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Nossa G, Monsivais H, Lee CG, Francis G, Wells EM, Park JH, Dydak U. Do toenail manganese and iron levels reflect brain metal levels or brain metabolism in welders? Neurotoxicology 2024:S0161-813X(24)00079-2. [PMID: 39002648 DOI: 10.1016/j.neuro.2024.07.007] [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: 04/05/2024] [Revised: 06/14/2024] [Accepted: 07/10/2024] [Indexed: 07/15/2024]
Abstract
Inhalation of welding fumes can cause metal accumulation in the brain, leading to Parkinsonian-like symptoms. Metal accumulation and altered neurochemical profiles have been observed using magnetic resonance imaging (MRI) in highly exposed welders, being associated with decreased motor function and cognition. While MRI is impractical to use as a health risk assessment tool in occupational settings, toenail metal levels are easier to assess and have been demonstrated to reflect an exposure window of7-12 months in the past. Yet, it is unclear whether toenail metal levels are associated with brain metal levels or changes in metabolism, which are the root of potential health concerns. This study investigates whether toenail manganese (Mn) and iron (Fe) levels, assessed at several time points, correlate with brain Mn and Fe levels, measured by MRI, as well as brain GABA, glutamate (Glu), and glutathione (GSH) levels, measured by Magnetic Resonance Spectroscopy (MRS), in seventeen Mn-exposed welders. Quantitative T1 and R2* MRI maps of the whole brain, along with GABA, Glu, and GSH MRS measurements from the thalamus and cerebellum were acquired at baseline (T0). Toenail clippings were collected at T0 and every three months after the MRI for a year to account for different exposure periods being reflected by toenail clippings and MRI. Spearman correlations of toenail metal levels were run against brain metal and metabolite levels, but no significant associations were found for Mn at any timepoint. Cerebellar GSH positively correlated with toenail Fe clipped twelve months after the MRI (p = 0.05), suggesting an association with Fe exposure at the time of the MRI. Neither thalamic GABA nor Glu correlated with toenail Fe levels. In conclusion, this study cannot support toenail Mn as a proxy for brain Mn levels or metabolic changes, while toenail Fe appears linked to brain metabolic alterations, underscoring the importance of considering other metals, including Fe, in studying Mn neurotoxicity.
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Affiliation(s)
- Gianna Nossa
- School of Health Sciences, Purdue University, West Lafayette, IN, United States
| | - Humberto Monsivais
- School of Health Sciences, Purdue University, West Lafayette, IN, United States
| | - Chang Geun Lee
- School of Health Sciences, Purdue University, West Lafayette, IN, United States
| | - Grace Francis
- School of Health Sciences, Purdue University, West Lafayette, IN, United States
| | - Ellen M Wells
- School of Health Sciences, Purdue University, West Lafayette, IN, United States; Department of Public Health, Purdue University, West Lafayette, IN, United States
| | - Jae Hong Park
- School of Health Sciences, Purdue University, West Lafayette, IN, United States
| | - Ulrike Dydak
- School of Health Sciences, Purdue University, West Lafayette, IN, United States; Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, United States.
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2
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Thomson AR, Pasanta D, Arichi T, Puts NA. Neurometabolite differences in Autism as assessed with Magnetic Resonance Spectroscopy: A systematic review and meta-analysis. Neurosci Biobehav Rev 2024; 162:105728. [PMID: 38796123 DOI: 10.1016/j.neubiorev.2024.105728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 04/23/2024] [Accepted: 05/14/2024] [Indexed: 05/28/2024]
Abstract
1H-Magnetic Resonance Spectroscopy (MRS) is a non-invasive technique that can be used to quantify the concentrations of metabolites in the brain in vivo. MRS findings in the context of autism are inconsistent and conflicting. We performed a systematic review and meta-analysis of MRS studies measuring glutamate and gamma-aminobutyric acid (GABA), as well as brain metabolites involved in energy metabolism (glutamine, creatine), neural and glial integrity (e.g. n-acetyl aspartate (NAA), choline, myo-inositol) and oxidative stress (glutathione) in autism cohorts. Data were extracted and grouped by metabolite, brain region and several other factors before calculation of standardised effect sizes. Overall, we find significantly lower concentrations of GABA and NAA in autism, indicative of disruptions to the balance between excitation/inhibition within brain circuits, as well as neural integrity. Further analysis found these alterations are most pronounced in autistic children and in limbic brain regions relevant to autism phenotypes. Additionally, we show how study outcome varies due to demographic and methodological factors , emphasising the importance of conforming with standardised consensus study designs and transparent reporting.
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Affiliation(s)
- Alice R Thomson
- Department of Forensic and Neurodevelopmental Sciences, King's College London, UK; MRC Centre for Neurodevelopmental Disorders, King's College London, UK; Centre for the Developing Brain, King's College London, London, UK
| | - Duanghathai Pasanta
- Department of Forensic and Neurodevelopmental Sciences, King's College London, UK
| | - Tomoki Arichi
- MRC Centre for Neurodevelopmental Disorders, King's College London, UK; Centre for the Developing Brain, King's College London, London, UK
| | - Nicolaas A Puts
- Department of Forensic and Neurodevelopmental Sciences, King's College London, UK; MRC Centre for Neurodevelopmental Disorders, King's College London, UK.
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3
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Hui SCN, Murali-Manohar S, Zöllner HJ, Hupfeld KE, Davies-Jenkins CW, Gudmundson AT, Song Y, Yedavalli V, Wisnowski JL, Gagoski B, Oeltzschner G, Edden RAE. Integrated Short-TE and Hadamard-edited Multi-Sequence (ISTHMUS) for advanced MRS. J Neurosci Methods 2024; 409:110206. [PMID: 38942238 DOI: 10.1016/j.jneumeth.2024.110206] [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: 02/22/2024] [Revised: 05/20/2024] [Accepted: 06/21/2024] [Indexed: 06/30/2024]
Abstract
BACKGROUND To examine data quality and reproducibility using ISTHMUS, which has been implemented as the standardized MR spectroscopy sequence for the multi-site Healthy Brain and Child Development (HBCD) study. METHODS ISTHMUS is the consecutive acquisition of short-TE PRESS (32 transients) and long-TE HERCULES (224 transients) data with dual-TE water reference scans. Voxels were positioned in the centrum semiovale, dorsal anterior cingulate cortex, posterior cingulate cortex and bilateral thalamus regions. After acquisition, ISTHMUS data were separated into the PRESS and HERCULES portions for analysis and modeled separately using Osprey. In vivo experiments were performed in 10 healthy volunteers (6 female; 29.5±6.6 years). Each volunteer underwent two scans on the same day. Differences in metabolite measurements were examined. T2 correction based on the dual-TE water integrals were compared with: 1) T2 correction based on the default white matter and gray matter T2 reference values in Osprey and 2) shorter WM and GM T2 values from recent literature. RESULTS No significant difference in linewidth was observed between PRESS and HERCULES. Bilateral thalamus spectra had produced significantly higher (p<0.001) linewidth compared to the other three regions. Linewidth measurements were similar between scans, with scan-to-scan differences under 1 Hz for most subjects. Paired t-tests indicated a significant difference only in PRESS NAAG between the two thalamus scans (p=0.002). T2 correction based on shorter T2 values showed better agreement to the dual-TE water integral ratio. CONCLUSIONS ISTHMUS facilitated data acquisition and post-processing and reduced operator workload to eliminate potential human error.
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Affiliation(s)
- Steve C N Hui
- Developing Brain Institute, Children's National Hospital, Washington, D.C., USA; Department of Radiology, The George Washington University School of Medicine and Health Sciences, Washington, D.C., USA; Department of Pediatrics, The George Washington University School of Medicine and Health Sciences, Washington, D.C., USA
| | - Saipavitra Murali-Manohar
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Helge J Zöllner
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Kathleen E Hupfeld
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Christopher W Davies-Jenkins
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Aaron T Gudmundson
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Yulu Song
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Vivek Yedavalli
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Jessica L Wisnowski
- Department of Radiology, Children's Hospital Los Angeles, Los Angeles, CA, USA; Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Borjan Gagoski
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Georg Oeltzschner
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Richard A E Edden
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.
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Sapey-Triomphe LA, Puts NAJ, Costa TL, Wagemans J. GABA and Glx predict EEG responses of visual sensitivity in autism. Autism Res 2024; 17:917-922. [PMID: 38576253 DOI: 10.1002/aur.3130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 03/21/2024] [Indexed: 04/06/2024]
Abstract
The mechanisms underlying atypical sensory processing in autism remain to be elucidated, but research points toward a role of the glutamatergic/GABAergic balance. To investigate the potential relationships between visual sensitivity and its molecular correlates in autism, we combined data from electroencephalography (EEG) and magnetic resonance spectroscopy (MRS) studies. Twenty autistic adults and sixteen neurotypical adults (NT) participated in both an EEG study assessing visual sensitivity (Sapey-Triomphe et al., Autism Research, 2023) and in an MRS study measuring Glx and GABA+ concentrations in the occipital cortex (Sapey-Triomphe et al., Molecular Autism, 2021). These studies revealed no group differences in neural detection thresholds or in Glx/GABA levels in the occipital cortex. Neural detection thresholds for contrast and spatial frequency (SF) were determined using fast periodic visual stimulations and neural frequency tagging. In the present study, Glx/GABA+ concentrations in the occipital cortex and neural detection thresholds did not differ between groups. Interestingly, lower Glx/GABA+ ratios were associated with lower contrast detection thresholds and higher SF detection thresholds. These correlations were also significant within the neurotypical and autistic groups. This report suggests that the Glx/GABA balance regulates visual detection thresholds across individuals. In both autistic and NTs, lower Glx/GABA ratios in the occipital cortex allow for better detection of visual inputs at the neural level. This study sheds light on the neurochemical underpinnings of visual sensitivity in autism and warrants further investigation.
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Affiliation(s)
- Laurie-Anne Sapey-Triomphe
- Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, Leuven, Belgium
- Université Claude Bernard Lyon 1, CNRS, INSERM, Centre de Recherche en Neurosciences de Lyon CRNL U1028 UMR5292, CAP Team, Bron, France
| | - Nicolaas A J Puts
- Department of Forensic and Neurodevelopmental Sciences and the Institute of Psychiatry, Psychology, and Neuroscience, Sackler Institute for Translational Neurodevelopment, King's College London, London, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - Thiago L Costa
- Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, Leuven, Belgium
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Johan Wagemans
- Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, Leuven, Belgium
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5
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Whelan TP, Daly E, Puts NA, Smith P, Allison C, Baron-Cohen S, Malievskaia E, Murphy DGM, McAlonan GM. The 'PSILAUT' protocol: an experimental medicine study of autistic differences in the function of brain serotonin targets of psilocybin. BMC Psychiatry 2024; 24:319. [PMID: 38658877 PMCID: PMC11044362 DOI: 10.1186/s12888-024-05768-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 04/15/2024] [Indexed: 04/26/2024] Open
Abstract
BACKGROUND The underlying neurobiology of the complex autism phenotype remains obscure, although accumulating evidence implicates the serotonin system and especially the 5HT2A receptor. However, previous research has largely relied upon association or correlation studies to link differences in serotonin targets to autism. To directly establish that serotonergic signalling is involved in a candidate brain function our approach is to change it and observe a shift in that function. We will use psilocybin as a pharmacological probe of the serotonin system in vivo. We will directly test the hypothesis that serotonergic targets of psilocybin - principally, but not exclusively, 5HT2A receptor pathways-function differently in autistic and non-autistic adults. METHODS The 'PSILAUT' "shiftability" study is a case-control study autistic and non-autistic adults. How neural responses 'shift' in response to low doses (2 mg and 5 mg) of psilocybin compared to placebo will be examined using multimodal techniques including functional MRI and EEG. Each participant will attend on up to three separate visits with drug or placebo administration in a double-blind and randomized order. RESULTS This study will provide the first direct evidence that the serotonin targets of psilocybin function differently in the autistic and non-autistic brain. We will also examine individual differences in serotonin system function. CONCLUSIONS This work will inform our understanding of the neurobiology of autism as well as decisions about future clinical trials of psilocybin and/or related compounds including stratification approaches. TRIAL REGISTRATION NCT05651126.
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Affiliation(s)
- Tobias P Whelan
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- COMPASS Pathfinder Ltd, London, UK
| | - Eileen Daly
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Nicolaas A Puts
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Medical Research Council Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - Paula Smith
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Carrie Allison
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Simon Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | | | - Declan G M Murphy
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Medical Research Council Centre for Neurodevelopmental Disorders, King's College London, London, UK
- NIHR-Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and the Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Grainne M McAlonan
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
- Medical Research Council Centre for Neurodevelopmental Disorders, King's College London, London, UK.
- NIHR-Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and the Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
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6
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Hui SC, Murali-Manohar S, Zöllner HJ, Hupfeld KE, Davies-Jenkins CW, Gudmundson AT, Song Y, Yedavalli V, Wisnowski JL, Gagoski B, Oeltzschner G, Edden RA. Integrated Short-TE and Hadamard-edited Multi-Sequence (ISTHMUS) for Advanced MRS. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.15.580516. [PMID: 38659947 PMCID: PMC11042202 DOI: 10.1101/2024.02.15.580516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
Background To examine data quality and reproducibility using ISTHMUS, which has been implemented as the standardized MR spectroscopy sequence for the multi-site Healthy Brain and Child Development (HBCD) study. Methods ISTHMUS is the consecutive acquisition of short-TE PRESS (32 transients) and long-TE HERCULES (224 transients) data with dual-TE water reference scans. Voxels were positioned in the centrum semiovale, dorsal anterior cingulate cortex, posterior cingulate cortex and bilateral thalamus regions. After acquisition, ISTHMUS data were separated into the PRESS and HERCULES portions for analysis and modeled separately using Osprey. In vivo experiments were performed in 10 healthy volunteers (6 female; 29.5±6.6 years). Each volunteer underwent two scans on the same day. Differences in metabolite measurements were examined. T2 correction based on the dual-TE water integrals were compared with: 1) T2 correction based the default white matter and gray matter T2 reference values in Osprey; 2) shorter WM and GM T2 values from recent literature; and 3) reduced CSF fractions. Results No significant difference in linewidth was observed between PRESS and HERCULES. Bilateral thalamus spectra had produced significantly higher (p<0.001) linewidth compared to the other three regions. Linewidth measurements were similar between scans, with scan-to-scan differences under 1 Hz for most subjects. Paired t-tests indicated a significant difference only in PRESS NAAG between the two thalamus scans (p=0.002). T2 correction based on shorter T2 values showed better agreement to the dual-TE water integral ratio. Conclusions ISTHMUS facilitated and standardized acquisition and post-processing and reduced operator workload to eliminate potential human error.
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Affiliation(s)
- Steve C.N. Hui
- Developing Brain Institute, Children’s National Hospital, Washington, D.C. USA
- Departments of Radiology, The George Washington University School of Medicine and Health Sciences, Washington, D.C. USA
- Departments of Pediatrics, The George Washington University School of Medicine and Health Sciences, Washington, D.C. USA
| | - Saipavitra Murali-Manohar
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Helge J. Zöllner
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Kathleen E. Hupfeld
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Christopher W. Davies-Jenkins
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Aaron T. Gudmundson
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Yulu Song
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Vivek Yedavalli
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Jessica L Wisnowski
- Department of Radiology, Children’s Hospital Los Angeles, Los Angeles, CA, USA
- Department of Pediatrics, Children’s Hospital Los Angeles, Los Angeles, CA, USA
| | - Borjan Gagoski
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Boston, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Georg Oeltzschner
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Richard A.E. Edden
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
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7
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Song Y, Hupfeld KE, Davies-Jenkins CW, Zöllner HJ, Murali-Manohar S, Mumuni AN, Crocetti D, Yedavalli V, Oeltzschner G, Alessi N, Batschelett MA, Puts NA, Mostofsky SH, Edden RA. Brain glutathione and GABA+ levels in autistic children. Autism Res 2024; 17:512-528. [PMID: 38279628 PMCID: PMC10963146 DOI: 10.1002/aur.3097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 12/28/2023] [Indexed: 01/28/2024]
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by social communication challenges and repetitive behaviors. Altered neurometabolite levels, including glutathione (GSH) and gamma-aminobutyric acid (GABA), have been proposed as potential contributors to the biology underlying ASD. This study investigated whether cerebral GSH or GABA levels differ between a cohort of children aged 8-12 years with ASD (n = 52) and typically developing children (TDC, n = 49). A comprehensive analysis of GSH and GABA levels in multiple brain regions, including the primary motor cortex (SM1), thalamus (Thal), medial prefrontal cortex (mPFC), and supplementary motor area (SMA), was conducted using single-voxel HERMES MR spectroscopy at 3T. The results revealed no significant differences in cerebral GSH or GABA levels between the ASD and TDC groups across all examined regions. These findings suggest that the concentrations of GSH (an important antioxidant and neuromodulator) and GABA (a major inhibitory neurotransmitter) do not exhibit marked alterations in children with ASD compared to TDC. A statistically significant positive correlation was observed between GABA levels in the SM1 and Thal regions with ADHD inattention scores. No significant correlation was found between metabolite levels and hyper/impulsive scores of ADHD, measures of core ASD symptoms (ADOS-2, SRS-P) or adaptive behavior (ABAS-2). While both GSH and GABA have been implicated in various neurological disorders, the current study provides valuable insights into the specific context of ASD and highlights the need for further research to explore other neurochemical alterations that may contribute to the pathophysiology of this complex disorder.
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Affiliation(s)
- Yulu Song
- The Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Kathleen E. Hupfeld
- The Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Christopher W. Davies-Jenkins
- The Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Helge J. Zöllner
- The Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Saipavitra Murali-Manohar
- The Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | | | - Deana Crocetti
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Vivek Yedavalli
- The Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Georg Oeltzschner
- The Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Natalie Alessi
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Mitchell A. Batschelett
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Nicolaas A.J. Puts
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, United Kingdom
- MRC Center for Neurodevelopmental Disorders, King’s College London, London, United Kingdom
| | - Stewart H. Mostofsky
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, United States
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Department of Psychiatry and Behavioral Sciences, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Richard A.E. Edden
- The Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
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8
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Gudmundson AT, Davies-Jenkins CW, Özdemir İ, Murali-Manohar S, Zöllner HJ, Song Y, Hupfeld KE, Schnitzler A, Oeltzschner G, Stark CEL, Edden RAE. Application of a 1H Brain MRS Benchmark Dataset to Deep Learning for Out-of-Voxel Artifacts. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.08.539813. [PMID: 37215030 PMCID: PMC10197548 DOI: 10.1101/2023.05.08.539813] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Neural networks are potentially valuable for many of the challenges associated with MRS data. The purpose of this manuscript is to describe the AGNOSTIC dataset, which contains 259,200 synthetic 1H MRS examples for training and testing neural networks. AGNOSTIC was created using 270 basis sets that were simulated across 18 field strengths and 15 echo times. The synthetic examples were produced to resemble in vivo brain data with combinations of metabolite, macromolecule, residual water signals, and noise. To demonstrate the utility, we apply AGNOSTIC to train two Convolutional Neural Networks (CNNs) to address out-of-voxel (OOV) echoes. A Detection Network was trained to identify the point-wise presence of OOV echoes, providing proof of concept for real-time detection. A Prediction Network was trained to reconstruct OOV echoes, allowing subtraction during post-processing. Complex OOV signals were mixed into 85% of synthetic examples to train two separate CNNs for the detection and prediction of OOV signals. AGNOSTIC is available through Dryad and all Python 3 code is available through GitHub. The Detection network was shown to perform well, identifying 95% of OOV echoes. Traditional modeling of these detected OOV signals was evaluated and may prove to be an effective method during linear-combination modeling. The Prediction Network greatly reduces OOV echoes within FIDs and achieved a median log10 normed-MSE of -1.79, an improvement of almost two orders of magnitude.
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Affiliation(s)
- Aaron T. Gudmundson
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute
| | - Christopher W. Davies-Jenkins
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute
| | - İpek Özdemir
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute
| | - Saipavitra Murali-Manohar
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute
| | - Helge J. Zöllner
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute
| | - Yulu Song
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute
| | - Kathleen E. Hupfeld
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute
| | - Alfons Schnitzler
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute
| | - Craig E. L. Stark
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA
| | - Richard A. E. Edden
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute
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9
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Levenstein JM, Driver C, Boyes A, Parker M, Shan Z, Lagopoulos J, Hermens DF. Sex differences in brain volumes and psychological distress: The first hundred brains cohort of the longitudinal adolescent brain study. NEUROIMAGE: REPORTS 2023. [DOI: 10.1016/j.ynirp.2023.100167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/30/2023]
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10
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Caramelo B, Monteiro-Alfredo T, Martins J, Sereno J, Castelhano J, Manadas B, Castelo-Branco M, Matafome P. Functional imaging and neurochemistry identify in vivo neuroprotection mechanisms counteracting excitotoxicity and neurovascular changes in the hippocampus and visual cortex of obese and type 2 diabetic animal models. J Neurochem 2023; 165:892-906. [PMID: 37026518 DOI: 10.1111/jnc.15825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 03/30/2023] [Accepted: 04/01/2023] [Indexed: 04/08/2023]
Abstract
Functional MRI (fMRI) with 1 H-MRS was combined on the hippocampus and visual cortex of animal models of obesity (high-fat diet, HFD) and type 2 diabetes (T2D) to identify the involved mechanisms and temporal evolution of neurometabolic changes in these disorders that could serve as potentially reliable clinical biomarkers. HFD rats presented elevated levels of N-acetylaspartylglutamate (NAAG) (p = 0.0365 vs. standard diet, SD) and glutathione (GSH) (p = 0.0494 vs. SD) in the hippocampus. NAAG and GSH levels in this structure proved to be correlated (r = 0.4652, p = 0.0336). This mechanism was not observed in diabetic rats. Combining MRS and fMRI-evaluated blood-oxygen-level-dependent (BOLD) response, elevated taurine (p = 0.0326 vs. HFD) and GABA type A receptor (GABAA R) (p = 0.0211 vs. SD and p = 0.0153 vs. HFD) were observed in the visual cortex of only diabetic rats, counteracting the elevated BOLD response and suggesting an adaptative mechanism against hyperexcitability observed in the primary visual cortex (V1) (p = 0.0226 vs. SD). BOLD amplitude was correlated with the glutamate levels (r = 0.4491; p = 0.0316). Therefore, here we found evidence for several biological dichotomies regarding excitotoxicity and neuroprotection in different brain regions, identifying putative markers of their different susceptibility and response to the metabolic and vascular insults of obesity and diabetes.
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Affiliation(s)
- Beatriz Caramelo
- Institute of Clinical and Biomedical Research (iCBR) and Institute of Physiology, Faculty of Medicine, University of Coimbra, Coimbra, Portugal
- Centre for Innovative Biomedicine and Biotechnology (CIBB), University of Coimbra, Coimbra, Portugal
- Clinical Academic Center, Coimbra, Portugal
| | - Tamaeh Monteiro-Alfredo
- Institute of Clinical and Biomedical Research (iCBR) and Institute of Physiology, Faculty of Medicine, University of Coimbra, Coimbra, Portugal
- Centre for Innovative Biomedicine and Biotechnology (CIBB), University of Coimbra, Coimbra, Portugal
- Clinical Academic Center, Coimbra, Portugal
| | - João Martins
- Institute of Clinical and Biomedical Research (iCBR) and Institute of Physiology, Faculty of Medicine, University of Coimbra, Coimbra, Portugal
- Centre for Innovative Biomedicine and Biotechnology (CIBB), University of Coimbra, Coimbra, Portugal
- Clinical Academic Center, Coimbra, Portugal
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
| | - José Sereno
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
- Coimbra Chemistry Centre (CQC), Chemistry Department, University of Coimbra, Coimbra, Portugal
| | - João Castelhano
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
- Centre for Neurosciences and Cell Biology (CNC), University of Coimbra, Coimbra, Portugal
| | - Bruno Manadas
- Centre for Innovative Biomedicine and Biotechnology (CIBB), University of Coimbra, Coimbra, Portugal
- Centre for Neurosciences and Cell Biology (CNC), University of Coimbra, Coimbra, Portugal
| | - Miguel Castelo-Branco
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
| | - Paulo Matafome
- Institute of Clinical and Biomedical Research (iCBR) and Institute of Physiology, Faculty of Medicine, University of Coimbra, Coimbra, Portugal
- Centre for Innovative Biomedicine and Biotechnology (CIBB), University of Coimbra, Coimbra, Portugal
- Clinical Academic Center, Coimbra, Portugal
- Instituto Politécnico de Coimbra, Coimbra Health School (ESTeSC), Coimbra, Portugal
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11
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Song Y, Zöllner HJ, Hui SCN, Hupfeld KE, Oeltzschner G, Edden RAE. Impact of gradient scheme and non-linear shimming on out-of-voxel echo artifacts in edited MRS. NMR IN BIOMEDICINE 2023; 36:e4839. [PMID: 36196802 PMCID: PMC9845189 DOI: 10.1002/nbm.4839] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 09/28/2022] [Accepted: 09/29/2022] [Indexed: 05/30/2023]
Abstract
Out-of-voxel (OOV) signals are common spurious echo artifacts in MRS. These signals often manifest in the spectrum as very strong "ripples," which interfere with spectral quantification by overlapping with targeted metabolite resonances. Dephasing optimization through coherence order pathway selection (DOTCOPS) gradient schemes are algorithmically optimized to suppress all potential alternative coherence transfer pathways (CTPs), and should suppress unwanted OOV echoes. In addition, second-order shimming uses non-linear gradient fields to maximize field homogeneity inside the voxel, which unfortunately increases the diversity of local gradient fields outside of the voxel. Given that strong local spatial B0 gradients can refocus unintended CTPs, it is possible that OOVs are less prevalent when only linear first-order shimming is applied. Here we compare the size of unwanted OOV signals in Hadamard-edited (HERMES) data acquired with either a local gradient scheme (which we refer to here as "Shared") or DOTCOPS, and with first- or second-order shimming. We collected data from 15 healthy volunteers in two brain regions (voxel size 30 × 26 × 26 mm3 ) from which it is challenging to acquire MRS data: medial prefrontal cortex and left temporal cortex. Characteristic OOV echoes were seen in both GABA- and GSH-edited spectra for both brain regions, gradient schemes, and shimming approaches. A linear mixed-effect model revealed a statistically significant difference in the average residual based on the gradient scheme in both GABA- (p < 0.001) and GSH-edited (p < 0.001) spectra: that is, the DOTCOPS gradient scheme resulted in smaller OOV artifacts compared with the Shared scheme. There were no significant differences in OOV artifacts associated with shimming method. Thus, these results suggest that the DOTCOPS gradient scheme for J-difference-edited PRESS acquisitions yields spectra with smaller OOV echo artifacts than the Shared gradient scheme implemented in a widely disseminated editing sequence.
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Affiliation(s)
- Yulu Song
- Russell H Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Helge J Zöllner
- Russell H Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Steve C N Hui
- Russell H Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Kathleen E Hupfeld
- Russell H Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Georg Oeltzschner
- Russell H Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Richard A E Edden
- Russell H Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
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12
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Hui SC, Saleh MG, Zöllner HJ, Oeltzschner G, Fan H, Li Y, Song Y, Jiang H, Near J, Lu H, Mori S, Edden RAE. MRSCloud: A cloud-based MRS tool for basis set simulation. Magn Reson Med 2022; 88:1994-2004. [PMID: 35775808 PMCID: PMC9420769 DOI: 10.1002/mrm.29370] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 05/16/2022] [Accepted: 06/05/2022] [Indexed: 11/07/2022]
Abstract
PURPOSE The purpose of this study is to present a cloud-based spectral simulation tool "MRSCloud," which allows MRS users to simulate a vendor-specific and sequence-specific basis set online in a convenient and time-efficient manner. This tool can simulate basis sets for GE, Philips, and Siemens MR scanners, including conventional acquisitions and spectral editing schemes with PRESS and semi-LASER localization at 3 T. METHODS The MRSCloud tool was built on the spectral simulation functionality in the FID-A software package. We added three extensions to accelerate computation (ie, one-dimensional projection method, coherence pathways filters, and precalculation of propagators). The RF waveforms were generated based on vendors' generic pulse shapes and timings. Simulations were compared within MRSCloud using different numbers of spatial resolution (21 × 21, 41 × 41, and 101 × 101). Simulated metabolite basis functions from MRSCloud were compared with those generated by the generic FID-A and MARSS, and a phantom-acquired basis set from LCModel. Intraclass correlation coefficients were calculated to measure the agreement between individual metabolite basis functions. Statistical analysis was performed using R in RStudio. RESULTS Simulation time for a full PRESS basis set is approximately 11 min on the server. The interclass correlation coefficients ICCs were at least 0.98 between MRSCloud and FID-A and were at least 0.96 between MRSCloud and MARSS. The interclass correlation coefficients between simulated MRSCloud basis spectra and acquired LCModel basis spectra were lowest for glutamine at 0.68 and highest for N-acetylaspartate at 0.96. CONCLUSIONS Substantial reductions in runtime have been achieved. High ICC values indicated that the accelerating features are running correctly and produce comparable and accurate basis sets.
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Affiliation(s)
- Steve C.N. Hui
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Muhammad G. Saleh
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Helge J. Zöllner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Hongli Fan
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Yue Li
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- AnatomyWorks, LLC, Ellicott City, Maryland, USA
| | - Yulu Song
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Hangyi Jiang
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Jamie Near
- Sunnybrook Research Institute and Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Hanzhang Lu
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Susumu Mori
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Richard A. E. Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
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13
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Harris KC, Dias JW, McClaskey CM, Rumschlag J, Prisciandaro J, Dubno JR. Afferent Loss, GABA, and Central Gain in Older Adults: Associations with Speech Recognition in Noise. J Neurosci 2022; 42:7201-7212. [PMID: 35995564 PMCID: PMC9512571 DOI: 10.1523/jneurosci.0242-22.2022] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 07/20/2022] [Accepted: 08/14/2022] [Indexed: 11/21/2022] Open
Abstract
Deficits in auditory nerve (AN) function for older adults reduce afferent input to the cortex. The extent to which the cortex in older adults adapts to this loss of afferent input and the mechanisms underlying this adaptation are not well understood. We took a neural systems approach measuring AN and cortical evoked responses within 50 older and 27 younger human adults (59 female) to estimate central gain or increased cortical activity despite reduced AN activity. Relative to younger adults, older adults' AN response amplitudes were smaller, but cortical responses were not. We used the relationship between AN and cortical response amplitudes in younger adults to predict cortical response amplitudes for older adults from their AN responses. Central gain in older adults was thus defined as the difference between their observed cortical responses and those predicted from the parameter estimates of younger adults. In older adults, decreased afferent input contributed to lower cortical GABA levels, greater central gain, and poorer speech recognition in noise (SIN). These effects on SIN occur in addition to, and independent from, effects attributed to elevated hearing thresholds. Our results are consistent with animal models of central gain and suggest that reduced AN afferent input in some older adults may result in changes in cortical encoding and inhibitory neurotransmission, which contribute to reduced SIN. An advancement in our understanding of the changes that occur throughout the auditory system in response to the gradual loss of input with increasing age may provide potential therapeutic targets for intervention.SIGNIFICANCE STATEMENT Age-related hearing loss is one of the most common chronic conditions of aging, yet little is known about how the cortex adapts to this loss of sensory input. We measured AN and cortical responses to the same stimulus in younger and older adults. In older adults we found hyperexcitability in cortical activity relative to concomitant declines in afferent input that are consistent with central gain. Lower levels of cortical GABA, an inhibitory neurotransmitter, were associated with greater central gain, which predicted poorer SIN. The results suggest that the cortex in older adults may adapt to attenuated sensory input by reducing inhibition to amplify the cortical response, but this amplification may lead to poorer SIN.
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Affiliation(s)
| | - James W Dias
- Department of Otolaryngology-Head and Neck Surgery
| | | | | | - James Prisciandaro
- Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, South Carolina 29425-5500
| | - Judy R Dubno
- Department of Otolaryngology-Head and Neck Surgery
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14
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Cortical inhibition in neurofibromatosis type 1 is modulated by lovastatin, as demonstrated by a randomized, triple-blind, placebo-controlled clinical trial. Sci Rep 2022; 12:13814. [PMID: 35970940 PMCID: PMC9378617 DOI: 10.1038/s41598-022-17873-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 08/02/2022] [Indexed: 11/24/2022] Open
Abstract
Neurofibromatosis type 1 (NF1) is associated with GABAergic dysfunction which has been suggested as the underlying cause of cognitive impairments. Previous intervention trials investigated the statins’ effects using cognitive outcome measures. However, available outcome measures have led to inconclusive results and there is a need to identify other options. Here, we aimed at investigating alternative outcome measures in a feasibility trial targeting cortical inhibition mechanisms known to be altered in NF1. We explored the neurochemical and physiological changes elicited by lovastatin, with magnetic resonance spectroscopy and transcranial magnetic stimulation (TMS). Fifteen NF1 adults participated in this randomized, triple-blind, placebo-controlled crossover trial (Clinicaltrials.gov NCT03826940) composed of one baseline and two reassessment visits after lovastatin/placebo intake (60 mg/day, 3-days). Motor cortex GABA+ and Glx concentrations were measured using HERMES and PRESS sequences, respectively. Cortical inhibition was investigated by paired-pulse, input–output curve, and cortical silent period (CSP) TMS protocols. CSP ratios were significantly increased by lovastatin (relative: p = 0.027; absolute: p = 0.034) but not by placebo. CSP durations showed a negative correlation with the LICI 50 ms amplitude ratio. Lovastatin was able to modulate cortical inhibition in NF1, as assessed by TMS CSP ratios. The link between this modulation of cortical inhibition and clinical improvements should be addressed by future large-scale studies.
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15
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Abuhaiba SI, Duarte IC, Castelhano J, Dionísio A, Sales F, Edden R, Castelo-Branco M. The impact of cathodal tDCS on the GABAergic system in the epileptogenic zone: A multimodal imaging study. Front Neurol 2022; 13:935029. [PMID: 35989912 PMCID: PMC9388822 DOI: 10.3389/fneur.2022.935029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 07/08/2022] [Indexed: 11/16/2022] Open
Abstract
Objectives We aimed to investigate the antiepileptic effects of cathodal transcranial direct current stimulation (c-tDCS) and mechanisms of action based on its effects on the neurotransmitters responsible for the abnormal synchrony patterns seen in pharmacoresistant epilepsy. This is the first study to test the impact of neurostimulation on epileptiform interictal discharges (IEDs) and to measure brain metabolites in the epileptogenic zone (EZ) and control regions simultaneously in patients with pharmacoresistant epilepsy. Methods This is a hypothesis-driven pilot prospective single-blinded repeated measure design study in patients diagnosed with pharmacoresistant epilepsy of temporal lobe onset. We included seven patients who underwent two sessions of c-tDCS (sham followed by real). The real tDCS session was 20 min in duration and had a current intensity of 1.5 mA delivered via two surface electrodes that had dimensions of 3 × 4 cm. The cathode electrode was placed at FT7 in the center whereas the anode at Oz in the center. After each session, we performed electroencephalographic recording to count epileptiform IEDs over 30 min. We also performed magnetic resonance spectroscopy (MRS) to measure brain metabolite concentrations in the two areas of interest (EZ and occipital region), namely, gamma-aminobutyric acid (GABA), glutamate (Glx), and glutathione. We focused on a homogenous sample where the EZ and antiepileptic medications are shared among patients. Results Real tDCS decreased the number of epileptiform IEDs per min (from 9.46 ± 2.68 after sham tDCS to 5.37 ± 3.38 after real tDCS), p = 0.018, as compared to sham tDCS. GABA was decreased in the EZ after real c-tDCS stimulation as compared to sham tDCS (from 0.129 ± 0.019 to 0.096 ± 0.018, p = 0.02). The reduction in EZ GABA correlated with the reduction in the frequency of epileptiform IED per min (rho: 0.9, p = 0.003). Conclusion These results provide a window into the antiepileptic mechanisms of action of tDCS, based on local and remote changes in GABA and neural oscillatory patterning responsible for the generation of interictal epileptiform discharges.
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Affiliation(s)
- Sulaiman I. Abuhaiba
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Coimbra, Portugal
- Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
- Epilepsy Unit, Faculty of Medicine, Clinical and Academic Center (CCAC), Coimbra, Portugal
| | - Isabel C. Duarte
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Coimbra, Portugal
- Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
- Faculty of Medicine, Clinical and Academic Center (CCAC), University of Coimbra, Coimbra, Portugal
| | - João Castelhano
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Coimbra, Portugal
- Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
- Faculty of Medicine, Clinical and Academic Center (CCAC), University of Coimbra, Coimbra, Portugal
| | - Ana Dionísio
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Coimbra, Portugal
- Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
- Faculty of Medicine, Clinical and Academic Center (CCAC), University of Coimbra, Coimbra, Portugal
| | - Francisco Sales
- Epilepsy Unit, Faculty of Medicine, Clinical and Academic Center (CCAC), Coimbra, Portugal
| | - Richard Edden
- Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
- FM Kirby Center for Functional MRI, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Miguel Castelo-Branco
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Coimbra, Portugal
- Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
- Faculty of Medicine, Clinical and Academic Center (CCAC), University of Coimbra, Coimbra, Portugal
- *Correspondence: Miguel Castelo-Branco
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16
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Koush Y, Rothman DL, Behar KL, de Graaf RA, Hyder F. Human brain functional MRS reveals interplay of metabolites implicated in neurotransmission and neuroenergetics. J Cereb Blood Flow Metab 2022; 42:911-934. [PMID: 35078383 PMCID: PMC9125492 DOI: 10.1177/0271678x221076570] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
While functional MRI (fMRI) localizes brain activation and deactivation, functional MRS (fMRS) provides insights into the underlying metabolic conditions. There is much interest in measuring task-induced and resting levels of metabolites implicated in neuroenergetics (e.g., lactate, glucose, or β-hydroxybutyrate (BHB)) and neurotransmission (e.g., γ-aminobutyric acid (GABA) or pooled glutamate and glutamine (Glx)). Ultra-high magnetic field (e.g., 7T) has boosted the fMRS quantification precision, reliability, and stability of spectroscopic observations using short echo-time (TE) 1H-MRS techniques. While short TE 1H-MRS lacks sensitivity and specificity for fMRS at lower magnetic fields (e.g., 3T or 4T), most of these metabolites can also be detected by J-difference editing (JDE) 1H-MRS with longer TE to filter overlapping resonances. The 1H-MRS studies show that JDE can detect GABA, Glx, lactate, and BHB at 3T, 4T and 7T. Most recently, it has also been demonstrated that JDE 1H-MRS is capable of reliable detection of metabolic changes in different brain areas at various magnetic fields. Combining fMRS measurements with fMRI is important for understanding normal brain function, but also clinically relevant for mechanisms and/or biomarkers of neurological and neuropsychiatric disorders. We provide an up-to-date overview of fMRS research in the last three decades, both in terms of applications and technological advances. Overall the emerging fMRS techniques can be expected to contribute substantially to our understanding of metabolism for brain function and dysfunction.
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Affiliation(s)
- Yury Koush
- Magnetic Resonance Research Center, Department of Radiology & Biomedical Imaging, Yale University, New Haven, CT, USA
| | - Douglas L Rothman
- Magnetic Resonance Research Center, Department of Radiology & Biomedical Imaging, Yale University, New Haven, CT, USA.,Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Kevin L Behar
- Magnetic Resonance Research Center, Department of Radiology & Biomedical Imaging, Yale University, New Haven, CT, USA.,Department of Psychiatry, Yale University, New Haven, CT, USA
| | - Robin A de Graaf
- Magnetic Resonance Research Center, Department of Radiology & Biomedical Imaging, Yale University, New Haven, CT, USA.,Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Fahmeed Hyder
- Magnetic Resonance Research Center, Department of Radiology & Biomedical Imaging, Yale University, New Haven, CT, USA.,Department of Biomedical Engineering, Yale University, New Haven, CT, USA
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17
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Weng G, Radojewski P, Sheriff S, Kiefer C, Schucht P, Wiest R, Maudsley AA, Slotboom J. SLOW: A novel spectral editing method for whole-brain MRSI at ultra high magnetic field. Magn Reson Med 2022; 88:53-70. [PMID: 35344608 PMCID: PMC9212787 DOI: 10.1002/mrm.29220] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 01/28/2022] [Accepted: 02/16/2022] [Indexed: 11/11/2022]
Abstract
PURPOSE At ultra-high field (UHF), B1 + -inhomogeneities and high specific absorption rate (SAR) of adiabatic slice-selective RF-pulses make spatial resolved spectral-editing extremely challenging with the conventional MEGA-approach. The purpose of the study was to develop a whole-brain resolved spectral-editing MRSI at UHF (UHF, B0 ≥ 7T) within clinical acceptable measurement-time and minimal chemical-shift-displacement-artifacts (CSDA) allowing for simultaneous GABA/Glx-, 2HG-, and PE-editing on a clinical approved 7T-scanner. METHODS Slice-selective adiabatic refocusing RF-pulses (2π-SSAP) dominate the SAR to the patient in (semi)LASER based MEGA-editing sequences, causing large CSDA and long measurement times to fulfill SAR requirements, even using SAR-minimized GOIA-pulses. Therefore, a novel type of spectral-editing, called SLOW-editing, using two different pairs of phase-compensated chemical-shift selective adiabatic refocusing-pulses (2π-CSAP) with different refocusing bandwidths were investigated to overcome these problems. RESULTS Compared to conventional echo-planar spectroscopic imaging (EPSI) and MEGA-editing, SLOW-editing shows robust refocusing and editing performance despite to B1 + -inhomogeneity, and robustness to B0 -inhomogeneities (0.2 ppm ≥ ΔB0 ≥ -0.2 ppm). The narrow bandwidth (∼0.6-0.8 kHz) CSAP reduces the SAR by 92%, RF peak power by 84%, in-excitation slab CSDA by 77%, and has no in-plane CSDA. Furthermore, the CSAP implicitly dephases water, lipid and all the other signals outside of range (≥ 4.6 ppm and ≤1.4 ppm), resulting in additional water and lipid suppression (factors ≥ 1000s) at zero SAR-cost, and no spectral aliasing artifacts. CONCLUSION A new spectral-editing has been developed that is especially suitable for UHF, and was successfully applied for 2HG, GABA+, PE, and Glx-editing within 10 min clinical acceptable measurement time.
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Affiliation(s)
- Guodong Weng
- Institute for Diagnostic and Interventional Neuroradiology, Support Center for Advanced Neuroimaging (SCAN), University of Bern, Bern, Switzerland
| | - Piotr Radojewski
- Institute for Diagnostic and Interventional Neuroradiology, Support Center for Advanced Neuroimaging (SCAN), University of Bern, Bern, Switzerland
| | - Sulaiman Sheriff
- Department of Radiology, University of Miami School of Medicine, Miami, Florida, USA
| | - Claus Kiefer
- Institute for Diagnostic and Interventional Neuroradiology, Support Center for Advanced Neuroimaging (SCAN), University of Bern, Bern, Switzerland
| | - Philippe Schucht
- Department of Neurosurgery, Inselspital Bern and University Hospital, Bern, Switzerland
| | - Roland Wiest
- Institute for Diagnostic and Interventional Neuroradiology, Support Center for Advanced Neuroimaging (SCAN), University of Bern, Bern, Switzerland
| | - Andrew A Maudsley
- Department of Radiology, University of Miami School of Medicine, Miami, Florida, USA
| | - Johannes Slotboom
- Institute for Diagnostic and Interventional Neuroradiology, Support Center for Advanced Neuroimaging (SCAN), University of Bern, Bern, Switzerland
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18
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Chen JJ, Thiyagarajah M, Song J, Chen C, Herrmann N, Gallagher D, Rapoport MJ, Black SE, Ramirez J, Andreazza AC, Oh P, Marzolini S, Graham SJ, Lanctôt KL. Altered central and blood glutathione in Alzheimer's disease and mild cognitive impairment: a meta-analysis. Alzheimers Res Ther 2022; 14:23. [PMID: 35123548 PMCID: PMC8818133 DOI: 10.1186/s13195-022-00961-5] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 01/06/2022] [Indexed: 01/01/2023]
Abstract
BACKGROUND Increasing evidence implicates oxidative stress (OS) in Alzheimer disease (AD) and mild cognitive impairment (MCI). Depletion of the brain antioxidant glutathione (GSH) may be important in OS-mediated neurodegeneration, though studies of post-mortem brain GSH changes in AD have been inconclusive. Recent in vivo measurements of the brain and blood GSH may shed light on GSH changes earlier in the disease. AIM To quantitatively review in vivo GSH in AD and MCI compared to healthy controls (HC) using meta-analyses. METHOD Studies with in vivo brain or blood GSH levels in MCI or AD with a HC group were identified using MEDLINE, PsychInfo, and Embase (1947-June 2020). Standardized mean differences (SMD) and 95% confidence intervals (CI) were calculated for outcomes using random effects models. Outcome measures included brain GSH (Meshcher-Garwood Point Resolved Spectroscopy (MEGA-PRESS) versus non-MEGA-PRESS) and blood GSH (intracellular versus extracellular) in AD and MCI. The Q statistic and Egger's test were used to assess heterogeneity and risk of publication bias, respectively. RESULTS For brain GSH, 4 AD (AD=135, HC=223) and 4 MCI (MCI=213, HC=211) studies were included. For blood GSH, 26 AD (AD=1203, HC=1135) and 7 MCI (MCI=434, HC=408) studies were included. Brain GSH overall did not differ in AD or MCI compared to HC; however, the subgroup of studies using MEGA-PRESS reported lower brain GSH in AD (SMD [95%CI] -1.45 [-1.83, -1.06], p<0.001) and MCI (-1.15 [-1.71, -0.59], z=4.0, p<0.001). AD had lower intracellular and extracellular blood GSH overall (-0.87 [-1. 30, -0.44], z=3.96, p<0.001). In a subgroup analysis, intracellular GSH was lower in MCI (-0.66 [-1.11, -0.21], p=0.025). Heterogeneity was observed throughout (I2 >85%) and not fully accounted by subgroup analysis. Egger's test indicated risk of publication bias. CONCLUSION Blood intracellular GSH decrease is seen in MCI, while both intra- and extracellular decreases were seen in AD. Brain GSH is decreased in AD and MCI in subgroup analysis. Potential bias and heterogeneity suggest the need for measurement standardization and additional studies to explore sources of heterogeneity.
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Affiliation(s)
- Jinghan Jenny Chen
- Neuropsychopharmacology Research Group, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, 2075 Bayview Avenue, Room FG52, Toronto, ON, M4N 3M5, Canada.,Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada
| | - Mathura Thiyagarajah
- Neuropsychopharmacology Research Group, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, 2075 Bayview Avenue, Room FG52, Toronto, ON, M4N 3M5, Canada.,Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada
| | - Jianmeng Song
- Neuropsychopharmacology Research Group, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, 2075 Bayview Avenue, Room FG52, Toronto, ON, M4N 3M5, Canada
| | - Clara Chen
- Neuropsychopharmacology Research Group, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, 2075 Bayview Avenue, Room FG52, Toronto, ON, M4N 3M5, Canada
| | - Nathan Herrmann
- Neuropsychopharmacology Research Group, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, 2075 Bayview Avenue, Room FG52, Toronto, ON, M4N 3M5, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Geriatric Psychiatry, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Damien Gallagher
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Geriatric Psychiatry, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Mark J Rapoport
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Geriatric Psychiatry, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Sandra E Black
- Evaluative Clinical Sciences, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada.,KITE-Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada
| | - Joel Ramirez
- Evaluative Clinical Sciences, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Ana C Andreazza
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada
| | - Paul Oh
- KITE-Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada
| | - Susan Marzolini
- KITE-Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada
| | - Simon J Graham
- Physical Sciences, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Krista L Lanctôt
- Neuropsychopharmacology Research Group, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, 2075 Bayview Avenue, Room FG52, Toronto, ON, M4N 3M5, Canada. .,Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada. .,Department of Psychiatry, University of Toronto, Toronto, ON, Canada. .,Geriatric Psychiatry, Sunnybrook Health Sciences Centre, Toronto, ON, Canada. .,Evaluative Clinical Sciences, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada.
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19
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Song Y, Lally PJ, Yanez Lopez M, Oeltzschner G, Nebel MB, Gagoski B, Kecskemeti S, Hui SCN, Zöllner HJ, Shukla D, Arichi T, De Vita E, Yedavalli V, Thayyil S, Fallin D, Dean DC, Grant PE, Wisnowski JL, Edden RAE. Edited magnetic resonance spectroscopy in the neonatal brain. Neuroradiology 2022; 64:217-232. [PMID: 34654960 PMCID: PMC8887832 DOI: 10.1007/s00234-021-02821-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 09/20/2021] [Indexed: 10/20/2022]
Abstract
J-difference-edited spectroscopy is a valuable approach for the detection of low-concentration metabolites with magnetic resonance spectroscopy (MRS). Currently, few edited MRS studies are performed in neonates due to suboptimal signal-to-noise ratio, relatively long acquisition times, and vulnerability to motion artifacts. Nonetheless, the technique presents an exciting opportunity in pediatric imaging research to study rapid maturational changes of neurotransmitter systems and other metabolic systems in early postnatal life. Studying these metabolic processes is vital to understanding the widespread and rapid structural and functional changes that occur in the first years of life. The overarching goal of this review is to provide an introduction to edited MRS for neonates, including the current state-of-the-art in editing methods and editable metabolites, as well as to review the current literature applying edited MRS to the neonatal brain. Existing challenges and future opportunities, including the lack of age-specific reference data, are also discussed.
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Affiliation(s)
- Yulu Song
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Peter J Lally
- Department of Brain Sciences, Imperial College London, London, UK
| | - Maria Yanez Lopez
- Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Mary Beth Nebel
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, 21205, USA.,Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Borjan Gagoski
- Department of Radiology, Division of Neuroradiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.,Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, USA
| | | | - Steve C N Hui
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Helge J Zöllner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Deepika Shukla
- Centre for Perinatal Neuroscience, Department of Brain Sciences, Imperial College London, London, UK
| | - Tomoki Arichi
- Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Department of Bioengineering, Imperial College London, South Kensington Campus, London, UK
| | - Enrico De Vita
- Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, St Thomas's Hospital, Westminster Bridge Road, Lambeth Wing, 3rd Floor, London, SE1 7EH, UK
| | - Vivek Yedavalli
- Division of Neuroradiology, Park 367G, The Johns Hopkins University School of Medicine, 600 N. Wolfe St. B-112 D, Baltimore, MD, 21287, USA
| | - Sudhin Thayyil
- Centre for Perinatal Neuroscience, Department of Brain Sciences, Imperial College London, London, UK
| | - Daniele Fallin
- Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins University, Baltimore, USA.,Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, USA
| | - Douglas C Dean
- Waisman Center, University of WI-Madison, Madison, WI, 53705, USA.,Department of Pediatrics, Division of Neonatology and Newborn Nursery, University of WI-Madison, School of Medicine and Public Health, Madison, WI, 53705, USA.,Department of Medical Physics, University of WI-Madison, School of Medicine and Public Health, Madison, WI, 53705, USA
| | - P Ellen Grant
- Department of Radiology, Division of Neuroradiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.,Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, USA.,Department of Medicine, Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jessica L Wisnowski
- Children's Hospital Los Angeles, Los Angeles, CA, 90027, USA.,Department of Radiology and Fetal and Neonatal Institute, CHLA Division of Neonatology, Department of Pediatrics, Children's Hospital of Los Angeles, University of Southern California, Los Angeles, CA, 90033, USA
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA. .,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA. .,Division of Neuroradiology, Park 367G, The Johns Hopkins University School of Medicine, 600 N. Wolfe St. B-112 D, Baltimore, MD, 21287, USA.
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20
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Song Y, Zöllner HJ, Hui SCN, Hupfeld K, Oeltzschner G, Prisciandaro JJ, Edden R. Importance of Linear Combination Modeling for Quantification of Glutathione and γ-Aminobutyric Acid Levels Using Hadamard-Edited Magnetic Resonance Spectroscopy. Front Psychiatry 2022; 13:872403. [PMID: 35546940 PMCID: PMC9082488 DOI: 10.3389/fpsyt.2022.872403] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Accepted: 03/07/2022] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND J-difference-edited 1H-MR spectra require modeling to quantify signals of low-concentration metabolites. Two main approaches are used for this spectral modeling: simple peak fitting and linear combination modeling (LCM) with a simulated basis set. Recent consensus recommended LCM as the method of choice for the spectral analysis of edited data. PURPOSE The aim of this study is to compare the performance of simple peak fitting and LCM in a test-retest dataset, hypothesizing that the more sophisticated LCM approach would improve quantification of Hadamard-edited data compared with simple peak fitting. METHODS A test-retest dataset was re-analyzed using Gannet (simple peak fitting) and Osprey (LCM). These data were obtained from the dorsal anterior cingulate cortex of twelve healthy volunteers, with TE = 80 ms for HERMES and TE = 120 ms for MEGA-PRESS of glutathione (GSH). Within-subject coefficients of variation (CVs) were calculated to quantify between-scan reproducibility of each metabolite estimate. RESULTS The reproducibility of HERMES GSH estimates was substantially improved using LCM compared to simple peak fitting, from a CV of 19.0-9.9%. For MEGA-PRESS GSH data, reproducibility was similar using LCM and simple peak fitting, with CVs of 7.3 and 8.8%. GABA + CVs from HERMES were 16.7 and 15.2%, respectively for the two models. CONCLUSION LCM with simulated basis functions substantially improved the reproducibility of GSH quantification for HERMES data.
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Affiliation(s)
- Yulu Song
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Helge J Zöllner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Steve C N Hui
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Kathleen Hupfeld
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - James J Prisciandaro
- Department of Psychiatry and Behavioral Sciences, Addiction Sciences Division, Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, United States
| | - Richard Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
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21
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Dehghani M, Edden R, Near J. Hadamard-encoded dual-voxel SPECIAL: Short-TE MRS acquired in two brain regions simultaneously using Hadamard encoding. Magn Reson Med 2021; 87:1649-1660. [PMID: 34932240 DOI: 10.1002/mrm.29129] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 11/09/2021] [Accepted: 12/01/2021] [Indexed: 12/20/2022]
Abstract
PURPOSE The spin-echo, full-intensity acquired localized (SPECIAL) sequence is a method for single-voxel, localized MRS in vivo with short TEs. In this study we modified the SPECIAL sequence to simultaneously record spectra from two volumes of interest. This new technique is called Hadamard-encoded dual-voxel SPECIAL (HD-SPECIAL). METHODS The SPECIAL sequence consists of a spin echo localized to a column of tissue, preceded by a slice-selective inversion pulse in alternating scans to invert a section of the column. Full localization is achieved by subtraction of the inversion-on scans from the inversion-off scans. In HD-SPECIAL, the two-step inversion scheme is replaced by a four-step Hadamard-encoded scheme involving single-band and dual-band inversion pulses to select two regions of the spin-echo column. By appropriate Hadamard combination of the four acquired shots, spectra can be reconstructed from both desired regions. This approach does not rely on parallel imaging reconstruction. Using a 3T scanner, HD-SPECIAL localization is demonstrated both in phantoms and in the human brain in vivo, and the performance of HD-SPECIAL is assessed by comparing with the conventional SPECIAL sequence. RESULTS Phantom and in vivo measurements show excellent agreement between measures from HD-SPECIAL and SPECIAL sequences. Relative to consecutive SPECIAL measurements from two regions, HD-SPECIAL reduces the total scan time 2-fold with minimal penalty in terms of spectral quality or SNR. CONCLUSION The HD-SPECIAL sequence enables reliable acquisition of MR spectra simultaneously from two regions at 3 T, offering the potential to study interregional variations in metabolite concentrations.
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Affiliation(s)
- Masoumeh Dehghani
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.,Department of Psychiatry, McGill University, Montreal, Quebec, Canada.,Centre d'Imagerie Cérébrale, Douglas Mental Health University, Montreal, Quebec, Canada
| | - Richard Edden
- Centre d'Imagerie Cérébrale, Douglas Mental Health University, Montreal, Quebec, Canada.,FM Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA.,Russell H Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institutions, Baltimore, Maryland, USA
| | - Jamie Near
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.,Department of Psychiatry, McGill University, Montreal, Quebec, Canada.,Centre d'Imagerie Cérébrale, Douglas Mental Health University, Montreal, Quebec, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
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22
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Sapey-Triomphe LA, Temmerman J, Puts NAJ, Wagemans J. Prediction learning in adults with autism and its molecular correlates. Mol Autism 2021; 12:64. [PMID: 34615532 PMCID: PMC8493731 DOI: 10.1186/s13229-021-00470-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 09/23/2021] [Indexed: 12/28/2022] Open
Abstract
Background According to Bayesian hypotheses, individuals with Autism Spectrum Disorder (ASD) have difficulties making accurate predictions about their environment. In particular, the mechanisms by which they assign precision to predictions or sensory inputs would be suboptimal in ASD. These mechanisms are thought to be mostly mediated by glutamate and GABA. Here, we aimed to shed light on prediction learning in ASD and on its neurobiological correlates. Methods Twenty-six neurotypical and 26 autistic adults participated in an associative learning task where they had to learn a probabilistic association between a tone and the rotation direction of two dots, in a volatile context. They also took part in magnetic resonance spectroscopy (MRS) measurements to quantify Glx (glutamate and glutamine), GABA + and glutathione in a low-level perceptual region (occipital cortex) and in a higher-level region involved in prediction learning (inferior frontal gyrus). Results Neurotypical and autistic adults had their percepts biased by their expectations, and this bias was smaller for individuals with a more atypical sensory sensitivity. Both groups were able to learn the association and to update their beliefs after a change in contingency. Interestingly, the percentage of correct predictions was correlated with the Glx/GABA + ratio in the occipital cortex (positive correlation) and in the right inferior frontal gyrus (negative correlation). In this region, MRS results also showed an increased concentration of Glx in the ASD group compared to the neurotypical group. Limitations We used a quite restrictive approach to select the MR spectra showing a good fit, which led to the exclusion of some MRS datasets and therefore to the reduction of the sample size for certain metabolites/regions. Conclusions Autistic adults appeared to have intact abilities to make predictions in this task, in contrast with the Bayesian hypotheses of ASD. Yet, higher ratios of Glx/GABA + in a frontal region were associated with decreased predictive abilities, and ASD individuals tended to have more Glx in this region. This neurobiological difference might contribute to suboptimal predictive mechanisms in ASD in certain contexts. Supplementary Information The online version contains supplementary material available at 10.1186/s13229-021-00470-6.
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Affiliation(s)
- Laurie-Anne Sapey-Triomphe
- Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium. .,Leuven Autism Research (LAuRes), KU Leuven, 3000, Leuven, Belgium.
| | - Joke Temmerman
- Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium
| | - Nicolaas A J Puts
- Department of Forensic and Neurodevelopmental Sciences and the Institute of Psychiatry, Psychology, and Neuroscience, Sackler Institute for Translational Neurodevelopment, King's College London, London, SE5 8AF, UK.,MRC Centre for Neurodevelopmental Disorders, King's College London, London, SE5 8AF, UK
| | - Johan Wagemans
- Department of Brain and Cognition, Leuven Brain Institute, KU Leuven, 3000, Leuven, Belgium.,Leuven Autism Research (LAuRes), KU Leuven, 3000, Leuven, Belgium
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23
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Chan KL, Hock A, Edden RAE, MacMillan EL, Henning A. Improved prospective frequency correction for macromolecule-suppressed GABA editing with metabolite cycling at 3T. Magn Reson Med 2021; 86:2945-2956. [PMID: 34431549 DOI: 10.1002/mrm.28950] [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: 03/03/2021] [Revised: 07/14/2021] [Accepted: 07/15/2021] [Indexed: 11/08/2022]
Abstract
PURPOSE To combine metabolite cycling with J-difference editing (MC MEGA) to allow for prospective frequency correction at each transient without additional acquisitions and compare it to water-suppressed MEGA-PRESS (WS MEGA) editing with intermittent prospective frequency correction. METHODS Macromolecule-suppressed gamma aminobutyric acid (GABA)-edited experiments were performed in a phantom and in the occipital lobe (OCC) (n = 12) and medial prefrontal cortex (mPFC) (n = 8) of the human brain. Water frequency consistency and average offset over acquisition time were compared. GABA multiplet patterns, signal intensities, and choline subtraction artifacts were evaluated. In vivo GABA concentrations were compared and related to frequency offset in the OCC. RESULTS MC MEGA was more stable with 21% and 32% smaller water frequency SDs in the OCC and mPFC, respectively. MC MEGA also had 39% and 40% smaller average frequency offsets in the OCC and mPFC, respectively. Phantom GABA multiplet patterns and signal intensities were similar. In vivo GABA concentrations were smaller in MC MEGA than in WS MEGA, with median (interquartile range) of 2.52 (0.27) and 2.29 (0.19) institutional units (i.u.), respectively in the OCC scans without prior DTI, and 0.99 (0.3) and 1.72 (0.5), respectively in the mPFC. OCC WS MEGA GABA concentrations, but not MC MEGA GABA concentrations were moderately correlated with frequency offset. mPFC WS MEGA spectra contained significantly more subtraction artifacts than MC MEGA spectra. CONCLUSION MC MEGA is feasible and allows for prospective frequency correction at every transient. MC MEGA GABA concentrations were not biased by frequency offsets and contained less subtraction artifacts compared to WS MEGA.
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Affiliation(s)
- Kimberly L Chan
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Andreas Hock
- MR Clinical Science, Philips Health Systems, Horgen, Switzerland
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Erin L MacMillan
- UBC MRI Research Centre, University of British Columbia, Vancouver, British Columbia, Canada.,SFU ImageTech Lab, Simon Fraser University, Surrey, British Columbia, Canada.,MR Clinical Science, Philips Healthcare, Markham, Ontario, Canada
| | - 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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24
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Near J, Harris AD, Juchem C, Kreis R, Marjańska M, Öz G, Slotboom J, Wilson M, Gasparovic C. Preprocessing, analysis and quantification in single-voxel magnetic resonance spectroscopy: experts' consensus recommendations. NMR IN BIOMEDICINE 2021; 34:e4257. [PMID: 32084297 PMCID: PMC7442593 DOI: 10.1002/nbm.4257] [Citation(s) in RCA: 153] [Impact Index Per Article: 51.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 12/21/2019] [Accepted: 12/22/2019] [Indexed: 05/05/2023]
Abstract
Once an MRS dataset has been acquired, several important steps must be taken to obtain the desired metabolite concentration measures. First, the data must be preprocessed to prepare them for analysis. Next, the intensity of the metabolite signal(s) of interest must be estimated. Finally, the measured metabolite signal intensities must be converted into scaled concentration units employing a quantitative reference signal to allow meaningful interpretation. In this paper, we review these three main steps in the post-acquisition workflow of a single-voxel MRS experiment (preprocessing, analysis and quantification) and provide recommendations for best practices at each step.
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Affiliation(s)
- Jamie Near
- Douglas Mental Health University Institute and Department of Psychiatry, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
| | - Ashley D. Harris
- Department of Radiology, University of Calgary, Calgary, Canada
- Alberta Children’s Hospital Research Institute, Calgary, Canada
- Hotchkiss Brain Institute, Calgary, Canada
| | - Christoph Juchem
- Department of Biomedical Engineering, Columbia University, New York NY, USA
| | - Roland Kreis
- Departments of Radiology and Biomedical Research, University Bern, Switzerland
| | - Małgorzata Marjańska
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis MN, USA
| | - Gülin Öz
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis MN, USA
| | - Johannes Slotboom
- Support Center for Advanced Neuroimaging (SCAN), Neuroradiology, University Hospital Inselspital, Bern, Switzerland
| | - Martin Wilson
- Centre for Human Brain Health and School of Psychology, University of Birmingham, Birmingham, England
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Choi IY, Andronesi OC, Barker P, Bogner W, Edden RAE, Kaiser LG, Lee P, Marjańska M, Terpstra M, de Graaf RA. Spectral editing in 1 H magnetic resonance spectroscopy: Experts' consensus recommendations. NMR IN BIOMEDICINE 2021; 34:e4411. [PMID: 32946145 PMCID: PMC8557623 DOI: 10.1002/nbm.4411] [Citation(s) in RCA: 62] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 08/31/2020] [Accepted: 09/01/2020] [Indexed: 05/08/2023]
Abstract
Spectral editing in in vivo 1 H-MRS provides an effective means to measure low-concentration metabolite signals that cannot be reliably measured by conventional MRS techniques due to signal overlap, for example, γ-aminobutyric acid, glutathione and D-2-hydroxyglutarate. Spectral editing strategies utilize known J-coupling relationships within the metabolite of interest to discriminate their resonances from overlying signals. This consensus recommendation paper provides a brief overview of commonly used homonuclear editing techniques and considerations for data acquisition, processing and quantification. Also, we have listed the experts' recommendations for minimum requirements to achieve adequate spectral editing and reliable quantification. These include selecting the right editing sequence, dealing with frequency drift, handling unwanted coedited resonances, spectral fitting of edited spectra, setting up multicenter clinical trials and recommending sequence parameters to be reported in publications.
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Affiliation(s)
- In-Young Choi
- Department of Neurology, Hoglund Biomedical Imaging Center, University of Kansas Medical Center, Kansas City, Kansas
| | - Ovidiu C Andronesi
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Peter Barker
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, F. M. Kirby Center for Functional MRI, Kennedy Krieger Institute, Baltimore, Maryland
| | - Wolfgang Bogner
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, F. M. Kirby Center for Functional MRI, Kennedy Krieger Institute, Baltimore, Maryland
| | - Lana G Kaiser
- Henry H. Wheeler, Jr. Brain Imaging Center, University of California, Berkeley, California
| | - Phil Lee
- Department of Radiology, Hoglund Biomedical Imaging Center, University of Kansas Medical Center, Kansas City, Kansas
| | - Małgorzata Marjańska
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota
| | - Melissa Terpstra
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota
| | - Robin A de Graaf
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, Connecticut
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Koush Y, de Graaf RA, Kupers R, Dricot L, Ptito M, Behar KL, Rothman DL, Hyder F. Metabolic underpinnings of activated and deactivated cortical areas in human brain. J Cereb Blood Flow Metab 2021; 41:986-1000. [PMID: 33472521 PMCID: PMC8054719 DOI: 10.1177/0271678x21989186] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 11/04/2020] [Accepted: 12/11/2020] [Indexed: 11/16/2022]
Abstract
Neuroimaging with functional MRI (fMRI) identifies activated and deactivated brain regions in task-based paradigms. These patterns of (de)activation are altered in diseases, motivating research to understand their underlying biochemical/biophysical mechanisms. Essentially, it remains unknown how aerobic metabolism of glucose to lactate (aerobic glycolysis) and excitatory-inhibitory balance of glutamatergic and GABAergic neuronal activities vary in these areas. In healthy volunteers, we investigated metabolic distinctions of activating visual cortex (VC, a task-positive area) using a visual task and deactivating posterior cingulate cortex (PCC, a task-negative area) using a cognitive task. We used fMRI-guided J-edited functional MRS (fMRS) to measure lactate, glutamate plus glutamine (Glx) and γ-aminobutyric acid (GABA), as indicators of aerobic glycolysis and excitatory-inhibitory balance, respectively. Both lactate and Glx increased upon activating VC, but did not change upon deactivating PCC. Basal GABA was negatively correlated with BOLD responses in both brain areas, but during functional tasks GABA decreased in VC upon activation and GABA increased in PCC upon deactivation, suggesting BOLD responses in relation to baseline are impacted oppositely by task-induced inhibition. In summary, opposite relations between BOLD response and GABAergic inhibition, and increases in aerobic glycolysis and glutamatergic activity distinguish the BOLD response in (de)activated areas.
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Affiliation(s)
- Yury Koush
- Magnetic Resonance Research Center, Department of Radiology & Biomedical Imaging, Yale University, New Haven, CT, USA
| | - Robin A de Graaf
- Magnetic Resonance Research Center, Department of Radiology & Biomedical Imaging, Yale University, New Haven, CT, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Ron Kupers
- BRAINlab, Department of Neuroscience, Panum Institute, University of Copenhagen, Copenhagen, Denmark
| | - Laurence Dricot
- Institute of NeuroScience (IoNS), Université catholique de Louvain (UCLouvain), Belgium
| | - Maurice Ptito
- School of Optometry, Université de Montreal, Montreal, Canada
| | - Kevin L Behar
- Magnetic Resonance Research Center, Department of Radiology & Biomedical Imaging, Yale University, New Haven, CT, USA
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | - Douglas L Rothman
- Magnetic Resonance Research Center, Department of Radiology & Biomedical Imaging, Yale University, New Haven, CT, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Fahmeed Hyder
- Magnetic Resonance Research Center, Department of Radiology & Biomedical Imaging, Yale University, New Haven, CT, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
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27
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Iqbal Z, Nguyen D, Thomas MA, Jiang S. Deep learning can accelerate and quantify simulated localized correlated spectroscopy. Sci Rep 2021; 11:8727. [PMID: 33888805 PMCID: PMC8062502 DOI: 10.1038/s41598-021-88158-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 03/25/2021] [Indexed: 11/16/2022] Open
Abstract
Nuclear magnetic resonance spectroscopy (MRS) allows for the determination of atomic structures and concentrations of different chemicals in a biochemical sample of interest. MRS is used in vivo clinically to aid in the diagnosis of several pathologies that affect metabolic pathways in the body. Typically, this experiment produces a one dimensional (1D) 1H spectrum containing several peaks that are well associated with biochemicals, or metabolites. However, since many of these peaks overlap, distinguishing chemicals with similar atomic structures becomes much more challenging. One technique capable of overcoming this issue is the localized correlated spectroscopy (L-COSY) experiment, which acquires a second spectral dimension and spreads overlapping signal across this second dimension. Unfortunately, the acquisition of a two dimensional (2D) spectroscopy experiment is extremely time consuming. Furthermore, quantitation of a 2D spectrum is more complex. Recently, artificial intelligence has emerged in the field of medicine as a powerful force capable of diagnosing disease, aiding in treatment, and even predicting treatment outcome. In this study, we utilize deep learning to: (1) accelerate the L-COSY experiment and (2) quantify L-COSY spectra. All training and testing samples were produced using simulated metabolite spectra for chemicals found in the human body. We demonstrate that our deep learning model greatly outperforms compressed sensing based reconstruction of L-COSY spectra at higher acceleration factors. Specifically, at four-fold acceleration, our method has less than 5% normalized mean squared error, whereas compressed sensing yields 20% normalized mean squared error. We also show that at low SNR (25% noise compared to maximum signal), our deep learning model has less than 8% normalized mean squared error for quantitation of L-COSY spectra. These pilot simulation results appear promising and may help improve the efficiency and accuracy of L-COSY experiments in the future.
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Affiliation(s)
- Zohaib Iqbal
- Medical Artificial Intelligence and Automation Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Dan Nguyen
- Medical Artificial Intelligence and Automation Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Michael Albert Thomas
- Department of Radiological Sciences, University of California Los Angles, Los Angeles, CA, USA
| | - Steve Jiang
- Medical Artificial Intelligence and Automation Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.
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28
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Mamone S, Schmidt AB, Schwaderlapp N, Lange T, von Elverfeldt D, Hennig J, Glöggler S. Localized singlet-filtered MRS in vivo. NMR IN BIOMEDICINE 2021; 34:e4400. [PMID: 32869915 DOI: 10.1002/nbm.4400] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Revised: 08/05/2020] [Accepted: 08/08/2020] [Indexed: 06/11/2023]
Abstract
MR is a prominent technology to investigate diseases, with millions of clinical procedures performed every year. Metabolic dysfunction is one common aspect associated with many diseases. Thus, understanding and monitoring metabolic changes is essential to develop cures for many illnesses, including for example cancer and neurodegeneration. MR methodologies are especially suited to study endogenous metabolites and processes within an organism in vivo, which has led to many insights about physiological functions. Advancing metabolic MR techniques is therefore key to further understand physiological processes. Here, we introduce an approach based on nuclear spin singlet states to specifically filter metabolic signals and particularly show that singlet-filtered glutamate can be observed distinctly in the hippocampus of a living mouse in vivo. This development opens opportunities to make use of the singlet spin phenomenon in vivo and besides its use as a filter to provide scope for new contrast agents.
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Affiliation(s)
- Salvatore Mamone
- NMR Signal Enhancement Group, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany
- Center for Biostructural Imaging of Neurodegeneration of UMG, Göttingen, Germany
| | - Andreas B Schmidt
- Department of Radiology, Medical Physics, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- German Consortium for Cancer Research (DKTK), partner site Freiburg, Freiburg, Germany
- German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Niels Schwaderlapp
- Department of Radiology, Medical Physics, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Thomas Lange
- Department of Radiology, Medical Physics, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Dominik von Elverfeldt
- Department of Radiology, Medical Physics, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Jürgen Hennig
- Department of Radiology, Medical Physics, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Stefan Glöggler
- NMR Signal Enhancement Group, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany
- Center for Biostructural Imaging of Neurodegeneration of UMG, Göttingen, Germany
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Saleh MG, Edden RAE, Chang L, Ernst T. Motion correction in magnetic resonance spectroscopy. Magn Reson Med 2020; 84:2312-2326. [PMID: 32301174 PMCID: PMC8386494 DOI: 10.1002/mrm.28287] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2019] [Revised: 03/25/2020] [Accepted: 03/26/2020] [Indexed: 12/15/2022]
Abstract
In vivo proton magnetic resonance spectroscopy and spectroscopic imaging (MRS/MRSI) are valuable tools to study normal and abnormal human brain physiology. However, they are sensitive to motion, due to strong crusher gradients, long acquisition times, reliance on high magnetic field homogeneity, and particular acquisition methods such as spectral editing. The effects of motion include incorrect spatial localization, phase fluctuations, incoherent averaging, line broadening, and ultimately quantitation errors. Several retrospective methods have been proposed to correct motion-related artifacts. Recent advances in hardware also allow prospective (real-time) correction of the effects of motion, including adjusting voxel location, center frequency, and magnetic field homogeneity. This article reviews prospective and retrospective methods available in the literature and their implications for clinical MRS/MRSI. In combination, these methods can attenuate or eliminate most motion-related artifacts and facilitate the acquisition of high-quality data in the clinical research setting.
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Affiliation(s)
- Muhammad G. Saleh
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Maryland, USA
- F. M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Richard A. E. Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Maryland, USA
- F. M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Linda Chang
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland, Baltimore, USA
| | - Thomas Ernst
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland, Baltimore, USA
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30
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Mikkelsen M, Tapper S, Near J, Mostofsky SH, Puts NAJ, Edden RAE. Correcting frequency and phase offsets in MRS data using robust spectral registration. NMR IN BIOMEDICINE 2020; 33:e4368. [PMID: 32656879 PMCID: PMC9652614 DOI: 10.1002/nbm.4368] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 06/10/2020] [Accepted: 06/16/2020] [Indexed: 05/16/2023]
Abstract
An algorithm for retrospective correction of frequency and phase offsets in MRS data is presented. The algorithm, termed robust spectral registration (rSR), contains a set of subroutines designed to robustly align individual transients in a given dataset even in cases of significant frequency and phase offsets or unstable lipid contamination and residual water signals. Data acquired by complex multiplexed editing approaches with distinct subspectral profiles are also accurately aligned. Automated removal of unstable lipid contamination and residual water signals is applied first, when needed. Frequency and phase offsets are corrected in the time domain by aligning each transient to a weighted average reference in a statistically optimal order using nonlinear least-squares optimization. The alignment of subspectra in edited datasets is performed using an approach that specifically targets subtraction artifacts in the frequency domain. Weighted averaging is then used for signal averaging to down-weight poorer-quality transients. Algorithm performance was assessed on one simulated and 67 in vivo pediatric GABA-/GSH-edited HERMES datasets and compared with the performance of a multistep correction method previously developed for aligning HERMES data. The performance of the novel approach was quantitatively assessed by comparing the estimated frequency/phase offsets against the known values for the simulated dataset or by examining the presence of subtraction artifacts in the in vivo data. Spectral quality was improved following robust alignment, especially in cases of significant spectral distortion. rSR reduced more subtraction artifacts than the multistep method in 64% of the GABA difference spectra and 75% of the GSH difference spectra. rSR overcomes the major challenges of frequency and phase correction.
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Affiliation(s)
- Mark Mikkelsen
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Sofie Tapper
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Jamie Near
- Douglas Mental Health University Institute and Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Stewart H. Mostofsky
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, Maryland
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of Psychiatry and Behavioral Sciences, The Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Nicolaas A. J. Puts
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
- Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Richard A. E. Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
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31
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Dacko M, Lange T. Flexible MEGA editing scheme with asymmetric adiabatic pulses applied for T 2 measurement of lactate in human brain. Magn Reson Med 2020; 85:1160-1174. [PMID: 32975334 DOI: 10.1002/mrm.28500] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Revised: 08/03/2020] [Accepted: 08/05/2020] [Indexed: 11/09/2022]
Abstract
PURPOSE A flexible MEGA editing scheme which decouples the editing efficiency from TE is proposed and the utility of asymmetric adiabatic pulses for this new technique is explored. It is demonstrated that the method enables robust T 2 measurement of lactate in healthy human brain. METHODS The proposed variation of the MEGA scheme applies editing pulses in both acquired spectra, ensuring that the difference in J-evolution of the target resonance leads to maximal signal yield in the difference spectrum for arbitrary TE. A MEGA-sLASER sequence is augmented with asymmetric adiabatic editing pulses for enhanced flexibility and immunity to B 1 + miscalibration and inhomogeneities. The technique is validated and optimized for flexible lactate editing via a simple analytical model, numerical simulations and in vitro experiments. The T 2 relaxation constant of lactate is determined in vivo via multiple-TE measurements with the proposed method and a dedicated postprocessing and quantification approach. RESULTS Asymmetric adiabatic editing pulses improve robustness and facilitate efficient J-editing in sequences or protocols with strong timing constraints. Single voxel measurements using the proposed MEGA scheme in the occipital cortex of six healthy subjects yield a relaxation constant of T 2 = 171 ± 19 ms for the methyl resonance of lactate at a field strength of 3T. CONCLUSIONS The proposed MEGA editing scheme allows for novel kinds of J-editing experiments and promises to be an asset to robust T 2 measurement of lactate and potentially other J-coupled metabolites in vivo.
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Affiliation(s)
- Michael Dacko
- Center for Diagnostic and Therapeutic Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Thomas Lange
- Center for Diagnostic and Therapeutic Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
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32
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Oeltzschner G, Zöllner HJ, Hui SCN, Mikkelsen M, Saleh MG, Tapper S, Edden RAE. Osprey: Open-source processing, reconstruction & estimation of magnetic resonance spectroscopy data. J Neurosci Methods 2020; 343:108827. [PMID: 32603810 PMCID: PMC7477913 DOI: 10.1016/j.jneumeth.2020.108827] [Citation(s) in RCA: 76] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2020] [Revised: 06/10/2020] [Accepted: 06/22/2020] [Indexed: 12/22/2022]
Abstract
BACKGROUND Processing and quantitative analysis of magnetic resonance spectroscopy (MRS) data are far from standardized and require interfacing with third-party software. Here, we present Osprey, a fully integrated open-source data analysis pipeline for MRS data, with seamless integration of pre-processing, linear-combination modelling, quantification, and data visualization. NEW METHOD Osprey loads multiple common MRS data formats, performs phased-array coil combination, frequency-and phase-correction of individual transients, signal averaging and Fourier transformation. Linear combination modelling of the processed spectrum is carried out using simulated basis sets and a spline baseline. The MRS voxel is coregistered to an anatomical image, which is segmented for tissue correction and quantification is performed based upon modelling parameters and tissue segmentation. The results of each analysis step are visualized in the Osprey GUI. The analysis pipeline is demonstrated in 12 PRESS, 11 MEGA-PRESS, and 8 HERMES datasets acquired in healthy subjects. RESULTS Osprey successfully loads, processes, models, and quantifies MRS data acquired with a variety of conventional and spectral editing techniques. COMPARISON WITH EXISTING METHOD(S) Osprey is the first MRS software to combine uniform pre-processing, linear-combination modelling, tissue correction and quantification into a coherent ecosystem. Compared to existing compiled, often closed-source modelling software, Osprey's open-source code philosophy allows researchers to integrate state-of-the-art data processing and modelling routines, and potentially converge towards standardization of analysis. CONCLUSIONS Osprey combines robust, peer-reviewed data processing methods into a modular workflow that is easily augmented by community developers, allowing the rapid implementation of new methods.
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Affiliation(s)
- Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States.
| | - Helge J Zöllner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Steve C N Hui
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Mark Mikkelsen
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Muhammad G Saleh
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Sofie Tapper
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
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Kreis R, Boer V, Choi I, Cudalbu C, de Graaf RA, Gasparovic C, Heerschap A, Krššák M, Lanz B, Maudsley AA, Meyerspeer M, Near J, Öz G, Posse S, Slotboom J, Terpstra M, Tkáč I, Wilson M, Bogner W. Terminology and concepts for the characterization of in vivo MR spectroscopy methods and MR spectra: Background and experts' consensus recommendations. NMR IN BIOMEDICINE 2020; 34:e4347. [PMID: 32808407 PMCID: PMC7887137 DOI: 10.1002/nbm.4347] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Revised: 05/20/2020] [Accepted: 05/21/2020] [Indexed: 05/04/2023]
Abstract
With a 40-year history of use for in vivo studies, the terminology used to describe the methodology and results of magnetic resonance spectroscopy (MRS) has grown substantially and is not consistent in many aspects. Given the platform offered by this special issue on advanced MRS methodology, the authors decided to describe many of the implicated terms, to pinpoint differences in their meanings and to suggest specific uses or definitions. This work covers terms used to describe all aspects of MRS, starting from the description of the MR signal and its theoretical basis to acquisition methods, processing and to quantification procedures, as well as terms involved in describing results, for example, those used with regard to aspects of quality, reproducibility or indications of error. The descriptions of the meanings of such terms emerge from the descriptions of the basic concepts involved in MRS methods and examinations. This paper also includes specific suggestions for future use of terms where multiple conventions have emerged or coexisted in the past.
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Affiliation(s)
- Roland Kreis
- Department of Radiology, Neuroradiology, and Nuclear Medicine and Department of Biomedical ResearchUniversity BernBernSwitzerland
| | - Vincent Boer
- Danish Research Centre for Magnetic Resonance, Funktions‐ og Billeddiagnostisk EnhedCopenhagen University Hospital HvidovreHvidovreDenmark
| | - In‐Young Choi
- Department of Neurology, Hoglund Brain Imaging CenterUniversity of Kansas Medical CenterKansas CityKansasUSA
| | - Cristina Cudalbu
- Centre d'Imagerie Biomedicale (CIBM)Ecole Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland
| | - Robin A. de Graaf
- Department of Radiology and Biomedical Imaging & Department of Biomedical EngineeringYale UniversityNew HavenConnecticutUSA
| | | | - Arend Heerschap
- Department of Radiology and Nuclear MedicineRadboud University Medical CenterNijmegenThe Netherlands
| | - Martin Krššák
- Division of Endocrinology and Metabolism, Department of Internal Medicine III & High Field MR Centre, Department of Biomedical Imaging and Image guided TherapyMedical University of ViennaViennaAustria
| | - Bernard Lanz
- Laboratory of Functional and Metabolic Imaging (LIFMET)Ecole Polytechnique Fédérale de LausanneLausanneSwitzerland
- Sir Peter Mansfield Imaging Centre, School of MedicineUniversity of NottinghamNottinghamUK
| | - Andrew A. Maudsley
- Department of Radiology, Miller School of MedicineUniversity of MiamiMiamiFloridaUSA
| | - Martin Meyerspeer
- Center for Medical Physics and Biomedical EngineeringMedical University of ViennaViennaAustria
- High Field MR CenterMedical University of ViennaViennaAustria
| | - Jamie Near
- Douglas Mental Health University Institute and Department of PsychiatryMcGill UniversityMontrealCanada
| | - Gülin Öz
- Center for Magnetic Resonance Research, Department of RadiologyUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Stefan Posse
- Department of NeurologyUniversity of New Mexico School of MedicineAlbuquerqueNew MexicoUSA
| | - Johannes Slotboom
- Department of Radiology, Neuroradiology, and Nuclear MedicineUniversity Hospital BernBernSwitzerland
| | - Melissa Terpstra
- Center for Magnetic Resonance Research, Department of RadiologyUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Ivan Tkáč
- Center for Magnetic Resonance Research, Department of RadiologyUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Martin Wilson
- Centre for Human Brain Health and School of PsychologyUniversity of BirminghamBirminghamUK
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
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34
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Tang L, Zhao Y, Li Y, Guo R, Clifford B, El Fakhri G, Ma C, Liang ZP, Luo J. Accelerated J-resolved 1 H-MRSI with limited and sparse sampling of ( k , t 1 , t 2 -space. Magn Reson Med 2020; 85:30-41. [PMID: 32726510 DOI: 10.1002/mrm.28413] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Revised: 06/13/2020] [Accepted: 06/15/2020] [Indexed: 01/18/2023]
Abstract
PURPOSE To accelerate the acquisition of J-resolved proton magnetic resonance spectroscopic imaging (1 H-MRSI) data for high-resolution mapping of brain metabolites and neurotransmitters. METHODS The proposed method used a subspace model to represent multidimensional spatiospectral functions, which significantly reduced the number of parameters to be determined from J-resolved 1 H-MRSI data. A semi-LASER-based (Localization by Adiabatic SElective Refocusing) echo-planar spectroscopic imaging (EPSI) sequence was used for data acquisition. The proposed data acquisition scheme sampled k , t 1 , t 2 -space in variable density, where t1 and t2 specify the J-coupling and chemical-shift encoding times, respectively. Selection of the J-coupling encoding times (or, echo time values) was based on a Cramer-Rao lower bound analysis, which were optimized for gamma-aminobutyric acid (GABA) detection. In image reconstruction, parameters of the subspace-based spatiospectral model were determined by solving a constrained optimization problem. RESULTS Feasibility of the proposed method was evaluated using both simulated and experimental data from a spectroscopic phantom. The phantom experimental results showed that the proposed method, with a factor of 12 acceleration in data acquisition, could determine the distribution of J-coupled molecules with expected accuracy. In vivo study with healthy human subjects also showed that 3D maps of brain metabolites and neurotransmitters can be obtained with a nominal spatial resolution of 3.0 × 3.0 × 4.8 mm3 from J-resolved 1 H-MRSI data acquired in 19.4 min. CONCLUSIONS This work demonstrated the feasibility of highly accelerated J-resolved 1 H-MRSI using limited and sparse sampling of k , t 1 , t 2 -space and subspace modeling. With further development, the proposed method may enable high-resolution mapping of brain metabolites and neurotransmitters in clinical applications.
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Affiliation(s)
- Lihong Tang
- Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yibo Zhao
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Yudu Li
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Rong Guo
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Bryan Clifford
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Georges El Fakhri
- Department of Radiology, Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Chao Ma
- Department of Radiology, Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Zhi-Pei Liang
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Jie Luo
- Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
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Saleh MG, Wang M, Mikkelsen M, Hui SC, Oeltzschner G, Boissoneault J, Stennett B, Edden RA, Porges EC. Simultaneous edited MRS of GABA, glutathione, and ethanol. NMR IN BIOMEDICINE 2020; 33:e4227. [PMID: 31943424 PMCID: PMC7405912 DOI: 10.1002/nbm.4227] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2019] [Revised: 10/03/2019] [Accepted: 10/27/2019] [Indexed: 06/10/2023]
Abstract
The aim of this work was to develop simultaneous edited MRS of γ-aminobutyric acid (GABA), glutathione (GSH), and ethanol (EtOH) using Hadamard encoding and reconstruction of MEGA-edited spectroscopy (HERMES) at 3T. Density-matrix simulations of HERMES were carried out and compared with phantom experiments. In vivo experiments were performed in six healthy volunteers about 30 min after alcohol consumption. Simulations of HERMES showed GABA-, GSH-, and EtOH-edited spectra with low levels of crosstalk and excellent agreement with phantom spectra. In vivo experiments showed well edited GABA signals at 3.0 ppm, GSH at 2.95 ppm, and EtOH at 1.18 ppm in the respective Hadamard combination spectra. Measured integral ratios were 0.082 ± 0.012 for GABA/Cr, 0.037 ± 0.006 for GSH/Cr, and 0.305 ± 0.129 for EtOH/Cr. Simulated, phantom, and in vivo measurements of HERMES show excellent separation of GABA-, GSH-, and EtOH-edited signals with negligible levels of crosstalk. HERMES allows a threefold acceleration of editing while maintaining spectral quality compared with sequentially acquired MEGA-PRESS measurements.
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Affiliation(s)
- Muhammad G. Saleh
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Min Wang
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Mark Mikkelsen
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Steve C.N. Hui
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Jeff Boissoneault
- Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
- Center for Pain Research and Behavioral Health, Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
- Center for Addiction Research and Education, Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
| | - Bethany Stennett
- Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
- Center for Pain Research and Behavioral Health, Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
- Center for Addiction Research and Education, Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
| | - Richard A.E. Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Eric C. Porges
- Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
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Prisciandaro JJ, Mikkelsen M, Saleh MG, Edden RAE. An evaluation of the reproducibility of 1H-MRS GABA and GSH levels acquired in healthy volunteers with J-difference editing sequences at varying echo times. Magn Reson Imaging 2019; 65:109-113. [PMID: 31707293 DOI: 10.1016/j.mri.2019.10.004] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Revised: 09/18/2019] [Accepted: 10/08/2019] [Indexed: 10/25/2022]
Abstract
Recent advances in J-difference-edited proton magnetic resonance spectroscopy (1H MRS) data acquisition and processing have led to the development of Hadamard Encoding and Reconstruction of MEGA-Edited Spectroscopy (HERMES) techniques, which enable the simultaneous measurement of ɣ-aminobutyric acid (GABA), the primary inhibitory amino acid neurotransmitter in the central nervous system, and of glutathione (GSH), the most abundant antioxidant in living tissue, at the commonly available magnetic field strength of 3 T. However, the reproducibility of brain levels of GABA and GSH measured across multiple scans in human subjects using HERMES remains to be established. In the present study, twelve healthy volunteers completed two consecutive HERMES scans of the dorsal anterior cingulate cortex (dACC) to assess the test-retest reproducibility of the technique for GABA and GSH measurements at TE = 80 ms. Eleven of the twelve participants additionally completed two consecutive MEGA-PRESS scans at TE = 120 ms, with editing pulses configured for GSH acquisition, to compare the reliability of GSH in the same voxel measured using the standard MEGA-PRESS at TE = 120 ms. The primary findings of study were that, 1) the coefficient of variation (CV) of measuring GABA with HERMES was 16.7%, which is in agreement with the reliability we previously reported for measuring GABA using MEGA-PRESS; and 2) the reliability of measuring GSH with MEGA-PRESS at TE = 120 ms was more than twice as high as that for measuring the antioxidant with HERMES at TE = 80 ms (CV = 7.3% vs. 19.0% respectively). These findings suggest that HERMES and MEGA-PRESS offer similar reliabilities for measuring GABA, while MEGA-PRESS at TE = 120 ms is more reliable for measuring GSH relative to HERMES at TE = 80 ms.
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Affiliation(s)
- James J Prisciandaro
- Department of Psychiatry and Behavioral Sciences, Addiction Sciences Division, Center for Biomedical Imaging, Medical University of SC, Charleston, SC, United States of America.
| | - Mark Mikkelsen
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States of America; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States of America
| | - Muhammad G Saleh
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States of America; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States of America
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States of America; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States of America
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Landheer K, Schulte RF, Treacy MS, Swanberg KM, Juchem C. Theoretical description of modern1H in Vivo magnetic resonance spectroscopic pulse sequences. J Magn Reson Imaging 2019; 51:1008-1029. [DOI: 10.1002/jmri.26846] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Revised: 06/14/2019] [Accepted: 06/17/2019] [Indexed: 01/20/2023] Open
Affiliation(s)
- Karl Landheer
- Biomedical Engineering, Columbia University Fu Foundation School of Engineering and Applied Science New York New York USA
| | | | - Michael S. Treacy
- Biomedical Engineering, Columbia University Fu Foundation School of Engineering and Applied Science New York New York USA
| | - Kelley M. Swanberg
- Biomedical Engineering, Columbia University Fu Foundation School of Engineering and Applied Science New York New York USA
| | - Christoph Juchem
- Biomedical Engineering, Columbia University Fu Foundation School of Engineering and Applied Science New York New York USA
- Radiology, Columbia University College of Physicians and Surgeons New York New York USA
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Motor cortex metabolite alterations in amyotrophic lateral sclerosis assessed in vivo using edited and non-edited magnetic resonance spectroscopy. Brain Res 2019; 1718:22-31. [PMID: 31002818 DOI: 10.1016/j.brainres.2019.04.018] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2018] [Revised: 03/09/2019] [Accepted: 04/15/2019] [Indexed: 12/11/2022]
Abstract
Previous MRI and proton spectroscopy (1H-MRS) studies have revealed impaired neuronal integrity and altered neurometabolite concentrations in the motor cortex of patients with amyotrophic lateral sclerosis (ALS). Here, we aim to use MRI with conventional and novel MRS sequences to further investigate neurometabolic changes in the motor cortex of ALS patients and their relation to clinical parameters. We utilized the novel HERMES (Hadamard Encoding and Reconstruction of MEGA-Edited Spectroscopy) MRS sequence to simultaneously quantify the inhibitory neurotransmitter GABA and antioxidant glutathione in ALS patients (n = 7) and healthy controls (n = 7). In addition, we have also quantified other MRS observable neurometabolites using a conventional point-resolved MR spectroscopy (PRESS) sequence in ALS patients (n = 20) and healthy controls (n = 20). We observed a trend towards decreasing glutathione concentrations in the motor cortex of ALS patients (p = 0.0842). In addition, we detected a 11% decrease in N-acetylaspartate (NAA) (p = 0.025), a 15% increase in glutamate + glutamine (Glx) (p = 0.0084) and a 21% increase in myo-inositol (mIns) (p = 0.0051) concentrations for ALS patients compared to healthy controls. Furthermore, significant positive correlations were found between GABA-NAA (p = 0.0480; Rρ = 0.7875) and NAA-mIns (p = 0.0448; Rρ = -0.4651) levels among the patients. NAA levels in the bulbar-onset patient group were found to be significantly (p = 0.0097) lower compared to the limb-onset group. A strong correlation (p < 0.0001; Rρ = -0,8801) for mIns and a weak correlation (p = 0.0066; Rρ = -0,6673) for Glx was found for the disease progression, measured by declining of the ALS Functional Rating Scale-Revised criteria (ALSFRS-R). Concentrations of mIns and Glx also correlated with disease severity measured by forced vital capacity (FVC). Results suggest that mean neurometabolite concentrations detected in the motor cortex may indicate clinical and pathological changes in ALS.
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Chan KL, Oeltzschner G, Saleh MG, Edden RAE, Barker PB. Simultaneous editing of GABA and GSH with Hadamard-encoded MR spectroscopic imaging. Magn Reson Med 2019; 82:21-32. [PMID: 30793803 DOI: 10.1002/mrm.27702] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2018] [Revised: 01/28/2019] [Accepted: 01/30/2019] [Indexed: 12/23/2022]
Abstract
PURPOSE To evaluate the feasibility of simultaneous MR spectroscopic imaging (MRSI) of gamma-aminobutyric acid (GABA) and glutathione (GSH) in the human brain using Hadamard Encoding and Reconstruction of MEGA-Edited Spectroscopy (HERMES). METHODS Point RESolved Spectroscopy (PRESS)-localized MRSI was performed in GABA and GSH phantoms and in the human brain (n = 3) using HERMES editing and compared to conventional MEGA editing of each metabolite. Multiplet patterns, signal intensities, and metabolite crosstalk were compared between methods. GABA+ and GSH levels were compared between methods for bias and variability. Linear regression of HERMES-MRSI GABA+/H2 O and GSH/H2 O versus gray matter (GM) fraction were performed to assess differences between GM and white matter (WM). RESULTS Phantom HERMES-MRSI scans gave comparable GABA+ and GSH signals to MEGA-MRSI across the PRESS-localized volume. In vivo, HERMES-reconstructed GABA+ and GSH values had minimal measurement bias and variability relative to MEGA-MRSI. Intersubject coefficients of variation (CV) from two regions within the PRESS-localized volume for HERMES and MEGA were 6-12% for GABA+ and 6-19% for GSH. Interregion CVs were 5-15% for GABA+ and 3-17% for GSH. The GABA+/H2 O and GSH/H2 O ratios were ~1.8 times higher and ~1.9 times higher, respectively, in GM than in WM. CONCLUSION HERMES-MRSI of GABA+ and GSH was found to be practical in the human brain with minimal measurement bias and comparable variability to separate MEGA-edited acquisitions of each metabolite performed in double the scan time. The HERMES-MRSI is a promising method for simultaneously mapping the distribution of multiple low-concentration metabolites.
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Affiliation(s)
- Kimberly L Chan
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland.,Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Muhammad G Saleh
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Peter B Barker
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
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40
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Saleh MG, Rimbault D, Mikkelsen M, Oeltzschner G, Wang AM, Jiang D, Alhamud A, Near J, Schär M, Noeske R, Murdoch JB, Ersland L, Craven AR, Dwyer GE, Grüner ER, Pan L, Ahn S, Edden RAE. Multi-vendor standardized sequence for edited magnetic resonance spectroscopy. Neuroimage 2019; 189:425-431. [PMID: 30682536 DOI: 10.1016/j.neuroimage.2019.01.056] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2018] [Revised: 01/18/2019] [Accepted: 01/21/2019] [Indexed: 12/12/2022] Open
Abstract
Spectral editing allows direct measurement of low-concentration metabolites, such as GABA, glutathione (GSH) and lactate (Lac), relevant for understanding brain (patho)physiology. The most widely used spectral editing technique is MEGA-PRESS, which has been diversely implemented across research sites and vendors, resulting in variations in the final resolved edited signal. In this paper, we describe an effort to develop a new universal MEGA-PRESS sequence with HERMES functionality for the major MR vendor platforms with standardized RF pulse shapes, durations, amplitudes and timings. New RF pulses were generated for the universal sequence. Phantom experiments were conducted on Philips, Siemens, GE and Canon 3 T MRI scanners using 32-channel head coils. In vivo experiments were performed on the same six subjects on Philips and Siemens scanners, and on two additional subjects, one on GE and one on Canon scanners. On each platform, edited MRS experiments were conducted with the vendor-native and universal MEGA-PRESS sequences for GABA (TE = 68 ms) and Lac editing (TE = 140 ms). Additionally, HERMES for GABA and GSH was performed using the universal sequence at TE = 80 ms. The universal sequence improves inter-vendor similarity of GABA-edited and Lac-edited MEGA-PRESS spectra. The universal HERMES sequence yields both GABA- and GSH-edited spectra with negligible levels of crosstalk on all four platforms, and with strong agreement among vendors for both edited spectra. In vivo GABA+/Cr, Lac/Cr and GSH/Cr ratios showed relatively low variation between scanners using the universal sequence. In conclusion, phantom and in vivo experiments demonstrate successful implementation of the universal sequence across all four major vendors, allowing editing of several metabolites across a range of TEs.
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Affiliation(s)
- Muhammad G Saleh
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.
| | - Daniel Rimbault
- Medical Imaging Research Unit, Division of Biomedical Engineering, University of Cape Town, Cape Town, South Africa
| | - Mark Mikkelsen
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Anna M Wang
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Dengrong Jiang
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ali Alhamud
- Medical Imaging Research Unit, Division of Biomedical Engineering, University of Cape Town, Cape Town, South Africa; Department of Nuclear Engineering, University of Tripoli, Tripoli, Libya
| | - Jamie Near
- Douglas Mental Health University Institute and Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Michael Schär
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | | | | | - Lars Ersland
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway; NORMENT - Norwegian Center for Mental Disorders Research, University of Bergen, Bergen, Norway; Department of Clinical Engineering, Haukeland University Hospital, Bergen, Norway
| | - Alexander R Craven
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway; NORMENT - Norwegian Center for Mental Disorders Research, University of Bergen, Bergen, Norway
| | - Gerard Eric Dwyer
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway; NORMENT - Norwegian Center for Mental Disorders Research, University of Bergen, Bergen, Norway
| | - Eli Renate Grüner
- Department of Clinical Radiology, Haukeland University Hospital, Bergen, Norway; Department of Physics and Technology, University of Bergen, Norway
| | - Li Pan
- Siemens Healthineers, USA
| | | | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
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Oeltzschner G, Saleh MG, Rimbault D, Mikkelsen M, Chan KL, Puts NAJ, Edden RAE. Advanced Hadamard-encoded editing of seven low-concentration brain metabolites: Principles of HERCULES. Neuroimage 2019; 185:181-190. [PMID: 30296560 PMCID: PMC6289748 DOI: 10.1016/j.neuroimage.2018.10.002] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2018] [Revised: 09/17/2018] [Accepted: 10/01/2018] [Indexed: 11/25/2022] Open
Abstract
PURPOSE To demonstrate the framework of a novel Hadamard-encoded spectral editing approach for simultaneously detecting multiple low-concentration brain metabolites in vivo at 3T. METHODS HERCULES (Hadamard Editing Resolves Chemicals Using Linear-combination Estimation of Spectra) is a four-step Hadamard-encoded editing scheme. 20-ms editing pulses are applied at: (A) 4.58 and 1.9 ppm; (B) 4.18 and 1.9 ppm; (C) 4.58 ppm; and (D) 4.18 ppm. Edited signals from γ-aminobutyric acid (GABA), glutathione (GSH), ascorbate (Asc), N-acetylaspartate (NAA), N-acetylaspartylglutamate (NAAG), aspartate (Asp), lactate (Lac), and likely 2-hydroxyglutarate (2-HG) are separated with reduced signal overlap into distinct Hadamard combinations: (A+B+C+D); (A+B-C-D); and (A-B+C-D). HERCULES uses a novel multiplexed linear-combination modeling approach, fitting all three Hadamard combinations at the same time, maximizing the amount of information used for model parameter estimation, in order to quantify the levels of these compounds. Fitting also allows estimation of the levels of total choline (tCho), myo-inositol (Ins), glutamate (Glu), and glutamine (Gln). Quantitative HERCULES results were compared between two grey- and white-matter-rich brain regions (11 min acquisition time each) in 10 healthy volunteers. Coefficients of variation (CV) of quantified measurements from the HERCULES fitting approach were compared against those from a single-spectrum fitting approach, and against estimates from short-TE PRESS data. RESULTS HERCULES successfully segregates overlapping resonances into separate Hadamard combinations, allowing for the estimation of levels of seven coupled metabolites that would usually require a single 11-min editing experiment each. Metabolite levels and CVs agree well with published values. CVs of quantified measurements from the multiplexed HERCULES fitting approach outperform single-spectrum fitting and short-TE PRESS for most of the edited metabolites, performing only slightly to moderately worse than the fitting method that gives the lowest CVs for tCho, NAA, NAAG, and Asp. CONCLUSION HERCULES is a new experimental approach with the potential for simultaneous editing and multiplexed fitting of up to seven coupled low-concentration and six high-concentration metabolites within a single 11-min acquisition at 3T.
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Affiliation(s)
- Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States.
| | - Muhammad G Saleh
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Daniel Rimbault
- Medical Imaging Research Unit, Division of Biomedical Engineering, Department of Human Biology, University of Cape Town, Cape Town, South Africa
| | - Mark Mikkelsen
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Kimberly L Chan
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States; Department of Bioengineering, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Nicolaas A J Puts
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
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Mikkelsen M, Saleh MG, Near J, Chan KL, Gong T, Harris AD, Oeltzschner G, Puts NAJ, Cecil KM, Wilkinson ID, Edden RAE. Frequency and phase correction for multiplexed edited MRS of GABA and glutathione. Magn Reson Med 2018; 80:21-28. [PMID: 29215137 PMCID: PMC5876096 DOI: 10.1002/mrm.27027] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2017] [Revised: 10/10/2017] [Accepted: 11/03/2017] [Indexed: 12/24/2022]
Abstract
PURPOSE Detection of endogenous metabolites using multiplexed editing substantially improves the efficiency of edited magnetic resonance spectroscopy. Multiplexed editing (i.e., performing more than one edited experiment in a single acquisition) requires a tailored, robust approach for correction of frequency and phase offsets. Here, a novel method for frequency and phase correction (FPC) based on spectral registration is presented and compared against previously presented approaches. METHODS One simulated dataset and 40 γ-aminobutyric acid-/glutathione-edited HERMES datasets acquired in vivo at three imaging centers were used to test four FPC approaches: no correction; spectral registration; spectral registration with post hoc choline-creatine alignment; and multistep FPC. The performance of each routine for the simulated dataset was assessed by comparing the estimated frequency/phase offsets against the known values, whereas the performance for the in vivo data was assessed quantitatively by calculation of an alignment quality metric based on choline subtraction artifacts. RESULTS The multistep FPC approach returned corrections that were closest to the true values for the simulated dataset. Alignment quality scores were on average worst for no correction, and best for multistep FPC in both the γ-aminobutyric acid- and glutathione-edited spectra in the in vivo data. CONCLUSIONS Multistep FPC results in improved correction of frequency/phase errors in multiplexed γ-aminobutyric acid-/glutathione-edited magnetic resonance spectroscopy experiments. The optimal FPC strategy is experiment-specific, and may even be dataset-specific. Magn Reson Med 80:21-28, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Mark Mikkelsen
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Muhammad G. Saleh
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Jamie Near
- Douglas Mental Health University Institute and Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Kimberly L. Chan
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Tao Gong
- Shandong Medical Imaging Research Institute, Shandong University, Jinan, China
| | - Ashley D. Harris
- Department of Radiology, University of Calgary, Calgary, AB, Canada
- Child and Adolescent Imaging Research (CAIR) Program, Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Nicolaas A. J. Puts
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Kim M. Cecil
- Department of Radiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
| | | | - Richard A. E. Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
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Oeltzschner G, Chan KL, Saleh MG, Mikkelsen M, Puts NA, Edden RAE. Hadamard editing of glutathione and macromolecule-suppressed GABA. NMR IN BIOMEDICINE 2018; 31:10.1002/nbm.3844. [PMID: 29073732 PMCID: PMC5737628 DOI: 10.1002/nbm.3844] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2017] [Revised: 08/23/2017] [Accepted: 09/16/2017] [Indexed: 05/20/2023]
Abstract
The primary inhibitory neurotransmitter γ-aminobutyric acid (GABA) and the major antioxidant glutathione (GSH) are compounds of high importance for the function and integrity of the human brain. In this study, a method for simultaneous J-difference spectral-edited magnetic resonance spectroscopy (MRS) of GSH and GABA with suppression of macromolecular (MM) signals at 3 T is proposed. MM-suppressed Hadamard encoding and reconstruction of MEGA (Mescher-Garwood)-edited spectroscopy (HERMES) consists of four sub-experiments (TE = 80 ms), with 20-ms editing pulses applied at: (A) 4.56 and 1.9 ppm; (B) 4.56 and 1.5 ppm; (C) 1.9 ppm; and (D) 1.5 ppm. One Hadamard combination (A + B - C - D) yields GSH-edited spectra, and another (A - B + C - D) yields GABA-edited spectra, with symmetric suppression of the co-edited MM signal. MM-suppressed HERMES, conventional HERMES and separate Mescher-Garwood point-resolved spectroscopy (MEGA-PRESS) data were successfully acquired from a (33 mm)3 voxel in the parietal lobe in 10 healthy subjects. GSH- and GABA-edited MM-suppressed HERMES spectra were in close agreement with the respective MEGA-PRESS spectra. Mean GABA (and GSH) estimates were 1.10 ± 0.15 i.u. (0.59 ± 0.12 i.u.) for MM-suppressed HERMES, and 1.13 ± 0.09 i.u. (0.66 ± 0.09 i.u.) for MEGA-PRESS. Mean GABA (and GSH) differences between MM-suppressed HERMES and MEGA-PRESS were -0.03 ± 0.11 i.u. (-0.07 ± 0.11 i.u.). The mean signal-to-noise ratio (SNR) improvement of MM-suppressed HERMES over MEGA-PRESS was 1.45 ± 0.25 for GABA and 1.32 ± 0.24 for GSH. These results indicate that symmetric suppression of the MM signal can be accommodated into the Hadamard editing framework. Compared with sequential single-metabolite MEGA-PRESS experiments, MM-suppressed HERMES allows for simultaneous edited measurements of GSH and GABA without MM contamination in only half the scan time, and SNR is maintained.
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Affiliation(s)
- Georg Oeltzschner
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Kimberly L. Chan
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Muhammad G. Saleh
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Mark Mikkelsen
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Nicolaas A. Puts
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Richard A. E. Edden
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
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Saleh MG, Mikkelsen M, Oeltzschner G, Chan KL, Berrington A, Barker PB, Edden RAE. Simultaneous editing of GABA and glutathione at 7T using semi-LASER localization. Magn Reson Med 2017; 80:474-479. [PMID: 29285783 DOI: 10.1002/mrm.27044] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2017] [Revised: 11/13/2017] [Accepted: 11/18/2017] [Indexed: 12/12/2022]
Abstract
PURPOSE To demonstrate simultaneous editing of the two most commonly edited and overlapping signals, γ-aminobutyric acid (GABA), and glutathione (GSH), with Hadamard encoding and reconstruction of MEGA-edited spectroscopy (HERMES) using sLASER localization at 7T. METHODS Density matrix simulations of HERMES at 7T were carried out and compared with phantom experiments. Additional phantom experiments were performed to characterize the echo time (TE) -dependent modulation of GABA- and GSH-edited HERMES spectra at TE of 80-160 ms. In vivo experiments were performed in 10 healthy volunteers, comparing HERMES (11 min) to sequentially acquired MEGA-sLASER detection of GABA and GSH (2 × 11 min). RESULTS Simulations of HERMES show GABA- and GSH-edited spectra with negligible levels of crosstalk, and give modest agreement with phantom spectra. The TE series of GABA- and GSH-edited HERMES spectra modulate as a result of T2 relaxation and coupling evolution, with GABA showing a stronger TE-dependence. In vivo HERMES experiments show well-edited GABA and GSH signals. Measured concentrations are not statistically different between HERMES and MEGA-sLASER for GABA (1. 051 ± 0.254 i.u. and 1.053 ± 0.248 i.u; P > 0.985) or GSH (0.300 ± 0.091 i.u. and 0.302 ± 0.093 i.u; P > 0.940). CONCLUSION Simulated, phantom and in vivo measurements of HERMES show excellent segregation of GABA- and GSH-edited signals, and excellent agreement with separately acquired MEGA-sLASER data. HERMES allows two-fold acceleration of editing while maintaining spectral quality compared with sequentially acquired MEGA-sLASER measurements. Magn Reson Med 80:474-479, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Muhammad G Saleh
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Mark Mikkelsen
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Kimberly L Chan
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA.,Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Adam Berrington
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Peter B Barker
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
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Schmidt-Wilcke T, Fuchs E, Funke K, Vlachos A, Müller-Dahlhaus F, Puts NAJ, Harris RE, Edden RAE. GABA-from Inhibition to Cognition: Emerging Concepts. Neuroscientist 2017; 24:501-515. [PMID: 29283020 DOI: 10.1177/1073858417734530] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Neural functioning and plasticity can be studied on different levels of organization and complexity ranging from the molecular and synaptic level to neural circuitry of whole brain networks. Across neuroscience different methods are being applied to better understand the role of various neurotransmitter systems in the evolution of perception and cognition. GABA is the main inhibitory neurotransmitter in the adult mammalian brain and, depending on the brain region, up to 25% of the total number of cortical neurons are GABAergic interneurons. At the one end of the spectrum, GABAergic neurons have been accurately described with regard to cell morphological, molecular, and electrophysiological properties; at the other end researchers try to link GABA concentrations in specific brain regions to human behavior using magnetic resonance spectroscopy. One of the main challenges of modern neuroscience currently is to integrate knowledge from highly specialized subfields at distinct biological scales into a coherent picture that bridges the gap between molecules and behavior. In the current review, recent findings from different fields of GABA research are summarized delineating a potential strategy to develop a more holistic picture of the function and role of GABA.
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Affiliation(s)
- T Schmidt-Wilcke
- 1 Institute of Clinical Neuroscience and Medical Psychology, University of Düsseldorf, Düsseldorf, Germany.,2 Mauritius Therapieklinik Meerbusch, Meerbusch, Germany
| | - E Fuchs
- 3 Department of Clinical Neurobiology, Medical Faculty of Heidelberg University and German Cancer Research Center, Heidelberg, Germany
| | - K Funke
- 4 Department of Neurophysiology, Medical Faculty of Ruhr-University Bochum, Bochum, Germany
| | - A Vlachos
- 5 Department of Neuroanatomy, Institute of Anatomy and Cell Biology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - F Müller-Dahlhaus
- 6 Department of Psychiatry and Psychotherapy, University Medical Center Mainz, Mainz, Germany.,7 Department of Neurology and Stroke, and Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - N A J Puts
- 8 Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,9 F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - R E Harris
- 10 Chronic Pain and Fatigue Research Center, Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA
| | - R A E Edden
- 8 Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,9 F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
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Mikkelsen M, Barker PB, Bhattacharyya PK, Brix MK, Buur PF, Cecil KM, Chan KL, Chen DYT, Craven AR, Cuypers K, Dacko M, Duncan NW, Dydak U, Edmondson DA, Ende G, Ersland L, Gao F, Greenhouse I, Harris AD, He N, Heba S, Hoggard N, Hsu TW, Jansen JFA, Kangarlu A, Lange T, Lebel RM, Li Y, Lin CYE, Liou JK, Lirng JF, Liu F, Ma R, Maes C, Moreno-Ortega M, Murray SO, Noah S, Noeske R, Noseworthy MD, Oeltzschner G, Prisciandaro JJ, Puts NAJ, Roberts TPL, Sack M, Sailasuta N, Saleh MG, Schallmo MP, Simard N, Swinnen SP, Tegenthoff M, Truong P, Wang G, Wilkinson ID, Wittsack HJ, Xu H, Yan F, Zhang C, Zipunnikov V, Zöllner HJ, Edden RAE. Big GABA: Edited MR spectroscopy at 24 research sites. Neuroimage 2017; 159:32-45. [PMID: 28716717 PMCID: PMC5700835 DOI: 10.1016/j.neuroimage.2017.07.021] [Citation(s) in RCA: 111] [Impact Index Per Article: 15.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2017] [Revised: 06/20/2017] [Accepted: 07/11/2017] [Indexed: 12/14/2022] Open
Abstract
Magnetic resonance spectroscopy (MRS) is the only biomedical imaging method that can noninvasively detect endogenous signals from the neurotransmitter γ-aminobutyric acid (GABA) in the human brain. Its increasing popularity has been aided by improvements in scanner hardware and acquisition methodology, as well as by broader access to pulse sequences that can selectively detect GABA, in particular J-difference spectral editing sequences. Nevertheless, implementations of GABA-edited MRS remain diverse across research sites, making comparisons between studies challenging. This large-scale multi-vendor, multi-site study seeks to better understand the factors that impact measurement outcomes of GABA-edited MRS. An international consortium of 24 research sites was formed. Data from 272 healthy adults were acquired on scanners from the three major MRI vendors and analyzed using the Gannet processing pipeline. MRS data were acquired in the medial parietal lobe with standard GABA+ and macromolecule- (MM-) suppressed GABA editing. The coefficient of variation across the entire cohort was 12% for GABA+ measurements and 28% for MM-suppressed GABA measurements. A multilevel analysis revealed that most of the variance (72%) in the GABA+ data was accounted for by differences between participants within-site, while site-level differences accounted for comparatively more variance (20%) than vendor-level differences (8%). For MM-suppressed GABA data, the variance was distributed equally between site- (50%) and participant-level (50%) differences. The findings show that GABA+ measurements exhibit strong agreement when implemented with a standard protocol. There is, however, increased variability for MM-suppressed GABA measurements that is attributed in part to differences in site-to-site data acquisition. This study's protocol establishes a framework for future methodological standardization of GABA-edited MRS, while the results provide valuable benchmarks for the MRS community.
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Affiliation(s)
- Mark Mikkelsen
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Peter B Barker
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Pallab K Bhattacharyya
- Imaging Institute, Cleveland Clinic Foundation, Cleveland, OH, USA; Radiology, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH, USA
| | - Maiken K Brix
- Department of Radiology, Haukeland University Hospital, Bergen, Norway; Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Pieter F Buur
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands
| | - Kim M Cecil
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Kimberly L Chan
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA; Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - David Y-T Chen
- Department of Radiology, Taipei Medical University Shuang Ho Hospital, New Taipei City, Taiwan
| | - Alexander R Craven
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway; NORMENT - Norwegian Center for Mental Disorders Research, University of Bergen, Bergen, Norway
| | - Koen Cuypers
- Department of Kinesiology, KU Leuven, Leuven, Belgium; REVAL Rehabilitation Research Center, Hasselt University, Diepenbeek, Belgium
| | - Michael Dacko
- Department of Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Niall W Duncan
- Brain and Consciousness Research Centre, Taipei Medical University, Taipei, Taiwan
| | - Ulrike Dydak
- School of Health Sciences, Purdue University, West Lafayette, IN, USA
| | - David A Edmondson
- School of Health Sciences, Purdue University, West Lafayette, IN, USA
| | - Gabriele Ende
- Department of Neuroimaging, Central Institute of Mental Health, Mannheim, Germany
| | - Lars Ersland
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway; NORMENT - Norwegian Center for Mental Disorders Research, University of Bergen, Bergen, Norway; Department of Clinical Engineering, Haukeland University Hospital, Bergen, Norway
| | - Fei Gao
- Shandong Medical Imaging Research Institute, Shandong University, Jinan, China
| | - Ian Greenhouse
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Ashley D Harris
- Department of Radiology, University of Calgary, Calgary, AB, Canada
| | - Naying He
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Stefanie Heba
- Department of Neurology, BG University Hospital Bergmannsheil, Bochum, Germany
| | - Nigel Hoggard
- Academic Unit of Radiology, University of Sheffield, Sheffield, UK
| | - Tun-Wei Hsu
- Department of Radiology, Taipei Veterans General Hospital, National Yang-Ming University School of Medicine, Taipei, Taiwan
| | - Jacobus F A Jansen
- Department of Radiology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Alayar Kangarlu
- Department of Psychiatry, Columbia University, New York, NY, USA; New York State Psychiatric Institute, New York, NY, USA
| | - Thomas Lange
- Department of Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | | | - Yan Li
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | | | - Jy-Kang Liou
- Department of Radiology, Taipei Veterans General Hospital, National Yang-Ming University School of Medicine, Taipei, Taiwan
| | - Jiing-Feng Lirng
- Department of Radiology, Taipei Veterans General Hospital, National Yang-Ming University School of Medicine, Taipei, Taiwan
| | - Feng Liu
- New York State Psychiatric Institute, New York, NY, USA
| | - Ruoyun Ma
- School of Health Sciences, Purdue University, West Lafayette, IN, USA
| | - Celine Maes
- Department of Kinesiology, KU Leuven, Leuven, Belgium
| | | | - Scott O Murray
- Department of Psychology, University of Washington, Seattle, WA, USA
| | - Sean Noah
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | | | - Michael D Noseworthy
- Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - James J Prisciandaro
- Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Nicolaas A J Puts
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Timothy P L Roberts
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Markus Sack
- Department of Neuroimaging, Central Institute of Mental Health, Mannheim, Germany
| | - Napapon Sailasuta
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Muhammad G Saleh
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | | | - Nicholas Simard
- School of Biomedical Engineering, McMaster University, Hamilton, ON, Canada
| | - Stephan P Swinnen
- Department of Kinesiology, KU Leuven, Leuven, Belgium; Leuven Research Institute for Neuroscience & Disease (LIND), KU Leuven, Leuven, Belgium
| | - Martin Tegenthoff
- Department of Neurology, BG University Hospital Bergmannsheil, Bochum, Germany
| | - Peter Truong
- Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Guangbin Wang
- Shandong Medical Imaging Research Institute, Shandong University, Jinan, China
| | - Iain D Wilkinson
- Academic Unit of Radiology, University of Sheffield, Sheffield, UK
| | - Hans-Jörg Wittsack
- Department of Diagnostic and Interventional Radiology, Medical Faculty, Heinrich-Heine-University, Duesseldorf, Germany
| | - Hongmin Xu
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Fuhua Yan
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chencheng Zhang
- Department of Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Vadim Zipunnikov
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Helge J Zöllner
- Department of Diagnostic and Interventional Radiology, Medical Faculty, Heinrich-Heine-University, Duesseldorf, Germany; Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine-University, Duesseldorf, Germany
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.
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Oeltzschner G, Snoussi K, Puts NA, Mikkelsen M, Harris AD, Pradhan S, Tsapkini K, Schär M, Barker PB, Edden RAE. Effects of eddy currents on selective spectral editing experiments at 3T. J Magn Reson Imaging 2017; 47:673-681. [PMID: 28734060 DOI: 10.1002/jmri.25813] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2017] [Accepted: 06/24/2017] [Indexed: 11/09/2022] Open
Abstract
PURPOSE To investigate frequency-offset effects in edited magnetic resonance spectroscopy (MRS) experiments arising from B0 eddy currents. MATERIALS AND METHODS Macromolecule-suppressed (MM-suppressed) γ-aminobutyric acid (GABA)-edited experiments were performed at 3T. Saturation-offset series of MEGA-PRESS experiments were performed in phantoms, in order to investigate different aspects of the relationship between the effective editing frequencies and eddy currents associated with gradient pulses in the sequence. Difference integrals were quantified for each series, and the offset dependence of the integrals was analyzed to quantify the difference in frequency (Δf) between the actual vs. nominal expected saturation frequency. RESULTS Saturation-offset N-acetyl-aspartate-phantom experiments show that Δf varied with voxel orientation, ranging from 10.4 Hz (unrotated) to 6.4 Hz (45° rotation about the caudal-cranial axis) and 0.4 Hz (45° rotation about left-right axis), indicating that gradient-related B0 eddy currents vary with crusher-gradient orientation. Fixing the crusher-gradient coordinate-frame substantially reduced the orientation dependence of Δf (to ∼2 Hz). Water-suppression crusher gradients also introduced a frequency offset, with Δf = 0.6 Hz ("excitation" water suppression), compared to 10.2 Hz (no water suppression). In vivo spectra showed a negative edited "GABA" signal, suggesting Δf on the order of 10 Hz; with fixed crusher-gradient coordinate-frame, the expected positive edited "GABA" signal was observed. CONCLUSION Eddy currents associated with pulsed field gradients may have a considerable impact on highly frequency-selective spectral-editing experiments, such as MM-suppressed GABA editing at 3T. Careful selection of crusher gradient orientation may ameliorate these effects. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:673-681.
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Affiliation(s)
- Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F. M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Karim Snoussi
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F. M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Nicolaas A Puts
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F. M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Mark Mikkelsen
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F. M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Ashley D Harris
- CAIR Program, Alberta Children's Hospital Research Institute, University of Calgary, AB, Canada.,Department of Radiology, University of Calgary, AB, Canada.,Hotchkiss Brain Institute and Alberta Children's Hospital Research Institute, Calgary, AB, Canada
| | - Subechhya Pradhan
- Diagnostic Imaging and Radiology, Children's National Health System, Washington, DC, USA.,Department of Radiology, George Washington University, Washington, DC, USA
| | - Kyrana Tsapkini
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Michael Schär
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Peter B Barker
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F. M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F. M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
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48
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Bogner W, Hangel G, Esmaeili M, Andronesi OC. 1D-spectral editing and 2D multispectral in vivo 1H-MRS and 1H-MRSI - Methods and applications. Anal Biochem 2017; 529:48-64. [PMID: 28034791 DOI: 10.1016/j.ab.2016.12.020] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2016] [Revised: 12/16/2016] [Accepted: 12/23/2016] [Indexed: 12/27/2022]
Abstract
This article reviews the methodological aspects of detecting low-abundant J-coupled metabolites via 1D spectral editing techniques and 2D nuclear magnetic resonance (NMR) methods applied in vivo, in humans, with a focus on the brain. A brief explanation of the basics of J-evolution will be followed by an introduction to 1D spectral editing techniques (e.g., J-difference editing, multiple quantum coherence filtering) and 2D-NMR methods (e.g., correlation spectroscopy, J-resolved spectroscopy). Established and recently developed methods will be discussed and the most commonly edited J-coupled metabolites (e.g., neurotransmitters, antioxidants, onco-markers, and markers for metabolic processes) will be briefly summarized along with their most important applications in neuroscience and clinical diagnosis.
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Affiliation(s)
- Wolfgang Bogner
- 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.
| | - Morteza Esmaeili
- Department of Circulation and Medical Imaging, NTNU, Norwegian University of Science and Technology, Trondheim, Norway; Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
| | - Ovidiu C Andronesi
- Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
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49
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Chan KL, Oeltzschner G, Schär M, Barker PB, Edden RAE. Spatial Hadamard encoding of J-edited spectroscopy using slice-selective editing pulses. NMR IN BIOMEDICINE 2017; 30:10.1002/nbm.3688. [PMID: 28128481 PMCID: PMC5388576 DOI: 10.1002/nbm.3688] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2016] [Revised: 11/17/2016] [Accepted: 12/05/2016] [Indexed: 06/06/2023]
Abstract
A new approach for simultaneous dual-voxel J-difference spectral editing is described, which uses spatially selective spectral-editing pulses and Hadamard encoding. A theoretical framework for spatial Hadamard editing and reconstruction for parallel acquisition (SHERPA) was developed, applying gradient pulses during the frequency-selective editing pulses. Spectral simulations were performed for either one (gamma-aminobutyric acid, GABA) or two molecules (glutathione and lactate) simultaneously detected in two voxels. The method was tested in a two-compartment GABA phantom, and finally applied to the left and right hemispheres of 10 normal control subjects, scanned at 3 T. SHERPA was successfully implemented at 3 T and gave results in close agreement with conventional MEGA-PRESS scans in both the phantom and in vivo experiments. Simulations for GABA editing for (3 cm)3 voxels in the left and right hemispheres suggest that both editing efficiency losses and contamination between voxels are about 2%. Compared with conventional single-voxel single-metabolite J-difference editing, two- or fourfold acceleration is possible without significant loss of SNR using the SHERPA method. Unlike some other dual-voxel methods, the method can be used with single-channel receiver coils, and there is no SNR loss due to unfavorable receive-coil geometry factors.
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Affiliation(s)
- Kimberly L. Chan
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD
- F. M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD
- F. M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD
| | - Michael Schär
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD
| | - Peter B. Barker
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD
- F. M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD
| | - Richard A. E. Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD
- F. M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD
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Chan KL, Saleh MG, Oeltzschner G, Barker PB, Edden RAE. Simultaneous measurement of Aspartate, NAA, and NAAG using HERMES spectral editing at 3 Tesla. Neuroimage 2017; 155:587-593. [PMID: 28438664 DOI: 10.1016/j.neuroimage.2017.04.043] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2017] [Revised: 04/07/2017] [Accepted: 04/19/2017] [Indexed: 10/19/2022] Open
Abstract
It has previously been shown that the HERMES method ('Hadamard Encoding and Reconstruction of MEGA-Edited Spectroscopy') can be used to simultaneously edit pairs of metabolites (such as N-acetyl-aspartate (NAA) and N-acetyl aspartyl glutamate (NAAG), or glutathione and GABA). In this study, HERMES is extended for the simultaneous editing of three overlapping signals, and illustrated for the example of NAA, NAAG and Aspartate (Asp). Density-matrix simulations were performed in order to optimize the HERMES sequence. The method was tested in NAA and Asp phantoms, and applied to the centrum semiovale of the nine healthy control subjects that were scanned at 3T. Both simulations and phantom experiments showed similar metabolite multiplet patterns with good segregation of all three metabolites. In vivo measurements show consistent relative signal intensities and multiplet patterns with concentrations in agreement with literature values. Simulations indicate co-editing of glutathione, glutamine, and glutamate, but their signals do not significantly overlap with the detected aspartyl resonances. This study demonstrates that a four-step Hadamard-encoded editing scheme can be used to simultaneously edit three otherwise overlapping metabolites, and can measure NAA, NAAG, and Asp in vivo in the brain at 3T with minimal crosstalk.
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Affiliation(s)
- Kimberly L Chan
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Muhammad G Saleh
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Peter B Barker
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States.
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