRODUCTION Standardisation of imaging acquisition is essential in facilitating multicentre studies related to childhood CNS tumours. It is important to ensure that the imaging protocol can be adopted by centres with varying imaging capabilities without compromising image quality. MATERIALS AND METHOD An imaging protocol has been developed by the Brain Tumour Imaging Working Group of the European Society for Paediatric Oncology (SIOPE) based on consensus among its members, which consists of neuroradiologists, imaging scientists and paediatric neuro-oncologists. This protocol has been developed to facilitate SIOPE led studies and regularly reviewed by the imaging working group. RESULTS The protocol consists of essential MRI sequences with imaging parameters for 1.5 and 3 Tesla MRI scanners and a set of optional sequences that can be used in appropriate clinical settings. The protocol also provides guidelines for early post-operative imaging and surveillance imaging. The complementary use of multimodal advanced MRI including diffusion tensor imaging (DTI), MR spectroscopy and perfusion imaging is encouraged, and optional guidance is provided in this publication. CONCLUSION The SIOPE brain tumour imaging protocol will enable consistent imaging across multiple centres involved in paediatric CNS tumour studies.
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Affiliation(s)
- Shivaram Avula
- Department of Radiology, Alder Hey Children's NHS Foundation Trust, East Prescot Road, Liverpool, L14 5AB, UK.
| | - Andrew Peet
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.,Birmingham Women's and Children's Hospital NHS Foundation Trust, Birmingham, UK
| | - Giovanni Morana
- Department of Neurosciences, University of Turin, Turin, Italy
| | - Paul Morgan
- Department of Medical Physics, Nottingham University Hospitals, Nottingham, UK
| | - Monika Warmuth-Metz
- Institute of Diagnostic and Interventional Neuroradiology, University of Würzburg, Würzburg, Germany
| | - Tim Jaspan
- Department of Radiology, Nottingham University Hospitals, Nottingham, UK
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218
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Simulated basis sets for semi-LASER: the impact of including shaped RF pulses and magnetic field gradients. MAGMA (NEW YORK, N.Y.) 2021; 34:545-554. [PMID: 33355720 PMCID: PMC8338815 DOI: 10.1007/s10334-020-00900-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 11/26/2020] [Accepted: 11/27/2020] [Indexed: 12/24/2022]
Abstract
Objective To study the need for inclusion of shaped RF pulses and magnetic field gradients in simulations of basis sets for the analysis of proton MR spectra of single voxels of the brain acquired with a semi-LASER pulse sequence. Materials and methods MRS basis sets where simulated at different echo times with hard RF pulses as well as with shaped RF pulses without or with magnetic field gradients included. The influence on metabolite concentration quantification was assessed using both phantom and in vivo measurements. For comparison, simulations and measurements were performed with the PRESS pulse sequence. Results The effect of including gradients in the simulations was smaller for semi-LASER than for PRESS, however, still noticeable. The difference was larger for strongly coupled metabolites and at longer echo times. Metabolite quantification using semi-LASER was thereby less dependent on the inclusion of gradients than PRESS, which was seen in both phantom and in vivo measurements. Discussion The inclusion of the shaped RF pulses and magnetic field gradients in the simulation of basis sets for semi-LASER is only important for strongly coupled metabolites. If computational time is a limiting factor, simple simulations with hard RF pulses can provide almost as accurate metabolite quantification as those that include the chemical-shift related displacement. Supplementary Information The online version contains supplementary material available at 10.1007/s10334-020-00900-1.
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219
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Gajdošík M, Landheer K, Swanberg KM, Adlparvar F, Madelin G, Bogner W, Juchem C, Kirov II. Hippocampal single-voxel MR spectroscopy with a long echo time at 3 T using semi-LASER sequence. NMR IN BIOMEDICINE 2021; 34:e4538. [PMID: 33956374 PMCID: PMC10874619 DOI: 10.1002/nbm.4538] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 04/01/2021] [Accepted: 04/19/2021] [Indexed: 06/12/2023]
Abstract
The hippocampus is one of the most challenging brain regions for proton MR spectroscopy (MRS) applications. Moreover, quantification of J-coupled species such as myo-inositol (m-Ins) and glutamate + glutamine (Glx) is affected by the presence of macromolecular background. While long echo time (TE) MRS eliminates the macromolecules, it also decreases the m-Ins and Glx signal and, as a result, these metabolites are studied mainly with short TE. Here, we investigate the feasibility of reproducibly measuring their concentrations at a long TE of 120 ms, using a semi-adiabatic localization by adiabatic selective refocusing (sLASER) sequence, as this sequence was recently recommended as a standard for clinical MRS. Gradient offset-independent adiabatic refocusing pulses were implemented, and an optimal long TE for the detection of m-Ins and Glx was determined using the T2 relaxation times of macromolecules. Metabolite concentrations and their coefficients of variation (CVs) were obtained for a 3.4-mL voxel centered on the left hippocampus on 3-T MR systems at two different sites with three healthy subjects (aged 32.5 ± 10.2 years [mean ± standard deviation]) per site, with each subject scanned over two sessions, and with each session comprising three scans. Concentrations of m-Ins, choline, creatine, Glx and N-acetyl-aspartate were 5.4 ± 1.5, 1.7 ± 0.2, 5.8 ± 0.3, 11.6 ± 1.2 and 5.9 ± 0.4 mM (mean ± standard deviation), respectively. Their respective mean within-session CVs were 14.5% ± 5.9%, 6.5% ± 5.3%, 6.0% ± 3.4%, 10.6% ± 6.2% and 3.5% ± 1.4%, and their mean within-subject CVs were 17.8% ± 18.2%, 7.5% ± 6.3%, 7.4% ± 6.4%, 12.4% ± 5.3% and 4.8% ± 3.0%. The between-subject CVs were 25.0%, 12.3%, 5.3%, 10.7% and 6.4%, respectively. Hippocampal long-TE sLASER single voxel spectroscopy can provide macromolecule-independent assessment of all major metabolites including Glx and m-Ins.
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Affiliation(s)
- Martin Gajdošík
- Center for Advanced Imaging Innovation and Research (CAIR), Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States
- Department of Biomedical Engineering, Columbia University Fu Foundation School of Engineering and Applied Science, New York, NY, United States
| | - Karl Landheer
- Department of Biomedical Engineering, Columbia University Fu Foundation School of Engineering and Applied Science, New York, NY, United States
| | - Kelley M. Swanberg
- Department of Biomedical Engineering, Columbia University Fu Foundation School of Engineering and Applied Science, New York, NY, United States
| | - Fatemeh Adlparvar
- Center for Advanced Imaging Innovation and Research (CAIR), Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States
| | - Guillaume Madelin
- Center for Advanced Imaging Innovation and Research (CAIR), Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States
| | - Wolfgang Bogner
- High-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Christoph Juchem
- Department of Biomedical Engineering, Columbia University Fu Foundation School of Engineering and Applied Science, New York, NY, United States
- Department of Radiology, Columbia University College of Physicians and Surgeons, New York, NY, United States
| | - Ivan I. Kirov
- Center for Advanced Imaging Innovation and Research (CAIR), Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States
- Department of Neurology, New York University Grossman School of Medicine, New York, NY, United States
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Abstract
The central role of MRI in neuro-oncology is undisputed. The technique is used, both in clinical practice and in clinical trials, to diagnose and monitor disease activity, support treatment decision-making, guide the use of focused treatments and determine response to treatment. Despite recent substantial advances in imaging technology and image analysis techniques, clinical MRI is still primarily used for the qualitative subjective interpretation of macrostructural features, as opposed to quantitative analyses that take into consideration multiple pathophysiological features. However, the field of quantitative imaging and imaging biomarker development is maturing. The European Imaging Biomarkers Alliance (EIBALL) and Quantitative Imaging Biomarkers Alliance (QIBA) are setting standards for biomarker development, validation and implementation, as well as promoting the use of quantitative imaging and imaging biomarkers by demonstrating their clinical value. In parallel, advanced imaging techniques are reaching the clinical arena, providing quantitative, commonly physiological imaging parameters that are driving the discovery, validation and implementation of quantitative imaging and imaging biomarkers in the clinical routine. Additionally, computational analysis techniques are increasingly being used in the research setting to convert medical images into objective high-dimensional data and define radiomic signatures of disease states. Here, I review the definition and current state of MRI biomarkers in neuro-oncology, and discuss the clinical potential of quantitative image analysis techniques.
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221
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An R-Package for the Deconvolution and Integration of 1D NMR Data: MetaboDecon1D. Metabolites 2021; 11:metabo11070452. [PMID: 34357346 PMCID: PMC8305572 DOI: 10.3390/metabo11070452] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 07/03/2021] [Accepted: 07/12/2021] [Indexed: 11/17/2022] Open
Abstract
NMR spectroscopy is a widely used method for the detection and quantification of metabolites in complex biological fluids. However, the large number of metabolites present in a biological sample such as urine or plasma leads to considerable signal overlap in one-dimensional NMR spectra, which in turn hampers both signal identification and quantification. As a consequence, we have developed an easy to use R-package that allows the fully automated deconvolution of overlapping signals in the underlying Lorentzian line-shapes. We show that precise integral values are computed, which are required to obtain both relative and absolute quantitative information. The algorithm is independent of any knowledge of the corresponding metabolites, which also allows the quantitative description of features of yet unknown identity.
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Kang D, Hesam-Shariati N, McAuley JH, Alam M, Trost Z, Rae CD, Gustin SM. Disruption to normal excitatory and inhibitory function within the medial prefrontal cortex in people with chronic pain. Eur J Pain 2021; 25:2242-2256. [PMID: 34242465 DOI: 10.1002/ejp.1838] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
BACKGROUND Growing evidence indicates a link between changes in the medial prefrontal cortex and the pathophysiology of chronic pain. In particular, chronic pain is associated with altered medial prefrontal anatomy and biochemistry. Due to the comorbid affective disorders seen across all pain conditions, the medial prefrontal cortex is a region of significance as it is involved in emotional processing. We have recently reported that a decrease in medial prefrontal N-acetylaspartate and glutamate is associated with increased emotional dysregulation, indicating there are neurotransmitter imbalances in chronic pain. Therefore, we compared medial prefrontal neurochemistry in 24 people with chronic pain conditions to 24 age and sex-matched healthy controls with no history of chronic pain. METHOD GABA-edited MEGA-PRESS was used to measure GABA+ levels, and short TE PRESS was used to measure glutamate levels in the medial prefrontal cortex. Psychometric measures regarding pain intensity a week before scanning, during the scan and the total duration of chronic pain, were also recorded and compared to measured GABA+ and glutamate levels. RESULTS This study reveals that the presence of chronic pain is associated with significant decreases in medial prefrontal GABA+ and glutamate. These findings support the hypothesis that chronic pain is associated with altered medial prefrontal biochemistry. CONCLUSION The dysregulation of glutamatergic and GABAergic neurotransmitter systems supports a model of disinhibition of chronic pain, which may play a key role in both the experience of persistent pain and its associated affective disturbances. SIGNIFICANCE This study reveals a significant reduction in γ-aminobutyric acid (GABA+ ) and glutamate within the medial prefrontal cortex in chronic pain sufferers. While the current findings should be considered with reference to a small sample size, the disruption to normal excitatory and inhibitory medial prefrontal cortex function may be key in the development and maintenance of chronic pain and comorbid mental health disorders.
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Affiliation(s)
- David Kang
- Centre for Pain IMPACT, Neuroscience Research Australia, Sydney, NSW, Australia
| | - Negin Hesam-Shariati
- Centre for Pain IMPACT, Neuroscience Research Australia, Sydney, NSW, Australia.,School of Psychology, University of New South, Sydney, NSW, Australia
| | - James H McAuley
- Centre for Pain IMPACT, Neuroscience Research Australia, Sydney, NSW, Australia.,School of Health Sciences, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia
| | - Monzurul Alam
- Centre for Pain IMPACT, Neuroscience Research Australia, Sydney, NSW, Australia.,School of Psychology, University of New South, Sydney, NSW, Australia
| | - Zina Trost
- Department of Physical Medicine and Rehabilitation, Virginia Commonwealth University, Richmond, VA, USA
| | | | - Sylvia M Gustin
- Centre for Pain IMPACT, Neuroscience Research Australia, Sydney, NSW, Australia.,School of Psychology, University of New South, Sydney, NSW, Australia
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McGee KP, Hwang K, Sullivan DC, Kurhanewicz J, Hu Y, Wang J, Li W, Debbins J, Paulson E, Olsen JR, Hua C, Warner L, Ma D, Moros E, Tyagi N, Chung C. Magnetic resonance biomarkers in radiation oncology: The report of AAPM Task Group 294. Med Phys 2021; 48:e697-e732. [PMID: 33864283 PMCID: PMC8361924 DOI: 10.1002/mp.14884] [Citation(s) in RCA: 12] [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: 11/19/2020] [Revised: 03/24/2021] [Accepted: 03/28/2021] [Indexed: 12/16/2022] Open
Abstract
A magnetic resonance (MR) biologic marker (biomarker) is a measurable quantitative characteristic that is an indicator of normal biological and pathogenetic processes or a response to therapeutic intervention derived from the MR imaging process. There is significant potential for MR biomarkers to facilitate personalized approaches to cancer care through more precise disease targeting by quantifying normal versus pathologic tissue function as well as toxicity to both radiation and chemotherapy. Both of which have the potential to increase the therapeutic ratio and provide earlier, more accurate monitoring of treatment response. The ongoing integration of MR into routine clinical radiation therapy (RT) planning and the development of MR guided radiation therapy systems is providing new opportunities for MR biomarkers to personalize and improve clinical outcomes. Their appropriate use, however, must be based on knowledge of the physical origin of the biomarker signal, the relationship to the underlying biological processes, and their strengths and limitations. The purpose of this report is to provide an educational resource describing MR biomarkers, the techniques used to quantify them, their strengths and weakness within the context of their application to radiation oncology so as to ensure their appropriate use and application within this field.
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Affiliation(s)
| | - Ken‐Pin Hwang
- Department of Imaging PhysicsDivision of Diagnostic ImagingMD Anderson Cancer CenterUniversity of TexasHoustonTexasUSA
| | | | - John Kurhanewicz
- Department of RadiologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Yanle Hu
- Department of Radiation OncologyMayo ClinicScottsdaleArizonaUSA
| | - Jihong Wang
- Department of Radiation OncologyMD Anderson Cancer CenterUniversity of TexasHoustonTexasUSA
| | - Wen Li
- Department of Radiation OncologyUniversity of ArizonaTucsonArizonaUSA
| | - Josef Debbins
- Department of RadiologyBarrow Neurologic InstitutePhoenixArizonaUSA
| | - Eric Paulson
- Department of Radiation OncologyMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Jeffrey R. Olsen
- Department of Radiation OncologyUniversity of Colorado Denver ‐ Anschutz Medical CampusDenverColoradoUSA
| | - Chia‐ho Hua
- Department of Radiation OncologySt. Jude Children’s Research HospitalMemphisTennesseeUSA
| | | | - Daniel Ma
- Department of Radiation OncologyMayo ClinicRochesterMinnesotaUSA
| | - Eduardo Moros
- Department of Radiation OncologyMoffitt Cancer CenterTampaFloridaUSA
| | - Neelam Tyagi
- Department of Medical PhysicsMemorial Sloan Kettering Cancer CenterNew YorkNew YorkUSA
| | - Caroline Chung
- Department of Radiation OncologyMD Anderson Cancer CenterUniversity of TexasHoustonTexasUSA
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224
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Landheer K, Juchem C. Are Cramér-Rao lower bounds an accurate estimate for standard deviations in in vivo magnetic resonance spectroscopy? NMR IN BIOMEDICINE 2021; 34:e4521. [PMID: 33876459 DOI: 10.1002/nbm.4521] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Revised: 03/10/2021] [Accepted: 03/22/2021] [Indexed: 06/12/2023]
Abstract
Due to inherent time constraints for in vivo experiments, it is infeasible to repeat multiple MRS scans to estimate standard deviations on the desired measured parameters. As such, the Cramér-Rao lower bounds (CRLBs) have become the routine method to approximate standard deviations for in vivo experiments. Cramér-Rao lower bounds, however, as the name suggests, are theoretically a lower bound on the standard deviation and it is not clear if and under what circumstances this approximation is valid. Realistic synthetic 3 T spectra were used to investigate the relationship between estimated CRLBs, true CRLBs and standard deviations. Here we demonstrate that, although the CRLBs are theoretically truly a lower bound on the standard deviation (not an equality) for the problem typically encountered in quantification, they are still an adequate approximation to standard deviation as long as the model perfectly characterizes the data. In the case when the macromolecule basis deviates from the measured macromolecules it was shown that the CRLBs can deviate from standard deviations by approximately 50% for N-acetylaspartic acid, creatine and glutamate and of the order of 100% or more for myo-inositol and γ-aminobutyric acid. In the case when the model perfectly reflects the data the CRLBs are within approximately 10% of standard deviations for all metabolites. The result of the CRLB being within 10% of standard deviations means that, for an accurate model, novel quantification methods such as machine learning or deep learning will not be able to obtain substantially more precise estimates for the desired parameters than traditional maximum-likelihood estimation.
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Affiliation(s)
- Karl Landheer
- Department of Biomedical Engineering, Columbia University Fu Foundation School of Engineering and Applied Science, New York, New York, USA
| | - Christoph Juchem
- Department of Biomedical Engineering, Columbia University Fu Foundation School of Engineering and Applied Science, New York, New York, USA
- Department of Radiology, Columbia University College of Physicians and Surgeons, New York, New York, USA
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225
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Lee J, Andronesi OC, Torrado-Carvajal A, Ratai EM, Loggia ML, Weerasekera A, Berry MP, Ellingsen DM, Isaro L, Lazaridou A, Paschali M, Grahl A, Wasan AD, Edwards RR, Napadow V. 3D magnetic resonance spectroscopic imaging reveals links between brain metabolites and multidimensional pain features in fibromyalgia. Eur J Pain 2021; 25:2050-2064. [PMID: 34102707 DOI: 10.1002/ejp.1820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Revised: 06/01/2021] [Accepted: 06/04/2021] [Indexed: 11/08/2022]
Abstract
BACKGROUND Fibromyalgia is a centralized multidimensional chronic pain syndrome, but its pathophysiology is not fully understood. METHODS We applied 3D magnetic resonance spectroscopic imaging (MRSI), covering multiple cortical and subcortical brain regions, to investigate the association between neuro-metabolite (e.g. combined glutamate and glutamine, Glx; myo-inositol, mIno; and combined (total) N-acetylaspartate and N-acetylaspartylglutamate, tNAA) levels and multidimensional clinical/behavioural variables (e.g. pain catastrophizing, clinical pain severity and evoked pain sensitivity) in women with fibromyalgia (N = 87). RESULTS Pain catastrophizing scores were positively correlated with Glx and tNAA levels in insular cortex, and negatively correlated with mIno levels in posterior cingulate cortex (PCC). Clinical pain severity was positively correlated with Glx levels in insula and PCC, and with tNAA levels in anterior midcingulate cortex (aMCC), but negatively correlated with mIno levels in aMCC and thalamus. Evoked pain sensitivity was negatively correlated with levels of tNAA in insular cortex, MCC, PCC and thalamus. CONCLUSIONS These findings support single voxel placement targeting nociceptive processing areas in prior 1 H-MRS studies, but also highlight other areas not as commonly targeted, such as PCC, as important for chronic pain pathophysiology. Identifying target brain regions linked to multidimensional symptoms of fibromyalgia (e.g. negative cognitive/affective response to pain, clinical pain, evoked pain sensitivity) may aid the development of neuromodulatory and individualized therapies. Furthermore, efficient multi-region sampling with 3D MRSI could reduce the burden of lengthy scan time for clinical research applications of molecular brain-based mechanisms supporting multidimensional aspects of fibromyalgia. SIGNIFICANCE This large N study linked brain metabolites and pain features in fibromyalgia patients, with a better spatial resolution and brain coverage, to understand a molecular mechanism underlying pain catastrophizing and other aspects of pain transmission. Metabolite levels in self-referential cognitive processing area as well as pain-processing regions were associated with pain outcomes. These results could help the understanding of its pathophysiology and treatment strategies for clinicians.
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Affiliation(s)
- Jeungchan Lee
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Ovidiu C Andronesi
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Angel Torrado-Carvajal
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.,Medical Image Analysis and Biometry Laboratory, Universidad Rey Juan Carlos, Madrid, Spain
| | - Eva-Maria Ratai
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Marco L Loggia
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Akila Weerasekera
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Michael P Berry
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Dan-Mikael Ellingsen
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.,Department of Psychology, University of Oslo, Oslo, Norway
| | - Laura Isaro
- Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Asimina Lazaridou
- Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Myrella Paschali
- Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Arvina Grahl
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Ajay D Wasan
- Department of Anesthesiology and Perioperative Medicine, Center for Innovation in Pain Care, University of Pittsburgh, Pittsburgh, PA, USA
| | - Robert R Edwards
- Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Vitaly Napadow
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.,Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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226
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Kumon M, Nakae S, Murayama K, Kato T, Ohba S, Inamasu J, Yamada S, Abe M, Sasaki H, Ohno Y, Hasegawa M, Kurahashi H, Hirose Y. Myoinositol to Total Choline Ratio in Glioblastomas as a Potential Prognostic Factor in Preoperative Magnetic Resonance Spectroscopy. Neurol Med Chir (Tokyo) 2021; 61:453-460. [PMID: 34078827 PMCID: PMC8365238 DOI: 10.2176/nmc.oa.2020-0312] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Isocitrate dehydrogenase (IDH) wild-type diffuse astrocytic tumors tend to be pathologically diagnosed as glioblastomas (GBMs). We previously reported that myoinositol to total choline (Ins/Cho) ratio in GBMs on magnetic resonance (MR) spectroscopy was significantly lower than that in IDH-mutant gliomas. We then hypothesized that a low Ins/Cho ratio is a poor prognosis factor in patients with GBMs, IDH-wild-type. In the present study, we calculated the Ins/Cho ratios of patients with GBMs and investigated their progression-free survival (PFS) and overall survival (OS) to determine their utility as prognostic marker. We classified patients with GBMs harboring wild-type IDH (n = 27) into two groups based on the Ins/Cho ratio, and compared patient backgrounds, pathological findings, PFS, OS, and copy number aberrations between the high and low Ins/Cho groups. Patients with GBMs in the low Ins/Cho ratio group indicated shorter PFS (P = 0.021) and OS (P = 0.048) than those in the high Ins/Cho group. Multivariate analysis demonstrated that the Ins/Cho ratio was significantly correlated with PFS (hazard ratio 0.24, P = 0.028). In conclusion, the preoperative Ins/Cho ratio can be used as a novel potential prognostic factor for GBM, IDH-wild-type.
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Affiliation(s)
| | | | - Kazuhiro Murayama
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University
| | - Takema Kato
- Division of Molecular Genetics, Institute for Comprehensive Medical Science, Fujita Health University
| | - Shigeo Ohba
- Department of Neurosurgery, Fujita Health University
| | - Joji Inamasu
- Department of Neurosurgery, Fujita Health University
| | - Seiji Yamada
- Department of Pathology, Fujita Health University
| | - Masato Abe
- Department of Pathology, Fujita Health University
| | - Hikaru Sasaki
- Department of Neurosurgery, Keio University School of Medicine
| | | | | | - Hiroki Kurahashi
- Division of Molecular Genetics, Institute for Comprehensive Medical Science, Fujita Health University
| | - Yuichi Hirose
- Department of Neurosurgery, Fujita Health University
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227
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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: 59] [Impact Index Per Article: 14.8] [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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228
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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: 4.3] [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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229
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Sourdon J, Roussel T, Costes C, Viout P, Guye M, Ranjeva JP, Bernard M, Kober F, Rapacchi S. Comparison of single-voxel 1H-cardiovascular magnetic resonance spectroscopy techniques for in vivo measurement of myocardial creatine and triglycerides at 3T. J Cardiovasc Magn Reson 2021; 23:53. [PMID: 33980263 PMCID: PMC8117273 DOI: 10.1186/s12968-021-00748-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Accepted: 03/18/2021] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Single-voxel proton cardiovascular magnetic resonance spectroscopy (1H-CMRS) benefits from 3 T to detect metabolic abnormalities with the quantification of intramyocardial fatty acids (FA) and creatine (Cr). Conventional point resolved spectroscopy (PRESS) sequence remains the preferred choice for CMRS, despite its chemical shift displacement error (CSDE) at high field (≥ 3 T). Alternative candidate sequences are the semi-adiabatic Localization by Adiabatic SElective Refocusing (sLASER) recommended for brain and musculoskeletal applications and the localized stimulated echo acquisition mode (STEAM). In this study, we aim to compare these three single-voxel 1H-CMRS techniques: PRESS, sLASER and STEAM for reproducible quantification of myocardial FA and Cr at 3 T. Sequences are compared both using breath-hold (BH) and free-breathing (FB) acquisitions. METHODS CMRS accuracy and theoretical CSDE were verified on a purposely-designed fat-water phantom. FA and Cr CMRS data quality and reliability were evaluated in the interventricular septum of 10 healthy subjects, comparing repeated BH and free-breathing with retrospective gating. RESULTS Measured FA/W ratio deviated from expected phantom ratio due to CSDE with all sequences. sLASER supplied the lowest bias (10%, vs -28% and 27% for PRESS and STEAM). In vivo, PRESS provided the highest signal-to-noise ratio (SNR) in FB scans (27.5 for Cr and 103.2 for FA). Nevertheless, a linear regression analysis between the two BH showed a better correlation between myocardial Cr content measured with sLASER compared to PRESS (r = 0.46; p = 0.03 vs. r = 0.35; p = 0.07) and similar slopes of regression lines for FA measurements (r = 0.94; p < 0.001 vs. r = 0.87; p < 0.001). STEAM was unable to perform Cr measurement and was the method with the lowest correlation (r = 0.59; p = 0.07) for FA. No difference was found between measurements done either during BH or FB for Cr, FA and triglycerides using PRESS, sLASER and STEAM. CONCLUSION When quantifying myocardial lipids and creatine with CMR proton spectroscopy at 3 T, PRESS provided higher SNR, while sLASER was more reproducible both with single BH and FB scans.
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Affiliation(s)
- Joevin Sourdon
- Aix-Marseille Univ, CNRS, CRMBM UMR 7339, Marseille, France.
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France.
| | - Tangi Roussel
- Aix-Marseille Univ, CNRS, CRMBM UMR 7339, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Claire Costes
- Aix-Marseille Univ, CNRS, CRMBM UMR 7339, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Patrick Viout
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Maxime Guye
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Jean-Philippe Ranjeva
- Aix-Marseille Univ, CNRS, CRMBM UMR 7339, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | | | - Frank Kober
- Aix-Marseille Univ, CNRS, CRMBM UMR 7339, Marseille, France
| | - Stanislas Rapacchi
- Aix-Marseille Univ, CNRS, CRMBM UMR 7339, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
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230
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Tivarus ME, Zhuang Y, Wang L, Murray KD, Venkataraman A, Weber MT, Zhong J, Qiu X, Schifitto G. Mitochondrial toxicity before and after combination antiretroviral therapy, a Magnetic Resonance Spectroscopy study. NEUROIMAGE-CLINICAL 2021; 31:102693. [PMID: 34020161 PMCID: PMC8144469 DOI: 10.1016/j.nicl.2021.102693] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/13/2020] [Revised: 03/21/2021] [Accepted: 05/04/2021] [Indexed: 11/29/2022]
Abstract
The aim of this study was to quantify, via Magnetic Resonance Spectroscopy (MRS), the effect of combination antiretroviral therapy (cART) on brain metabolites and characterize any possible associations between changes in metabolites, age, blood biomarkers of neuronal damage, functional connectivity and cognitive performance. As cART has dramatically increased the life expectancy of HIV-infected (HIV + ) individuals and unmasked an increase in HIV-associated neurocognitive disorders, it is still not clear whether cART neurotoxicity contributes to these disorders. We hypothesized a bimodal effect, with early cART treatment of HIV infection decreasing inflammation as measured by MRS metabolites and improving cognitive performance, and chronic exposure to cART contributing to persistence of cognitive impairment via its effect on mitochondrial function. Basal ganglia metabolites, functional connectivity, cognitive scores, as well as plasma levels of neurofilament light chain (NfL) and tau protein were measured before and after 12 weeks, 1 year and 2 years of cART in a cohort of 50 cART-naïve HIV + subjects and 72 age matched HIV- healthy controls. Glutamate (Glu) levels were lower in the cART naïve patients than in healthy controls and were inversely correlated with plasma levels of NfL. There were no other significant metabolite differences between HIV + and uninfected individuals. Treatment improved Glu levels in HIV+, however, no associations were found between Glu, functional connectivity and cognitive performance. Stable brain metabolites and plasma levels of NfL and Tau over two-years of follow-ups suggest there are no signs of cART neurotoxicity in this relatively young cohort of HIV + individuals.
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Affiliation(s)
- Madalina E Tivarus
- Department of Imaging Sciences, University of Rochester Medical Center, Rochester NY, USA; Department of Neuroscience, University of Rochester Medical Center, Rochester NY, USA.
| | - Yuchuan Zhuang
- Department of Electrical and Computer Engineering, University of Rochester, Rochester, USA
| | - Lu Wang
- Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester NY, USA
| | - Kyle D Murray
- Department of Physics and Astronomy, University of Rochester, Rochester NY, USA
| | - Arun Venkataraman
- Department of Physics and Astronomy, University of Rochester, Rochester NY, USA
| | - Miriam T Weber
- Department of Neurology, University of Rochester Medical Center, Rochester NY, USA
| | - Jianhui Zhong
- Department of Imaging Sciences, University of Rochester Medical Center, Rochester NY, USA; Department of Physics and Astronomy, University of Rochester, Rochester NY, USA; Department of Biomedical Engineering, University of Rochester, Rochester NY, USA
| | - Xing Qiu
- Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester NY, USA
| | - Giovanni Schifitto
- Department of Imaging Sciences, University of Rochester Medical Center, Rochester NY, USA; Department of Neurology, University of Rochester Medical Center, Rochester NY, USA
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Juchem C, Cudalbu C, de Graaf RA, Gruetter R, Henning A, Hetherington HP, Boer VO. B 0 shimming for in vivo magnetic resonance spectroscopy: Experts' consensus recommendations. NMR IN BIOMEDICINE 2021; 34:e4350. [PMID: 32596978 DOI: 10.1002/nbm.4350] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2019] [Revised: 05/14/2020] [Accepted: 05/19/2020] [Indexed: 05/07/2023]
Abstract
Magnetic resonance spectroscopy (MRS) and spectroscopic imaging (MRSI) allow the chemical analysis of physiological processes in vivo and provide powerful tools in the life sciences and for clinical diagnostics. Excellent homogeneity of the static B0 magnetic field over the object of interest is essential for achieving high-quality spectral results and quantitative metabolic measurements. The experimental minimization of B0 variation is performed in a process called B0 shimming. In this article, we summarize the concepts of B0 field shimming using spherical harmonic shimming techniques, specific strategies for B0 homogenization and crucial factors to consider for implementation and use in both brain and body. In addition, experts' recommendations are provided for minimum requirements for B0 shim hardware and evaluation criteria for the primary outcome of adequate B0 shimming for MRS and MRSI, such as the water spectroscopic linewidth.
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Affiliation(s)
- Christoph Juchem
- Departments of Biomedical Engineering and Radiology, Columbia University, New York, New York
| | - Cristina Cudalbu
- Centre d'Imagerie Biomedicale (CIBM), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Robin A de Graaf
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, Connecticut
| | - Rolf Gruetter
- Laboratory for Functional and Metabolic Imaging, Center for Biomedical Imaging, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
| | - Anke Henning
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas
- Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
| | | | - Vincent O Boer
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
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232
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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: 49] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [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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233
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Bogner W, Otazo R, Henning A. Accelerated MR spectroscopic imaging-a review of current and emerging techniques. NMR IN BIOMEDICINE 2021; 34:e4314. [PMID: 32399974 PMCID: PMC8244067 DOI: 10.1002/nbm.4314] [Citation(s) in RCA: 73] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Revised: 03/24/2020] [Accepted: 03/30/2020] [Indexed: 05/14/2023]
Abstract
Over more than 30 years in vivo MR spectroscopic imaging (MRSI) has undergone an enormous evolution from theoretical concepts in the early 1980s to the robust imaging technique that it is today. The development of both fast and efficient sampling and reconstruction techniques has played a fundamental role in this process. State-of-the-art MRSI has grown from a slow purely phase-encoded acquisition technique to a method that today combines the benefits of different acceleration techniques. These include shortening of repetition times, spatial-spectral encoding, undersampling of k-space and time domain, and use of spatial-spectral prior knowledge in the reconstruction. In this way in vivo MRSI has considerably advanced in terms of spatial coverage, spatial resolution, acquisition speed, artifact suppression, number of detectable metabolites and quantification precision. Acceleration not only has been the enabling factor in high-resolution whole-brain 1 H-MRSI, but today is also common in non-proton MRSI (31 P, 2 H and 13 C) and applied in many different organs. In this process, MRSI techniques had to constantly adapt, but have also benefitted from the significant increase of magnetic field strength boosting the signal-to-noise ratio along with high gradient fidelity and high-density receive arrays. In combination with recent trends in image reconstruction and much improved computation power, these advances led to a number of novel developments with respect to MRSI acceleration. Today MRSI allows for non-invasive and non-ionizing mapping of the spatial distribution of various metabolites' tissue concentrations in animals or humans, is applied for clinical diagnostics and has been established as an important tool for neuro-scientific and metabolism research. This review highlights the developments of the last five years and puts them into the context of earlier MRSI acceleration techniques. In addition to 1 H-MRSI it also includes other relevant nuclei and is not limited to certain body regions or specific applications.
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Affiliation(s)
- Wolfgang Bogner
- High‐Field MR Center, Department of Biomedical Imaging and Image‐Guided TherapyMedical University of ViennaViennaAustria
| | - Ricardo Otazo
- Department of Medical PhysicsMemorial Sloan Kettering Cancer CenterNew York, New YorkUSA
| | - Anke Henning
- Max Planck Institute for Biological CyberneticsTübingenGermany
- Advanced Imaging Research Center, UT Southwestern Medical CenterDallasTexasUSA
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234
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Dubois J, Alison M, Counsell SJ, Hertz‐Pannier L, Hüppi PS, Benders MJ. MRI of the Neonatal Brain: A Review of Methodological Challenges and Neuroscientific Advances. J Magn Reson Imaging 2021; 53:1318-1343. [PMID: 32420684 PMCID: PMC8247362 DOI: 10.1002/jmri.27192] [Citation(s) in RCA: 98] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Revised: 04/24/2020] [Accepted: 04/24/2020] [Indexed: 01/04/2023] Open
Abstract
In recent years, exploration of the developing brain has become a major focus for researchers and clinicians in an attempt to understand what allows children to acquire amazing and unique abilities, as well as the impact of early disruptions (eg, prematurity, neonatal insults) that can lead to a wide range of neurodevelopmental disorders. Noninvasive neuroimaging methods such as MRI are essential to establish links between the brain and behavioral changes in newborns and infants. In this review article, we aim to highlight recent and representative studies using the various techniques available: anatomical MRI, quantitative MRI (relaxometry, diffusion MRI), multiparametric approaches, and functional MRI. Today, protocols use 1.5 or 3T MRI scanners, and specialized methodologies have been put in place for data acquisition and processing to address the methodological challenges specific to this population, such as sensitivity to motion. MR sequences must be adapted to the brains of newborns and infants to obtain relevant good soft-tissue contrast, given the small size of the cerebral structures and the incomplete maturation of tissues. The use of age-specific image postprocessing tools is also essential, as signal and contrast differ from the adult brain. Appropriate methodologies then make it possible to explore multiple neurodevelopmental mechanisms in a precise way, and assess changes with age or differences between groups of subjects, particularly through large-scale projects. Although MRI measurements only indirectly reflect the complex series of dynamic processes observed throughout development at the molecular and cellular levels, this technique can provide information on brain morphology, structural connectivity, microstructural properties of gray and white matter, and on the functional architecture. Finally, MRI measures related to clinical, behavioral, and electrophysiological markers have a key role to play from a diagnostic and prognostic perspective in the implementation of early interventions to avoid long-term disabilities in children. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY STAGE: 1.
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Affiliation(s)
- Jessica Dubois
- University of ParisNeuroDiderot, INSERM,ParisFrance
- UNIACT, NeuroSpin, CEA; Paris‐Saclay UniversityGif‐sur‐YvetteFrance
| | - Marianne Alison
- University of ParisNeuroDiderot, INSERM,ParisFrance
- Department of Pediatric RadiologyAPHP, Robert‐Debré HospitalParisFrance
| | - Serena J. Counsell
- Centre for the Developing BrainSchool of Biomedical Engineering & Imaging Sciences, King's College LondonLondonUK
| | - Lucie Hertz‐Pannier
- University of ParisNeuroDiderot, INSERM,ParisFrance
- UNIACT, NeuroSpin, CEA; Paris‐Saclay UniversityGif‐sur‐YvetteFrance
| | - Petra S. Hüppi
- Division of Development and Growth, Department of Woman, Child and AdolescentUniversity Hospitals of GenevaGenevaSwitzerland
| | - Manon J.N.L. Benders
- Department of NeonatologyUniversity Medical Center Utrecht, Utrecht UniversityUtrechtthe Netherlands
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235
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Deelchand DK, Berrington A, Noeske R, Joers JM, Arani A, Gillen J, Schär M, Nielsen JF, Peltier S, Seraji-Bozorgzad N, Landheer K, Juchem C, Soher BJ, Noll DC, Kantarci K, Ratai EM, Mareci TH, Barker PB, Öz G. Across-vendor standardization of semi-LASER for single-voxel MRS at 3T. NMR IN BIOMEDICINE 2021; 34:e4218. [PMID: 31854045 PMCID: PMC7299834 DOI: 10.1002/nbm.4218] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Revised: 10/18/2019] [Accepted: 10/21/2019] [Indexed: 05/23/2023]
Abstract
The semi-adiabatic localization by adiabatic selective refocusing (sLASER) sequence provides single-shot full intensity signal with clean localization and minimal chemical shift displacement error and was recommended by the international MRS Consensus Group as the preferred localization sequence at high- and ultra-high fields. Across-vendor standardization of the sLASER sequence at 3 tesla has been challenging due to the B1 requirements of the adiabatic inversion pulses and maximum B1 limitations on some platforms. The aims of this study were to design a short-echo sLASER sequence that can be executed within a B1 limit of 15 μT by taking advantage of gradient-modulated RF pulses, to implement it on three major platforms and to evaluate the between-vendor reproducibility of its perfomance with phantoms and in vivo. In addition, voxel-based first and second order B0 shimming and voxel-based B1 adjustments of RF pulses were implemented on all platforms. Amongst the gradient-modulated pulses considered (GOIA, FOCI and BASSI), GOIA-WURST was identified as the optimal refocusing pulse that provides good voxel selection within a maximum B1 of 15 μT based on localization efficiency, contamination error and ripple artifacts of the inversion profile. An sLASER sequence (30 ms echo time) that incorporates VAPOR water suppression and 3D outer volume suppression was implemented with identical parameters (RF pulse type and duration, spoiler gradients and inter-pulse delays) on GE, Philips and Siemens and generated identical spectra on the GE 'Braino' phantom between vendors. High-quality spectra were consistently obtained in multiple regions (cerebellar white matter, hippocampus, pons, posterior cingulate cortex and putamen) in the human brain across vendors (5 subjects scanned per vendor per region; mean signal-to-noise ratio > 33; mean water linewidth between 6.5 Hz to 11.4 Hz). The harmonized sLASER protocol is expected to produce high reproducibility of MRS across sites thereby allowing large multi-site studies with clinical cohorts.
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Affiliation(s)
- Dinesh K Deelchand
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Adam Berrington
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University, Baltimore, MD, USA
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | | | - James M Joers
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Arvin Arani
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Joseph Gillen
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University, Baltimore, MD, USA
| | - Michael Schär
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University, Baltimore, MD, USA
| | | | - Scott Peltier
- Department of Biomedical Engineering, University of Michigan, MI, USA
| | | | - Karl Landheer
- Departments of Biomedical Engineering and Radiology, Columbia University, New York, NY, USA
| | - Christoph Juchem
- Departments of Biomedical Engineering and Radiology, Columbia University, New York, NY, USA
| | - Brian J Soher
- Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, NC, USA
| | - Douglas C Noll
- Department of Biomedical Engineering, University of Michigan, MI, USA
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Eva M Ratai
- Department of Radiology, Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, Boston, MA, USA
| | - Thomas H Mareci
- Department of Biochemistry and Molecular Biology, University of Florida, Gainesville, FL, USA
| | - Peter B Barker
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University, Baltimore, MD, USA
- The Kennedy Krieger Institute, Baltimore, MD, USA
| | - Gülin Öz
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
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236
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Choi IY, Kreis R. Advanced methodology for in vivo magnetic resonance spectroscopy. NMR IN BIOMEDICINE 2021; 34:e4504. [PMID: 33709530 DOI: 10.1002/nbm.4504] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Accepted: 02/21/2021] [Indexed: 06/12/2023]
Affiliation(s)
- In-Young Choi
- Department of Neurology, Hoglund Brain Imaging Center, University of Kansas Medical Center, Kansas City, Kansas, USA
| | - Roland Kreis
- Department of Radiology, Nuclear Medicine, and Neuroradiology and Department of Biomedical Research, University Bern, Bern, Switzerland
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237
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Maudsley AA, Andronesi OC, Barker PB, Bizzi A, Bogner W, Henning A, Nelson SJ, Posse S, Shungu DC, Soher BJ. Advanced magnetic resonance spectroscopic neuroimaging: Experts' consensus recommendations. NMR IN BIOMEDICINE 2021; 34:e4309. [PMID: 32350978 PMCID: PMC7606742 DOI: 10.1002/nbm.4309] [Citation(s) in RCA: 79] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2019] [Revised: 02/01/2020] [Accepted: 03/10/2020] [Indexed: 05/04/2023]
Abstract
Magnetic resonance spectroscopic imaging (MRSI) offers considerable promise for monitoring metabolic alterations associated with disease or injury; however, to date, these methods have not had a significant impact on clinical care, and their use remains largely confined to the research community and a limited number of clinical sites. The MRSI methods currently implemented on clinical MRI instruments have remained essentially unchanged for two decades, with only incremental improvements in sequence implementation. During this time, a number of technological developments have taken place that have already greatly benefited the quality of MRSI measurements within the research community and which promise to bring advanced MRSI studies to the point where the technique becomes a true imaging modality, while making the traditional review of individual spectra a secondary requirement. Furthermore, the increasing use of biomedical MR spectroscopy studies has indicated clinical areas where advanced MRSI methods can provide valuable information for clinical care. In light of this rapidly changing technological environment and growing understanding of the value of MRSI studies for biomedical studies, this article presents a consensus from a group of experts in the field that reviews the state-of-the-art for clinical proton MRSI studies of the human brain, recommends minimal standards for further development of vendor-provided MRSI implementations, and identifies areas which need further technical development.
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Affiliation(s)
- Andrew A Maudsley
- Department of Radiology, Miller School of Medicine, University of Miami, Miami, Florida, USA
| | - Ovidiu C Andronesi
- Department of Radiology, Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, Boston, Massachusetts
| | - Peter B Barker
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, and the Kennedy Krieger Institute, F.M. Kirby Center for Functional Brain Imaging, Baltimore, Maryland
| | - Alberto Bizzi
- Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University Vienna, Vienna, Austria
| | - Anke Henning
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Sarah J Nelson
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | - Stefan Posse
- Department of Neurology, University of New Mexico, Albuquerque, New Mexico
| | - Dikoma C Shungu
- Department of Neuroradiology, Weill Cornell Medical College, New York, New York
| | - Brian J Soher
- Department of Radiology, Duke University Medical Center, Durham, North Carolina
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238
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Tkáč I, Deelchand D, Dreher W, Hetherington H, Kreis R, Kumaragamage C, Považan M, Spielman DM, Strasser B, de Graaf RA. Water and lipid suppression techniques for advanced 1 H MRS and MRSI of the human brain: Experts' consensus recommendations. NMR IN BIOMEDICINE 2021; 34:e4459. [PMID: 33327042 PMCID: PMC8569948 DOI: 10.1002/nbm.4459] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Accepted: 11/23/2020] [Indexed: 05/09/2023]
Abstract
The neurochemical information provided by proton magnetic resonance spectroscopy (MRS) or MR spectroscopic imaging (MRSI) can be severely compromised if strong signals originating from brain water and extracranial lipids are not properly suppressed. The authors of this paper present an overview of advanced water/lipid-suppression techniques and describe their advantages and disadvantages. Moreover, they provide recommendations for choosing the most appropriate techniques for proper use. Methods of water signal handling are primarily focused on the VAPOR technique and on MRS without water suppression (metabolite cycling). The section on lipid-suppression methods in MRSI is divided into three parts. First, lipid-suppression techniques that can be implemented on most clinical MR scanners (volume preselection, outer-volume suppression, selective lipid suppression) are described. Second, lipid-suppression techniques utilizing the combination of k-space filtering, high spatial resolutions and lipid regularization are presented. Finally, three promising new lipid-suppression techniques, which require special hardware (a multi-channel transmit system for dynamic B1+ shimming, a dedicated second-order gradient system or an outer volume crusher coil) are introduced.
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Affiliation(s)
- Ivan Tkáč
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Dinesh Deelchand
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Wolfgang Dreher
- Department of Chemistry, In vivo-MR Group, University Bremen, Bremen, Germany
| | - Hoby Hetherington
- Department of Radiology Magnetic Resonance Research Center, University of Pittsburgh, Pittsburgh, PA, USA
| | - Roland Kreis
- Departments of Radiology and Biomedical Research, University Bern, Bern, Switzerland
| | - Chathura Kumaragamage
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, CT, USA
| | - Michal Považan
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Daniel M. Spielman
- Department of Radiology, Stanford University, Stanford, California, CA, USA
| | - Bernhard Strasser
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Department of Radiology, Boston, MA, USA
| | - Robin A. de Graaf
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, CT, USA
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239
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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, Experts' Working Group on Reporting Standards for MR Spectroscopy. 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: 165] [Impact Index Per Article: 41.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [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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240
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Just N. Proton functional magnetic resonance spectroscopy in rodents. NMR IN BIOMEDICINE 2021; 34:e4254. [PMID: 31967711 DOI: 10.1002/nbm.4254] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Revised: 12/04/2019] [Accepted: 12/16/2019] [Indexed: 06/10/2023]
Abstract
Proton functional magnetic resonance spectroscopy (1 H-fMRS) in the human brain is able to assess and quantify the metabolic response due to localized brain activity. Currently, 1 H-fMRS of the human brain is complementary to functional magnetic resonance imaging (fMRI) and a recommended technique at high field strengths (>7 T) for the investigation of neurometabolic couplings, thereby providing insight into the mechanisms underlying brain activity and brain connectivity. Understanding typical healthy brain metabolism during a task is expected to provide a baseline from which to detect and characterize neurochemical alterations associated with various neurological or psychiatric disorders and diseases. It is of paramount importance to resolve fundamental questions related to the regulation of neurometabolic processes. New techniques such as optogenetics may be coupled to fMRI and fMRS to bring more specificity to investigations of brain cell populations during cerebral activation thus enabling a higher link to molecular changes and therapeutic advances. These rather novel techniques are mainly available for rodent applications and trigger renewed interest in animal fMRS. However, rodent fMRS remains fairly confidential due to its inherent low signal-to-noise ratio and its dependence on anesthesia. For instance, the accurate determination of metabolic concentration changes during stimulation requires robust knowledge of the physiological environment of the measured region of interest linked to anesthesia in most cases. These factors may also have a strong influence on B0 homogeneity. Therefore, a degree of calibration of the stimulus strength and duration may be needed for increased knowledge of the underpinnings of cerebral activity. Here, we propose an early review of the current status of 1 H-fMRS in rodents and summarize current difficulties and future perspectives.
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Affiliation(s)
- Nathalie Just
- Department of Clinical Radiology, University Hospital Münster, Germany
- INRAE, Centre, Tours Val de Loire, France
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241
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Ip IB, Bridge H. Investigating the neurochemistry of the human visual system using magnetic resonance spectroscopy. Brain Struct Funct 2021; 227:1491-1505. [PMID: 33900453 PMCID: PMC9046312 DOI: 10.1007/s00429-021-02273-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Accepted: 04/09/2021] [Indexed: 11/29/2022]
Abstract
Biochemical processes underpin the structure and function of the visual cortex, yet our understanding of the fundamental neurochemistry of the visual brain is incomplete. Proton magnetic resonance spectroscopy (1H-MRS) is a non-invasive brain imaging tool that allows chemical quantification of living tissue by detecting minute differences in the resonant frequency of molecules. Application of MRS in the human brain in vivo has advanced our understanding of how the visual brain consumes energy to support neural function, how its neural substrates change as a result of disease or dysfunction, and how neural populations signal during perception and plasticity. The aim of this review is to provide an entry point to researchers interested in investigating the neurochemistry of the visual system using in vivo measurements. We provide a basic overview of MRS principles, and then discuss recent findings in four topics of vision science: (i) visual perception, plasticity in the (ii) healthy and (iii) dysfunctional visual system, and (iv) during visual stimulation. Taken together, evidence suggests that the neurochemistry of the visual system provides important novel insights into how we perceive the world.
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Affiliation(s)
- I Betina Ip
- Wellcome Centre for Integrative Neuroimaging, FMRIB Building, Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Holly Bridge
- Wellcome Centre for Integrative Neuroimaging, FMRIB Building, Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, UK.
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Nakae S, Kumon M, Murayama K, Ohba S, Sasaki H, Inamasu J, Kuwahara K, Yamada S, Abe M, Hirose Y. Association of preoperative seizures with tumor metabolites quantified by magnetic resonance spectroscopy in gliomas. Sci Rep 2021; 11:7927. [PMID: 33846339 PMCID: PMC8041994 DOI: 10.1038/s41598-021-86487-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 03/16/2021] [Indexed: 02/02/2023] Open
Abstract
Seizures are common in patients with gliomas; however, the mechanisms of epileptogenesis in gliomas have not been fully understood. This study hypothesized that analyzing quantified metabolites using magnetic resonance spectroscopy (MRS) might provide novel insights to better understand the epileptogenesis in gliomas, and specific metabolites might be indicators of preoperative seizures in gliomas. We retrospectively investigated patient information (gender, age at diagnosis of tumor, their survival time) and tumor information (location, histology, genetic features, and metabolites according to MRS) in patients with gliomas. The data were correlated with the incidence of seizure and analyzed statistically. Of 146 adult supratentorial gliomas, isocitrate dehydrogenase (IDH) mutant tumors significantly indicated higher incidence of preoperative seizures than IDH wild-type gliomas. However, MRS study indicated that glutamate concentration in IDH wild-type gliomas was higher than that in IDH mutant gliomas. Glutamate was not associated with high frequency of preoperative seizures in patients with gliomas. Instead, increased total N-acetyl-L-aspartate (tNAA) was significantly associated with them. Moreover, multivariable analysis indicated that increased level of tNAA was an independent predictor of preoperative seizures. According to MRS analysis, tNAA, rather than glutamate, might be a useful to detect preoperative seizures in patient with supratentorial gliomas.
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Affiliation(s)
- Shunsuke Nakae
- Department of Neurosurgery, Fujita Health University, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan.
| | - Masanobu Kumon
- Department of Neurosurgery, Fujita Health University, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan
| | - Kazuhiro Murayama
- Department of Radiology, Fujita Health University, Toyoake, Aichi, Japan
| | - Shigeo Ohba
- Department of Neurosurgery, Fujita Health University, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan
| | - Hikaru Sasaki
- Department of Neurosurgery, Keio University, Tokyo, Japan
| | - Joji Inamasu
- Department of Neurosurgery, Fujita Health University, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan
| | - Kiyonori Kuwahara
- Department of Neurosurgery, Fujita Health University, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan
| | - Seiji Yamada
- Department of Pathology, Fujita Health University, Toyoake, Aichi, Japan
| | - Masato Abe
- Department of Pathology, Fujita Health University, Toyoake, Aichi, Japan
| | - Yuichi Hirose
- Department of Neurosurgery, Fujita Health University, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan
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243
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Abstract
Magnetic resonance spectroscopy (MRS), being able to identify and measure some brain components (metabolites) in pathologic lesions and in normal-appearing tissue, offers a valuable additional diagnostic tool to assess several pediatric neurological diseases. In this review we will illustrate the basic principles and clinical applications of brain proton (H1; hydrogen) MRS (H1MRS), by now the only MRS method widely available in clinical practice. Performing H1MRS in the brain is inherently less complicated than in other tissues (e.g., liver, muscle), in which spectra are heavily affected by magnetic field inhomogeneities, respiration artifacts, and dominating signals from the surrounding adipose tissues. H1MRS in pediatric neuroradiology has some advantages over acquisitions in adults (lack of motion due to children sedation and lack of brain iron deposition allow optimal results), but it requires a deep knowledge of pediatric pathologies and familiarity with the developmental changes in spectral patterns, particularly occurring in the first two years of life. Examples from our database, obtained mainly from a 1.5 Tesla clinical scanner in a time span of 15 years, will demonstrate the efficacy of H1MRS in the diagnosis of a wide range of selected pediatric pathologies, like brain tumors, infections, neonatal hypoxic-ischemic encephalopathy, metabolic and white matter disorders.
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Affiliation(s)
- Roberto Liserre
- Department of Radiology, Neuroradiology Unit, ASST Spedali Civili University Hospital, Brescia, Italy
| | - Lorenzo Pinelli
- Department of Radiology, Neuroradiology Unit, ASST Spedali Civili University Hospital, Brescia, Italy
| | - Roberto Gasparotti
- Neuroradiology Unit, Department of Medical-Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy
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244
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Zöllner HJ, Považan M, Hui SC, Tapper S, Edden RA, Oeltzschner G. Comparison of different linear-combination modeling algorithms for short-TE proton spectra. NMR IN BIOMEDICINE 2021; 34:e4482. [PMID: 33530131 PMCID: PMC8935349 DOI: 10.1002/nbm.4482] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 01/09/2021] [Indexed: 05/08/2023]
Abstract
Short-TE proton MRS is used to study metabolism in the human brain. Common analysis methods model the data as a linear combination of metabolite basis spectra. This large-scale multi-site study compares the levels of the four major metabolite complexes in short-TE spectra estimated by three linear-combination modeling (LCM) algorithms. 277 medial parietal lobe short-TE PRESS spectra (TE = 35 ms) from a recent 3 T multi-site study were preprocessed with the Osprey software. The resulting spectra were modeled with Osprey, Tarquin and LCModel, using the same three vendor-specific basis sets (GE, Philips and Siemens) for each algorithm. Levels of total N-acetylaspartate (tNAA), total choline (tCho), myo-inositol (mI) and glutamate + glutamine (Glx) were quantified with respect to total creatine (tCr). Group means and coefficient of variations of metabolite estimates agreed well for tNAA and tCho across vendors and algorithms, but substantially less so for Glx and mI, with mI systematically estimated as lower by Tarquin. The cohort mean coefficient of determination for all pairs of LCM algorithms across all datasets and metabolites was R 2 ¯ = 0.39, indicating generally only moderate agreement of individual metabolite estimates between algorithms. There was a significant correlation between local baseline amplitude and metabolite estimates (cohort mean R 2 ¯ = 0.10). While mean estimates of major metabolite complexes broadly agree between linear-combination modeling algorithms at group level, correlations between algorithms are only weak-to-moderate, despite standardized preprocessing, a large sample of young, healthy and cooperative subjects, and high spectral quality. These findings raise concerns about the comparability of MRS studies, which typically use one LCM software and much smaller sample sizes.
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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
| | - Michal Považan
- 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
| | - 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
| | - 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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245
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Bartnik-Olson BL, Alger JR, Babikian T, Harris AD, Holshouser B, Kirov II, Maudsley AA, Thompson PM, Dennis EL, Tate DF, Wilde EA, Lin A. The clinical utility of proton magnetic resonance spectroscopy in traumatic brain injury: recommendations from the ENIGMA MRS working group. Brain Imaging Behav 2021; 15:504-525. [PMID: 32797399 PMCID: PMC7882010 DOI: 10.1007/s11682-020-00330-6] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Proton (1H) magnetic resonance spectroscopy provides a non-invasive and quantitative measure of brain metabolites. Traumatic brain injury impacts cerebral metabolism and a number of research groups have successfully used this technique as a biomarker of injury and/or outcome in both pediatric and adult TBI populations. However, this technique is underutilized, with studies being performed primarily at centers with access to MR research support. In this paper we present a technical introduction to the acquisition and analysis of in vivo 1H magnetic resonance spectroscopy and review 1H magnetic resonance spectroscopy findings in different injury populations. In addition, we propose a basic 1H magnetic resonance spectroscopy data acquisition scheme (Supplemental Information) that can be added to any imaging protocol, regardless of clinical magnetic resonance platform. We outline a number of considerations for study design as a way of encouraging the use of 1H magnetic resonance spectroscopy in the study of traumatic brain injury, as well as recommendations to improve data harmonization across groups already using this technique.
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Affiliation(s)
| | - Jeffry R Alger
- Departments of Neurology and Radiology, University of California Los Angeles, Los Angeles, CA, USA
- NeuroSpectroScopics LLC, Sherman Oaks, Los Angeles, CA, USA
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Talin Babikian
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA, USA
- UCLA Steve Tisch BrainSPORT Program, Los Angeles, CA, USA
| | - Ashley D Harris
- Department of Radiology, University of Calgary, Calgary, Canada
- Child and Adolescent Imaging Research Program, Alberta Children's Hospital Research Institute and the Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Barbara Holshouser
- Department of Radiology, Loma Linda University Medical Center, Loma Linda, CA, USA
| | - Ivan I Kirov
- Bernard and Irene Schwartz Center for Biomedical Imaging, Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University School of Medicine, New York, NY, USA
| | - Andrew A Maudsley
- Department of Radiology, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, Los Angeles, CA, USA
- Departments of Neurology, Pediatrics, Psychiatry, Radiology, Engineering, and Ophthalmology, USC, Los Angeles, CA, USA
| | - Emily L Dennis
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, Los Angeles, CA, USA
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
- Psychiatry Neuroimaging Laboratory, Brigham & Women's Hospital, Boston, MA, USA
| | - David F Tate
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
- George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, USA
| | - Elisabeth A Wilde
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
- George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, USA
- H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, TX, USA
| | - Alexander Lin
- Center for Clinical Spectroscopy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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246
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Vanherp L, Poelmans J, Weerasekera A, Hillen A, Croitor-Sava AR, Sorrell TC, Lagrou K, Vande Velde G, Himmelreich U. Trehalose as quantitative biomarker for in vivo diagnosis and treatment follow-up in cryptococcomas. Transl Res 2021; 230:111-122. [PMID: 33166695 DOI: 10.1016/j.trsl.2020.11.001] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 10/29/2020] [Accepted: 11/03/2020] [Indexed: 12/26/2022]
Abstract
Brain lesions caused by Cryptococcus neoformans or C. gattii (cryptococcomas) are typically difficult to diagnose correctly and treat effectively, but rapid differential diagnosis and treatment initiation are crucial for good outcomes. In previous studies, cultured cryptococcal isolates and ex vivo lesion material contained high concentrations of the virulence factor and fungal metabolite trehalose. Here, we studied the in vivo metabolic profile of cryptococcomas in the brain using magnetic resonance spectroscopy (MRS) and assessed the relationship between trehalose concentration, fungal burden, and treatment response in order to validate its suitability as marker for early and noninvasive diagnosis and its potential to monitor treatment in vivo. We investigated the metabolites present in early and late stage cryptococcomas using in vivo 1H MRS in a murine model and evaluated changes in trehalose concentrations induced by disease progression and antifungal treatment. Animal data were compared to 1H and 13C MR spectra of Cryptococcus cultures and in vivo data from 2 patients with cryptococcomas in the brain. In vivo MRS allowed the noninvasive detection of high concentrations of trehalose in cryptococcomas and showed a comparable metabolic profile of cryptococcomas in the murine model and human cases. Trehalose concentrations correlated strongly with the fungal burden. Treatment studies in cultures and animal models showed that trehalose concentrations decrease following exposure to effective antifungal therapy. Although further cases need to be studied for clinical validation, this translational study indicates that the noninvasive MRS-based detection of trehalose is a promising marker for diagnosis and therapeutic follow-up of cryptococcomas.
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Affiliation(s)
- Liesbeth Vanherp
- Biomedical MRI, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Jennifer Poelmans
- Biomedical MRI, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Akila Weerasekera
- Biomedical MRI, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium; A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School (MGH/HMS), Boston, Massachusetts, USA
| | - Amy Hillen
- Biomedical MRI, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Anca R Croitor-Sava
- Biomedical MRI, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium; STADIUS, Department of Electrical Engineering (ESAT), KU Leuven, Leuven, Belgium
| | - Tania C Sorrell
- Marie Bashir Institute for Infectious Diseases and Biosecurity, University of Sydney, and Westmead Institute for Medical Research, Centre for Infectious Diseases and Microbiology, Sydney, Australia
| | - Katrien Lagrou
- Laboratory of Clinical Bacteriology and Mycology, Department of Microbiology, Immunology and Transplantation, KU Leuven, Leuven, Belgium; National Reference Centre for Mycosis, Department of Laboratory Medicine, University Hospitals Leuven, Leuven, Belgium
| | - Greetje Vande Velde
- Biomedical MRI, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Uwe Himmelreich
- Biomedical MRI, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium.
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247
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Bilingualism is a long-term cognitively challenging experience that modulates metabolite concentrations in the healthy brain. Sci Rep 2021; 11:7090. [PMID: 33782462 PMCID: PMC8007713 DOI: 10.1038/s41598-021-86443-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 03/16/2021] [Indexed: 02/01/2023] Open
Abstract
Cognitively demanding experiences, including complex skill acquisition and processing, have been shown to induce brain adaptations, at least at the macroscopic level, e.g. on brain volume and/or functional connectivity. However, the neurobiological bases of these adaptations, including at the cellular level, are unclear and understudied. Here we use bilingualism as a case study to investigate the metabolic correlates of experience-based brain adaptations. We employ Magnetic Resonance Spectroscopy to measure metabolite concentrations in the basal ganglia, a region critical to language control which is reshaped by bilingualism. Our results show increased myo-Inositol and decreased N-acetyl aspartate concentrations in bilinguals compared to monolinguals. Both metabolites are linked to synaptic pruning, a process underlying experience-based brain restructuring. Interestingly, both concentrations correlate with relative amount of bilingual engagement. This suggests that degree of long-term cognitive experiences matters at the level of metabolic concentrations, which might accompany, if not drive, macroscopic brain adaptations.
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248
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Castellano A, Bailo M, Cicone F, Carideo L, Quartuccio N, Mortini P, Falini A, Cascini GL, Minniti G. Advanced Imaging Techniques for Radiotherapy Planning of Gliomas. Cancers (Basel) 2021; 13:1063. [PMID: 33802292 PMCID: PMC7959155 DOI: 10.3390/cancers13051063] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Revised: 02/24/2021] [Accepted: 02/26/2021] [Indexed: 02/07/2023] Open
Abstract
The accuracy of target delineation in radiation treatment (RT) planning of cerebral gliomas is crucial to achieve high tumor control, while minimizing treatment-related toxicity. Conventional magnetic resonance imaging (MRI), including contrast-enhanced T1-weighted and fluid-attenuated inversion recovery (FLAIR) sequences, represents the current standard imaging modality for target volume delineation of gliomas. However, conventional sequences have limited capability to discriminate treatment-related changes from viable tumors, owing to the low specificity of increased blood-brain barrier permeability and peritumoral edema. Advanced physiology-based MRI techniques, such as MR spectroscopy, diffusion MRI and perfusion MRI, have been developed for the biological characterization of gliomas and may circumvent these limitations, providing additional metabolic, structural, and hemodynamic information for treatment planning and monitoring. Radionuclide imaging techniques, such as positron emission tomography (PET) with amino acid radiopharmaceuticals, are also increasingly used in the workup of primary brain tumors, and their integration in RT planning is being evaluated in specialized centers. This review focuses on the basic principles and clinical results of advanced MRI and PET imaging techniques that have promise as a complement to RT planning of gliomas.
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Affiliation(s)
- Antonella Castellano
- Neuroradiology Unit, IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, 20132 Milan, Italy; (A.C.); (A.F.)
| | - Michele Bailo
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, 20132 Milan, Italy; (M.B.); (P.M.)
| | - Francesco Cicone
- Department of Experimental and Clinical Medicine, “Magna Graecia” University of Catanzaro, and Nuclear Medicine Unit, University Hospital “Mater Domini”, 88100 Catanzaro, Italy;
| | - Luciano Carideo
- National Cancer Institute, G. Pascale Foundation, 80131 Naples, Italy;
| | - Natale Quartuccio
- A.R.N.A.S. Ospedale Civico Di Cristina Benfratelli, 90144 Palermo, Italy;
| | - Pietro Mortini
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, 20132 Milan, Italy; (M.B.); (P.M.)
| | - Andrea Falini
- Neuroradiology Unit, IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, 20132 Milan, Italy; (A.C.); (A.F.)
| | - Giuseppe Lucio Cascini
- Department of Experimental and Clinical Medicine, “Magna Graecia” University of Catanzaro, and Nuclear Medicine Unit, University Hospital “Mater Domini”, 88100 Catanzaro, Italy;
| | - Giuseppe Minniti
- Radiation Oncology Unit, Department of Medicine, Surgery and Neurosciences, University of Siena, Policlinico Le Scotte, 53100 Siena, Italy;
- IRCCS Neuromed, 86077 Pozzilli (IS), Italy
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249
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Sassani M, Alix JJ, McDermott CJ, Baster K, Hoggard N, Wild JM, Mortiboys HJ, Shaw PJ, Wilkinson ID, Jenkins TM. Magnetic resonance spectroscopy reveals mitochondrial dysfunction in amyotrophic lateral sclerosis. Brain 2021; 143:3603-3618. [PMID: 33439988 DOI: 10.1093/brain/awaa340] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 07/16/2020] [Accepted: 08/08/2020] [Indexed: 12/16/2022] Open
Abstract
Mitochondrial dysfunction is postulated to be central to amyotrophic lateral sclerosis (ALS) pathophysiology. Evidence comes primarily from disease models and conclusive data to support bioenergetic dysfunction in vivo in patients is currently lacking. This study is the first to assess mitochondrial dysfunction in brain and muscle in individuals living with ALS using 31P-magnetic resonance spectroscopy (MRS), the modality of choice to assess energy metabolism in vivo. We recruited 20 patients and 10 healthy age and gender-matched control subjects in this cross-sectional clinico-radiological study. 31P-MRS was acquired from cerebral motor regions and from tibialis anterior during rest and exercise. Bioenergetic parameter estimates were derived including: ATP, phosphocreatine, inorganic phosphate, adenosine diphosphate, Gibbs free energy of ATP hydrolysis (ΔGATP), phosphomonoesters, phosphodiesters, pH, free magnesium concentration, and muscle dynamic recovery constants. Linear regression was used to test for associations between brain data and clinical parameters (revised amyotrophic functional rating scale, slow vital capacity, and upper motor neuron score) and between muscle data and clinico-neurophysiological measures (motor unit number and size indices, force of contraction, and speed of walking). Evidence for primary dysfunction of mitochondrial oxidative phosphorylation was detected in the brainstem where ΔGATP and phosphocreatine were reduced. Alterations were also detected in skeletal muscle in patients where resting inorganic phosphate, pH, and phosphomonoesters were increased, whereas resting ΔGATP, magnesium, and dynamic phosphocreatine to inorganic phosphate recovery were decreased. Phosphocreatine in brainstem correlated with respiratory dysfunction and disability; in muscle, energy metabolites correlated with motor unit number index, muscle power, and speed of walking. This study provides in vivo evidence for bioenergetic dysfunction in ALS in brain and skeletal muscle, which appears clinically and electrophysiologically relevant. 31P-MRS represents a promising technique to assess the pathophysiology of mitochondrial function in vivo in ALS and a potential tool for future clinical trials targeting bioenergetic dysfunction.
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Affiliation(s)
- Matilde Sassani
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
| | - James J Alix
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
| | - Christopher J McDermott
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
| | - Kathleen Baster
- Statistical Service Unit, University of Sheffield, Sheffield, UK
| | - Nigel Hoggard
- Academic Unit of Radiology, University of Sheffield, Sheffield, UK
| | - Jim M Wild
- Academic Unit of Radiology, University of Sheffield, Sheffield, UK
| | - Heather J Mortiboys
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
| | - Pamela J Shaw
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
| | - Iain D Wilkinson
- Academic Unit of Radiology, University of Sheffield, Sheffield, UK
| | - Thomas M Jenkins
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
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250
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Overcast WB, Davis KM, Ho CY, Hutchins GD, Green MA, Graner BD, Veronesi MC. Advanced imaging techniques for neuro-oncologic tumor diagnosis, with an emphasis on PET-MRI imaging of malignant brain tumors. Curr Oncol Rep 2021; 23:34. [PMID: 33599882 PMCID: PMC7892735 DOI: 10.1007/s11912-021-01020-2] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/11/2021] [Indexed: 12/15/2022]
Abstract
PURPOSE OF REVIEW This review will explore the latest in advanced imaging techniques, with a focus on the complementary nature of multiparametric, multimodality imaging using magnetic resonance imaging (MRI) and positron emission tomography (PET). RECENT FINDINGS Advanced MRI techniques including perfusion-weighted imaging (PWI), MR spectroscopy (MRS), diffusion-weighted imaging (DWI), and MR chemical exchange saturation transfer (CEST) offer significant advantages over conventional MR imaging when evaluating tumor extent, predicting grade, and assessing treatment response. PET performed in addition to advanced MRI provides complementary information regarding tumor metabolic properties, particularly when performed simultaneously. 18F-fluoroethyltyrosine (FET) PET improves the specificity of tumor diagnosis and evaluation of post-treatment changes. Incorporation of radiogenomics and machine learning methods further improve advanced imaging. The complementary nature of combining advanced imaging techniques across modalities for brain tumor imaging and incorporating technologies such as radiogenomics has the potential to reshape the landscape in neuro-oncology.
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Affiliation(s)
- Wynton B. Overcast
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 550 N University Blvd. Room 0663, Indianapolis, IN 46202 USA
| | - Korbin M. Davis
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 550 N University Blvd. Room 0663, Indianapolis, IN 46202 USA
| | - Chang Y. Ho
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Goodman Hall, 355 West 16th Street, Suite 4100, Indianapolis, IN 46202 USA
| | - Gary D. Hutchins
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Research 2 Building (R2), Room E124, 920 W. Walnut Street, Indianapolis, IN 46202-5181 USA
| | - Mark A. Green
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Research 2 Building (R2), Room E124, 920 W. Walnut Street, Indianapolis, IN 46202-5181 USA
| | - Brian D. Graner
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Goodman Hall, 355 West 16th Street, Suite 4100, Indianapolis, IN 46202 USA
| | - Michael C. Veronesi
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Research 2 Building (R2), Room E174, 920 W. Walnut Street, Indianapolis, IN 46202-5181 USA
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