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Chen AM, Gerhalter T, Dehkharghani S, Peralta R, Gajdošík M, Gajdošík M, Tordjman M, Zabludovsky J, Sheriff S, Ahn S, Babb JS, Bushnik T, Zarate A, Silver JM, Im BS, Wall SP, Madelin G, Kirov II. Replicability of proton MR spectroscopic imaging findings in mild traumatic brain injury: Implications for clinical applications. Neuroimage Clin 2023; 37:103325. [PMID: 36724732 PMCID: PMC9898311 DOI: 10.1016/j.nicl.2023.103325] [Citation(s) in RCA: 2] [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: 08/09/2022] [Revised: 11/06/2022] [Accepted: 01/16/2023] [Indexed: 01/20/2023]
Abstract
PURPOSE Proton magnetic resonance spectroscopy (1H MRS) offers biomarkers of metabolic damage after mild traumatic brain injury (mTBI), but a lack of replicability studies hampers clinical translation. In a conceptual replication study design, the results reported in four previous publications were used as the hypotheses (H1-H7), specifically: abnormalities in patients are diffuse (H1), confined to white matter (WM) (H2), comprise low N-acetyl-aspartate (NAA) levels and normal choline (Cho), creatine (Cr) and myo-inositol (mI) (H3), and correlate with clinical outcome (H4); additionally, a lack of findings in regional subcortical WM (H5) and deep gray matter (GM) structures (H6), except for higher mI in patients' putamen (H7). METHODS 26 mTBI patients (20 female, age 36.5 ± 12.5 [mean ± standard deviation] years), within two months from injury and 21 age-, sex-, and education-matched healthy controls were scanned at 3 Tesla with 3D echo-planar spectroscopic imaging. To test H1-H3, global analysis using linear regression was used to obtain metabolite levels of GM and WM in each brain lobe. For H4, patients were stratified into non-recovered and recovered subgroups using the Glasgow Outcome Scale Extended. To test H5-H7, regional analysis using spectral averaging estimated metabolite levels in four GM and six WM structures segmented from T1-weighted MRI. The Mann-Whitney U test and weighted least squares analysis of covariance were used to examine mean group differences in metabolite levels between all patients and all controls (H1-H3, H5-H7), and between recovered and non-recovered patients and their respectively matched controls (H4). Replicability was defined as the support or failure to support the null hypotheses in accordance with the content of H1-H7, and was further evaluated using percent differences, coefficients of variation, and effect size (Cohen's d). RESULTS Patients' occipital lobe WM Cho and Cr levels were 6.0% and 4.6% higher than controls', respectively (Cho, d = 0.37, p = 0.04; Cr, d = 0.63, p = 0.03). The same findings, i.e., higher patients' occipital lobe WM Cho and Cr (both p = 0.01), but with larger percent differences (Cho, 8.6%; Cr, 6.3%) and effect sizes (Cho, d = 0.52; Cr, d = 0.88) were found in the comparison of non-recovered patients to their matched controls. For the lobar WM Cho and Cr comparisons without statistical significance (frontal, parietal, temporal), unidirectional effect sizes were observed (Cho, d = 0.07 - 0.37; Cr, d = 0.27 - 0.63). No differences were found in any metabolite in any lobe in the comparison between recovered patients and their matched controls. In the regional analyses, no differences in metabolite levels were found in any GM or WM region, but all WM regions (posterior, frontal, corona radiata, and the genu, body, and splenium of the corpus callosum) exhibited unidirectional effect sizes for Cho and Cr (Cho, d = 0.03 - 0.34; Cr, d = 0.16 - 0.51). CONCLUSIONS We replicated findings of diffuse WM injury, which correlated with clinical outcome (supporting H1-H2, H4). These findings, however, were among the glial markers Cho and Cr, not the neuronal marker NAA (not supporting H3). No differences were found in regional GM and WM metabolite levels (supporting H5-H6), nor in putaminal mI (not supporting H7). Unidirectional effect sizes of higher patients' Cho and Cr within all WM analyses suggest widespread injury, and are in line with the conclusion from the previous publications, i.e., that detection of WM injury may be more dependent upon sensitivity of the 1H MRS technique than on the selection of specific regions. The findings lend further support to the corollary that clinic-ready 1H MRS biomarkers for mTBI may best be achieved by using high signal-to-noise-ratio single-voxels placed anywhere within WM. The biochemical signature of the injury, however, may differ and therefore absolute levels, rather than ratios may be preferred. Future replication efforts should further test the generalizability of these findings.
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Affiliation(s)
- Anna M Chen
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Teresa Gerhalter
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Seena Dehkharghani
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA; Department of Neurology, New York University Grossman School of Medicine, New York, NY, USA
| | - Rosemary Peralta
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Mia Gajdošík
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Martin Gajdošík
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Mickael Tordjman
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA; Department of Radiology, Hôpital Cochin, Paris, France
| | - Julia Zabludovsky
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Sulaiman Sheriff
- Department of Radiology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Sinyeob Ahn
- Siemens Medical Solutions USA Inc., Malvern, PA, USA
| | - James S Babb
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Tamara Bushnik
- Department of Rehabilitation Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | - Alejandro Zarate
- Department of Rehabilitation Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | - Jonathan M Silver
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, USA
| | - Brian S Im
- Department of Rehabilitation Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | - Stephen P Wall
- Ronald O. Perelman Department of Emergency Medicine, New York University Grossman School of Medicine, New York, NY, USA
| | - Guillaume Madelin
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Ivan I Kirov
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA; Department of Neurology, New York University Grossman School of Medicine, New York, NY, USA; Center for Advanced Imaging Innovation and Research, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA.
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Azilinon M, Makhalova J, Zaaraoui W, Medina Villalon S, Viout P, Roussel T, El Mendili MM, Ridley B, Ranjeva J, Bartolomei F, Jirsa V, Guye M. Combining sodium MRI, proton MR spectroscopic imaging, and intracerebral EEG in epilepsy. Hum Brain Mapp 2022; 44:825-840. [PMID: 36217746 PMCID: PMC9842896 DOI: 10.1002/hbm.26102] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 09/12/2022] [Accepted: 09/17/2022] [Indexed: 01/25/2023] Open
Abstract
Whole brain ionic and metabolic imaging has potential as a powerful tool for the characterization of brain diseases. We combined sodium MRI (23 Na MRI) and 1 H-MR Spectroscopic Imaging (1 H-MRSI), assessing changes within epileptogenic networks in comparison with electrophysiologically normal networks as defined by stereotactic EEG (SEEG) recordings analysis. We applied a multi-echo density adapted 3D projection reconstruction pulse sequence at 7 T (23 Na-MRI) and a 3D echo-planar spectroscopic imaging sequence at 3 T (1 H-MRSI) in 19 patients suffering from drug-resistant focal epilepsy who underwent presurgical SEEG. We investigated 23 Na MRI parameters including total sodium concentration (TSC) and the sodium signal fraction associated with the short component of T2 * decay (f), alongside the level of metabolites N-acetyl aspartate (NAA), choline compounds (Cho), and total creatine (tCr). All measures were extracted from spherical regions of interest (ROIs) centered between two adjacent SEEG electrode contacts and z-scored against the same ROI in controls. Group comparison showed a significant increase in f only in the epileptogenic zone (EZ) compared to controls and compared to patients' propagation zone (PZ) and non-involved zone (NIZ). TSC was significantly increased in all patients' regions compared to controls. Conversely, NAA levels were significantly lower in patients compared to controls, and lower in the EZ compared to PZ and NIZ. Multiple regression analyzing the relationship between sodium and metabolites levels revealed significant relations in PZ and in NIZ but not in EZ. Our results are in agreement with the energetic failure hypothesis in epileptic regions associated with widespread tissue reorganization.
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Affiliation(s)
- Mikhael Azilinon
- Aix Marseille Univ, CNRS, CRMBMMarseilleFrance,Aix Marseille Univ, INSERM, INS, Inst Neurosci SystMarseilleFrance,APHM, Timone Hospital, CEMEREMMarseilleFrance
| | - Julia Makhalova
- APHM, Timone Hospital, CEMEREMMarseilleFrance,Epileptology DepartmentAPHM, Timone HospitalMarseilleFrance
| | - Wafaa Zaaraoui
- Aix Marseille Univ, CNRS, CRMBMMarseilleFrance,APHM, Timone Hospital, CEMEREMMarseilleFrance
| | - Samuel Medina Villalon
- Aix Marseille Univ, INSERM, INS, Inst Neurosci SystMarseilleFrance,Epileptology DepartmentAPHM, Timone HospitalMarseilleFrance
| | - Patrick Viout
- Aix Marseille Univ, CNRS, CRMBMMarseilleFrance,APHM, Timone Hospital, CEMEREMMarseilleFrance
| | - Tangi Roussel
- Aix Marseille Univ, CNRS, CRMBMMarseilleFrance,APHM, Timone Hospital, CEMEREMMarseilleFrance
| | - Mohamed M. El Mendili
- Aix Marseille Univ, CNRS, CRMBMMarseilleFrance,APHM, Timone Hospital, CEMEREMMarseilleFrance
| | - Ben Ridley
- IRCCS Istituto delle Scienze Neurologiche di BolognaBolognaItaly
| | - Jean‐Philippe Ranjeva
- Aix Marseille Univ, CNRS, CRMBMMarseilleFrance,APHM, Timone Hospital, CEMEREMMarseilleFrance
| | - Fabrice Bartolomei
- Aix Marseille Univ, INSERM, INS, Inst Neurosci SystMarseilleFrance,Epileptology DepartmentAPHM, Timone HospitalMarseilleFrance
| | - Viktor Jirsa
- Aix Marseille Univ, INSERM, INS, Inst Neurosci SystMarseilleFrance
| | - Maxime Guye
- Aix Marseille Univ, CNRS, CRMBMMarseilleFrance,APHM, Timone Hospital, CEMEREMMarseilleFrance
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3
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Zhu D, Schär M, Qin Q. Ultrafast B1 mapping with RF-prepared 3D FLASH acquisition: Correcting the bias due to T 1 -induced k-space filtering effect. Magn Reson Med 2022; 88:757-769. [PMID: 35381114 PMCID: PMC9232926 DOI: 10.1002/mrm.29247] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 03/06/2022] [Accepted: 03/07/2022] [Indexed: 01/25/2023]
Abstract
Purpose The traditional radiofrequency (RF)‐prepared B1 mapping technique consists of one scan with an RF preparation module for flip angle‐encoding and a second scan without this module for normalizing. To reduce the T1‐induced k‐space filtering effect, this method is limited to 2D FLASH acquisition with a two‐parameter method. A novel 3D RF‐prepared three‐parameter method for ultrafast B1‐mapping is proposed to correct the T1‐induced quantification bias. Theory The point spread function analysis of FLASH shows that the prepared longitudinal magnetization before the FLASH acquisition and the image signal obeys a linear (not proportional) relationship. The intercept of the linear function causes the quantification bias and can be captured by a third saturated scan. Methods Using the 2D double‐angle method (DAM) as the reference, a 3D RF‐prepared three‐parameter protocol with 9 s duration was compared with the two‐parameter method, as well as the saturated DAM (SDAM) method, the dual refocusing echo acquisition mode (DREAM) method, and the actual flip‐angle imaging (AFI) method, for B1 mapping of brain, breast, and abdomen with different orientations and shim settings at 3T. Results The 3D RF‐prepared three‐parameter method with complex‐subtraction delivered consistently lower RMS error, error mean, error standard deviation, and higher concordance correlation coefficients values than the two‐parameter method, the three‐parameter method with magnitude‐subtraction, the multi‐slice DREAM and the 3D AFI, and were close to the results of 2D or multi‐slice SDAM. Conclusion The proposed ultrafast 3D RF‐prepared three‐parameter method with complex‐subtraction was demonstrated with high accuracy for B1 mapping of brain, breast, and abdomen.
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Affiliation(s)
- Dan Zhu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.,The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Michael Schär
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Qin Qin
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.,The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Klauser A, Klauser P, Grouiller F, Courvoisier S, Lazeyras F. Whole-brain high-resolution metabolite mapping with 3D compressed-sensing SENSE low-rank 1 H FID-MRSI. NMR IN BIOMEDICINE 2022; 35:e4615. [PMID: 34595791 PMCID: PMC9285075 DOI: 10.1002/nbm.4615] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 08/16/2021] [Accepted: 08/20/2021] [Indexed: 05/07/2023]
Abstract
There is a growing interest in the neuroscience community to map the distribution of brain metabolites in vivo. Magnetic resonance spectroscopic imaging (MRSI) is often limited by either a poor spatial resolution and/or a long acquisition time, which severely restricts its applications for clinical and research purposes. Building on a recently developed technique of acquisition-reconstruction for 2D MRSI, we combined a fast Cartesian 1 H-FID-MRSI acquisition sequence, compressed-sensing acceleration, and low-rank total-generalized-variation constrained reconstruction to produce 3D high-resolution whole-brain MRSI with a significant acquisition time reduction. We first evaluated the acceleration performance using retrospective undersampling of a fully sampled dataset. Second, a 20 min accelerated MRSI acquisition was performed on three healthy volunteers, resulting in metabolite maps with 5 mm isotropic resolution. The metabolite maps exhibited the detailed neurochemical composition of all brain regions and revealed parts of the underlying brain anatomy. The latter assessment used previous reported knowledge and a atlas-based analysis to show consistency of the concentration contrasts and ratio across all brain regions. These results acquired on a clinical 3 T MRI scanner successfully combined 3D 1 H-FID-MRSI with a constrained reconstruction to produce detailed mapping of metabolite concentrations at high resolution over the whole brain, with an acquisition time suitable for clinical or research settings.
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Affiliation(s)
- Antoine Klauser
- Department of Radiology and Medical InformaticsUniversity of GenevaSwitzerland
- Center for Biomedical Imaging (CIBM)GenevaSwitzerland
| | - Paul Klauser
- Center for Psychiatric Neuroscience, Department of PsychiatryLausanne University HospitalSwitzerland
- Service of Child and Adolescent Psychiatry, Department of PsychiatryLausanne University HospitalSwitzerland
| | - Frédéric Grouiller
- Swiss Center for Affective SciencesUniversity of GenevaSwitzerland
- Laboratory of Behavioral Neurology and Imaging of Cognition, Department of Fundamental NeuroscienceUniversity of GenevaSwitzerland
| | - Sébastien Courvoisier
- Department of Radiology and Medical InformaticsUniversity of GenevaSwitzerland
- Center for Biomedical Imaging (CIBM)GenevaSwitzerland
| | - François Lazeyras
- Department of Radiology and Medical InformaticsUniversity of GenevaSwitzerland
- Center for Biomedical Imaging (CIBM)GenevaSwitzerland
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5
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Hangel G, Spurny-Dworak B, Lazen P, Cadrien C, Sharma S, Hingerl L, Hečková E, Strasser B, Motyka S, Lipka A, Gruber S, Brandner C, Lanzenberger R, Rössler K, Trattnig S, Bogner W. Inter-subject stability and regional concentration estimates of 3D-FID-MRSI in the human brain at 7 T. NMR IN BIOMEDICINE 2021; 34:e4596. [PMID: 34382280 DOI: 10.1002/nbm.4596] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 07/14/2021] [Accepted: 07/14/2021] [Indexed: 05/13/2023]
Abstract
PURPOSE Recently, a 3D-concentric ring trajectory (CRT)-based free induction decay (FID)-MRSI sequence was introduced for fast high-resolution metabolic imaging at 7 T. This technique provides metabolic ratio maps of almost the entire brain within clinically feasible scan times, but its robustness has not yet been thoroughly investigated. Therefore, we have assessed quantitative concentration estimates and their variability in healthy volunteers using this approach. METHODS We acquired whole-brain 3D-CRT-FID-MRSI at 7 T in 15 min with 3.4 mm nominal isometric resolution in 24 volunteers (12 male, 12 female, mean age 27 ± 6 years). Concentration estimate maps were calculated for 15 metabolites using internal water referencing and evaluated in 55 different regions of interest (ROIs) in the brain. Data quality, mean metabolite concentrations, and their inter-subject coefficients of variation (CVs) were compared for all ROIs. RESULTS Of 24 datasets, one was excluded due to motion artifacts. The concentrations of total choline, total creatine, glutamate, myo-inositol, and N-acetylaspartate in 44 regions were estimated within quality thresholds. Inter-subject CVs (mean over 44 ROIs/minimum/maximum) were 9%/5%/19% for total choline, 10%/6%/20% for total creatine, 11%/7%/24% for glutamate, 10%/6%/19% for myo-inositol, and 9%/6%/19% for N-acetylaspartate. DISCUSSION We defined the performance of 3D-CRT-based FID-MRSI for metabolite concentration estimate mapping, showing which metabolites could be robustly quantified in which ROIs with which inter-subject CVs expected. However, the basal brain regions and lesser-signal metabolites in particular remain as a challenge due susceptibility effects from the proximity to nasal and auditory cavities. Further improvement in quantification and the mitigation of B0 /B1 -field inhomogeneities will be necessary to achieve reliable whole-brain coverage.
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Affiliation(s)
- Gilbert Hangel
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
- Department of Neurosurgery, Medical University of Vienna, Vienna, Austria
| | - Benjamin Spurny-Dworak
- Division of General Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Philipp Lazen
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Cornelius Cadrien
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
- Department of Neurosurgery, Medical University of Vienna, Vienna, Austria
| | - Sukrit Sharma
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Lukas Hingerl
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Eva Hečková
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Bernhard Strasser
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Stanislav Motyka
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Alexandra Lipka
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
- Institute for Clinical Molecular MRI, Karl Landsteiner Society, St. Pölten, Austria
| | - Stephan Gruber
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Christoph Brandner
- High-field MR Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Rupert Lanzenberger
- Division of General Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Karl Rössler
- Department of Neurosurgery, Medical University of Vienna, Vienna, Austria
| | - Siegfried Trattnig
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
- Institute for Clinical Molecular MRI, Karl Landsteiner Society, St. Pölten, Austria
| | - Wolfgang Bogner
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
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6
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Klauser A, Strasser B, Thapa B, Lazeyras F, Andronesi O. Achieving high-resolution 1H-MRSI of the human brain with compressed-sensing and low-rank reconstruction at 7 Tesla. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2021; 331:107048. [PMID: 34438355 PMCID: PMC8717865 DOI: 10.1016/j.jmr.2021.107048] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 06/29/2021] [Accepted: 08/08/2021] [Indexed: 06/02/2023]
Abstract
Low sensitivity MR techniques such as magnetic resonance spectroscopic imaging (MRSI) greatly benefit from the gain in signal-to-noise provided by ultra-high field MR. High-resolution and whole-slab brain MRSI remains however very challenging due to lengthy acquisition, low signal, lipid contamination and field inhomogeneity. In this study, we propose an acquisition-reconstruction scheme that combines 1H free-induction-decay (FID)-MRSI sequence, short TR acquisition, compressed sensing acceleration and low-rank modeling with total-generalized-variation constraint to achieve metabolite imaging in two and three dimensions at 7 Tesla. The resulting images and volumes reveal highly detailed distributions that are specific to each metabolite and follow the underlying brain anatomy. The MRSI method was validated in a high-resolution phantom containing fine metabolite structures, and in five healthy volunteers. This new application of compressed sensing acceleration paves the way for high-resolution MRSI in clinical setting with acquisition times of 5 min for 2D MRSI at 2.5 mm and of 20 min for 3D MRSI at 3.3 mm isotropic.
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Affiliation(s)
- Antoine Klauser
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Department of Radiology and Medical Informatics, University of Geneva, Switzerland; Center for Biomedical Imaging (CIBM), Geneva, Switzerland.
| | - Bernhard Strasser
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Bijaya Thapa
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Francois Lazeyras
- Department of Radiology and Medical Informatics, University of Geneva, Switzerland; Center for Biomedical Imaging (CIBM), Geneva, Switzerland
| | - Ovidiu Andronesi
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
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7
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Pan JW, Antony A, Tal A, Yushmanov V, Fong J, Richardson M, Schirda C, Bagic A, Gonen O, Hetherington HP. MR spectroscopic imaging at 3 T and outcomes in surgical epilepsy. NMR IN BIOMEDICINE 2021; 34:e4492. [PMID: 33751687 PMCID: PMC8122073 DOI: 10.1002/nbm.4492] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 01/23/2021] [Indexed: 05/09/2023]
Abstract
For the spectroscopic assessment of brain disorders that require large-volume coverage, the requirements of RF performance and field homogeneity are high. For epilepsy, this is also challenging given the inter-patient variation in location, severity and subtlety of anatomical identification and its tendency to involve the temporal region. We apply a targeted method to examine the utility of large-volume MR spectroscopic imaging (MRSI) in surgical epilepsy patients, implementing a two-step acquisition, comprised of a 3D acquisition to cover the fronto-parietal regions, and a contiguous parallel two-slice Hadamard-encoded acquisition to cover the temporal-occipital region, both with TR /TE = 2000/40 ms and matched acquisition times. With restricted (static, first/second-order) B0 shimming in their respective regions, the Cramér-Rao lower bounds for creatine from the temporal lobe two-slice Hadamard and frontal-parietal 3D acquisition are 8.1 ± 2.2% and 6.3 ± 1.9% respectively. The datasets are combined to provide a total 60 mm axial coverage over the frontal, parietal and superior temporal to middle temporal-occipital regions. We applied these acquisitions at a nominal 400 mm3 voxel resolution in n = 27 pre-surgical epilepsy patients and n = 20 controls. In controls, 86.6 ± 3.2% voxels with at least 50% tissue (white + gray matter, excluding CSF) survived spectral quality inclusion criteria. Since all patients were clinically followed for at least 1 year after surgery, seizure frequency outcome was available for all. The MRSI measurements of the total fractional metabolic dysfunction (characterized by the Cr/NAA metric) in FreeSurfer MRI gray matter segmented regions, in the patients compared with the controls, exhibited a significant Spearman correlation with post-surgical outcome. This finding suggests that a larger burden of metabolic dysfunction is seen in patients with poorer post-surgical seizure control.
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Affiliation(s)
- Jullie W Pan
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Arun Antony
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Assaf Tal
- Department of Chemical and Biological Physics, Weizmann Institute, Rehovot, Israel
| | - Victor Yushmanov
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Joanna Fong
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Mark Richardson
- Department of Neurosurgery, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Claud Schirda
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Anto Bagic
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Oded Gonen
- Department of Radiology, New York University, New York, New York
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Tal A, Zhao T, Schirda C, Hetherington HP, Pan JW, Gonen O. Fast, regional three-dimensional hybrid (1D-Hadamard 2D-rosette) proton MR spectroscopic imaging in the human temporal lobes. NMR IN BIOMEDICINE 2021; 34:e4507. [PMID: 33754420 PMCID: PMC8122085 DOI: 10.1002/nbm.4507] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 02/03/2021] [Accepted: 02/25/2021] [Indexed: 05/05/2023]
Abstract
1 H-MRSI is commonly performed with gradient phase encoding, due to its simplicity and minimal radio frequency (RF) heating (specific absorption rate). Its two well-known main problems-(i) "voxel bleed" due to the intrinsic point-spread function, and (ii) chemical shift displacement error (CSDE) when slice-selective RF pulses are used, which worsens with increasing volume of interest (VOI) size-have long become accepted as unavoidable. Both problems can be mitigated with Hadamard multislice RF encoding. This is demonstrated and quantified with numerical simulations, in a multislice phantom and in five healthy young adult volunteers at 3 T, targeting a 2-cm thick temporal lobe VOI through the bilateral hippocampus. This frequently targeted region (e.g. in epilepsy and Alzheimer's disease) is subject to strong, 1-2 ppm.cm-1 regional B0, susceptibility gradients that can dramatically reduce the signal-to-noise ratio (SNR) and water suppression effectiveness. The chemical shift imaging (CSI) sequence used a 3-ms Shinnar-Le Roux (SLR) 90° RF pulse, acquiring eight steps in the slice direction. The Hadamard sequence acquired two overlapping slices using the same SLR 90° pulses, under twofold stronger gradients that proportionally halved the CSDE. Both sequences used 2D 20 × 20 rosette spectroscopic imaging (RSI) for in-plane spatial localization and both used RF and gradient performance characteristics that are easily met by all modern MRI instruments. The results show that Hadamard spectroscopic imaging (HSI) suffered dramatically less signal bleed within the VOI compared with CSI (<1% vs. approximately 26% in simulations; and 5%-8% vs. >50%) in a phantom specifically designed to test these effects. The voxels' SNR per unit volume per unit time was also 40% higher for HSI. In a group of five healthy volunteers, we show that HSI with in-plane 2D-RSI facilitates fast, 3D multivoxel encoding at submilliliter spatial resolution, over the bilateral human hippocampus, in under 10 min, with negligible CSDE, spectral and spatial contamination and more than 6% improved SNR per unit time per unit volume.
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Affiliation(s)
- Assaf Tal
- Department of Chemical and Biological Physics, The Weizmann Institute of Science, Rehovot, Israel
| | - Tiejun Zhao
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
- Siemens Medical Solutions USA Inc., Malvern, Pennsylvania, USA
| | - Claudiu Schirda
- Departments of Radiology and Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Hoby P. Hetherington
- Departments of Radiology and Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Jullie W. Pan
- Departments of Radiology and Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Oded Gonen
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
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9
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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: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [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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10
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MRSI vs CEST MRI to understand tomato metabolism in ripening fruit: is there a better contrast? Anal Bioanal Chem 2021; 413:1251-1257. [PMID: 33404743 DOI: 10.1007/s00216-020-03101-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Revised: 11/03/2020] [Accepted: 11/26/2020] [Indexed: 12/18/2022]
Abstract
Besides structural information, magnetic resonance imaging (MRI) is crucial to reveal the presence and gradients of metabolites in organs constituted of several tissues. In plant science, such knowledge is key to better understand fruit development and metabolism. Routine methods based on fixation for cytological studies or dissection for metabolite measurements induce biases and plant sample destruction. Magnetic resonance spectroscopy imaging (MSRI) leads to one NMR spectrum per pixel while chemical exchange saturation transfer (CEST) MRI allows mapping metabolites having exchangeable protons. As both methods present different advantages and drawbacks, we compared them to map metabolites in ripe tomato fruits. We demonstrated that MRSI was difficult to interpret due to large spatial chemical shift variations while CEST MRI produced promising image mapping of the main carbohydrates and amino acids. It showed that glucose/fructose was mostly located in the locular tissue, whereas glutamate/glutamine/GABA was found inside the columella.Graphical abstract.
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11
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Sharma AA, Nenert R, Mueller C, Maudsley AA, Younger JW, Szaflarski JP. Repeatability and Reproducibility of in-vivo Brain Temperature Measurements. Front Hum Neurosci 2020; 14:598435. [PMID: 33424566 PMCID: PMC7785722 DOI: 10.3389/fnhum.2020.598435] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Accepted: 11/30/2020] [Indexed: 12/11/2022] Open
Abstract
Background: Magnetic resonance spectroscopic imaging (MRSI) is a neuroimaging technique that may be useful for non-invasive mapping of brain temperature (i.e., thermometry) over a large brain volume. To date, intra-subject reproducibility of MRSI-based brain temperature (MRSI-t) has not been investigated. The objective of this repeated measures MRSI-t study was to establish intra-subject reproducibility and repeatability of brain temperature, as well as typical brain temperature range. Methods: Healthy participants aged 23-46 years (N = 18; 7 females) were scanned at two time points ~12-weeks apart. Volumetric MRSI data were processed by reconstructing metabolite and water images using parametric spectral analysis. Brain temperature was derived using the frequency difference between water and creatine (TCRE) for 47 regions of interest (ROIs) delineated by the modified Automated Anatomical Labeling (AAL) atlas. Reproducibility was measured using the coefficient of variation for repeated measures (COVrep), and repeatability was determined using the standard error of measurement (SEM). For each region, the upper and lower bounds of Minimal Detectable Change (MDC) were established to characterize the typical range of TCRE values. Results: The mean global brain temperature over all subjects was 37.2°C with spatial variations across ROIs. There was a significant main effect for time [F (1, 1,591) = 37.0, p < 0.0001] and for brain region [F (46, 1,591) = 2.66, p < 0.0001]. The time*brain region interaction was not significant [F (46, 1,591) = 0.80, p = 0.83]. Participants' TCRE was stable for each ROI across both time points, with ROIs' COVrep ranging from 0.81 to 3.08% (mean COVrep = 1.92%); majority of ROIs had a COVrep <2.0%. Conclusions: Brain temperature measurements were highly consistent between both time points, indicating high reproducibility and repeatability of MRSI-t. MRSI-t may be a promising diagnostic, prognostic, and therapeutic tool for non-invasively monitoring brain temperature changes in health and disease. However, further studies of healthy participants with larger sample size(s) and numerous repeated acquisitions are imperative for establishing a reference range of typical brain TCRE, as well as the threshold above which TCRE is likely pathological.
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Affiliation(s)
- Ayushe A. Sharma
- Department of Psychology, University of Alabama at Birmingham (UAB), Birmingham, AL, United States
- Department of Neurobiology, University of Alabama at Birmingham (UAB), Birmingham, AL, United States
- University of Alabama at Birmingham Epilepsy Center (UABEC), Birmingham, AL, United States
| | - Rodolphe Nenert
- University of Alabama at Birmingham Epilepsy Center (UABEC), Birmingham, AL, United States
- Department of Neurology, University of Alabama at Birmingham (UAB), Birmingham, AL, United States
| | - Christina Mueller
- Department of Psychology, University of Alabama at Birmingham (UAB), Birmingham, AL, United States
| | - Andrew A. Maudsley
- Department of Radiology, Miller School of Medicine, University of Miami, Miami, FL, United States
| | - Jarred W. Younger
- Department of Psychology, University of Alabama at Birmingham (UAB), Birmingham, AL, United States
| | - Jerzy P. Szaflarski
- Department of Neurobiology, University of Alabama at Birmingham (UAB), Birmingham, AL, United States
- University of Alabama at Birmingham Epilepsy Center (UABEC), Birmingham, AL, United States
- Department of Neurology, University of Alabama at Birmingham (UAB), Birmingham, AL, United States
- Department of Neurosurgery, University of Alabama at Birmingham (UAB), Birmingham, AL, United States
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12
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Zhang Y, Taub E, Mueller C, Younger J, Uswatte G, DeRamus TP, Knight DC. Reproducibility of whole-brain temperature mapping and metabolite quantification using proton magnetic resonance spectroscopy. NMR IN BIOMEDICINE 2020; 33:e4313. [PMID: 32348017 DOI: 10.1002/nbm.4313] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2019] [Revised: 03/24/2020] [Accepted: 03/25/2020] [Indexed: 06/11/2023]
Abstract
Assessing brain temperature can provide important information about disease processes (e.g., stroke, trauma) and therapeutic effects (e.g., cerebral hypothermia treatment). Whole-brain magnetic resonance spectroscopic imaging (WB-MRSI) is increasingly used to quantify brain metabolites across the entire brain. However, its feasibility and reliability for estimating brain temperature needs further validation. Therefore, the present study evaluates the reproducibility of WB-MRSI for temperature mapping as well as metabolite quantification across the whole brain in healthy volunteers. Ten healthy adults were scanned on three occasions 1 week apart. Brain temperature, along with four commonly assessed brain metabolites-total N-acetyl-aspartate (tNAA), total creatine (tCr), total choline (tCho) and myo-inositol (mI)-were measured from WB-MRSI data. Reproducibility was evaluated using the coefficient of variation (CV). The measured mean (range) of the intra-subject CVs was 0.9% (0.6%-1.6%) for brain temperature mapping, and 4.7% (2.5%-15.7%), 6.4% (2.4%-18.9%) and 14.2% (4.4%-52.6%) for tNAA, tCho and mI, respectively, with reference to tCr. Consistently larger variability was found when using H2 O as the reference for metabolite quantifications: 7.8% (3.3%-17.8%), 7.8% (3.1%-18.0%), 9.8% (3.7%-31.0%) and 17.0% (5.9%-54.0%) for tNAA, tCr, tCho and mI, respectively. Further, the larger the brain region (indicated by a greater number of voxels within that region), the better the reproducibility for both temperature and metabolite estimates. Our results demonstrate good reproducibility of whole-brain temperature and metabolite measurements using the WB-MRSI technique.
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Affiliation(s)
- Yue Zhang
- Department of Psychology, University of Alabama at Birmingham, Alabama, US
- Department of Neurosurgery and Core for Advanced MRI, Baylor College of Medicine, Houston, Texas, US
| | - Edward Taub
- Department of Psychology, University of Alabama at Birmingham, Alabama, US
| | - Christina Mueller
- Department of Psychology, University of Alabama at Birmingham, Alabama, US
| | - Jarred Younger
- Department of Psychology, University of Alabama at Birmingham, Alabama, US
| | - Gitendra Uswatte
- Department of Psychology, University of Alabama at Birmingham, Alabama, US
- Department of Physical Therapy, University of Alabama at Birmingham, Alabama, US
| | - Thomas Patrick DeRamus
- TReNDs Center for Translational Research in Neuroimaging and Data Science, Georgia, US
- Department of Psychology, Georgia State University, Georgia, US
| | - David C Knight
- Department of Psychology, University of Alabama at Birmingham, Alabama, US
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13
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Moser P, Bogner W, Hingerl L, Heckova E, Hangel G, Motyka S, Trattnig S, Strasser B. Non-Cartesian GRAPPA and coil combination using interleaved calibration data - application to concentric-ring MRSI of the human brain at 7T. Magn Reson Med 2019; 82:1587-1603. [PMID: 31183893 PMCID: PMC6772100 DOI: 10.1002/mrm.27822] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Revised: 04/29/2019] [Accepted: 05/01/2019] [Indexed: 12/12/2022]
Abstract
PURPOSE Proton MR spectroscopic imaging (MRSI) benefits from B0 ≥ 7T and multichannel receive coils, promising substantial resolution improvements. However, MRSI acquisition with high spatial resolution requires efficient acceleration and coil combination. To speed up the already-fast sampling via concentric rings, we implemented additional, non-Cartesian, hybrid through-time/through-k-space (tt/tk)-generalized autocalibrating partially parallel acquisition (GRAPPA). A new multipurpose interleaved calibration scan (interleaved MUSICAL) acquires reference data for both coil combination and PI. This renders the reconstruction process (especially PI) less sensitive to instabilities. METHODS Six healthy volunteers were scanned at 7T. Three calibration datasets for coil combination and PI were recorded: a) iMUSICAL, b) static MUSICAL as prescan, c) moved MUSICAL as prescan with misaligned head position. The coil combination performance, including motion sensitivity, of iMUSICAL was compared to MUSICAL for single-slice free induction decay (FID)-MRSI. Through-time/through-k-space-GRAPPA with constant/variable-density undersampling was evaluated on the same data, comparing the three calibration datasets. Additionally, the proposed method was successfully applied to 3D whole-brain FID-MRSI. RESULTS Using iMUSICAL for coil combination yielded the highest signal-to-noise ratio (SNR) (+9%) and lowest Cramer-Rao lower bounds (CRLBs) (-6%) compared to both MUSICAL approaches, with similar metabolic map quality. Also, excellent mean g-factors of 1.07 and low residual lipid aliasing were obtained when using iMUSICAL as calibration data for two-fold, variable-density undersampling, while significantly degraded metabolic maps were obtained using the misaligned MUSICAL calibration data. CONCLUSION Through-time/through-k-space-GRAPPA can accelerate already time-efficient non-Cartesian spatial-spectral 2D/3D-MRSI encoding even further. Particularly promising results have been achieved using iMUSICAL as a robust, interleaved multipurpose calibration for MRSI reconstruction, without extra calibration prescan.
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Affiliation(s)
- Philipp Moser
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Lukas Hingerl
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Eva Heckova
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Gilbert Hangel
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Stanislav Motyka
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Siegfried Trattnig
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria.,Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria
| | - Bernhard Strasser
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria.,Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
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14
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Vidya Shankar R, Chang JC, Hu HH, Kodibagkar VD. Fast data acquisition techniques in magnetic resonance spectroscopic imaging. NMR IN BIOMEDICINE 2019; 32:e4046. [PMID: 30637822 DOI: 10.1002/nbm.4046] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2015] [Revised: 10/30/2018] [Accepted: 10/31/2018] [Indexed: 06/09/2023]
Abstract
Magnetic resonance spectroscopic imaging (MRSI) is an important technique for assessing the spatial variation of metabolites in vivo. The long scan times in MRSI limit clinical applicability due to patient discomfort, increased costs, motion artifacts, and limited protocol flexibility. Faster acquisition strategies can address these limitations and could potentially facilitate increased adoption of MRSI into routine clinical protocols with minimal addition to the current anatomical and functional acquisition protocols in terms of imaging time. Not surprisingly, a lot of effort has been devoted to the development of faster MRSI techniques that aim to capture the same underlying metabolic information (relative metabolite peak areas and spatial distribution) as obtained by conventional MRSI, in greatly reduced time. The gain in imaging time results, in some cases, in a loss of signal-to-noise ratio and/or in spatial and spectral blurring. This review examines the current techniques and advances in fast MRSI in two and three spatial dimensions and their applications. This review categorizes the acceleration techniques according to their strategy for acquisition of the k-space. Techniques such as fast/turbo-spin echo MRSI, echo-planar spectroscopic imaging, and non-Cartesian MRSI effectively cover the full k-space in a more efficient manner per TR . On the other hand, techniques such as parallel imaging and compressed sensing acquire fewer k-space points and employ advanced reconstruction algorithms to recreate the spatial-spectral information, which maintains statistical fidelity in test conditions (ie no statistically significant differences on voxel-wise comparisions) with the fully sampled data. The advantages and limitations of each state-of-the-art technique are reviewed in detail, concluding with a note on future directions and challenges in the field of fast spectroscopic imaging.
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Affiliation(s)
- Rohini Vidya Shankar
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - John C Chang
- Banner M D Anderson Cancer Center, Gilbert, AZ, USA
- School for Engineering of Matter, Transport and Energy, Arizona State University, Tempe, AZ, USA
| | - Houchun H Hu
- Department of Radiology and Medical Imaging, Phoenix Children's Hospital, Phoenix, AZ, USA
| | - Vikram D Kodibagkar
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA
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15
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Isobe T, Tadano K, Takakura Y, Sato E. [5. A Path to the Metabolite Quantification with MR Spectroscopy]. Nihon Hoshasen Gijutsu Gakkai Zasshi 2019; 75:832-838. [PMID: 31434856 DOI: 10.6009/jjrt.2019_jsrt_75.8.832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Affiliation(s)
- Tomonori Isobe
- Faculty of Medicine, University of Tsukuba
- Graduate School of Comprehensive Human Sciences,University of Tsukuba
| | - Kiichi Tadano
- Graduate School of Comprehensive Human Sciences,University of Tsukuba
- Faculty of Health Sciences, Kyorin University
| | - Yu Takakura
- Graduate School of Comprehensive Human Sciences,University of Tsukuba
- Department of Radiology, Toride Kitasoma Health Medical Center Medical Association Hospital
| | - Eisuke Sato
- Faculty of Health Science, Juntendo University
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16
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Klauser A, Courvoisier S, Kasten J, Kocher M, Guerquin-Kern M, Van De Ville D, Lazeyras F. Fast high-resolution brain metabolite mapping on a clinical 3T MRI by accelerated 1 H-FID-MRSI and low-rank constrained reconstruction. Magn Reson Med 2018; 81:2841-2857. [PMID: 30565314 DOI: 10.1002/mrm.27623] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Revised: 10/18/2018] [Accepted: 11/12/2018] [Indexed: 12/18/2022]
Abstract
PURPOSE Epitomizing the advantages of ultra short echo time and no chemical shift displacement error, high-resolution-free induction decay magnetic resonance spectroscopic imaging (FID-MRSI) sequences have proven to be highly effective in providing unbiased characterizations of metabolite distributions. However, its merits are often overshadowed in high-resolution settings by reduced signal-to-noise ratios resulting from the smaller voxel volumes procured by extensive phase encoding and the related acquisition times. METHODS To address these limitations, we here propose an acquisition and reconstruction scheme that offers both implicit dataset denoising and acquisition acceleration. Specifically, a slice selective high-resolution FID-MRSI sequence was implemented. Spectroscopic datasets were processed to remove fat contamination, and then reconstructed using a total generalized variation (TGV) regularized low-rank model. We further measured reconstruction performance for random undersampled data to assess feasibility of a compressed-sensing SENSE acceleration scheme. Performance of the lipid suppression was assessed using an ad hoc phantom, while that of the low-rank TGV reconstruction model was benchmarked using simulated MRSI data. To assess real-world performance, 2D FID-MRSI acquisitions of the brain in healthy volunteers were reconstructed using the proposed framework. RESULTS Results from the phantom and simulated data demonstrate that skull lipid contamination is effectively removed and that data reconstruction quality is improved with the low-rank TGV model. Also, we demonstrated that the presented acquisition and reconstruction methods are compatible with a compressed-sensing SENSE acceleration scheme. CONCLUSIONS An original reconstruction pipeline for 2D 1 H-FID-MRSI datasets was presented that places high-resolution metabolite mapping on 3T MR scanners within clinically feasible limits.
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Affiliation(s)
- Antoine Klauser
- Department of Radiology and Medical, Informatics, University of Geneva, Geneva, Switzerland
| | - Sebastien Courvoisier
- Department of Radiology and Medical, Informatics, University of Geneva, Geneva, Switzerland
| | - Jeffrey Kasten
- Department of Radiology and Medical, Informatics, University of Geneva, Geneva, Switzerland
| | - Michel Kocher
- Department of Radiology and Medical, Informatics, University of Geneva, Geneva, Switzerland
| | | | - Dimitri Van De Ville
- Department of Radiology and Medical, Informatics, University of Geneva, Geneva, Switzerland.,Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Francois Lazeyras
- Department of Radiology and Medical, Informatics, University of Geneva, Geneva, Switzerland
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17
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Hingerl L, Bogner W, Moser P, Považan M, Hangel G, Heckova E, Gruber S, Trattnig S, Strasser B. Density-weighted concentric circle trajectories for high resolution brain magnetic resonance spectroscopic imaging at 7T. Magn Reson Med 2018; 79:2874-2885. [PMID: 29106742 PMCID: PMC5873433 DOI: 10.1002/mrm.26987] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2017] [Revised: 09/09/2017] [Accepted: 10/07/2017] [Indexed: 12/18/2022]
Abstract
PURPOSE Full-slice magnetic resonance spectroscopic imaging at ≥7 T is especially vulnerable to lipid contaminations arising from regions close to the skull. This contamination can be mitigated by improving the point spread function via higher spatial resolution sampling and k-space filtering, but this prolongs scan times and reduces the signal-to-noise ratio (SNR) efficiency. Currently applied parallel imaging methods accelerate magnetic resonance spectroscopic imaging scans at 7T, but increase lipid artifacts and lower SNR-efficiency further. In this study, we propose an SNR-efficient spatial-spectral sampling scheme using concentric circle echo planar trajectories (CONCEPT), which was adapted to intrinsically acquire a Hamming-weighted k-space, thus termed density-weighted-CONCEPT. This minimizes voxel bleeding, while preserving an optimal SNR. THEORY AND METHODS Trajectories were theoretically derived and verified in phantoms as well as in the human brain via measurements of five volunteers (single-slice, field-of-view 220 × 220 mm2 , matrix 64 × 64, scan time 6 min) with free induction decay magnetic resonance spectroscopic imaging. Density-weighted-CONCEPT was compared to (a) the originally proposed CONCEPT with equidistant circles (here termed e-CONCEPT), (b) elliptical phase-encoding, and (c) 5-fold Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration accelerated elliptical phase-encoding. RESULTS By intrinsically sampling a Hamming-weighted k-space, density-weighted-CONCEPT removed Gibbs-ringing artifacts and had in vivo +9.5%, +24.4%, and +39.7% higher SNR than e-CONCEPT, elliptical phase-encoding, and the Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration accelerated elliptical phase-encoding (all P < 0.05), respectively, which lead to improved metabolic maps. CONCLUSION Density-weighted-CONCEPT provides clinically attractive full-slice high-resolution magnetic resonance spectroscopic imaging with optimal SNR at 7T. Magn Reson Med 79:2874-2885, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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Affiliation(s)
- Lukas Hingerl
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Wolfgang Bogner
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Christian Doppler Laboratory for Clinical Molecular MR ImagingMedical University of ViennaViennaAustria
| | - Philipp Moser
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Michal Považan
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Gilbert Hangel
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Eva Heckova
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Stephan Gruber
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Siegfried Trattnig
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Christian Doppler Laboratory for Clinical Molecular MR ImagingMedical University of ViennaViennaAustria
| | - Bernhard Strasser
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
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18
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Nassirpour S, Chang P, Avdievitch N, Henning A. Compressed sensing for high-resolution nonlipid suppressed 1 H FID MRSI of the human brain at 9.4T. Magn Reson Med 2018; 80:2311-2325. [PMID: 29707804 DOI: 10.1002/mrm.27225] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2017] [Revised: 03/06/2018] [Accepted: 03/26/2018] [Indexed: 12/17/2022]
Abstract
PURPOSE The aim of this study was to apply compressed sensing to accelerate the acquisition of high resolution metabolite maps of the human brain using a nonlipid suppressed ultra-short TR and TE 1 H FID MRSI sequence at 9.4T. METHODS X-t sparse compressed sensing reconstruction was optimized for nonlipid suppressed 1 H FID MRSI data. Coil-by-coil x-t sparse reconstruction was compared with SENSE x-t sparse and low rank reconstruction. The effect of matrix size and spatial resolution on the achievable acceleration factor was studied. Finally, in vivo metabolite maps with different acceleration factors of 2, 4, 5, and 10 were acquired and compared. RESULTS Coil-by-coil x-t sparse compressed sensing reconstruction was not able to reliably recover the nonlipid suppressed data, rather a combination of parallel and sparse reconstruction was necessary (SENSE x-t sparse). For acceleration factors of up to 5, both the low-rank and the compressed sensing methods were able to reconstruct the data comparably well (root mean squared errors [RMSEs] ≤ 10.5% for Cre). However, the reconstruction time of the low rank algorithm was drastically longer than compressed sensing. Using the optimized compressed sensing reconstruction, acceleration factors of 4 or 5 could be reached for the MRSI data with a matrix size of 64 × 64. For lower spatial resolutions, an acceleration factor of up to R∼4 was successfully achieved. CONCLUSION By tailoring the reconstruction scheme to the nonlipid suppressed data through parameter optimization and performance evaluation, we present high resolution (97 µL voxel size) accelerated in vivo metabolite maps of the human brain acquired at 9.4T within scan times of 3 to 3.75 min.
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Affiliation(s)
- Sahar Nassirpour
- Max Planck Institute for Biological Cybernetics, Tuebingen, Germany.,IMPRS for Cognitive and Systems Neuroscience, Eberhard-Karls University of Tuebingen, Germany
| | - Paul Chang
- Max Planck Institute for Biological Cybernetics, Tuebingen, Germany.,IMPRS for Cognitive and Systems Neuroscience, Eberhard-Karls University of Tuebingen, Germany
| | - Nikolai Avdievitch
- Max Planck Institute for Biological Cybernetics, Tuebingen, Germany.,Institute of Physics, Ernst-Moritz-Arndt University Greifswald, Greifswald, Germany
| | - Anke Henning
- Max Planck Institute for Biological Cybernetics, Tuebingen, Germany.,Institute of Physics, Ernst-Moritz-Arndt University Greifswald, Greifswald, Germany
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19
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Zhang Y, Taub E, Salibi N, Uswatte G, Maudsley AA, Sheriff S, Womble B, Mark VW, Knight DC. Comparison of reproducibility of single voxel spectroscopy and whole-brain magnetic resonance spectroscopy imaging at 3T. NMR IN BIOMEDICINE 2018; 31:e3898. [PMID: 29436038 PMCID: PMC6291009 DOI: 10.1002/nbm.3898] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2017] [Revised: 12/11/2017] [Accepted: 12/26/2017] [Indexed: 05/09/2023]
Abstract
To date, single voxel spectroscopy (SVS) is the most commonly used MRS technique. SVS is relatively easy to use and provides automated and immediate access to the resulting spectra. However, it is also limited in spatial coverage. A new and very promising MRS technique allows for whole-brain MR spectroscopic imaging (WB-MRSI) with much improved spatial resolution. Establishing the reproducibility of data obtained using SVS and WB-MRSI is an important first step for using these techniques to evaluate longitudinal changes in metabolite concentration. The purpose of this study was to assess and directly compare the reproducibility of metabolite quantification at 3T using SVS and WB-MRSI in 'hand-knob' areas of motor cortices and hippocampi in healthy volunteers. Ten healthy adults were scanned using both SVS and WB-MRSI on three occasions one week apart. N-acetyl aspartate (NAA), creatine (Cr), choline (Cho) and myo-inositol (mI) were quantified using SVS and WB-MRSI with reference to both Cr and H2 O. The reproducibility of each technique was evaluated using the coefficient of variation (CV), and the correspondence between the two techniques was assessed using Pearson correlation analysis. The measured mean (range) intra-subject CVs for SVS were 5.90 (2.65-10.66)% for metabolites (i.e. NAA, Cho, mI) relative to Cr, and 8.46 (4.21-21.07)% for metabolites (NAA, Cr, Cho, mI) relative to H2 O. The mean (range) CVs for WB-MRSI were 7.56 (2.78-11.41)% for metabolites relative to Cr, and 7.79 (4.57-14.11)% for metabolites relative to H2 O. Significant positive correlations were observed between metabolites quantified using SVS and WB-MRSI techniques when the Cr but not H2 O reference was used. The results demonstrate that reproducibilities of SVS and WB-MRSI are similar for quantifying the four major metabolites (NAA, Cr, Cho, mI); both SVS and WB-MRSI exhibited good reproducibility. Our findings add reference information for choosing the appropriate 1 H-MRS technique in future studies.
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Affiliation(s)
- Yue Zhang
- Department of Psychology, University of Alabama at Birmingham, AL, USA
| | - Edward Taub
- Department of Psychology, University of Alabama at Birmingham, AL, USA
| | | | - Gitendra Uswatte
- Department of Psychology, University of Alabama at Birmingham, AL, USA
- Department of Physical Therapy, University of Alabama at Birmingham, AL, USA
| | | | | | - Brent Womble
- Department of Psychology, University of Alabama at Birmingham, AL, USA
| | - Victor W Mark
- Department of Psychology, University of Alabama at Birmingham, AL, USA
- Department of Physical Medicine and Rehabilitation, University of Alabama at Birmingham, AL, USA
- Department of Neurology, University of Alabama at Birmingham, AL, USA
| | - David C Knight
- Department of Psychology, University of Alabama at Birmingham, AL, USA
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20
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Hangel G, Strasser B, Považan M, Heckova E, Hingerl L, Boubela R, Gruber S, Trattnig S, Bogner W. Ultra-high resolution brain metabolite mapping at 7 T by short-TR Hadamard-encoded FID-MRSI. Neuroimage 2018; 168:199-210. [DOI: 10.1016/j.neuroimage.2016.10.043] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2016] [Revised: 10/24/2016] [Accepted: 10/26/2016] [Indexed: 10/20/2022] Open
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21
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Non-invasive imaging modalities to study neurodegenerative diseases of aging brain. J Chem Neuroanat 2018; 95:54-69. [PMID: 29474853 DOI: 10.1016/j.jchemneu.2018.02.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2017] [Revised: 02/16/2018] [Accepted: 02/16/2018] [Indexed: 12/13/2022]
Abstract
The aim of this article is to highlight current approaches for imaging elderly brain, indispensable for cognitive neuroscience research with emphasis on the basic physical principles of various non-invasive neuroimaging techniques. The first part of this article presents a quick overview of the primary non-invasive neuroimaging modalities used by cognitive neuroscientists such as transcranial magnetic stimulation (TMS), transcranial electrical stimulation (tES), electroencephalography (EEG), magnetoencephalography (MEG), single photon emission computed tomography (SPECT), positron emission tomography (PET), magnetic resonance spectroscopic imaging (MRSI), Profusion imaging, functional magnetic resonance imaging (fMRI), near infrared spectroscopy (NIRS) and diffusion tensor imaging (DTI) along with tractography and connectomics. The second part provides a comprehensive overview of different multimodality imaging techniques for various cognitive neuroscience studies of aging brain.
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22
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Raschke F, Noeske R, Dineen RA, Auer DP. Measuring Cerebral and Cerebellar Glutathione in Children Using 1H MEGA-PRESS MRS. AJNR Am J Neuroradiol 2017; 39:375-379. [PMID: 29242361 DOI: 10.3174/ajnr.a5457] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2017] [Accepted: 09/13/2017] [Indexed: 12/29/2022]
Abstract
BACKGROUND AND PURPOSE Glutathione is an important antioxidant in the human brain and therefore of interest in neurodegenerative disorders. The purpose of this study was to investigate the feasibility of measuring glutathione in healthy nonsedated children by using the 1H Mescher-Garwood point-resolved spectroscopy (MEGA-PRESS) sequence at 3T and to compare glutathione levels between the medial parietal gray matter and the cerebellum. MATERIALS AND METHODS Glutathione was measured using MEGA-PRESS MRS (TR = 1.8 seconds, TE = 131 ms) in the parietal gray matter (35 × 25 × 20 mm3) of 6 healthy children (10.0 ± 2.4 years of age; range, 7-14 years; 3 males) and in the cerebellum of 11 healthy children (12.0 ± 2.7 years of age; range, 7-16 years; 6 males). A postprocessing pipeline was developed to account for frequency and phase variations in the edited ON and nonedited OFF spectra. Metabolites were quantified with LCModel and reported both as ratios and water-scaled values. Glutathione was quantified in the ON-OFF spectra, whereas total NAA, total Cho, total Cr, mIns, Glx, and taurine were quantified in the OFF spectra. RESULTS We found significantly higher glutathione, total Cho, total Cr, mIns, and taurine in the cerebellum (P < .01). Glx and total NAA were significantly higher in the parietal gray matter (P < .01). There was no significant difference in glutathione/total Cr (P = .93) between parietal gray matter and cerebellum. CONCLUSIONS We demonstrated that glutathione measurement in nonsedated children is feasible. We found significantly higher glutathione in the cerebellum compared with the parietal gray matter. Metabolite differences between the parietal gray matter and cerebellum agree with published MRS data in adults.
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Affiliation(s)
- F Raschke
- From the National Center for Tumor Diseases (F.R.), Partner Site Dresden, Dresden, Germany.,German Cancer Research Center (F.R.), Heidelberg, Germany.,Medical Faculty and University Hospital Carl Gustav Carus (F.R.), Technische Universität Dresden, Dresden, Germany.,Helmholtz Association/Helmholtz Zentrum Dresden Rossendorf (F.R.), Dresden, Germany
| | - R Noeske
- GE Healthcare (R.N.), Applied Science Lab Europe, Berlin, Germany
| | - R A Dineen
- Sir Peter Mansfield Imaging Centre (R.A.D., D.P.A.), University of Nottingham, Nottingham, UK .,Radiological Sciences, (R.A.D., D.P.A.), Division of Clinical Neuroscience, School of Medicine, University of Nottingham, Nottingham, UK.,National Institute for Health Research (R.A.D., D.P.A.), Nottingham Biomedical Research Centre, Nottingham, UK
| | - D P Auer
- Sir Peter Mansfield Imaging Centre (R.A.D., D.P.A.), University of Nottingham, Nottingham, UK.,Radiological Sciences, (R.A.D., D.P.A.), Division of Clinical Neuroscience, School of Medicine, University of Nottingham, Nottingham, UK.,National Institute for Health Research (R.A.D., D.P.A.), Nottingham Biomedical Research Centre, Nottingham, UK
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23
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Abstract
We have recently witnessed an explosion of large-scale initiatives and projects addressing mapping, modeling, simulation and atlasing of the human brain, including the BRAIN Initiative, the Human Brain Project, the Human Connectome Project (HCP), the Big Brain, the Blue Brain Project, the Allen Brain Atlas, the Brainnetome, among others. Besides these large and international initiatives, there are numerous mid-size and small brain atlas-related projects. My contribution to these global efforts has been to create adult human brain atlases in health and disease, and to develop atlas-based applications. For over two decades with my R&D lab I developed 35 brain atlases, licensed to 67 companies and made available in about 100 countries. This paper has two objectives. First, it provides an overview of the state of the art in brain atlasing. Second, as it is already 20 years from the release of our first brain atlas, I summarise my past and present efforts, share my experience in atlas creation, validation and commercialisation, compare with the state of the art, and propose future directions.
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Affiliation(s)
- Wieslaw L Nowinski
- John Paull II Center for Virtual Anatomy and Surgical Simulation, University of Cardinal Stefan Wyszynski in Warsaw, Poland
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24
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Donadieu M, Le Fur Y, Maarouf A, Gherib S, Ridley B, Pini L, Rapacchi S, Confort-Gouny S, Guye M, Schad LR, Maudsley AA, Pelletier J, Audoin B, Zaaraoui W, Ranjeva JP. Metabolic counterparts of sodium accumulation in multiple sclerosis: A whole brain 23Na-MRI and fast 1H-MRSI study. Mult Scler 2017; 25:39-47. [DOI: 10.1177/1352458517736146] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Background: Increase of brain total sodium concentrations (TSC) is present in multiple sclerosis (MS), but its pathological involvement has not been assessed yet. Objective: To determine in vivo the metabolic counterpart of brain sodium accumulation. Materials/methods: Whole brain 23Na-MR imaging and 3D-1H-EPSI data were collected in 21 relapsing-remitting multiple sclerosis (RRMS) patients and 20 volunteers. Metabolites and sodium levels were extracted from several regions of grey matter (GM), normal-appearing white matter (NAWM) and white matter (WM) T2 lesions. Metabolic and ionic levels expressed as Z-scores have been averaged over the different compartments and used to explain sodium accumulations through stepwise regression models. Results: MS patients showed significant 23Na accumulations with lower choline and glutamate–glutamine (Glx) levels in GM; 23Na accumulations with lower N-acetyl aspartate (NAA), Glx levels and higher Myo-Inositol (m-Ins) in NAWM; and higher 23Na, m-Ins levels with lower NAA in WM T2 lesions. Regression models showed associations of TSC increase with reduced NAA in GM, NAWM and T2 lesions, as well as higher total-creatine, and smaller decrease of m-Ins in T2 lesions. GM Glx levels were associated with clinical scores. Conclusion: Increase of TSC in RRMS is mainly related to neuronal mitochondrial dysfunction while dysfunction of neuro-glial interactions within GM is linked to clinical scores.
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Affiliation(s)
- Maxime Donadieu
- Aix-Marseille University, CNRS, CRMBM, APHM, Marseille, France/Timone University Hospital, CEMEREM, Marseille, France/Siemens Healthineers, Saint-Denis, France
| | - Yann Le Fur
- Aix-Marseille University, CNRS, CRMBM, APHM, Marseille, France/Timone University Hospital, CEMEREM, Marseille, France
| | - Adil Maarouf
- Aix-Marseille University, CNRS, CRMBM, APHM, Marseille, France/Timone University Hospital, CEMEREM, Marseille, France/APHM, Timone University Hospital, Department of Neurology, Marseille, FranceCNRS, CRMBM UMR 7339, Medical School of Marseille, Aix-Marseille University, Marseille, France/AP-HM, CHU Timone, Department of Imaging, CEMEREM, Marseille, France/AP-HM, CHU Timone, Pole de Neurosciences Cliniques, Department of Neurology, Marseille, France
| | - Soraya Gherib
- Aix-Marseille University, CNRS, CRMBM, APHM, Marseille, France/Timone University Hospital, CEMEREM, Marseille, France
| | - Ben Ridley
- Aix-Marseille University, CNRS, CRMBM, APHM, Marseille, France/Timone University Hospital, CEMEREM, Marseille, France
| | - Lauriane Pini
- Aix-Marseille University, CNRS, CRMBM, APHM, Marseille, France/Timone University Hospital, CEMEREM, Marseille, France
| | - Stanislas Rapacchi
- Aix-Marseille University, CNRS, CRMBM, APHM, Marseille, France/Timone University Hospital, CEMEREM, Marseille, France
| | - Sylviane Confort-Gouny
- Aix-Marseille University, CNRS, CRMBM, APHM, Marseille, France/Timone University Hospital, CEMEREM, Marseille, France
| | - Maxime Guye
- Aix-Marseille University, CNRS, CRMBM, APHM, Marseille, France/Timone University Hospital, CEMEREM, Marseille, France
| | - Lothar R Schad
- Computer Assisted Clinical Medicine, Mannheim University Hospital, Heidelberg University, Mannheim, Germany
| | - Andrew A Maudsley
- Department of Radiology, University of Miami School of Medicine, Miami, FL, USA
| | - Jean Pelletier
- Aix-Marseille University, CNRS, CRMBM, APHM, Marseille, France/Timone University Hospital, CEMEREM, Marseille, France/APHM, Timone University Hospital, Department of Neurology, Marseille, FranceCNRS, CRMBM UMR 7339, Medical School of Marseille, Aix-Marseille University, Marseille, France/AP-HM, CHU Timone, Department of Imaging, CEMEREM, Marseille, France/AP-HM, CHU Timone, Pole de Neurosciences Cliniques, Department of Neurology, Marseille, France
| | - Bertrand Audoin
- Aix-Marseille University, CNRS, CRMBM, APHM, Marseille, France/Timone University Hospital, CEMEREM, Marseille, France/APHM, Timone University Hospital, Department of Neurology, Marseille, FranceCNRS, CRMBM UMR 7339, Medical School of Marseille, Aix-Marseille University, Marseille, France/AP-HM, CHU Timone, Department of Imaging, CEMEREM, Marseille, France/AP-HM, CHU Timone, Pole de Neurosciences Cliniques, Department of Neurology, Marseille, France
| | - Wafaa Zaaraoui
- Aix-Marseille University, CNRS, CRMBM, APHM, Marseille, France/Timone University Hospital, CEMEREM, Marseille, France
| | - Jean-Philippe Ranjeva
- Aix-Marseille University, CNRS, CRMBM, APHM, Marseille, France/Timone University Hospital, CEMEREM, Marseille, France
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25
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DCE-MRI, DW-MRI, and MRS in Cancer: Challenges and Advantages of Implementing Qualitative and Quantitative Multi-parametric Imaging in the Clinic. Top Magn Reson Imaging 2017; 25:245-254. [PMID: 27748710 PMCID: PMC5081190 DOI: 10.1097/rmr.0000000000000103] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Multi-parametric magnetic resonance imaging (mpMRI) offers a unique insight into tumor biology by combining functional MRI techniques that inform on cellularity (diffusion-weighted MRI), vascular properties (dynamic contrast-enhanced MRI), and metabolites (magnetic resonance spectroscopy) and has scope to provide valuable information for prognostication and response assessment. Challenges in the application of mpMRI in the clinic include the technical considerations in acquiring good quality functional MRI data, development of robust techniques for analysis, and clinical interpretation of the results. This article summarizes the technical challenges in acquisition and analysis of multi-parametric MRI data before reviewing the key applications of multi-parametric MRI in clinical research and practice.
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26
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Nikolaidis A, Baniqued PL, Kranz MB, Scavuzzo CJ, Barbey AK, Kramer AF, Larsen RJ. Multivariate Associations of Fluid Intelligence and NAA. Cereb Cortex 2017; 27:2607-2616. [PMID: 27005991 DOI: 10.1093/cercor/bhw070] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Understanding the neural and metabolic correlates of fluid intelligence not only aids scientists in characterizing cognitive processes involved in intelligence, but it also offers insight into intervention methods to improve fluid intelligence. Here we use magnetic resonance spectroscopic imaging (MRSI) to measure N-acetyl aspartate (NAA), a biochemical marker of neural energy production and efficiency. We use principal components analysis (PCA) to examine how the distribution of NAA in the frontal and parietal lobes relates to fluid intelligence. We find that a left lateralized frontal-parietal component predicts fluid intelligence, and it does so independently of brain size, another significant predictor of fluid intelligence. These results suggest that the left motor regions play a key role in the visualization and planning necessary for spatial cognition and reasoning, and we discuss these findings in the context of the Parieto-Frontal Integration Theory of intelligence.
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Affiliation(s)
- Aki Nikolaidis
- Beckman Institute for Advanced Science and Technology.,Neuroscience Program and
| | - Pauline L Baniqued
- Beckman Institute for Advanced Science and Technology.,Psychology Department, University of Illinois at Urbana-Champaign, Urbana, IL, USA.,Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Michael B Kranz
- Beckman Institute for Advanced Science and Technology.,Psychology Department, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Claire J Scavuzzo
- Neuroscience Program and.,Psychology Department, University of Alberta, Edmonton, Alberta, Canada
| | - Aron K Barbey
- Beckman Institute for Advanced Science and Technology
| | - Arthur F Kramer
- Beckman Institute for Advanced Science and Technology.,Neuroscience Program and.,Psychology Department, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Ryan J Larsen
- Beckman Institute for Advanced Science and Technology
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27
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Al-Iedani O, Lechner-Scott J, Ribbons K, Ramadan S. Fast magnetic resonance spectroscopic imaging techniques in human brain- applications in multiple sclerosis. J Biomed Sci 2017; 24:17. [PMID: 28245815 PMCID: PMC5331701 DOI: 10.1186/s12929-017-0323-2] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2016] [Accepted: 02/08/2017] [Indexed: 01/04/2023] Open
Abstract
Multi voxel magnetic resonance spectroscopic imaging (MRSI) is an important imaging tool that combines imaging and spectroscopic techniques. MRSI of the human brain has been beneficially applied to different clinical applications in neurology, particularly in neurooncology but also in multiple sclerosis, stroke and epilepsy. However, a major challenge in conventional MRSI is the longer acquisition time required for adequate signal to be collected. Fast MRSI of the brain in vivo is an alternative approach to reduce scanning time and make MRSI more clinically suitable.Fast MRSI can be categorised into spiral, echo-planar, parallel and turbo imaging techniques, each with its own strengths. After a brief introduction on the basics of non-invasive examination (1H-MRS) and localization techniques principles, different fast MRSI techniques will be discussed from their initial development to the recent innovations with particular emphasis on their capacity to record neurochemical changes in the brain in a variety of pathologies.The clinical applications of whole brain fast spectroscopic techniques, can assist in the assessment of neurochemical changes in the human brain and help in understanding the roles they play in disease. To give a good example of the utilities of these techniques in clinical context, MRSI application in multiple sclerosis was chosen. The available up to date and relevant literature is discussed and an outline of future research is presented.
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Affiliation(s)
- Oun Al-Iedani
- School of Health Sciences, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW 2308, Australia
| | - Jeannette Lechner-Scott
- School of Medicine and Public Health, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW 2308, Australia.,Department of Neurology, John Hunter Hospital, Lookout Road, New Lambton, NSW 2305, Australia.,Hunter Medical Research Institute, Kookaburra Circuit, New Lambton, NSW 2305, Australia
| | - Karen Ribbons
- Department of Neurology, John Hunter Hospital, Lookout Road, New Lambton, NSW 2305, Australia
| | - Saadallah Ramadan
- School of Health Sciences, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW 2308, Australia.
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28
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Larsen RJ, Newman M, Nikolaidis A. Reduction of variance in measurements of average metabolite concentration in anatomically-defined brain regions. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2016; 272:73-81. [PMID: 27662403 DOI: 10.1016/j.jmr.2016.09.005] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2016] [Revised: 09/09/2016] [Accepted: 09/10/2016] [Indexed: 06/06/2023]
Abstract
Multiple methods have been proposed for using Magnetic Resonance Spectroscopy Imaging (MRSI) to measure representative metabolite concentrations of anatomically-defined brain regions. Generally these methods require spectral analysis, quantitation of the signal, and reconciliation with anatomical brain regions. However, to simplify processing pipelines, it is practical to only include those corrections that significantly improve data quality. Of particular importance for cross-sectional studies is knowledge about how much each correction lowers the inter-subject variance of the measurement, thereby increasing statistical power. Here we use a data set of 72 subjects to calculate the reduction in inter-subject variance produced by several corrections that are commonly used to process MRSI data. Our results demonstrate that significant reductions of variance can be achieved by performing water scaling, accounting for tissue type, and integrating MRSI data over anatomical regions rather than simply assigning MRSI voxels with anatomical region labels.
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Affiliation(s)
- Ryan J Larsen
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, United States.
| | - Michael Newman
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, United States
| | - Aki Nikolaidis
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, United States
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29
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McKay J, Tkáč I. Quantitative in vivo neurochemical profiling in humans: where are we now? Int J Epidemiol 2016; 45:1339-1350. [PMID: 27794521 DOI: 10.1093/ije/dyw235] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/22/2016] [Indexed: 11/14/2022] Open
Abstract
Proton nuclear magnetic resonance spectroscopy of biofluids has become one of the key techniques for metabolic profiling and phenotyping. This technique has been widely used in a number of epidemiological studies and in a variety of health disorders. However, its utilization in brain disorders is limited due to the blood-brain barrier, which not only protects the brain from unwanted substances in the blood, but also substantially limits the potential of finding biomarkers for neurological disorders in serum. This review article focuses on the potential of localized in vivo proton magnetic resonance spectroscopy (1H-MRS) for non-invasive neurochemical profiling in the human brain. First, methodological aspects of 1H-MRS (data acquisition, processing and metabolite quantification) that are essential for reliable non-invasive neurochemical profiling are described. Second, the power of 1H-MRS-based neurochemical profiling is demonstrated using some examples of its application in neuroscience and neurology. Finally, the authors present their vision and propose necessary steps to establish 1H-MRS as a method suitable for large-scale neurochemical profiling in epidemiological research.
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Affiliation(s)
- Jessica McKay
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Ivan Tkáč
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
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30
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Donadieu M, Le Fur Y, Lecocq A, Maudsley AA, Gherib S, Soulier E, Confort-Gouny S, Pariollaud F, Ranjeva MP, Pelletier J, Guye M, Zaaraoui W, Audoin B, Ranjeva JP. Metabolic voxel-based analysis of the complete human brain using fast 3D-MRSI: Proof of concept in multiple sclerosis. J Magn Reson Imaging 2016; 44:411-9. [PMID: 26756662 DOI: 10.1002/jmri.25139] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2015] [Accepted: 12/08/2015] [Indexed: 12/22/2022] Open
Abstract
PURPOSE To detect local metabolic abnormalities over the complete human brain in multiple sclerosis (MS) patients, we used optimized fast volumic echo planar spectroscopic imaging (3D-EPSI). MATERIALS AND METHODS Weighted mean combination of two 3D-EPSI covering the whole brain acquired at 3T in AC-PC and AC-PC+15° axial planes was performed to obtain high-quality metabolite maps for five metabolites: N-acetyl aspartate (NAA), glutamate+glutamine (Glx), choline (Cho), myo-inositol (m-Ins), and creatine+phosphocreatine (tCr). After spatial normalization, maps from 19 patients suffering from relapsing-remitting MS were compared to 19 matched controls using statistical mapping analyses to determine the topography of metabolic abnormalities. Probabilistic white matter (WM) T2 lesion maps and gray matter (GM) atrophy maps were also generated. RESULTS Two-group analysis of variance (ANOVA) (SPM8, P < 0.005, false discovery rate [FDR]-corrected P < 0.05 at the cluster level with age and sex as confounding covariates) comparing patients and controls matched for age and sex showed clusters of abnormal metabolite levels with 1) decreased NAA (around -15%) and Glx (around 20%) predominantly in GM within prefrontal cortices, motor cortices, bilateral thalami, and mesial temporal cortices in line with neuronal/neuro-astrocytic dysfunction; 2) increased m-Ins (around + 20%) inside WM T2 lesions and in the normal-appearing WM of temporal-occipital lobes, suggesting glial activation. CONCLUSION We demonstrate the ability to noninvasively map over the complete brain-from vertex to cerebellum-with a validated sequence, the metabolic abnormalities associated with MS, for characterizing the topography of pathological processes affecting widespread areas of WM and GM and its functional impact. J. Magn. Reson. Imaging 2016;44:411-419.
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Affiliation(s)
- Maxime Donadieu
- Aix Marseille Université, CNRS, CRMBM UMR 7339, Medical School of Marseille, Marseille, France.,AP-HM, CHU Timone, Pôle d'Imagerie, CEMEREM, Marseille, France
| | - Yann Le Fur
- Aix Marseille Université, CNRS, CRMBM UMR 7339, Medical School of Marseille, Marseille, France.,AP-HM, CHU Timone, Pôle d'Imagerie, CEMEREM, Marseille, France
| | - Angèle Lecocq
- Aix Marseille Université, CNRS, CRMBM UMR 7339, Medical School of Marseille, Marseille, France.,AP-HM, CHU Timone, Pôle d'Imagerie, CEMEREM, Marseille, France
| | - Andrew A Maudsley
- Miller School of Medicine, University of Miami, Department of Radiology, Miami, Florida, USA
| | - Soraya Gherib
- Aix Marseille Université, CNRS, CRMBM UMR 7339, Medical School of Marseille, Marseille, France.,AP-HM, CHU Timone, Pôle d'Imagerie, CEMEREM, Marseille, France.,AP-HM, CHU Timone, Pôle de Neurosciences Cliniques, Department of Neurology, Marseille, France
| | - Elisabeth Soulier
- Aix Marseille Université, CNRS, CRMBM UMR 7339, Medical School of Marseille, Marseille, France.,AP-HM, CHU Timone, Pôle d'Imagerie, CEMEREM, Marseille, France
| | - Sylviane Confort-Gouny
- Aix Marseille Université, CNRS, CRMBM UMR 7339, Medical School of Marseille, Marseille, France.,AP-HM, CHU Timone, Pôle d'Imagerie, CEMEREM, Marseille, France
| | - Fanelly Pariollaud
- Aix Marseille Université, CNRS, CRMBM UMR 7339, Medical School of Marseille, Marseille, France.,AP-HM, CHU Timone, Pôle d'Imagerie, CEMEREM, Marseille, France.,AP-HM, CHU Timone, Pôle de Neurosciences Cliniques, Department of Neurology, Marseille, France
| | - Marie-Pierre Ranjeva
- Aix Marseille Université, CNRS, CRMBM UMR 7339, Medical School of Marseille, Marseille, France.,AP-HM, CHU Timone, Pôle d'Imagerie, CEMEREM, Marseille, France.,AP-HM, CHU Timone, Pôle de Neurosciences Cliniques, Department of Neurology, Marseille, France
| | - Jean Pelletier
- Aix Marseille Université, CNRS, CRMBM UMR 7339, Medical School of Marseille, Marseille, France.,AP-HM, CHU Timone, Pôle de Neurosciences Cliniques, Department of Neurology, Marseille, France
| | - Maxime Guye
- Aix Marseille Université, CNRS, CRMBM UMR 7339, Medical School of Marseille, Marseille, France.,AP-HM, CHU Timone, Pôle d'Imagerie, CEMEREM, Marseille, France
| | - Wafaa Zaaraoui
- Aix Marseille Université, CNRS, CRMBM UMR 7339, Medical School of Marseille, Marseille, France.,AP-HM, CHU Timone, Pôle d'Imagerie, CEMEREM, Marseille, France
| | - Bertrand Audoin
- Aix Marseille Université, CNRS, CRMBM UMR 7339, Medical School of Marseille, Marseille, France.,AP-HM, CHU Timone, Pôle de Neurosciences Cliniques, Department of Neurology, Marseille, France
| | - Jean-Philippe Ranjeva
- Aix Marseille Université, CNRS, CRMBM UMR 7339, Medical School of Marseille, Marseille, France
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