1
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Correspondence among gray matter atrophy and atlas-based neurotransmitter maps is clinically relevant in multiple sclerosis. Mol Psychiatry 2023; 28:1770-1782. [PMID: 36658334 DOI: 10.1038/s41380-023-01943-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 12/29/2022] [Accepted: 01/06/2023] [Indexed: 01/20/2023]
Abstract
In multiple sclerosis (MS), gray matter (GM) atrophy progresses in a non-random manner, possibly in regions with a high distribution of specific neurotransmitters involved in several relevant central nervous system functions. We investigated the associations among regional GM atrophy, atlas-based neurotransmitter distributions and clinical manifestations in a large MS patients' group. Brain 3 T MRI scans, neurological examinations and neuropsychological evaluations were obtained from 286 MS patients and 172 healthy controls (HC). Spatial correlations among regional GM volume differences and atlas-based nuclear imaging-derived neurotransmitter maps, and their associations with MS clinical features were investigated using voxel-based morphometry and JuSpace toolbox. Compared to HC, MS patients showed widespread GM atrophy being spatially correlated with the majority of neurotransmitter maps (false discovery rate [FDR]-p ≤ 0.004). Patients with a disease duration ≥ 5 vs < 5 years had significant cortical, subcortical and cerebellar atrophy, being spatially correlated with a higher distribution of serotoninergic and dopaminergic receptors (FDR-p ≤ 0.03). Compared to mildly-disabled patients, those with Expanded Disability Status Scale ≥ 3.0 or ≥ 4.0 had significant cortical, subcortical and cerebellar atrophy being associated with serotonergic, dopaminergic, opioid and cholinergic maps (FDR-p ≤ 0.04). Cognitively impaired vs cognitively preserved patients had widespread GM atrophy being spatially associated with serotonergic, dopaminergic, noradrenergic, cholinergic and glutamatergic maps (FDR-p ≤ 0.04). Fatigued vs non-fatigued MS patients had significant cortical, subcortical and cerebellar atrophy, not associated with neurotransmitter maps. No significant association between GM atrophy and neurotransmitter maps was found for depression. Regional GM atrophy with specific neurotransmitter systems may explain part of MS clinical manifestations, including locomotor disability, cognitive impairment and fatigue.
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Al-Iedani O, Lea R, Ribbons K, Ramadan S, Lechner-Scott J. Neurometabolic changes in multiple sclerosis: Fingolimod versus beta interferon or glatiramer acetate therapy. J Neuroimaging 2022; 32:1109-1120. [PMID: 35922880 DOI: 10.1111/jon.13032] [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: 05/11/2022] [Revised: 07/20/2022] [Accepted: 07/22/2022] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND AND PURPOSE Fingolimod has been shown to be more effective in reducing relapse rate and disability than injectable therapies in clinical trials. An increase in N-acetylaspartate (NAA) as measured by MR spectroscopy is correlated with maintaining axonal metabolic functions. This study compared the neurometabolic and volumetric changes in relapsing-remitting multiple sclerosis (RRMS) patients on fingolimod or injectable therapies with healthy controls (HCs). METHODS Ninety-eight RRMS (52 on fingolimod, 46 on injectable therapies (27 on glatiramer acetate and 19 on interferon) were age and sex-matched to 51 HCs. RRMS patients underwent cognitive, fatigue, and mental health assessments, as well as an Expanded disability status scale (EDSS). MRI/S was acquired from the hippocampus, posterior cingulate gyrus (PCG), and prefrontal cortex (PFC). Volumetric and neurometabolic measures were compared across cohorts using a univariate general linear model and correlated with clinical severity and neuropsychological scores. RESULTS Clinical parameters, MR-volumetric, and neurometabolic profiles showed no differences between treatment groups (p > .05). Compared to HCs, both RRMS cohorts showed volume changes in white matter (-13%), gray matter (-16%), and cerebral spinal fluid (CSF) (+17-23%), as well as reduced NAA (-17%, p = .001, hippocampus), (-7%, p = .001, PCG), and (-9%, p = .001, PFC). MRI/S metrics in three regions were moderately correlated with cognition and fatigue functions. CONCLUSION While both treatment arms showed overall similar volumetric and neurometabolic profiles, longitudinal studies are warranted to clarify neurometabolic changes and associations with treatment efficacy.
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Affiliation(s)
- Oun Al-Iedani
- School of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, New South Wales, Australia.,Hunter Medical Research Institute, New Lambton, New South Wales, Australia
| | - Rodney Lea
- Hunter Medical Research Institute, New Lambton, New South Wales, Australia.,Institute of Health and Biomedical Innovation, School of Biomedical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Karen Ribbons
- Hunter Medical Research Institute, New Lambton, New South Wales, Australia
| | - Saadallah Ramadan
- Hunter Medical Research Institute, New Lambton, New South Wales, Australia.,School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, New South Wales, Australia
| | - Jeannette Lechner-Scott
- Hunter Medical Research Institute, New Lambton, New South Wales, Australia.,School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, New South Wales, Australia.,Department of Neurology, John Hunter Hospital, New Lambton Heights, New South Wales, Australia
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Nisar S, Bhat AA, Masoodi T, Hashem S, Akhtar S, Ali TA, Amjad S, Chawla S, Bagga P, Frenneaux MP, Reddy R, Fakhro K, Haris M. Genetics of glutamate and its receptors in autism spectrum disorder. Mol Psychiatry 2022; 27:2380-2392. [PMID: 35296811 PMCID: PMC9135628 DOI: 10.1038/s41380-022-01506-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Revised: 02/11/2022] [Accepted: 02/22/2022] [Indexed: 12/11/2022]
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental impairment characterized by deficits in social interaction skills, impaired communication, and repetitive and restricted behaviors that are thought to be due to altered neurotransmission processes. The amino acid glutamate is an essential excitatory neurotransmitter in the human brain that regulates cognitive functions such as learning and memory, which are usually impaired in ASD. Over the last several years, increasing evidence from genetics, neuroimaging, protein expression, and animal model studies supporting the notion of altered glutamate metabolism has heightened the interest in evaluating glutamatergic dysfunction in ASD. Numerous pharmacological, behavioral, and imaging studies have demonstrated the imbalance in excitatory and inhibitory neurotransmitters, thus revealing the involvement of the glutamatergic system in ASD pathology. Here, we review the effects of genetic alterations on glutamate and its receptors in ASD and the role of non-invasive imaging modalities in detecting these changes. We also highlight the potential therapeutic targets associated with impaired glutamatergic pathways.
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Affiliation(s)
- Sabah Nisar
- Laboratory of Molecular and Metabolic Imaging, Sidra Medicine, P.O. Box 26999, Doha, Qatar
| | - Ajaz A Bhat
- Laboratory of Molecular and Metabolic Imaging, Sidra Medicine, P.O. Box 26999, Doha, Qatar
| | - Tariq Masoodi
- Laboratory of Molecular and Metabolic Imaging, Sidra Medicine, P.O. Box 26999, Doha, Qatar
| | - Sheema Hashem
- Laboratory of Molecular and Metabolic Imaging, Sidra Medicine, P.O. Box 26999, Doha, Qatar
| | - Sabah Akhtar
- Laboratory of Molecular and Metabolic Imaging, Sidra Medicine, P.O. Box 26999, Doha, Qatar
| | - Tayyiba Akbar Ali
- Laboratory of Molecular and Metabolic Imaging, Sidra Medicine, P.O. Box 26999, Doha, Qatar
| | - Sara Amjad
- Shibli National College, Azamgarh, Uttar Pradesh, 276001, India
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Puneet Bagga
- Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Michael P Frenneaux
- Academic Health System, Hamad Medical Corporation, P.O. Box 3050, Doha, Qatar
| | - Ravinder Reddy
- Center for Advanced Metabolic Imaging in Precision Medicine, Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Khalid Fakhro
- Department of Human Genetics, Sidra Medicine, P.O. Box 26999, Doha, Qatar
- Department of Genetic Medicine, Weill Cornell Medical College, P.O. Box 24144, Doha, Qatar
| | - Mohammad Haris
- Laboratory of Molecular and Metabolic Imaging, Sidra Medicine, P.O. Box 26999, Doha, Qatar.
- Center for Advanced Metabolic Imaging in Precision Medicine, Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Laboratory of Animal Research, Qatar University, P.O. Box 2713, Doha, Qatar.
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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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Mueller C, Baird JF, Motl RW. Whole-Brain Metabolic Abnormalities Are Associated With Mobility in Older Adults With Multiple Sclerosis. Neurorehabil Neural Repair 2022; 36:286-297. [PMID: 35164595 DOI: 10.1177/15459683221076461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Older adults with multiple sclerosis (MS) experience mobility impairments, but conventional brain imaging is a poor predictor of walking abilities in this population. OBJECTIVE To test whether brain metabolites measured with Magnetic Resonance Spectroscopy (MRS) are associated with walking performance in older adults with MS. METHODS Fifteen older adults with MS (mean age: 60.9, SD: 5.1) and 22 age-matched healthy controls (mean age: 64.2, SD: 5.7) underwent whole-brain MRS and mobility testing. Levels of N-acetylaspartate (NAA), myo-inositol (MI), choline (CHO), and temperature in 47 brain regions were compared between groups and correlated with walking speed (Timed 25 Foot Walk) and walking endurance (Six-Minute Walk). RESULTS Older adults with MS had higher MI in 23 areas, including the bilateral frontal (right: t (21.449) = -2.605, P = .016; left: t (35) = -2.434, P = .020), temporal (right: t (35) = -3.063, P = .004; left: t (35) = -3.026, P = .005), and parietal lobes (right: t (21.100) = -2.886, P = .009; left: t (35) = -2.507, P = .017), and right thalamus (t (35) = -2.840, P = .007). MI in eleven regions correlated with walking speed, and MI in twelve regions correlated with walking endurance. NAA was lower in MS in the bilateral thalami (right: t (35) = 3.449, P < .001; left: t (35) = 2.061, P = .047), caudate nuclei (right: t (33) = 2.828, P = .008; left: t (32) = 2.132, P = .041), and posterior cingulum (right: t (35) = 3.077, P = .004; left: t (35) = 2.972, P = .005). NAA in four regions correlated with walking speed and endurance. Brain temperature was higher in MS patients in four regions, but did not correlate with mobility measures. There were no group differences in CHO. CONCLUSION MI and NAA may be useful imaging end-points for walking ability as a clinical outcome in older adults with MS.
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Affiliation(s)
- Christina Mueller
- Department of Neurology, 9967University of Alabama at Birmingham, Birmingham, AL, United States
| | - Jessica F Baird
- Department of Physical Therapy, 9968University of Alabama at Birmingham, Birmingham, AL, United States
| | - Robert W Motl
- Department of Physical Therapy, 9968University of Alabama at Birmingham, Birmingham, AL, United States
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Ma RE, Murdoch JB, Bogner W, Andronesi O, Dydak U. Atlas-based GABA mapping with 3D MEGA-MRSI: Cross-correlation to single-voxel MRS. NMR IN BIOMEDICINE 2021; 34:e4275. [PMID: 32078755 PMCID: PMC7438238 DOI: 10.1002/nbm.4275] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Revised: 01/11/2020] [Accepted: 01/23/2020] [Indexed: 06/10/2023]
Abstract
The purpose of this work is to develop and validate a new atlas-based metabolite quantification pipeline for edited magnetic resonance spectroscopic imaging (MEGA-MRSI) that enables group comparisons of brain structure-specific GABA levels. By using brain structure masks segmented from high-resolution MPRAGE images and coregistering these to MEGA-LASER 3D MRSI data, an automated regional quantification of neurochemical levels is demonstrated for the example of the thalamus. Thalamic gamma-aminobutyric acid + coedited macromolecules (GABA+) levels from 21 healthy subjects scanned at 3 T were cross-validated both against a single-voxel MEGA-PRESS acquisition in the same subjects and same scan sessions, as well as alternative MRSI processing techniques (ROI approach, four-voxel approach) using Pearson correlation analysis. In addition, reproducibility was compared across the MRSI processing techniques in test-retest data from 14 subjects. The atlas-based approach showed a significant correlation with SV MEGA-PRESS (correlation coefficient r [GABA+] = 0.63, P < 0.0001). However, the actual values for GABA+, NAA, tCr, GABA+/tCr and tNAA/tCr obtained from the atlas-based approach showed an offset to SV MEGA-PRESS levels, likely due to the fact that on average the thalamus mask used for the atlas-based approach only occupied 30% of the SVS volume, ie, somewhat different anatomies were sampled. Furthermore, the new atlas-based approach showed highly reproducible GABA+/tCr values with a low median coefficient of variance of 6.3%. In conclusion, the atlas-based metabolite quantification approach enables a more brain structure-specific comparison of GABA+ and other neurochemical levels across populations, even when using an MRSI technique with only cm-level resolution. This approach was successfully cross-validated against the typically used SVS technique as well as other different MRSI analysis methods, indicating the robustness of this quantification approach.
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Affiliation(s)
- Ruoyun E. Ma
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
- School of Health Sciences, Purdue University, West Lafayette, IN, USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Ovidiu Andronesi
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Ulrike Dydak
- School of Health Sciences, Purdue University, West Lafayette, IN, USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
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Andronesi OC, Bhattacharyya PK, Bogner W, Choi IY, Hess AT, Lee P, Meintjes E, Tisdall MD, Zaitzev M, van der Kouwe A. Motion correction methods for MRS: experts' consensus recommendations. NMR IN BIOMEDICINE 2021; 34:e4364. [PMID: 33089547 PMCID: PMC7855523 DOI: 10.1002/nbm.4364] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2019] [Revised: 06/07/2020] [Accepted: 06/08/2020] [Indexed: 05/07/2023]
Abstract
Long acquisition times due to intrinsically low signal-to-noise ratio and the need for highly homogeneous B0 field make MRS particularly susceptible to motion or scanner instability compared with MRI. Motion-induced changes in both localization and shimming (ie B0 homogeneity) degrade MRS data quality. To mitigate the effects of motion three approaches can be employed: (1) subject immobilization, (2) retrospective correction, and (3) prospective real-time correction using internal and/or external tracking methods. Prospective real-time correction methods can simultaneously update localization and the B0 field to improve MRS data quality. While localization errors can be corrected with both internal (navigators) and external (optical camera, NMR probes) tracking methods, the B0 field correction requires internal navigator methods to measure the B0 field inside the imaged volume and the possibility to update the scanner shim hardware in real time. Internal and external tracking can rapidly update the MRS localization with submillimeter and subdegree precision, while scanner frequency and first-order shims of scanner hardware can be updated by internal methods every sequence repetition. These approaches are most well developed for neuroimaging, for which rigid transformation is primarily applicable. Real-time correction greatly improves the stability of MRS acquisition and quantification, as shown in clinical studies on subjects prone to motion, including children and patients with movement disorders, enabling robust measurement of metabolite signals including those with low concentrations, such as gamma-aminobutyric acid and glutathione. Thus, motion correction is recommended for MRS users and calls for tighter integration and wider availability of such methods by MR scanner manufacturers.
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Affiliation(s)
- Ovidiu C. Andronesi
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Corresponding Author: Ovidiu C. Andronesi, MD, PhD, Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Thirteenth Street, Charlestown, MA 02129, USA;
| | | | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University Vienna, Vienna, Austria
| | - In-Young Choi
- Department of Neurology, Hoglund Biomedical Imaging Center, University of Kansas Medical Center, Kansas City, KS, USA
| | - Aaron T. Hess
- University of Oxford Centre for Clinical Magnetic Resonance Research, Division of Cardiovascular Medicine, University of Oxford
| | - Phil Lee
- Department of Radiology, Hoglund Biomedical Imaging Center, University of Kansas Medical Center, Kansas City, KS, USA
| | - Ernesta Meintjes
- UCT Medical Imaging Research Unit, Division of Biomedical Engineering, Department of Human Biology, University of Cape Town
| | - M. Dylan Tisdall
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania
| | - Maxim Zaitzev
- Department of Radiology, Medical Physics, Medical Center, University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- High Field Magnetic Resonance Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - André van der Kouwe
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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Petracca M, Pontillo G, Moccia M, Carotenuto A, Cocozza S, Lanzillo R, Brunetti A, Brescia Morra V. Neuroimaging Correlates of Cognitive Dysfunction in Adults with Multiple Sclerosis. Brain Sci 2021; 11:346. [PMID: 33803287 PMCID: PMC8000635 DOI: 10.3390/brainsci11030346] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 03/02/2021] [Accepted: 03/04/2021] [Indexed: 02/06/2023] Open
Abstract
Cognitive impairment is a frequent and meaningful symptom in multiple sclerosis (MS), caused by the accrual of brain structural damage only partially counteracted by effective functional reorganization. As both these aspects can be successfully investigated through the application of advanced neuroimaging, here, we offer an up-to-date overview of the latest findings on structural, functional and metabolic correlates of cognitive impairment in adults with MS, focusing on the mechanisms sustaining damage accrual and on the identification of useful imaging markers of cognitive decline.
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Affiliation(s)
- Maria Petracca
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.P.); (M.M.); (A.C.); (V.B.M.)
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (G.P.); (S.C.); (A.B.)
- Department of Electrical Engineering and Information Technology, University of Naples “Federico II”, 80125 Naples, Italy
| | - Marcello Moccia
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.P.); (M.M.); (A.C.); (V.B.M.)
| | - Antonio Carotenuto
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.P.); (M.M.); (A.C.); (V.B.M.)
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (G.P.); (S.C.); (A.B.)
| | - Roberta Lanzillo
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.P.); (M.M.); (A.C.); (V.B.M.)
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (G.P.); (S.C.); (A.B.)
| | - Vincenzo Brescia Morra
- Department of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.P.); (M.M.); (A.C.); (V.B.M.)
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Gray Matter Atrophy in the Cortico-Striatal-Thalamic Network and Sensorimotor Network in Relapsing-Remitting and Primary Progressive Multiple Sclerosis. Neuropsychol Rev 2021; 31:703-720. [PMID: 33582965 DOI: 10.1007/s11065-021-09479-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Accepted: 01/04/2021] [Indexed: 02/05/2023]
Abstract
Gray matter atrophy in multiple sclerosis (MS) is thought to be associated with disability and cognitive impairment, but previous studies have sometimes had discordant results, and the atrophy patterns of relapsing-remitting multiple sclerosis (RRMS) and primary progressive multiple sclerosis (PPMS) remain to be clarified. We conducted a meta-analysis using anisotropic effect-size-based algorithms (AES-SDM) to identify consistent findings from whole-brain voxel-based morphometry (VBM) studies of gray matter volume (GMV) in 924 RRMS patients and 204 PPMS patients. This study is registered with PROSPERO (number CRD42019121319). Compared with healthy controls, RRMS and PPMS patients showed gray matter atrophy in the cortico-striatal-thalamic network, sensorimotor network, and bilateral insula. RRMS patients had a larger GMV in the left insula, cerebellum, right precentral gyrus, and bilateral putamen as well as a smaller GMV in the bilateral cingulate, caudate nucleus, right thalamus, superior temporal gyrus and left postcentral gyrus than PPMS patients. The disease duration, Expanded Disability Status Scale score, Paced Auditory Serial Addition Test z-score, and T2-weighted lesion load were associated with specific gray matter regions in RRMS or PPMS. Alterations in the cortico-striatal-thalamic networks, sensorimotor network, and insula may be involved in the common pathogenesis of RRMS and PPMS. The deficits in the cingulate gyrus and caudate nucleus are more apparent in RRMS than in PPMS. The more severe cerebellum atrophy in PPMS may be a brain feature associated with its neurological manifestations. These imaging biomarkers provide morphological evidence for the pathophysiology of MS and should be verified in future research.
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Zhu Y, Huang M, Zhao Y, Pei Y, Wang Y, Wang L, He T, Zhou F, Zeng X. Local functional connectivity of patients with acute and remitting multiple sclerosis: A Kendall's coefficient of concordance- and coherence-regional homogeneity study. Medicine (Baltimore) 2020; 99:e22860. [PMID: 33120824 PMCID: PMC7581181 DOI: 10.1097/md.0000000000022860] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 09/15/2020] [Accepted: 09/24/2020] [Indexed: 02/03/2023] Open
Abstract
Using Kendall's coefficient of concordance (KCC-) and Coherence (Cohe-) regional homogeneity (ReHo) to explore the alterations of brain local functional connectivity in acute and remitting relapsing-remitting multiple sclerosis (RRMS), and its clinical relevance.18 acute RRMS, 26 remitting RRMS and 20 healthy controls received resting-state functional magnetic resonance imaging scanning. After data preprocessing and ReHo (KCC-ReHo and Cohe-ReHo) calculation, analysis of variance and followed post hoc analysis was used to compare the KCC-ReHo or Cohe ReHo maps across groups.After analysis of variance analysis, regions with significant among-group differences detected by the 2 ReHo analysis were overlapped, these overlapped regions located in the left superior frontal gyrus (SFG), right SFG, left cuneus and right middle occipital gyrus (P < .01, Gaussian random field theory correction). Followed post hoc tests showed that, compared with healthy controls,Both acute and remitting RRMS patients has disease-related brain dysfunction, interestingly, relative to remitting RRMS, the acute RRMS patients mobilized more brain regions involving visual information processing in an attempt to maintain functional stability. In addition, our results also provide a methodological consideration for future ReHo analysis.
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Affiliation(s)
- Yanyan Zhu
- Department of Radiology, The First Affiliated Hospital, Nanchang University
- Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, Jiangxi, People's Republic of China
| | - Muhua Huang
- Department of Radiology, The First Affiliated Hospital, Nanchang University
- Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, Jiangxi, People's Republic of China
| | - Yanlin Zhao
- Department of Radiology, The First Affiliated Hospital, Nanchang University
- Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, Jiangxi, People's Republic of China
| | - Yixiu Pei
- Department of Radiology, The First Affiliated Hospital, Nanchang University
- Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, Jiangxi, People's Republic of China
| | - Yao Wang
- Department of Radiology, The First Affiliated Hospital, Nanchang University
- Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, Jiangxi, People's Republic of China
| | - Lei Wang
- Department of Radiology, The First Affiliated Hospital, Nanchang University
- Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, Jiangxi, People's Republic of China
| | - Ting He
- Department of Radiology, The First Affiliated Hospital, Nanchang University
- Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, Jiangxi, People's Republic of China
| | - Fuqing Zhou
- Department of Radiology, The First Affiliated Hospital, Nanchang University
- Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, Jiangxi, People's Republic of China
| | - Xianjun Zeng
- Department of Radiology, The First Affiliated Hospital, Nanchang University
- Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, Jiangxi, People's Republic of China
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Al-Iedani O, Ribbons K, Gholizadeh N, Lechner-Scott J, Quadrelli S, Lea R, Andronesi O, Ramadan S. Spiral MRSI and tissue segmentation of normal-appearing white matter and white matter lesions in relapsing remitting multiple sclerosis patients ☆. Magn Reson Imaging 2020; 74:21-30. [PMID: 32898652 DOI: 10.1016/j.mri.2020.09.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Revised: 09/02/2020] [Accepted: 09/02/2020] [Indexed: 12/17/2022]
Abstract
PURPOSE To evaluate the performance of novel spiral MRSI and tissue segmentation pipeline of the brain, to investigate neurometabolic changes in normal-appearing white matter (NAWM) and white matter lesions (WML) of stable relapsing remitting multiple sclerosis (RRMS) compared to healthy controls (HCs). METHODS Spiral 3D MRSI using LASER-GOIA-W [16,4] was undertaken on 16 RRMS patients and 9 HCs, to acquire MRSI data from a large volume of interest (VOI) 320 cm3 and analyzed using LCModel. MRSI data and voxel tissue segmentation were compared between the two cohorts using t-tests. Support vector machine (SVM) was used to classify tissue types and assessed by accuracy, sensitivity and specificity. RESULTS Compared to HCs, RRMS demonstrated a statistically significant reduction in all mean brain tissues and increase in CSF volume. Within VOI, WM decreased (-10%) and CSF increased (41%) in RRMS compared to HCs (p < 0.001). MRSI revealed that total creatine (tCr) ratios of N-acetylaspartate and glutamate+glutamine in WML were significantly lower than NAWM-MS (-9%, -8%) and HCs (-14%, -10%), respectively. Myo-inositol/tCr in WML was significantly higher than NAWM-MS (14%) and HCs (10%). SVM of MRSI yielded accuracy, sensitivity and specificity of 86%, 95%, and 70%, respectively for HCs vs WML, which were higher than HC vs NAWM and WML vs NAWM models. CONCLUSION This study demonstrates the benefit of MRSI in evaluating MS neurometabolic changes in NAWM. SVM of MRSI data in the MS brain may be suited for clinical monitoring and progression of MS patients. Longitudinal MRSI studies are warranted.
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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; Hunter Medical Research Institute, Newcastle, Australia
| | - Karen Ribbons
- Hunter Medical Research Institute, Newcastle, Australia
| | - Neda Gholizadeh
- School of Health Sciences, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW 2308, Australia
| | - Jeannette Lechner-Scott
- Hunter Medical Research Institute, Newcastle, Australia; Department of Neurology, John Hunter Hospital, New Lambton Heights, NSW 2305, Australia; School of Medicine and Public Health, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW 2305, Australia
| | - Scott Quadrelli
- Princess Alexandra Hospital, Radiology Department, Woolloongabba. QLD 4102, Australia; Faculty of Medicine, University of Queensland, Herston, QLD 4006, Australia
| | - Rodney Lea
- Hunter Medical Research Institute, Newcastle, Australia
| | - Ovidiu Andronesi
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, USA
| | - Saadallah Ramadan
- School of Health Sciences, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW 2308, Australia; Hunter Medical Research Institute, Newcastle, Australia.
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12
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Altered hypothalamic metabolism in early multiple sclerosis – MR spectroscopy study. J Neurol Sci 2019; 407:116458. [DOI: 10.1016/j.jns.2019.116458] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Revised: 08/19/2019] [Accepted: 09/10/2019] [Indexed: 12/31/2022]
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13
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Swanberg KM, Landheer K, Pitt D, Juchem C. Quantifying the Metabolic Signature of Multiple Sclerosis by in vivo Proton Magnetic Resonance Spectroscopy: Current Challenges and Future Outlook in the Translation From Proton Signal to Diagnostic Biomarker. Front Neurol 2019; 10:1173. [PMID: 31803127 PMCID: PMC6876616 DOI: 10.3389/fneur.2019.01173] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Accepted: 10/21/2019] [Indexed: 01/03/2023] Open
Abstract
Proton magnetic resonance spectroscopy (1H-MRS) offers a growing variety of methods for querying potential diagnostic biomarkers of multiple sclerosis in living central nervous system tissue. For the past three decades, 1H-MRS has enabled the acquisition of a rich dataset suggestive of numerous metabolic alterations in lesions, normal-appearing white matter, gray matter, and spinal cord of individuals with multiple sclerosis, but this body of information is not free of seeming internal contradiction. The use of 1H-MRS signals as diagnostic biomarkers depends on reproducible and generalizable sensitivity and specificity to disease state that can be confounded by a multitude of influences, including experiment group classification and demographics; acquisition sequence; spectral quality and quantifiability; the contribution of macromolecules and lipids to the spectroscopic baseline; spectral quantification pipeline; voxel tissue and lesion composition; T1 and T2 relaxation; B1 field characteristics; and other features of study design, spectral acquisition and processing, and metabolite quantification about which the experimenter may possess imperfect or incomplete information. The direct comparison of 1H-MRS data from individuals with and without multiple sclerosis poses a special challenge in this regard, as several lines of evidence suggest that experimental cohorts may differ significantly in some of these parameters. We review the existing findings of in vivo1H-MRS on central nervous system metabolic abnormalities in multiple sclerosis and its subtypes within the context of study design, spectral acquisition and processing, and metabolite quantification and offer an outlook on technical considerations, including the growing use of machine learning, by future investigations into diagnostic biomarkers of multiple sclerosis measurable by 1H-MRS.
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Affiliation(s)
- Kelley M Swanberg
- Department of Biomedical Engineering, Columbia University Fu Foundation School of Engineering and Applied Science, New York, NY, United States
| | - Karl Landheer
- Department of Biomedical Engineering, Columbia University Fu Foundation School of Engineering and Applied Science, New York, NY, United States
| | - David Pitt
- Department of Neurology, Yale University School of Medicine, New Haven, CT, United States
| | - Christoph Juchem
- Department of Biomedical Engineering, Columbia University Fu Foundation School of Engineering and Applied Science, New York, NY, United States.,Department of Radiology, Columbia University College of Physicians and Surgeons, New York, NY, United States
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14
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Liu T, Chen Y, Thomas AM, Song X. CEST MRI with distribution-based analysis for assessment of early stage disease activity in a mouse model of multiple sclerosis: An initial study. NMR IN BIOMEDICINE 2019; 32:e4139. [PMID: 31342587 DOI: 10.1002/nbm.4139] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2019] [Revised: 06/14/2019] [Accepted: 06/14/2019] [Indexed: 06/10/2023]
Abstract
Imaging biomarkers that can detect pathological changes at an early stage of multiple sclerosis (MS) may allow earlier therapeutic intervention with an improved outcome. Using a mouse model of MS, termed as experimental autoimmune encephalomyelitis (EAE), we performed chemical exchange saturation transfer (CEST) MRI at a very early stage before symptom onset (6 days post-induction) for assessment of changes in tissues that appear "normal" with conventional MRI. The collected CEST Z-spectra signals (Ssat /S0 ) were analyzed using a histogram-guided method to determine the contributions from various offset frequencies. Histogram analysis showed that EAE mice exhibit a more heterogeneous distribution with lower peak heights in the hindbrain compared with naïve mice at saturation offsets of 1 and 2 ppm. At these two offsets, both the mean Ssat /S0 and the mean MTRasym values in the cerebellum and brain stem are significantly different between EAE and naïve mice (P < 0.05). Immunofluorescent staining validated the presence of neuroinflammation, with IBA1-positive cells detected throughout the hindbrain including the cerebellum and brain stem. Follow-up MRI at the symptom onset (score = 1.5-2.5, 13 days post-induction) confirmed gadolinium-enhanced periventricular lesions. CEST Z-spectra signals also changed by this time. The proposed three-level histogram-oriented analysis is simple to execute and robust for detecting subtle changes in Z-spectra signals, which does not require a priori knowledge of damage locations or contributing offset components. CEST MRI signals at 1 and 2 ppm were sensitive to the subtle pathological changes at an early stage in EAE mice, and have potential as novel imaging biomarkers complementary to functional and physiological MRI measures.
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Affiliation(s)
- Tao Liu
- Russell H. Morgan Dept. of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, Maryland
- Dept. of Neurology, Hainan General Hospital, Haikou, Hainan, China
- Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Yanrong Chen
- Russell H. Morgan Dept. of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, Maryland
- Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland
- Dept. of Information Sciences and Technology, Northwest University, Xi'an, Shaanxi, China
| | - Aline M Thomas
- Russell H. Morgan Dept. of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, Maryland
- Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Xiaolei Song
- Russell H. Morgan Dept. of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, Maryland
- Cellular Imaging Section and Vascular Biology Program, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland
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15
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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: 233] [Impact Index Per Article: 46.6] [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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16
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Motyka S, Moser P, Hingerl L, Hangel G, Heckova E, Strasser B, Eckstein K, Daniel Robinson S, Poser BA, Gruber S, Trattnig S, Bogner W. The influence of spatial resolution on the spectral quality and quantification accuracy of whole-brain MRSI at 1.5T, 3T, 7T, and 9.4T. Magn Reson Med 2019; 82:551-565. [PMID: 30932248 PMCID: PMC6563461 DOI: 10.1002/mrm.27746] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2018] [Revised: 02/28/2019] [Accepted: 02/28/2019] [Indexed: 12/17/2022]
Abstract
PURPOSE Inhomogeneities in the static magnetic field (B0 ) deteriorate MRSI data quality by lowering the spectral resolution and SNR. MRSI with low spatial resolution is also prone to lipid bleeding. These problems are increasingly problematic at ultra-high fields. An approach to tackling these challenges independent of B0 -shim hardware is to increase the spatial resolution. Therefore, we investigated the effect of improved spatial resolution on spectral quality and quantification at 4 field strengths. METHODS Whole-brain MRSI data was simulated for 3 spatial resolutions and 4 B0 s based on experimentally acquired MRI data and simulated free induction decay signals of metabolites and lipids. To compare the spectral quality and quantification, we derived SNR normalized to the voxel size (nSNR), linewidth and metabolite concentration ratios, their Cramer-Rao-lower-bounds (CRLBs), and the absolute percentage error (APE) of estimated concentrations compared to the gold standard for the whole-brain and 8 brain regions. RESULTS At 7T, we found up to a 3.4-fold improved nSNR (in the frontal lobe) and a 2.8-fold reduced linewidth (in the temporal lobe) for 1 cm3 versus 0.25 cm3 resolution. This effect was much more pronounced at higher and less homogenous B0 (1.6-fold improved nSNR and 1.8-fold improved linewidth in the parietal lobe at 3T). This had direct implications for quantification: the volume of reliably quantified spectra increased with resolution by 1.2-fold and 1.5-fold (when thresholded by CRLBs or APE, respectively). CONCLUSION MRSI data quality benefits from increased spatial resolution particularly at higher B0 , and leads to more reliable metabolite quantification. In conjunction with the development of better B0 shimming hardware, this will enable robust whole-brain MRSI at ultra-high field.
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Affiliation(s)
- Stanislav Motyka
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Philipp Moser
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Lukas Hingerl
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Gilbert Hangel
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Eva Heckova
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Bernhard Strasser
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.,Department of Radiology, Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Korbinian Eckstein
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Simon Daniel Robinson
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Benedikt A Poser
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands.,Maastricht Brain Imaging Centre, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Stephan Gruber
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Siegfried Trattnig
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.,Christian Doppler Laboratory for Clinical Molecular MR Imaging, Medical University of Vienna, Vienna, Austria
| | - Wolfgang Bogner
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
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17
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Maghsudi H, Schütze M, Maudsley AA, Dadak M, Lanfermann H, Ding XQ. Age-related Brain Metabolic Changes up to Seventh Decade in Healthy Humans : Whole-brain Magnetic Resonance Spectroscopic Imaging Study. Clin Neuroradiol 2019; 30:581-589. [PMID: 31350597 DOI: 10.1007/s00062-019-00814-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Accepted: 07/03/2019] [Indexed: 12/28/2022]
Abstract
PURPOSE To study brain metabolic changes under normal aging and to collect reference data for the study of neurodegenerative diseases. METHODS A total of 55 healthy subjects aged 20-70 years (n ≥ 5 per age decade for each gender) underwent whole-brain magnetic resonance spectroscopic imaging at 3T after completing a DemTect test and the Beck depressions inventory II to exclude cognitive impairment and mental disorder. Regional concentrations of N-acetylaspartate (NAA), choline-containing compounds (Cho), total creatine (tCr), glutamine and glutamate (Glx), and myo-inositol (mI) were determined in 12 brain regions of interest (ROIs). The two-sided t‑test was used to estimate gender differences and linear regression analysis was carried out to estimate age dependence of brain regional metabolite contents. RESULTS Brain regional metabolite concentrations changed with age in the majority of selected brain regions. The NAA decreased in 8 ROIs with a rate varying from -4.9% to -1.9% per decade, reflecting a general reduction of brain neuronal function or volume and density in older age; Cho increased in 4 ROIs with a rate varying from 4.3% to 6.1%; tCr and mI increased in one ROI (4.2% and 8.2% per decade, respectively), whereas Glx decreased in one ROI (-5.1% per decade), indicating an inhomogeneous increase of cell membrane turnover (Cho) with altered energy metabolism (tCr) and glutamatergic neuronal activity (Glx) as well as function of glia cell (mI) in normal aging brain. CONCLUSION Healthy aging up to the seventh decade of life is associated with regional dependent alterations of brain metabolism. These results provide a reference database for future studies of patients.
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Affiliation(s)
- Helen Maghsudi
- Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany.
| | - Martin Schütze
- Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
| | - Andrew A Maudsley
- Department of Radiology, University of Miami School of Medicine, Miami, FL, USA
| | - Mete Dadak
- Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
| | - Heinrich Lanfermann
- Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
| | - Xiao-Qi Ding
- Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
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18
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Heckova E, Strasser B, Hangel GJ, Považan M, Dal-Bianco A, Rommer PS, Bednarik P, Gruber S, Leutmezer F, Lassmann H, Trattnig S, Bogner W. 7 T Magnetic Resonance Spectroscopic Imaging in Multiple Sclerosis: How Does Spatial Resolution Affect the Detectability of Metabolic Changes in Brain Lesions? Invest Radiol 2019; 54:247-254. [PMID: 30433892 PMCID: PMC7612616 DOI: 10.1097/rli.0000000000000531] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVES The aim of this study was to assess the utility of increased spatial resolution of magnetic resonance spectroscopic imaging (MRSI) at 7 T for the detection of neurochemical changes in multiple sclerosis (MS)-related brain lesions. MATERIALS AND METHODS This prospective, institutional review board-approved study was performed in 20 relapsing-remitting MS patients (9 women/11 men; mean age ± standard deviation, 30.8 ± 7.7 years) after receiving written informed consent. Metabolic patterns in MS lesions were compared at 3 different spatial resolutions of free induction decay MRSI with implemented parallel imaging acceleration: 2.2 × 2.2 × 8 mm; 3.4 × 3.4 × 8 mm; and 6.8 × 6.8 × 8 mm voxel volumes, that is, matrix sizes of 100 × 100, 64 × 64, and 32 × 32, respectively. The quality of data was assessed by signal-to-noise ratio and Cramér-Rao lower bounds. Statistical analysis was performed using Wilcoxon signed-rank tests with correction for multiple testing. RESULTS Seventy-seven T2-hyperintense MS lesions were investigated (median volume, 155.7 mm; range, 10.8-747.0 mm). The mean metabolic ratios in lesions differed significantly between the 3 MRSI resolutions (ie, 100 × 100 vs 64 × 64, 100 × 100 vs 32 × 32, and 64 × 64 vs 32 × 32; P < 0.001). With the ultra-high resolution (100 × 100), we obtained 40% to 80% higher mean metabolic ratios and 100% to 150% increase in maximum metabolic ratios in the MS lesions compared with the lowest resolution (32 × 32), while maintaining good spectral quality (signal-to-noise ratio >12, Cramér-Rao lower bounds <20%) and measurement time of 6 minutes. There were 83% of MS lesions that showed increased myo-inositol/N-acetylaspartate with the 100 × 100 resolution, but only 66% were distinguishable with the 64 × 64 resolution and 35% with the 32 × 32 resolution. CONCLUSIONS Ultra-high-resolution MRSI (~2 × 2 × 8 mm voxel volume) can detect metabolic alterations in MS, which cannot be recognized by conventional MRSI resolutions, within clinically acceptable time.
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Affiliation(s)
- Eva Heckova
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Bernhard Strasser
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States
| | - Gilbert J. Hangel
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Michal Považan
- Russell H. Morgan Department of Radiology and Radiological Science, The John Hopkins University School of Medicine, Baltimore, Maryland, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, United States
| | | | - Paulus S. Rommer
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Petr Bednarik
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Stephan Gruber
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Fritz Leutmezer
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Hans Lassmann
- Center for Brain Research, Medical University of Vienna, Vienna, Austria
| | - Siegfried Trattnig
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
- Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria
| | - Wolfgang Bogner
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
- Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria
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19
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Abstract
PURPOSE OF REVIEW Clinical MRI is of paramount importance for multiple sclerosis diagnosis but lacks the specificity to investigate the pathogenic mechanisms underlying disease onset and progression. The application of advanced MR sequences allows the characterization of diverse and complex pathological mechanisms, granting insights into multiple sclerosis natural history and response to treatment. RECENT FINDINGS This review provides an update on the most recent international guidelines for optimal standard imaging of multiple sclerosis and discusses advantages and limitations of advanced imaging approaches for investigating inflammation, demyelination and neurodegeneration. An overview is provided for methods devoted to imaging leptomeningeal enhancement, microglial activation, demyelination, neuronal metabolic damage and neuronal loss. SUMMARY The application of magnetic resonance (MR) guidelines to standard-of-care MR protocols, although still limited, would substantially contribute to the optimization of multiple sclerosis management. From an academic perspective, different mechanism-specific imaging techniques are available and offer a powerful tool to elucidate multiple sclerosis pathogenesis, monitor disease progression and guide therapeutic choices.
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20
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Tyurina AN, Fadeeva LM, Kornienko VN, Zakharova NE, Batalov AI, Mertsalova MP, Rodionov PV, Pogosbekyan EL, Pronin IN. [3D proton MR spectroscopy of the gray and white brain matter. A study of 15 volunteers]. ZHURNAL VOPROSY NEĬROKHIRURGII IMENI N. N. BURDENKO 2019; 82:23-29. [PMID: 30721214 DOI: 10.17116/neiro20188206123] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
One of the important problems of modern diagnostics of brain diseases is detection of early lesions, which determines the choice of patient management and the disease outcome. The introduction of magnetic resonance imaging in practice has significantly improved the quality of diagnosis. Multivoxel proton magnetic resonance spectroscopy is an additional and clarifying technique enabling non-invasive examination of changes in brain metabolism in tumors as well as simultaneous acquisition of information on metabolism in surrounding tissues and in the intact brain matter. Along with single voxel MR spectroscopy (SV MRS) and 2D MRS (CSI Chemical Shift Imaging), 3D proton MRS (MRSI) has been increasingly used in clinical practice, which enables single-run acquisition of data on the metabolite composition for the entire volume of interest. OBJECTIVE To assess the possibility of using multivoxel 3D proton MRS in healthy volunteers without organic brain pathology. MATERIAL AND METHODS In this study, 15 volunteers without organic brain pathology were examined using the 3D 1H-MRS. CONCLUSION 3D proton MRS has proven to be an effective technique in studying the brain metabolism. One short-term series of examinations provided information on intact brain metabolism at different anatomical levels, which enabled their comparison both in spectral data and in parametric maps of the major metabolite distribution.
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Affiliation(s)
- A N Tyurina
- Burdenko Neurosurgical Institute, Moscow, Russia
| | - L M Fadeeva
- Burdenko Neurosurgical Institute, Moscow, Russia
| | | | | | - A I Batalov
- Burdenko Neurosurgical Institute, Moscow, Russia
| | | | - P V Rodionov
- Burdenko Neurosurgical Institute, Moscow, Russia
| | | | - I N Pronin
- Burdenko Neurosurgical Institute, Moscow, Russia
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21
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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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22
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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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23
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O'Grady KP, Dula AN, Lyttle BD, Thompson LM, Conrad BN, Box BA, McKeithan LJ, Pawate S, Bagnato F, Landman BA, Newhouse P, Smith SA. Glutamate-sensitive imaging and evaluation of cognitive impairment in multiple sclerosis. Mult Scler 2018; 25:1580-1592. [PMID: 30230400 DOI: 10.1177/1352458518799583] [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] [Indexed: 01/05/2023]
Abstract
BACKGROUND Cognitive impairment (CI) profoundly impacts quality of life for patients with multiple sclerosis (MS). Dysfunctional regulation of glutamate in gray matter (GM) has been implicated in the pathogenesis of MS by post-mortem pathological studies and in CI by in vivo magnetic resonance spectroscopy, yet GM pathology is subtle and difficult to detect using conventional T1- and T2-weighted magnetic resonance imaging (MRI). There is a need for high-resolution, clinically accessible imaging techniques that probe molecular changes in GM. OBJECTIVE To study cortical GM pathology related to CI in MS using glutamate-sensitive chemical exchange saturation transfer (GluCEST) MRI at 7.0 Tesla (7T). METHODS A total of 20 patients with relapsing-remitting MS and 20 healthy controls underwent cognitive testing, anatomical imaging, and GluCEST imaging. Glutamate-sensitive image contrast was quantified for cortical GM, compared between cohorts, and correlated with clinical measures of CI. RESULTS AND CONCLUSION Glutamate-sensitive contrast was significantly increased in the prefrontal cortex of MS patients with accumulated disability (p < 0.05). In addition, glutamate-sensitive contrast in the prefrontal cortex was significantly correlated with symbol digit modality test (rS = -0.814) and choice reaction time (rS = 0.772) scores in patients (p < 0.05), suggesting that GluCEST MRI may have utility as a marker for GM pathology and CI.
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Affiliation(s)
- Kristin P O'Grady
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Adrienne N Dula
- Department of Neurology, Dell Medical School, The University of Texas at Austin, Austin, TX, USA
| | - Bailey D Lyttle
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lindsey M Thompson
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Benjamin N Conrad
- Neuroscience Graduate Program, Vanderbilt Brain Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Bailey A Box
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lydia J McKeithan
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Siddharama Pawate
- Vanderbilt Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Francesca Bagnato
- Neuroimaging Unit, Neuroimmunology Division, Vanderbilt Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Bennett A Landman
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA/Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA/Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA/Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Paul Newhouse
- Department of Psychiatry and Behavioral Sciences, Center for Cognitive Medicine, Vanderbilt University Medical Center, Nashville, TN, USA/Veterans Affairs Tennessee Valley Healthcare System Geriatric Research, Education, and Clinical Center (VA TVHS GRECC), Nashville, TN, USA
| | - Seth A Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA/Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA/Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
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24
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Abstract
Multiple sclerosis is a multifactorial disease with heterogeneous pathogenetic mechanisms, which deserve to be studied to evaluate new possible targets for treatments and improve patient management. MR spectroscopy and PET allow assessing in vivo the molecular and metabolic mechanisms underlying the pathogenesis of multiple sclerosis. This article focuses on the relationship between these imaging techniques and the biologic and chemical pathways leading to multiple sclerosis pathology and its clinical features. Future directions of research are also presented.
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Affiliation(s)
- Marcello Moccia
- NMR Research Unit, Queen Square MS Centre, University College London, Institute of Neurology, 10-12 Russell Square, London WC1B 5EH, UK; MS Clinical Care and Research Centre, Department of Neuroscience, Federico II University, Via Sergio Pansini 5, Naples 80131, Italy
| | - Olga Ciccarelli
- NMR Research Unit, Queen Square MS Centre, University College London, Institute of Neurology, 10-12 Russell Square, London WC1B 5EH, UK; NIHR University College London Hospitals, Biomedical Research Centre, Maple House Suite A 1st floor, 149 Tottenham Court Road, London W1T 7DN, UK.
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25
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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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26
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Schirda CV, Zhao T, Yushmanov VE, Lee Y, Ghearing GR, Lieberman FS, Panigrahy A, Hetherington HP, Pan JW. Fast 3D rosette spectroscopic imaging of neocortical abnormalities at 3 T: Assessment of spectral quality. Magn Reson Med 2017; 79:2470-2480. [PMID: 28905419 DOI: 10.1002/mrm.26901] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2017] [Revised: 08/11/2017] [Accepted: 08/14/2017] [Indexed: 12/24/2022]
Abstract
PURPOSE To use a fast 3D rosette spectroscopic imaging acquisition to quantitatively evaluate how spectral quality influences detection of the endogenous variation of gray and white matter metabolite differences in controls, and demonstrate how rosette spectroscopic imaging can detect metabolic dysfunction in patients with neocortical abnormalities. METHODS Data were acquired on a 3T MR scanner and 32-channel head coil, with rosette spectroscopic imaging covering a 4-cm slab of fronto-parietal-temporal lobes. The influence of acquisition parameters and filtering on spectral quality and sensitivity to tissue composition was assessed by LCModel analysis, the Cramer-Rao lower bound, and the standard errors from regression analyses. The optimized protocol was used to generate normative white and gray matter regressions and evaluate three patients with neocortical abnormalities. RESULTS As a measure of the sensitivity to detect abnormalities, the standard errors of regression for Cr/NAA and Ch/NAA were significantly correlated with the Cramer-Rao lower bound values (R = 0.89 and 0.92, respectively, both with P < 0.001). The rosette acquisition with a duration of 9.6 min, produces a mean Cramer-Rao lower bound (%) over the entire slab of 4.6 ± 2.6 and 5.8 ± 2.3 for NAA and Cr, respectively. This enables a Cr/NAA standard error of 0.08 (i.e., detection sensitivity of 25% for a 50/50 mixed gray and white matter voxel). In healthy controls, the regression of Cr/NAA versus fraction gray matter in the cingulate differs from frontal and parietal regions. CONCLUSIONS Fast rosette spectroscopic imaging acquisitions with regression analyses are able to identify metabolic differences across 4-cm slabs of the brain centrally and over the cortical periphery with high efficiency, generating results that are consistent with clinical findings. Magn Reson Med 79:2470-2480, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Claudiu V Schirda
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Tiejun Zhao
- Siemens Healthcare, Siemens Medical Solutions USA Inc, Pittsburgh, Pennsylvania, USA
| | - Victor E Yushmanov
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Yoojin Lee
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Gena R Ghearing
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Frank S Lieberman
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Ashok Panigrahy
- Department of Pediatric Radiology, Children's Hospital of Pittsburgh, UPMC, Pittsburgh, Pennsylvania, USA
| | - Hoby P Hetherington
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Jullie W Pan
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.,Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
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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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