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Joyce JM, La PL, Walker R, Harris A. Magnetic resonance spectroscopy of traumatic brain injury and subconcussive hits: A systematic review and meta-analysis. J Neurotrauma 2022; 39:1455-1476. [PMID: 35838132 DOI: 10.1089/neu.2022.0125] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Magnetic resonance spectroscopy (MRS) is a non-invasive technique used to study metabolites in the brain. MRS findings in traumatic brain injury (TBI) and subconcussive hit literature have been mixed. The most common observation is a decrease in N-acetyl-aspartate (NAA), traditionally considered a marker of neuronal integrity. Other metabolites, however, such as creatine (Cr), choline (Cho), glutamate+glutamine (Glx) and myo-inositol (mI) have shown inconsistent changes in these populations. The objective of this systematic review and meta-analysis was to synthesize MRS literature in head injury and explore factors (brain region, injury severity, time since injury, demographic, technical imaging factors, etc.) that may contribute to differential findings. One hundred and thirty-eight studies met inclusion criteria for the systematic review and of those, 62 NAA, 24 Cr, 49 Cho, 18 Glx and 21 mI studies met inclusion criteria for meta-analysis. A random effects model was used for meta-analyses with brain region as a subgroup for each of the five metabolites studied. Meta-regression was used to examine the influence of potential moderators including injury severity, time since injury, age, sex, tissue composition and methodological factors. In this analysis of 1428 unique head-injured subjects and 1132 controls, the corpus callosum was identified as a brain region highly susceptible to metabolite alteration. NAA was consistently decreased in TBI of all severity, but not in subconcussive hits. Cho and mI were found to be increased in moderate-to-severe TBI but not mild TBI. Glx and Cr were largely unaffected, however did show alterations in certain conditions.
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Affiliation(s)
- Julie Michele Joyce
- University of Calgary, 2129, Radiology, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, 157742, Calgary, Alberta, Canada.,Alberta Children's Hospital Research Institute, 157744, Calgary, Alberta, Canada.,Integrated Concussion Research Program, Calgary, Alberta, Canada;
| | - Parker L La
- University of Calgary, 2129, Radiology, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, 157742, Calgary, Alberta, Canada.,Alberta Children's Hospital Research Institute, 157744, Calgary, Alberta, Canada.,Integrated Concussion Research Program, Calgary, Alberta, Canada;
| | - Robyn Walker
- University of Calgary, 2129, Radiology, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, 157742, Calgary, Alberta, Canada.,Alberta Children's Hospital Research Institute, 157744, Calgary, Alberta, Canada.,Integrated Concussion Research Program, Calgary, Alberta, Canada;
| | - Ashley Harris
- University of Calgary, Radiology, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, 157742, Calgary, Alberta, Canada.,Alberta Children's Hospital Research Institute, 157744, Calgary, Alberta, Canada.,Integrated Concussion Research Program, Calgary, Alberta, Canada;
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2
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Chan KL, Ziegs T, Henning A. Improved signal-to-noise performance of MultiNet GRAPPA 1 H FID MRSI reconstruction with semi-synthetic calibration data. Magn Reson Med 2022; 88:1500-1515. [PMID: 35657035 DOI: 10.1002/mrm.29314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 04/29/2022] [Accepted: 05/06/2022] [Indexed: 11/09/2022]
Abstract
PURPOSE To further develop MultiNet GRAPPA, a neural-network-based reconstruction, for lower SNR proton MRSI (1 H MRSI) data using adapted undersampling schemes and improved training sets. METHODS 1 H FID-MRSI data and an anatomical image for GRAPPA reconstruction were acquired in two slices in the human brain (n = 6) at 7T. MRSI data were retrospectively undersampled for a 4×, 6×, and 7× acceleration rate. Signal-to-noise, relative error (RE) between accelerated and fully sampled metabolic maps, RMS of the lipid artifacts, and fitting reliability were compared across acceleration rates, to the fully sampled data, and with different kinds and amounts of training images. RESULTS Training with semi-synthetic images resulted in higher SNR and lower lipid RMS relative to training with acquired images from one or several subjects. SNR increased with the number of semi-synthetic training images and the 4× accelerated data retains ∼30% more SNR than other accelerated data. Spectra reconstructed with 20 semi-synthetic averages retained ∼100% more SNR and had ∼5% lower lipid RMS than those reconstructed with the center k-space points of one image as was originally proposed for very high SNR MRSI data and had higher fitting reliability. The metabolite RE was lowest when training with 20-semi-synthetic training images and highest when training with the center k-space points of one image. CONCLUSION MultiNet GRAPPA is feasible with lower SNR 1 H MRSI data if 20-semi-synthetic training images are used at a 4× acceleration rate. This acceleration rate provided the best trade-off between scan time and spectral SNR.
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Affiliation(s)
- Kimberly L Chan
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Theresia Ziegs
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Anke Henning
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Max Planck Institute for Biological Cybernetics, Tübingen, Germany
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3
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Kumar M, Nanga RPR, Verma G, Wilson N, Brisset JC, Nath K, Chawla S. Emerging MR Imaging and Spectroscopic Methods to Study Brain Tumor Metabolism. Front Neurol 2022; 13:789355. [PMID: 35370872 PMCID: PMC8967433 DOI: 10.3389/fneur.2022.789355] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 01/31/2022] [Indexed: 11/13/2022] Open
Abstract
Proton magnetic resonance spectroscopy (1H-MRS) provides a non-invasive biochemical profile of brain tumors. The conventional 1H-MRS methods present a few challenges mainly related to limited spatial coverage and low spatial and spectral resolutions. In the recent past, the advent and development of more sophisticated metabolic imaging and spectroscopic sequences have revolutionized the field of neuro-oncologic metabolomics. In this review article, we will briefly describe the scientific premises of three-dimensional echoplanar spectroscopic imaging (3D-EPSI), two-dimensional correlation spectroscopy (2D-COSY), and chemical exchange saturation technique (CEST) MRI techniques. Several published studies have shown how these emerging techniques can significantly impact the management of patients with glioma by determining histologic grades, molecular profiles, planning treatment strategies, and assessing the therapeutic responses. The purpose of this review article is to summarize the potential clinical applications of these techniques in studying brain tumor metabolism.
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Affiliation(s)
- Manoj Kumar
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Ravi Prakash Reddy Nanga
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | - Gaurav Verma
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Neil Wilson
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | | | - Kavindra Nath
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
- *Correspondence: Sanjeev Chawla
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4
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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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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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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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7
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Moser P, Eckstein K, Hingerl L, Weber M, Motyka S, Strasser B, van der Kouwe A, Robinson S, Trattnig S, Bogner W. Intra-session and inter-subject variability of 3D-FID-MRSI using single-echo volumetric EPI navigators at 3T. Magn Reson Med 2019; 83:1920-1929. [PMID: 31721294 PMCID: PMC7065144 DOI: 10.1002/mrm.28076] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 09/25/2019] [Accepted: 10/22/2019] [Indexed: 01/25/2023]
Abstract
Purpose In this study, we demonstrate the first combination of 3D FID proton MRSI and spatial encoding via concentric‐ring trajectories (CRTs) at 3T. FID‐MRSI has many benefits including high detection sensitivity, in particular for J‐coupled metabolites (e.g., glutamate/glutamine). This makes it highly attractive, not only for clinical, but also for, potentially, functional MRSI. However, this requires excellent reliability and temporal stability. We have, therefore, augmented this 3D‐FID‐MRSI sequence with single‐echo, imaging‐based volumetric navigators (se‐vNavs) for real‐time motion/shim‐correction (SHMOCO), which is 2× quicker than the original double‐echo navigators (de‐vNavs), hence allowing more efficient integration also in short‐TR sequences. Methods The tracking accuracy (position and B0‐field) of our proposed se‐vNavs was compared to the original de‐vNavs in phantoms (rest and translation) and in vivo (voluntary head rotation). Finally, the intra‐session stability of a 5:40 min 3D‐FID‐MRSI scan was evaluated with SHMOCO and no correction (NOCO) in 5 resting subjects. Intra/inter‐subject coefficients of variation (CV) and intra‐class correlations (ICC) over the whole 3D volume and in selected regions of interest ROI were assessed. Results Phantom and in vivo scans showed highly consistent tracking performance for se‐vNavs compared to the original de‐vNavs, but lower frequency drift. Up to ~30% better intra‐subject CVs were obtained for SHMOCO (P < 0.05), with values of 9.3/6.9/6.5/7.8% over the full VOI for Glx/tNAA/tCho/m‐Ins ratios to tCr. ICCs were good‐to‐high (91% for Glx/tCr in motor cortex), whereas the inter‐subject variability was ~11–19%. Conclusion Real‐time motion/shim corrected 3D‐FID‐MRSI with time‐efficient CRT‐sampling at 3T allows reliable, high‐resolution metabolic imaging that is fast enough for clinical use and even, potentially, for functional MRSI.
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Affiliation(s)
- Philipp Moser
- High-Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Korbinian Eckstein
- 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
| | - Michael Weber
- 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
| | - Bernhard Strasser
- High-Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.,Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Andre van der Kouwe
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Simon Robinson
- High-Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, 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.,Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, 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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8
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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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9
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Wilson M, Andronesi O, Barker PB, Bartha R, Bizzi A, Bolan PJ, Brindle KM, Choi IY, Cudalbu C, Dydak U, Emir UE, Gonzalez RG, Gruber S, Gruetter R, Gupta RK, Heerschap A, Henning A, Hetherington HP, Huppi PS, Hurd RE, Kantarci K, Kauppinen RA, Klomp DWJ, Kreis R, Kruiskamp MJ, Leach MO, Lin AP, Luijten PR, Marjańska M, Maudsley AA, Meyerhoff DJ, Mountford CE, Mullins PG, Murdoch JB, Nelson SJ, Noeske R, Öz G, Pan JW, Peet AC, Poptani H, Posse S, Ratai EM, Salibi N, Scheenen TWJ, Smith ICP, Soher BJ, Tkáč I, Vigneron DB, Howe FA. Methodological consensus on clinical proton MRS of the brain: Review and recommendations. Magn Reson Med 2019; 82:527-550. [PMID: 30919510 PMCID: PMC7179569 DOI: 10.1002/mrm.27742] [Citation(s) in RCA: 235] [Impact Index Per Article: 47.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2018] [Revised: 02/01/2019] [Accepted: 02/25/2019] [Indexed: 12/14/2022]
Abstract
Proton MRS (1 H MRS) provides noninvasive, quantitative metabolite profiles of tissue and has been shown to aid the clinical management of several brain diseases. Although most modern clinical MR scanners support MRS capabilities, routine use is largely restricted to specialized centers with good access to MR research support. Widespread adoption has been slow for several reasons, and technical challenges toward obtaining reliable good-quality results have been identified as a contributing factor. Considerable progress has been made by the research community to address many of these challenges, and in this paper a consensus is presented on deficiencies in widely available MRS methodology and validated improvements that are currently in routine use at several clinical research institutions. In particular, the localization error for the PRESS localization sequence was found to be unacceptably high at 3 T, and use of the semi-adiabatic localization by adiabatic selective refocusing sequence is a recommended solution. Incorporation of simulated metabolite basis sets into analysis routines is recommended for reliably capturing the full spectral detail available from short TE acquisitions. In addition, the importance of achieving a highly homogenous static magnetic field (B0 ) in the acquisition region is emphasized, and the limitations of current methods and hardware are discussed. Most recommendations require only software improvements, greatly enhancing the capabilities of clinical MRS on existing hardware. Implementation of these recommendations should strengthen current clinical applications and advance progress toward developing and validating new MRS biomarkers for clinical use.
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Affiliation(s)
- Martin Wilson
- Centre for Human Brain Health and School of Psychology, University of Birmingham, Birmingham, England
| | - Ovidiu Andronesi
- Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Peter B Barker
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Robert Bartha
- Robarts Research Institute, University of Western Ontario, London, Canada
| | - Alberto Bizzi
- U.O. Neuroradiologia, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, Italy
| | - Patrick J Bolan
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota
| | - Kevin M Brindle
- Department of Biochemistry, University of Cambridge, Cambridge, England
| | - In-Young Choi
- Department of Neurology, Hoglund Brain Imaging Center, University of Kansas Medical Center, Kansas City, Kansas
| | - Cristina Cudalbu
- Center for Biomedical Imaging, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
| | - Ulrike Dydak
- School of Health Sciences, Purdue University, West Lafayette, Indiana
| | - Uzay E Emir
- School of Health Sciences, Purdue University, West Lafayette, Indiana
| | - Ramon G Gonzalez
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Stephan Gruber
- High Field MR Center, Department of Biomedical imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Rolf Gruetter
- Laboratory for Functional and Metabolic Imaging, Center for Biomedical Imaging, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
| | - Rakesh K Gupta
- Fortis Memorial Research Institute, Gurugram, Haryana, India
| | - Arend Heerschap
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Anke Henning
- Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
| | | | - Petra S Huppi
- Department of Pediatrics, University of Geneva, Geneva, Switzerland
| | - Ralph E Hurd
- Stanford Radiological Sciences Lab, Stanford, California
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
| | - Risto A Kauppinen
- School of Psychological Science, University of Bristol, Bristol, England
| | | | - Roland Kreis
- Departments of Radiology and Biomedical Research, University of Bern, Bern, Switzerland
| | | | - Martin O Leach
- CRUK Cancer Imaging Centre, Institute of Cancer Research and Royal Marsden Hospital, London, England
| | - Alexander P Lin
- Center for Clinical Spectroscopy, Brigham and Women's Hospital, Harvard University Medical School, Boston, Massachusetts
| | | | - Małgorzata Marjańska
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota
| | | | - Dieter J Meyerhoff
- DVA Medical Center and Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | | | - Paul G Mullins
- Bangor Imaging Unit, School of Psychology, Bangor University, Bangor, Wales
| | | | - Sarah J Nelson
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | | | - Gülin Öz
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota
| | - Julie W Pan
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Andrew C Peet
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, England
| | - Harish Poptani
- Centre for Preclinical Imaging, Institute of Translational Medicine, University of Liverpool, Liverpool, England
| | - Stefan Posse
- Department of Neurology, University of New Mexico, Albuquerque, New Mexico
| | - Eva-Maria Ratai
- Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Nouha Salibi
- MR R&D, Siemens Healthineers, Malvern, Pennsylvania
| | - Tom W J Scheenen
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands
| | | | - Brian J Soher
- Department of Radiology, Duke University Medical Center, Durham, North Carolina
| | - Ivan Tkáč
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | - Franklyn A Howe
- Molecular and Clinical Sciences, St George's University of London, London, England
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10
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Verma G, Chawla S, Mohan S, Wang S, Nasrallah M, Sheriff S, Desai A, Brem S, O'Rourke DM, Wolf RL, Maudsley AA, Poptani H. Three-dimensional echo planar spectroscopic imaging for differentiation of true progression from pseudoprogression in patients with glioblastoma. NMR IN BIOMEDICINE 2019; 32:e4042. [PMID: 30556932 PMCID: PMC6519064 DOI: 10.1002/nbm.4042] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Revised: 10/30/2018] [Accepted: 10/31/2018] [Indexed: 05/20/2023]
Abstract
Accurate differentiation of true progression (TP) from pseudoprogression (PsP) in patients with glioblastomas (GBMs) is essential for planning adequate treatment and for estimating clinical outcome measures and future prognosis. The purpose of this study was to investigate the utility of three-dimensional echo planar spectroscopic imaging (3D-EPSI) in distinguishing TP from PsP in GBM patients. For this institutional review board approved and HIPAA compliant retrospective study, 27 patients with GBM demonstrating enhancing lesions within six months of completion of concurrent chemo-radiation therapy were included. Of these, 18 were subsequently classified as TP and 9 as PsP based on histological features or follow-up MRI studies. Parametric maps of choline/creatine (Cho/Cr) and choline/N-acetylaspartate (Cho/NAA) were computed and co-registered with post-contrast T1 -weighted and FLAIR images. All lesions were segmented into contrast enhancing (CER), immediate peritumoral (IPR), and distal peritumoral (DPR) regions. For each region, Cho/Cr and Cho/NAA ratios were normalized to corresponding metabolite ratios from contralateral normal parenchyma and compared between TP and PsP groups. Logistic regression analyses were performed to obtain the best model to distinguish TP from PsP. Significantly higher Cho/NAA was observed from CER (2.69 ± 1.00 versus 1.56 ± 0.51, p = 0.003), IPR (2.31 ± 0.92 versus 1.53 ± 0.56, p = 0.030), and DPR (1.80 ± 0.68 versus 1.19 ± 0.28, p = 0.035) regions in TP patients compared with those with PsP. Additionally, significantly elevated Cho/Cr (1.74 ± 0.44 versus 1.34 ± 0.26, p = 0.023) from CER was observed in TP compared with PsP. When these parameters were incorporated in multivariate regression analyses, a discriminatory model with a sensitivity of 94% and a specificity of 87% was observed in distinguishing TP from PsP. These results indicate the utility of 3D-EPSI in differentiating TP from PsP with high sensitivity and specificity.
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Affiliation(s)
- Gaurav Verma
- Department of RadiologyPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPAUSA
| | - Sanjeev Chawla
- Department of RadiologyPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPAUSA
| | - Suyash Mohan
- Department of RadiologyPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPAUSA
| | - Sumei Wang
- Department of RadiologyPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPAUSA
| | - MacLean Nasrallah
- Department of Pathology and Lab MedicinePerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPAUSA
| | | | - Arati Desai
- Department of Hematology‐OncologyPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPAUSA
| | - Steven Brem
- Department of NeurosurgeryPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPAUSA
| | - Donald M. O'Rourke
- Department of NeurosurgeryPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPAUSA
| | - Ronald L. Wolf
- Department of RadiologyPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPAUSA
| | | | - Harish Poptani
- Department of RadiologyPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPAUSA
- Department of Cellular and Molecular PhysiologyUniversity of LiverpoolLiverpoolUK
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11
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Nassirpour S, Chang P, Henning A. MultiNet PyGRAPPA: Multiple neural networks for reconstructing variable density GRAPPA (a 1H FID MRSI study). Neuroimage 2018; 183:336-345. [DOI: 10.1016/j.neuroimage.2018.08.032] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2018] [Revised: 08/05/2018] [Accepted: 08/15/2018] [Indexed: 10/28/2022] Open
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12
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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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13
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Hamilton J, Franson D, Seiberlich N. Recent advances in parallel imaging for MRI. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2017; 101:71-95. [PMID: 28844222 PMCID: PMC5927614 DOI: 10.1016/j.pnmrs.2017.04.002] [Citation(s) in RCA: 106] [Impact Index Per Article: 15.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2017] [Revised: 04/09/2017] [Accepted: 04/17/2017] [Indexed: 05/22/2023]
Abstract
Magnetic Resonance Imaging (MRI) is an essential technology in modern medicine. However, one of its main drawbacks is the long scan time needed to localize the MR signal in space to generate an image. This review article summarizes some basic principles and recent developments in parallel imaging, a class of image reconstruction techniques for shortening scan time. First, the fundamentals of MRI data acquisition are covered, including the concepts of k-space, undersampling, and aliasing. It is demonstrated that scan time can be reduced by sampling a smaller number of phase encoding lines in k-space; however, without further processing, the resulting images will be degraded by aliasing artifacts. Nearly all modern clinical scanners acquire data from multiple independent receiver coil arrays. Parallel imaging methods exploit properties of these coil arrays to separate aliased pixels in the image domain or to estimate missing k-space data using knowledge of nearby acquired k-space points. Three parallel imaging methods-SENSE, GRAPPA, and SPIRiT-are described in detail, since they are employed clinically and form the foundation for more advanced methods. These techniques can be extended to non-Cartesian sampling patterns, where the collected k-space points do not fall on a rectangular grid. Non-Cartesian acquisitions have several beneficial properties, the most important being the appearance of incoherent aliasing artifacts. Recent advances in simultaneous multi-slice imaging are presented next, which use parallel imaging to disentangle images of several slices that have been acquired at once. Parallel imaging can also be employed to accelerate 3D MRI, in which a contiguous volume is scanned rather than sequential slices. Another class of phase-constrained parallel imaging methods takes advantage of both image magnitude and phase to achieve better reconstruction performance. Finally, some applications are presented of parallel imaging being used to accelerate MR Spectroscopic Imaging.
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Affiliation(s)
- Jesse Hamilton
- Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
| | - Dominique Franson
- Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
| | - Nicole Seiberlich
- Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA; Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA.
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14
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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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15
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Strasser B, Považan M, Hangel G, Hingerl L, Chmelik M, Gruber S, Trattnig S, Bogner W. (2 + 1)D-CAIPIRINHA accelerated MR spectroscopic imaging of the brain at 7T. Magn Reson Med 2016; 78:429-440. [PMID: 27548836 PMCID: PMC5535010 DOI: 10.1002/mrm.26386] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2016] [Revised: 07/25/2016] [Accepted: 07/27/2016] [Indexed: 12/15/2022]
Abstract
Purpose To compare a new parallel imaging (PI) method for multislice proton magnetic resonance spectroscopic imaging (1H‐MRSI), termed (2 + 1)D‐CAIPIRINHA, with two standard PI methods: 2D‐GRAPPA and 2D‐CAIPIRINHA at 7 Tesla (T). Methods (2 + 1)D‐CAIPIRINHA is a combination of 2D‐CAIPIRINHA and slice‐CAIPIRINHA. Eight healthy volunteers were measured on a 7T MR scanner using a 32‐channel head coil. The best undersampling patterns were estimated for all three PI methods. The artifact powers, g‐factors, Cramér–Rao lower bounds (CRLB), and root mean square errors (RMSE) were compared quantitatively among the three PI methods. Metabolic maps and spectra were compared qualitatively. Results (2 + 1)D‐CAIPIRINHA allows acceleration in three spatial dimensions in contrast to 2D‐GRAPPA and 2D‐CAIPIRINHA. Thus, this sequence significantly decreased the RMSE of the metabolic maps by 12.1 and 6.9%, on average, for 4 < R < 11, compared with 2D‐GRAPPA and 2D‐CAIPIRINHA, respectively. The artifact power was 22.6 and 8.4% lower, and the CRLB were 3.4 and 0.6% lower, respectively. Conclusion (2 + 1)‐CAIPIRINHA can be implemented for multislice MRSI in the brain, enabling higher accelerations than possible with two‐dimensional (2D) parallel imaging methods. An eight‐fold acceleration was still feasible in vivo with negligible PI artifacts with lipid decontamination, thus decreasing the measurement time from 120 to 15 min for a 64 × 64 × 4 matrix. Magn Reson Med 78:429–440, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- B Strasser
- MRCE, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - M Považan
- MRCE, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.,Christian Doppler Laboratory for Clinical Molecular MR Imaging, Medical University of Vienna, Vienna, Austria
| | - G Hangel
- MRCE, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - L Hingerl
- MRCE, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - M Chmelik
- MRCE, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.,Christian Doppler Laboratory for Clinical Molecular MR Imaging, Medical University of Vienna, Vienna, Austria
| | - S Gruber
- MRCE, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - S Trattnig
- MRCE, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.,Christian Doppler Laboratory for Clinical Molecular MR Imaging, Medical University of Vienna, Vienna, Austria
| | - W Bogner
- MRCE, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
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16
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Jayakumar AR, Bak LK, Rama Rao KV, Waagepetersen HS, Schousboe A, Norenberg MD. Neuronal Cell Death Induced by Mechanical Percussion Trauma in Cultured Neurons is not Preceded by Alterations in Glucose, Lactate and Glutamine Metabolism. Neurochem Res 2016; 41:307-15. [PMID: 26729365 DOI: 10.1007/s11064-015-1801-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2015] [Revised: 12/07/2015] [Accepted: 12/09/2015] [Indexed: 11/24/2022]
Abstract
Traumatic brain injury (TBI) is a devastating neurological disorder that usually presents in acute and chronic forms. Brain edema and associated increased intracranial pressure in the early phase following TBI are major consequences of acute trauma. On the other hand, neuronal injury, leading to neurobehavioral and cognitive impairments, that usually develop months to years after single or repetitive episodes of head trauma, are major consequences of chronic TBI. The molecular mechanisms responsible for TBI-induced injury, however, are unclear. Recent studies have suggested that early mitochondrial dysfunction and subsequent energy failure play a role in the pathogenesis of TBI. We therefore examined whether oxidative metabolism of (13)C-labeled glucose, lactate or glutamine is altered early following in vitro mechanical percussion-induced trauma (5 atm) to neurons (4-24 h), and whether such events contribute to the development of neuronal injury. Cell viability was assayed using the release of the cytoplasmic enzyme lactate dehydrogenase (LDH), together with fluorescence-based cell staining (calcein and ethidium homodimer-1 for live and dead cells, respectively). Trauma had no effect on the LDH release in neurons from 1 to 18 h. However, a significant increase in LDH release was detected at 24 h after trauma. Similar findings were identified when traumatized neurons were stained with fluorescent markers. Additionally (13)C-labeling of glutamate showed a small, but statistically significant decrease at 14 h after trauma. However, trauma had no effect on the cycling ratio of the TCA cycle at any time-period examined. These findings indicate that trauma does not cause a disturbance in oxidative metabolism of any of the substrates used for neurons. Accordingly, such metabolic disturbance does not appear to contribute to the neuronal death in the early stages following trauma.
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Affiliation(s)
- A R Jayakumar
- Laboratory of Neuropathology, Veterans Affairs Medical Center, Miami, FL, USA
| | - L K Bak
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, 2100, Copenhagen, Denmark
| | - K V Rama Rao
- Laboratory of Neuropathology, Veterans Affairs Medical Center, Miami, FL, USA
| | - H S Waagepetersen
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, 2100, Copenhagen, Denmark
| | - A Schousboe
- Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, 2100, Copenhagen, Denmark
| | - M D Norenberg
- Laboratory of Neuropathology, Veterans Affairs Medical Center, Miami, FL, USA. .,Department of Pathology (D-33), University of Miami School of Medicine, P.O. Box 016960, Miami, FL, 33101, USA. .,Department of Biochemistry and Molecular Biology, University of Miami School of Medicine, Miami, FL, USA.
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17
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Tsai SY, Hsu YC, Chu YH, Kuo WJ, Lin FH. Combining parallel detection of proton echo planar spectroscopic imaging (PEPSI) measurements with a data-consistency constraint improves SNR. NMR IN BIOMEDICINE 2015; 28:1678-1687. [PMID: 26484749 DOI: 10.1002/nbm.3425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2015] [Revised: 09/09/2015] [Accepted: 09/10/2015] [Indexed: 06/05/2023]
Abstract
One major challenge of MRSI is the poor signal-to-noise ratio (SNR), which can be improved by using a surface coil array. Here we propose to exploit the spatial sensitivity of different channels of a coil array to enforce the k-space data consistency (DC) in order to suppress noise and consequently to improve MRSI SNR. MRSI data were collected using a proton echo planar spectroscopic imaging (PEPSI) sequence at 3 T using a 32-channel coil array and were averaged with one, two and eight measurements (avg-1, avg-2 and avg-8). The DC constraint was applied using a regularization parameter λ of 1, 2, 3, 5 or 10. Metabolite concentrations were quantified using LCModel. Our results show that the suppression of noise by applying the DC constraint to PEPSI reconstruction yields up to 32% and 27% SNR gain for avg-1 and avg-2 data with λ = 5, respectively. According to the reported Cramer-Rao lower bounds, the improvement in metabolic fitting was significant (p < 0.01) when the DC constraint was applied with λ ≥ 2. Using the DC constraint with λ = 3 or 5 can minimize both root-mean-square errors and spatial variation for all subjects using the avg-8 data set as reference values. Our results suggest that MRSI reconstructed with a DC constraint can save around 70% of scanning time to obtain images and spectra with similar SNRs using λ = 5.
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Affiliation(s)
- Shang-Yueh Tsai
- Graduate Institute of Applied Physics, National Chengchi University, Taipei, Taiwan
- Research Center for Mind, Brain and Learning, National Chengchi University, Taipei, Taiwan
| | - Yi-Cheng Hsu
- Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan
| | - Ying-Hua Chu
- Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan
| | - Wen-Jui Kuo
- Institute of Neuroscience, National Yang Ming University, Taipei, Taiwan
| | - Fa-Hsuan Lin
- Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan
- Department of Biomedical Engineering and Computational Science, Aalto University, Espoo, Finland
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18
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Hangel G, Strasser B, Považan M, Gruber S, Chmelík M, Gajdošík M, Trattnig S, Bogner W. Lipid suppression via double inversion recovery with symmetric frequency sweep for robust 2D-GRAPPA-accelerated MRSI of the brain at 7 T. NMR IN BIOMEDICINE 2015; 28:1413-25. [PMID: 26370781 PMCID: PMC4973691 DOI: 10.1002/nbm.3386] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2015] [Revised: 07/20/2015] [Accepted: 07/29/2015] [Indexed: 05/06/2023]
Abstract
This work presents a new approach for high-resolution MRSI of the brain at 7 T in clinically feasible measurement times. Two major problems of MRSI are the long scan times for large matrix sizes and the possible spectral contamination by the transcranial lipid signal. We propose a combination of free induction decay (FID)-MRSI with a short acquisition delay and acceleration via in-plane two-dimensional generalised autocalibrating partially parallel acquisition (2D-GRAPPA) with adiabatic double inversion recovery (IR)-based lipid suppression to allow robust high-resolution MRSI. We performed Bloch simulations to evaluate the magnetisation pathways of lipids and metabolites, and compared the results with phantom measurements. Acceleration factors in the range 2-25 were tested in a phantom. Five volunteers were scanned to verify the value of our MRSI method in vivo. GRAPPA artefacts that cause fold-in of transcranial lipids were suppressed via double IR, with a non-selective symmetric frequency sweep. The use of long, low-power inversion pulses (100 ms) reduced specific absorption rate requirements. The symmetric frequency sweep over both pulses provided good lipid suppression (>90%), in addition to a reduced loss in metabolite signal-to-noise ratio (SNR), compared with conventional IR suppression (52-70%). The metabolic mapping over the whole brain slice was not limited to a rectangular region of interest. 2D-GRAPPA provided acceleration up to a factor of nine for in vivo FID-MRSI without a substantial increase in g-factors (<1.1). A 64 × 64 matrix can be acquired with a common repetition time of ~1.3 s in only 8 min without lipid artefacts caused by acceleration. Overall, we present a fast and robust MRSI method, using combined double IR fat suppression and 2D-GRAPPA acceleration, which may be used in (pre)clinical studies of the brain at 7 T.
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Affiliation(s)
- Gilbert Hangel
- MR Centre of Excellence (MRCE), Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Bernhard Strasser
- MR Centre of Excellence (MRCE), Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Michal Považan
- MR Centre of Excellence (MRCE), Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Stephan Gruber
- MR Centre of Excellence (MRCE), Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Marek Chmelík
- MR Centre of Excellence (MRCE), Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Martin Gajdošík
- MR Centre of Excellence (MRCE), Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Siegfried Trattnig
- MR Centre of Excellence (MRCE), Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
- Christian Doppler Laboratory for Clinical Molecular MR Imaging, Medical University of Vienna, Vienna, Austria
| | - Wolfgang Bogner
- MR Centre of Excellence (MRCE), Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
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19
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Schirda CV, Zhao T, Andronesi OC, Lee Y, Pan JW, Mountz JM, Hetherington HP, Boada FE. In vivo brain rosette spectroscopic imaging (RSI) with LASER excitation, constant gradient strength readout, and automated LCModel quantification for all voxels. Magn Reson Med 2015; 76:380-90. [PMID: 26308482 DOI: 10.1002/mrm.25896] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2014] [Revised: 06/29/2015] [Accepted: 07/27/2015] [Indexed: 12/21/2022]
Abstract
PURPOSE To optimize the Rosette trajectories for high-sensitivity in vivo brain spectroscopic imaging and reduced gradient demands. METHODS Using LASER localization, a rosette based sampling scheme for in vivo brain spectroscopic imaging data on a 3 Tesla (T) system is described. The two-dimensional (2D) and 3D rosette spectroscopic imaging (RSI) data were acquired using 20 × 20 in-plane resolution (8 × 8 mm(2) ), and 1 (2D) -18 mm (1.1 cc) or 12 (3D) -8 mm partitions (0.5 cc voxels). The performance of the RSI acquisition was compared with a conventional spectroscopic imaging (SI) sequence using LASER localization and 2D or 3D elliptical phase encoding (ePE). Quantification of the entire RSI data set was performed using an LCModel based pipeline. RESULTS The RSI acquisitions took 32 s for the 2D scan, and as short as 5 min for the 3D 20 × 20 × 12 scan, using a maximum gradient strength Gmax=5.8 mT/m and slew-rate Smax=45 mT/m/ms. The Bland-Altman agreement between RSI and ePE CSI, characterized by the 95% confidence interval for their difference (RSI-ePE), is within 13% of the mean (RSI+ePE)/2. Compared with the 3D ePE at the same nominal resolution, the effective RSI voxel size was three times smaller while the measured signal-to-noise ratio sensitivity, after normalization for differences in effective size, was 43% greater. CONCLUSION 3D LASER-RSI is a fast, high-sensitivity spectroscopic imaging sequence, which can acquire medium-to-high resolution SI data in clinically acceptable scan times (5-10 min), with reduced stress on the gradient system. Magn Reson Med 76:380-390, 2016. © 2015 Wiley Periodicals, Inc.
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Affiliation(s)
- Claudiu V Schirda
- University of Pittsburgh School of Medicine, Department of Radiology, Pittsburgh, Pennsylvania, USA
| | - Tiejun Zhao
- Siemens Healthcare, Siemens Medical Solutions USA, Inc., Pittsburgh, Pennsylvania, USA
| | - Ovidiu C Andronesi
- Massachusetts General Hospital, Department of Radiology, Boston, Massachusetts, USA
| | - Yoojin Lee
- University of Pittsburgh School of Medicine, Department of Radiology, Pittsburgh, Pennsylvania, USA
| | - Jullie W Pan
- University of Pittsburgh School of Medicine, Department of Radiology, Pittsburgh, Pennsylvania, USA.,University of Pittsburgh School of Medicine, Department of Neurology, Pittsburgh, Pennsylvania, USA
| | - James M Mountz
- University of Pittsburgh School of Medicine, Department of Radiology, Pittsburgh, Pennsylvania, USA
| | - Hoby P Hetherington
- University of Pittsburgh School of Medicine, Department of Radiology, Pittsburgh, Pennsylvania, USA
| | - Fernando E Boada
- New York University, Department of Radiology, New York, New York, USA
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20
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Sabati M, Sheriff S, Gu M, Wei J, Zhu H, Barker PB, Spielman DM, Alger JR, Maudsley AA. Multivendor implementation and comparison of volumetric whole-brain echo-planar MR spectroscopic imaging. Magn Reson Med 2014; 74:1209-20. [PMID: 25354190 DOI: 10.1002/mrm.25510] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2014] [Revised: 10/02/2014] [Accepted: 10/03/2014] [Indexed: 12/14/2022]
Abstract
PURPOSE To assess volumetric proton MR spectroscopic imaging (MRSI) of the human brain on multivendor MRI instruments. METHODS Echo-planar spectroscopic imaging was developed on instruments from three manufacturers, with matched specifications and acquisition protocols that accounted for differences in sampling performance, radiofrequency (RF) power, and data formats. Intersite reproducibility was evaluated for signal-normalized maps of N-acetylaspartate (NAA), creatine (Cre), and choline using phantom and human subject measurements. Comparative analyses included metrics for spectral quality, spatial coverage, and mean values in atlas-registered brain regions. RESULTS Intersite differences for phantom measurements were less than 1.7% for individual metabolites and less than 0.2% for ratio measurements. Spatial uniformity ranged from 79% to 91%. The human studies found differences of mean values in the temporal lobe, but good agreement in other white matter regions, with maximum differences relative to their mean of under 3.2%. For NAA/Cre, the maximum difference was 1.8%. In gray matter, a significant difference was observed for frontal lobe NAA. Primary causes of intersite differences were attributed to shim quality, B0 drift, and accuracy of RF excitation. Correlation coefficients for measurements at each site were over 0.60, indicating good reliability. CONCLUSION A volumetric intensity-normalized MRSI acquisition can be implemented in a comparable manner across multivendor MR instruments.
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Affiliation(s)
- Mohammad Sabati
- Department of Radiology, University of Miami, Miami, Florida, USA.,Department of Radiology, University of Calgary, Calgary, Canada
| | - Sulaiman Sheriff
- Department of Radiology, University of Miami, Miami, Florida, USA
| | - Meng Gu
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Juan Wei
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, and the F.M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Henry Zhu
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, and the F.M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Peter B Barker
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, and the F.M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Daniel M Spielman
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Jeffry R Alger
- Neurology and Radiological Sciences, University of California, Los Angeles, California, USA
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Use of high-resolution volumetric MR spectroscopic imaging in assessing treatment response of glioblastoma to an HDAC inhibitor. AJR Am J Roentgenol 2014; 203:W158-65. [PMID: 25055291 DOI: 10.2214/ajr.14.12518] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
OBJECTIVE Improved predictive imaging would enable personalization and adjustment of treatment, which are critical for patients with glioblastomain whom therapy is likely to fail. This article describes the use of MR spectroscopic imaging (MRSI) to predict early clinical and behavioral response to a therapy and an effort to develop high-resolution, volumetric MRSI to improve its clinical application. CONCLUSION MRSI may enable quantitative analysis of brain tumor response, offering a precise tool for monitoring of patients in clinical trials.
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Erratum. J Magn Reson Imaging 2014. [DOI: 10.1002/jmri.24733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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Ding XQ, Maudsley AA, Sabati M, Sheriff S, Dellani PR, Lanfermann H. Reproducibility and reliability of short-TE whole-brain MR spectroscopic imaging of human brain at 3T. Magn Reson Med 2014; 73:921-8. [PMID: 24677384 DOI: 10.1002/mrm.25208] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2013] [Revised: 02/11/2014] [Accepted: 02/20/2014] [Indexed: 12/29/2022]
Abstract
PURPOSE A feasibility study of an echo-planar spectroscopic imaging (EPSI) using a short echo time (TE) that trades off sensitivity, compared with other short-TE methods, to achieve whole brain coverage using inversion recovery and spatial oversampling to control lipid bleeding. METHODS Twenty subjects were scanned to examine intersubject variance. One subject was scanned five times to examine intrasubject reproducibility. Data were analyzed to determine coefficients of variance (COV) and intraclass correlation coefficient (ICC) for N-acetylaspartate (NAA), total creatine (tCr), total choline (tCho), glutamine/glutamate (Glx), and myo-inositol (mI). Regional metabolite concentrations were derived by using multi-voxel analysis based on lobar-level anatomic regions. RESULTS For whole-brain mean values, the intrasubject COVs were 14%, 15%, and 20% for NAA, tCr, and tCho, respectively, and 31% for Glx and mI. The intersubject COVs were up to 6% higher. For regional distributions, the intrasubject COVs were ≤ 5% for NAA, tCr, and tCho; ≤ 9% for Glx; and ≤15% for mI, with about 6% higher intersubject COVs. The ICCs of 5 metabolites were ≥ 0.7, indicating the reliability of the measurements. CONCLUSION The present EPSI method enables estimation of the whole-brain metabolite distributions, including Glx and mI with small voxel size, and a reasonable scan time and reproducibility.
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Affiliation(s)
- Xiao-Qi Ding
- Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany
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Quantification in magnetic resonance spectroscopy based on semi-parametric approaches. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2013; 27:113-30. [DOI: 10.1007/s10334-013-0393-4] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2013] [Revised: 07/08/2013] [Accepted: 07/08/2013] [Indexed: 10/26/2022]
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