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Bugler H, Berto R, Souza R, Harris AD. Frequency and phase correction of GABA-edited magnetic resonance spectroscopy using complex-valued convolutional neural networks. Magn Reson Imaging 2024; 111:186-195. [PMID: 38744351 DOI: 10.1016/j.mri.2024.05.008] [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: 10/18/2023] [Revised: 05/09/2024] [Accepted: 05/10/2024] [Indexed: 05/16/2024]
Abstract
PURPOSE To determine the significance of complex-valued inputs and complex-valued convolutions compared to real-valued inputs and real-valued convolutions in convolutional neural networks (CNNs) for frequency and phase correction (FPC) of GABA-edited magnetic resonance spectroscopy (MRS) data. METHODS An ablation study using simulated data was performed to determine the most effective input (real or complex) and convolution type (real or complex) to predict frequency and phase shifts in GABA-edited MEGA-PRESS data using CNNs. The best CNN model was subsequently compared using both simulated and in vivo data to two recently proposed deep learning (DL) methods for FPC of GABA-edited MRS. All methods were trained using the same experimental setup and evaluated using the signal-to-noise ratio (SNR) and linewidth of the GABA peak, choline artifact, and by visually assessing the reconstructed final difference spectrum. Statistical significance was assessed using the Wilcoxon signed rank test. RESULTS The ablation study showed that using complex values for the input represented by real and imaginary channels in our model input tensor, with complex convolutions was most effective for FPC. Overall, in the comparative study using simulated data, our CC-CNN model (that received complex-valued inputs with complex convolutions) outperformed the other models as evaluated by the mean absolute error. CONCLUSION Our results indicate that the optimal CNN configuration for GABA-edited MRS FPC uses a complex-valued input and complex convolutions. Overall, this model outperformed existing DL models.
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Affiliation(s)
- Hanna Bugler
- Department of Biomedical Engineering, University of Calgary, Canada; Department of Radiology, University of Calgary, Canada; Hotchkiss Brain Institute, University of Calgary,Canada; Alberta Children's Hospital Research Institute, University of Calgary, Canada.
| | - Rodrigo Berto
- Department of Biomedical Engineering, University of Calgary, Canada; Department of Radiology, University of Calgary, Canada; Hotchkiss Brain Institute, University of Calgary,Canada; Alberta Children's Hospital Research Institute, University of Calgary, Canada
| | - Roberto Souza
- Hotchkiss Brain Institute, University of Calgary,Canada; Department of Electrical and Software Engineering, University of Calgary, Canada
| | - Ashley D Harris
- Department of Radiology, University of Calgary, Canada; Hotchkiss Brain Institute, University of Calgary,Canada; Alberta Children's Hospital Research Institute, University of Calgary, Canada
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Wang Q, Yang C, Chen S, Li J. Miniaturized Electrochemical Sensing Platforms for Quantitative Monitoring of Glutamate Dynamics in the Central Nervous System. Angew Chem Int Ed Engl 2024; 63:e202406867. [PMID: 38829963 DOI: 10.1002/anie.202406867] [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: 04/10/2024] [Revised: 05/30/2024] [Accepted: 06/03/2024] [Indexed: 06/05/2024]
Abstract
Glutamate is one of the most important excitatory neurotransmitters within the mammalian central nervous system. The role of glutamate in regulating neural network signaling transmission through both synaptic and extra-synaptic paths highlights the importance of the real-time and continuous monitoring of its concentration and dynamics in living organisms. Progresses in multidisciplinary research have promoted the development of electrochemical glutamate sensors through the co-design of materials, interfaces, electronic devices, and integrated systems. This review summarizes recent works reporting various electrochemical sensor designs and their applicability as miniaturized neural probes to in vivo sensing within biological environments. We start with an overview of the role and physiological significance of glutamate, the metabolic routes, and its presence in various bodily fluids. Next, we discuss the design principles, commonly employed validation models/protocols, and successful demonstrations of multifunctional, compact, and bio-integrated devices in animal models. The final section provides an outlook on the development of the next generation glutamate sensors for neuroscience and neuroengineering, with the aim of offering practical guidance for future research.
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Affiliation(s)
- Qi Wang
- Department of Materials Science and Engineering, The Ohio State University, Columbus, OH 43210, USA
| | - Chunyu Yang
- Department of Materials Science and Engineering, The Ohio State University, Columbus, OH 43210, USA
| | - Shulin Chen
- Department of Materials Science and Engineering, The Ohio State University, Columbus, OH 43210, USA
| | - Jinghua Li
- Department of Materials Science and Engineering, The Ohio State University, Columbus, OH 43210, USA
- Chronic Brain Injury Program, The Ohio State University, Columbus, OH 43210, USA
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Thomson AR, Hwa H, Pasanta D, Hopwood B, Powell HJ, Lawrence R, Tabuenca ZG, Arichi T, Edden RAE, Chai X, Puts NA. The developmental trajectory of 1H-MRS brain metabolites from childhood to adulthood. Cereb Cortex 2024; 34:bhae046. [PMID: 38430105 PMCID: PMC10908220 DOI: 10.1093/cercor/bhae046] [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: 10/05/2023] [Revised: 01/15/2024] [Accepted: 01/16/2024] [Indexed: 03/03/2024] Open
Abstract
Human brain development is ongoing throughout childhood, with for example, myelination of nerve fibers and refinement of synaptic connections continuing until early adulthood. 1H-Magnetic Resonance Spectroscopy (1H-MRS) can be used to quantify the concentrations of endogenous metabolites (e.g. glutamate and γ -aminobutyric acid (GABA)) in the human brain in vivo and so can provide valuable, tractable insight into the biochemical processes that support postnatal neurodevelopment. This can feasibly provide new insight into and aid the management of neurodevelopmental disorders by providing chemical markers of atypical development. This study aims to characterize the normative developmental trajectory of various brain metabolites, as measured by 1H-MRS from a midline posterior parietal voxel. We find significant non-linear trajectories for GABA+ (GABA plus macromolecules), Glx (glutamate + glutamine), total choline (tCho) and total creatine (tCr) concentrations. Glx and GABA+ concentrations steeply decrease across childhood, with more stable trajectories across early adulthood. tCr and tCho concentrations increase from childhood to early adulthood. Total N-acetyl aspartate (tNAA) and Myo-Inositol (mI) concentrations are relatively stable across development. Trajectories likely reflect fundamental neurodevelopmental processes (including local circuit refinement) which occur from childhood to early adulthood and can be associated with cognitive development; we find GABA+ concentrations significantly positively correlate with recognition memory scores.
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Affiliation(s)
- Alice R Thomson
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, 16 De Crespigny Park, London, SE5 8AF, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, Department of Neurodevelopmental Disorders, New Hunt's House, Guy's Campus, King's College London, London, SE1 1UL, United Kingdom
| | - Hannah Hwa
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, 16 De Crespigny Park, London, SE5 8AF, United Kingdom
| | - Duanghathai Pasanta
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, 16 De Crespigny Park, London, SE5 8AF, United Kingdom
| | - Benjamin Hopwood
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, 16 De Crespigny Park, London, SE5 8AF, United Kingdom
| | - Helen J Powell
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, 16 De Crespigny Park, London, SE5 8AF, United Kingdom
| | - Ross Lawrence
- Division of Cognitive Neurology, Department of Neurology, Johns Hopkins University, 1629 Thames Street Suite 350, Baltimore, MD 21231, United States
| | - Zeus G Tabuenca
- Department of Statistical Methods, University of Zaragoza, Pedro Cerbuna 12, Zaragoza, 50009, Spain
| | - Tomoki Arichi
- MRC Centre for Neurodevelopmental Disorders, Department of Neurodevelopmental Disorders, New Hunt's House, Guy's Campus, King's College London, London, SE1 1UL, United Kingdom
- Centre for the Developing Brain, Department of Perinatal Imaging & Health, 1st Floor, South Wing, St Thomas’ Hospital, London, SE1 7EH, United Kingdom
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, 601 North Caroline Street, Baltimore, MD 21287, United States
- F.M. Kirby Research Centre for Functional Brain Imaging, Kennedy Krieger Institute, 707 North Broadway, Baltimore, MD 21205, United States
| | - Xiaoqian Chai
- Department of Neurology and Neurosurgery, McGill University, QC H3A2B4, Canada
| | - Nicolaas A Puts
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, 16 De Crespigny Park, London, SE5 8AF, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, Department of Neurodevelopmental Disorders, New Hunt's House, Guy's Campus, King's College London, London, SE1 1UL, United Kingdom
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Sirucek L, Zoelch N, Schweinhardt P. Improving magnetic resonance spectroscopy in the brainstem periaqueductal gray using spectral registration. Magn Reson Med 2024; 91:28-38. [PMID: 37800387 DOI: 10.1002/mrm.29832] [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: 03/31/2023] [Revised: 07/08/2023] [Accepted: 07/31/2023] [Indexed: 10/07/2023]
Abstract
PURPOSE Functional understanding of the periaqueductal gray (PAG), a clinically relevant brainstem region, can be advanced using 1 H-MRS. However, the PAG's small size and high levels of physiological noise are methodologically challenging. This study aimed to (1) improve 1 H-MRS quality in the PAG using spectral registration for frequency and phase error correction; (2) investigate whether spectral registration is particularly useful in cases of greater head motion; and (3) examine metabolite quantification using literature-based or individual-based water relaxation times. METHODS Spectra were acquired in 33 healthy volunteers (50.1 years, SD = 17.19, 18 females) on a 3 T Philipps MR system using a point-resolved spectroscopy (PRESS) sequence optimized with very selective saturation pulses (OVERPRESS) and voxel-based flip angle calibration (effective volume of interest size: 8.8 × 10.2 × 12.2 mm3 ). Spectra were fitted using LCModel and SNR, NAA peak linewidths and Cramér-Rao lower bounds (CRLBs) were measured after spectral registration and after minimal frequency alignment. RESULTS Spectral registration improved SNR by 5% (p = 0.026, median value post-correction: 18.0) and spectral linewidth by 23% (p < 0.001, 4.3 Hz), and reduced the metabolites' CRLBs by 1% to 15% (p < 0.026). Correlational analyses revealed smaller SNR improvements with greater head motion (p = 0.010) recorded using a markerless motion tracking system. Higher metabolite concentrations were detected using individual-based compared to literature-based water relaxation times (p < 0.001). CONCLUSION This study demonstrates high-quality 1 H-MRS acquisition in the PAG using spectral registration. This shows promise for future 1 H-MRS studies in the PAG and possibly other clinically relevant brain regions with similar methodological challenges.
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Affiliation(s)
- Laura Sirucek
- Department of Chiropractic Medicine, Integrative Spinal Research Group, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich, Zurich, Switzerland
| | - Niklaus Zoelch
- Department of Forensic Medicine and Imaging, Institute of Forensic Medicine, University of Zurich, Zurich, Switzerland
- Department of Psychiatry, Psychotherapy, and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Petra Schweinhardt
- Department of Chiropractic Medicine, Integrative Spinal Research Group, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich, Zurich, Switzerland
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Davies-Jenkins CW, Döring A, Fasano F, Kleban E, Mueller L, Evans CJ, Afzali M, Jones DK, Ronen I, Branzoli F, Tax CMW. Practical considerations of diffusion-weighted MRS with ultra-strong diffusion gradients. Front Neurosci 2023; 17:1258408. [PMID: 38144210 PMCID: PMC10740196 DOI: 10.3389/fnins.2023.1258408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 11/03/2023] [Indexed: 12/26/2023] Open
Abstract
Introduction Diffusion-weighted magnetic resonance spectroscopy (DW-MRS) offers improved cellular specificity to microstructure-compared to water-based methods alone-but spatial resolution and SNR is severely reduced and slow-diffusing metabolites necessitate higher b-values to accurately characterize their diffusion properties. Ultra-strong gradients allow access to higher b-values per-unit time, higher SNR for a given b-value, and shorter diffusion times, but introduce additional challenges such as eddy-current artefacts, gradient non-uniformity, and mechanical vibrations. Methods In this work, we present initial DW-MRS data acquired on a 3T Siemens Connectom scanner equipped with ultra-strong (300 mT/m) gradients. We explore the practical issues associated with this manner of acquisition, the steps that may be taken to mitigate their impact on the data, and the potential benefits of ultra-strong gradients for DW-MRS. An in-house DW-PRESS sequence and data processing pipeline were developed to mitigate the impact of these confounds. The interaction of TE, b-value, and maximum gradient amplitude was investigated using simulations and pilot data, whereby maximum gradient amplitude was restricted. Furthermore, two DW-MRS voxels in grey and white matter were acquired using ultra-strong gradients and high b-values. Results Simulations suggest T2-based SNR gains that are experimentally confirmed. Ultra-strong gradient acquisitions exhibit similar artefact profiles to those of lower gradient amplitude, suggesting adequate performance of artefact mitigation strategies. Gradient field non-uniformity influenced ADC estimates by up to 4% when left uncorrected. ADC and Kurtosis estimates for tNAA, tCho, and tCr align with previously published literature. Discussion In conclusion, we successfully implemented acquisition and data processing strategies for ultra-strong gradient DW-MRS and results indicate that confounding effects of the strong gradient system can be ameliorated, while achieving shorter diffusion times and improved metabolite SNR.
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Affiliation(s)
- Christopher W. Davies-Jenkins
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, United Kingdom
| | - André Döring
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, United Kingdom
- CIBM Center for Biomedical Imaging, EPFL CIBM-AIT, EPFL Lausanne, Lausanne, Switzerland
| | - Fabrizio Fasano
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, United Kingdom
- Siemens Healthcare Ltd., Camberly, United Kingdom
| | - Elena Kleban
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, United Kingdom
- Department of Radiology, Universität Bern, Bern, Switzerland
| | - Lars Mueller
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, United Kingdom
- Leeds Institute of Cardiovascular & Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - C. John Evans
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, United Kingdom
| | - Maryam Afzali
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, United Kingdom
- Leeds Institute of Cardiovascular & Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Derek K. Jones
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, United Kingdom
| | - Itamar Ronen
- Clinical Sciences Institue, Brighton and Sussex Medical School, Brighton, United Kingdom
| | - Francesca Branzoli
- Center for NeuroImaging Research (CENIR), Paris Brain Institute (ICM), Pitié-Salpêtrière Hospital, Paris, France
- Inserm U1127, CNRS U7225, Sorbonne Universités, Paris, France
| | - Chantal M. W. Tax
- Brain Research Imaging Centre, School Physics and Astronomy, Cardiff University, Cardiff, United Kingdom
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands
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6
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Gursan A, Hendriks AD, Welting D, de Jong PA, Klomp DWJ, Prompers JJ. Deuterium body array for the simultaneous measurement of hepatic and renal glucose metabolism and gastric emptying with dynamic 3D deuterium metabolic imaging at 7 T. NMR IN BIOMEDICINE 2023:e4926. [PMID: 36929629 DOI: 10.1002/nbm.4926] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 02/23/2023] [Accepted: 02/24/2023] [Indexed: 06/18/2023]
Abstract
Deuterium metabolic imaging (DMI) is a novel noninvasive method to assess tissue metabolism and organ (patho)physiology in vivo using deuterated substrates, such as [6,6'-2 H2 ]-glucose. The liver and kidneys play a central role in whole-body glucose homeostasis, and in type 2 diabetes, both hepatic and renal glucose metabolism are dysregulated. Diabetes is also associated with gastric emptying abnormalities. In this study, we developed a four-channel 2 H transmit/receive body array coil for DMI in the human abdomen at 7 T and assessed its performance. In addition, the feasibility of simultaneously measuring gastric emptying, and hepatic and renal glucose uptake and metabolism with dynamic 3D DMI upon administration of deuterated glucose, was investigated. Simulated and measured B1 + patterns were in good agreement. The intrasession variability of the natural abundance deuterated water signal in the liver and right kidney, measured in nine healthy volunteers, was 5.6% ± 0.9% and 4.9% ± 0.7%, respectively. Dynamic 3D DMI scans with oral administration of [6,6'-2 H2 ]-glucose showed similar kinetics of deuterated glucose appearance and disappearance in the liver and kidney. The measured gastric emptying half time was 80 ± 10 min, which is in good agreement with scintigraphy measurements. In conclusion, DMI with oral administration of [6,6'-2 H2 ]-glucose enables simultaneous assessment of gastric emptying and liver and kidney glucose uptake and metabolism. When applied in patients with diabetes, this approach may advance our understanding of the interplay between disturbances in liver and kidney glucose uptake and metabolism and gastric emptying, at a detail that cannot be achieved by any other method.
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Affiliation(s)
- Ayhan Gursan
- Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Arjan D Hendriks
- Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Dimitri Welting
- Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Pim A de Jong
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Dennis W J Klomp
- Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jeanine J Prompers
- Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
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Yurista SR, Eder RA, Kwon DH, Farrar CT, Yen YF, Tang WHW, Nguyen CT. Magnetic resonance imaging of cardiac metabolism in heart failure: how far have we come? Eur Heart J Cardiovasc Imaging 2022; 23:1277-1289. [PMID: 35788836 PMCID: PMC10202438 DOI: 10.1093/ehjci/jeac121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 06/06/2022] [Accepted: 06/10/2022] [Indexed: 11/12/2022] Open
Abstract
As one of the highest energy consumer organs in the body, the heart requires tremendous amount of adenosine triphosphate (ATP) to maintain its continuous mechanical work. Fatty acids, glucose, and ketone bodies are the primary fuel source of the heart to generate ATP with perturbations in ATP generation possibly leading to contractile dysfunction. Cardiac metabolic imaging with magnetic resonance imaging (MRI) plays a crucial role in understanding the dynamic metabolic changes occurring in the failing heart, where the cardiac metabolism is deranged. Also, targeting and quantifying metabolic changes in vivo noninvasively is a promising approach to facilitate diagnosis, determine prognosis, and evaluate therapeutic response. Here, we summarize novel MRI techniques used for detailed investigation of cardiac metabolism in heart failure including magnetic resonance spectroscopy (MRS), hyperpolarized MRS, and chemical exchange saturation transfer based on evidence from preclinical and clinical studies and to discuss the potential clinical application in heart failure.
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Affiliation(s)
- Salva R Yurista
- Cardiovascular Research Center, Corrigan Minehan Heart Center, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Charlestown, MA 02129, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Charlestown, MA 02129, USA
| | - Robert A Eder
- Cardiovascular Research Center, Corrigan Minehan Heart Center, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Charlestown, MA 02129, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Charlestown, MA 02129, USA
| | - Deborah H Kwon
- Department of Cardiovascular Medicine, Heart, Vascular, and Thoracic Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195, USA
| | - Christian T Farrar
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Charlestown, MA 02129, USA
| | - Yi Fen Yen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Charlestown, MA 02129, USA
| | - W H Wilson Tang
- Department of Cardiovascular Medicine, Heart, Vascular, and Thoracic Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195, USA
| | - Christopher T Nguyen
- Cardiovascular Research Center, Corrigan Minehan Heart Center, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Charlestown, MA 02129, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Charlestown, MA 02129, USA
- Division of Health Science Technology, Harvard-Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA 02139, USA
- Cardiovascular Innovation Research Center, Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, 9500 Euclid Avenue, Cleveland, OH 44195, USA
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Does the change in glutamate to GABA ratio correlate with change in depression severity? A randomized, double-blind clinical trial. Mol Psychiatry 2022; 27:3833-3841. [PMID: 35982258 PMCID: PMC9712215 DOI: 10.1038/s41380-022-01730-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 07/09/2022] [Accepted: 07/29/2022] [Indexed: 02/08/2023]
Abstract
Previous proton magnetic resonance spectroscopy (1H-MRS) studies suggest a perturbation in glutamate and/or GABA in Major Depressive Disorder (MDD). However, no studies examine the ratio of glutamate and glutamine (Glx) to GABA (Glx/GABA) as it relates to depressive symptoms, which may be more sensitive than either single metabolite. Using a within-subject design, we hypothesized that reduction in depressive symptoms correlates with reduction in Glx/GABA in the anterior cingulate cortex (ACC). The present trial is a randomized clinical trial that utilized 1H-MRS to examine Glx/GABA before and after 8 weeks of escitalopram or placebo. Participants completed the 17-item Hamilton Depression Rating Scale (HDRS17) and underwent magnetic resonance spectroscopy before and after treatment. Two GABA-edited MEGA-PRESS acquisitions were interleaved with a water unsuppressed reference scan. GABA and Glx were quantified from the average difference spectrum, with preprocessing using Gannet and spectral fitting using TARQUIN. Linear mixed models were utilized to evaluate relationships between change in HDRS17 and change in Glx/GABA using a univariate linear regression model, multiple linear regression incorporating treatment type as a covariate, and Bayes Factor (BF) hypothesis testing to examine strength of evidence. No significant relationship was detected between percent change in Glx, GABA, or Glx/GABA and percent change in HDRS17, regardless of treatment type. Further, MDD severity before/after treatment did not correlate with ACC Glx/GABA. In light of variable findings in the literature and lack of association in our investigation, future directions should include evaluating glutamate and glutamine individually to shed light on the underpinnings of MDD severity. Advancing Personalized Antidepressant Treatment Using PET/MRI, ClinicalTrials.gov, NCT02623205.
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Hui SC, Zöllner HJ, Oeltzschner G, Edden RAE, Saleh MG. In vivo spectral editing of phosphorylethanolamine. Magn Reson Med 2022; 87:50-56. [PMID: 34411324 PMCID: PMC8616810 DOI: 10.1002/mrm.28976] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 07/07/2021] [Accepted: 07/29/2021] [Indexed: 01/03/2023]
Abstract
PURPOSE To demonstrate J-difference editing of phosphorylethanolamine (PE) with chemical shifts at 3.22 (PE3.22 ) and 3.98 (PE3.98 ) ppm, and compare the merits of two editing strategies. METHODS Density-matrix simulations of MEGA-PRESS (Mescher-Garwood PRESS) for PE were performed at TEs ranging from 80 to 200 ms in steps of 2 ms, applying 20-ms editing pulses (ON/OFF) at (1) 3.98/7.5 ppm to detect PE3.22 and (2) 3.22/7.5 ppm to detect PE3.98 . Phantom experiments were performed using a PE phantom to validate simulation results. Ten subjects were scanned using a Philips 3T MRI scanner at TEs of 90 ms and 110 ms to edit PE3.22 and PE3.98 . Osprey was used for data processing, modeling, and quantification. RESULTS Simulations show substantial TE modulation of the intensity and shape of the edited signals due to coupling evolution. Simulated and phantom integrals suggest that TEs of 110 ms and 90 ms were optimal for the edited detection of PE3.22 and PE3.98 , respectively. Phantom results indicated strong agreement with the simulated spectra and integrals. In vivo quantification of the PE3.22 /total creatine and PE3.98 /total creatine concentration ratio yielded values of 0.26 ± 0.04 (between-subject coefficient of variation [CV]: 15.4%) and 0.18 ± 0.04 (CV: 22.8%), respectively, at TE = 90 ms, and 0.24 ± 0.02 (CV: 8.2%) and 0.23 ± 0.04 (CV: 18.0%), respectively, at TE = 110 ms. CONCLUSION Simulations and in vivo MEGA-PRESS of PE demonstrate that both PE3.22 and PE3.98 are potential candidates for editing, but PE3.22 at TE = 110 ms yields lower variation across TEs.
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Affiliation(s)
- Steve C.N. Hui
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, USA
| | - Helge J. Zöllner
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, USA
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, USA
| | - Richard A. E. Edden
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, USA
| | - Muhammad G. Saleh
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, USA
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10
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Smucny J, Carter CS, Maddock RJ. Medial Prefrontal Cortex Glutamate Is Reduced in Schizophrenia and Moderated by Measurement Quality: A Meta-analysis of Proton Magnetic Resonance Spectroscopy Studies. Biol Psychiatry 2021; 90:643-651. [PMID: 34344534 PMCID: PMC9303057 DOI: 10.1016/j.biopsych.2021.06.008] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 06/01/2021] [Accepted: 06/06/2021] [Indexed: 02/08/2023]
Abstract
BACKGROUND Magnetic resonance spectroscopy studies measuring brain glutamate separately from glutamine are helping elucidate schizophrenia pathophysiology. An expanded literature and improved methodologies motivate an updated meta-analysis examining effects of measurement quality and other moderating factors in characterizing abnormal glutamate levels in schizophrenia. METHODS Searching previous meta-analyses and the MEDLINE database identified 83 proton magnetic resonance spectroscopy datasets published through March 25, 2020. Three quality metrics were extracted-Cramér-Rao lower bound (CRLB), line width, and coefficient of variation. Pooled effect sizes (Hedges' g) were calculated with random-effects, inverse variance-weighted models. Moderator analyses were conducted using quality metrics, field strength, echo time, medication, age, and stage of illness. RESULTS Across 36 datasets (2086 participants), medial prefrontal cortex glutamate was significantly reduced in patients (g = -0.19, confidence interval [CI] = -0.07 to -0.32). CRLB and coefficient of variation quality subgroups significantly moderated this effect. Glutamate was significantly more reduced in studies with lower CRLB or coefficient of variation (g = -0.44, CI = -0.29 to -0.60, and g = -0.43, CI = -0.29 to -0.57, respectively). Studies using echo time ≤20 ms also showed significantly greater reduction in glutamate (g = -0.41, CI = -0.26 to -0.55). Across 11 hippocampal datasets, group differences and moderator effects were nonsignificant. Group effects in thalamus and dorsolateral prefrontal cortex were also nonsignificant. CONCLUSIONS High-quality measurements reveal consistently reduced medial prefrontal cortex glutamate in schizophrenia. Stricter CRLB criteria and reduced nuisance variance may increase the sensitivity of future studies examining additional regions and the pathophysiological significance of abnormal glutamate levels in schizophrenia.
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Affiliation(s)
- Jason Smucny
- Department of Psychiatry and Behavioral Sciences, University of California Davis, Davis, California
| | - Cameron S Carter
- Department of Psychiatry and Behavioral Sciences, University of California Davis, Davis, California
| | - Richard J Maddock
- Department of Psychiatry and Behavioral Sciences, University of California Davis, Davis, California.
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11
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Rideaux R, Mikkelsen M, Edden RAE. Comparison of methods for spectral alignment and signal modelling of GABA-edited MR spectroscopy data. Neuroimage 2021; 232:117900. [PMID: 33652146 PMCID: PMC8245134 DOI: 10.1016/j.neuroimage.2021.117900] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 02/10/2021] [Accepted: 02/17/2021] [Indexed: 01/25/2023] Open
Abstract
Many methods exist for aligning and quantifying magnetic resonance spectroscopy (MRS) data to measure in vivo γ-aminobutyric acid (GABA). Research comparing the performance of these methods is scarce partly due to the lack of ground-truth measurements. The concentration of GABA is approximately two times higher in grey matter than in white matter. Here we use the proportion of grey matter within the MRS voxel as a proxy for ground-truth GABA concentration to compare the performance of four spectral alignment methods (i.e., retrospective frequency and phase drift correction) and six GABA signal modelling methods. We analyse a diverse dataset of 432 MEGA-PRESS scans targeting multiple brain regions and find that alignment to the creatine (Cr) signal produces GABA+ estimates that account for approximately twice as much of the variance in grey matter as the next best performing alignment method. Further, Cr alignment was the most robust, producing the fewest outliers. By contrast, all signal modelling methods, except for the single-Lorentzian model, performed similarly well. Our results suggest that variability in performance is primarily caused by differences in the zero-order phase estimated by each alignment method, rather than frequency, resulting from first-order phase offsets within subspectra. These results provide support for Cr alignment as the optimal method of processing MEGA-PRESS to quantify GABA. However, more broadly, they demonstrate a method of benchmarking quantification of in vivo metabolite concentration from other MRS sequences.
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Affiliation(s)
- Reuben Rideaux
- Department of Psychology, Downing Street, University of Cambridge, UK.
| | - 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
| | - 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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12
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Marsman A, Lind A, Petersen ET, Andersen M, Boer VO. Prospective frequency and motion correction for edited 1H magnetic resonance spectroscopy. Neuroimage 2021; 233:117922. [PMID: 33662573 DOI: 10.1016/j.neuroimage.2021.117922] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Revised: 02/18/2021] [Accepted: 02/25/2021] [Indexed: 12/18/2022] Open
Abstract
The major inhibitory neurotransmitter gamma-aminobutyric acid (GABA) and the dominant antioxidant glutathione (GSH) both play a crucial role in brain functioning and are involved in several neurodegenerative and psychiatric diseases. Magnetic resonance spectroscopy (MRS) is a unique way to measure these neurometabolites non-invasively, but the measurement is highly sensitive to head movements, and especially in specific patient groups, motion stabilization in MRS could be valuable. Conventional MRS is acquired at relatively short echo times (TE), however, for unambiguous detection of GABA and GSH, spectral editing techniques are typically used. These depend on longer TEs and use frequency selective spectral editing pulses to separate the low-intensity peaks of GABA and GSH from overlapping resonances, but results in further increased motion sensitivity. Low-intensity metabolite peaks are usually edited one-by-one, however, simultaneous editing of multiple metabolites can be achieved using a Hadamard scheme, resulting in a substantial reduction in scan time. To investigate and correct for motion sensitivity in both conventional short-TE MRS (PRESS) and edited MRS (HERMES), we implemented a navigator-based prospective motion correction strategy including reacquisition of corrupted data. PRESS and HERMES spectra were acquired without motion, with motion with correction (repeated twice), and with motion without correction. Results indicate that when sufficient retrospective outlier removal is used, no significant differences in concentration and spectral quality were observed between motion conditions, even without prospective correction. HERMES spectral editing data showed to be more sensitive to motion, as significant differences in metabolite estimates and variability of spectral quality measures were observed for tCr, GABA+ and GSH when only retrospective outlier removal was applied. When using both prospective and retrospective correction, spectral quality was improved to almost the level of the no-motion acquisition. No differences in metabolite ratios for GABA and GSH could be observed when using motion correction. In conclusion, edited MRS showed to be more prone to motion artifacts, and prospective motion correction can restore most of the spectral quality in both conventional and edited MRS.
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Affiliation(s)
- Anouk Marsman
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark.
| | - Anna Lind
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark
| | - Esben Thade Petersen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark; Center for Magnetic Resonance, Department of Electrical Engineering, Technical University of Denmark, Lyngby, Denmark
| | | | - Vincent Oltman Boer
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark
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13
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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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