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Kumaragamage C, McIntyre S, Nixon TW, De Feyter HM, de Graaf RA. High-quality lipid suppression and B0 shimming for human brain 1H MRSI. Neuroimage 2024; 300:120845. [PMID: 39276817 DOI: 10.1016/j.neuroimage.2024.120845] [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: 03/27/2024] [Revised: 06/06/2024] [Accepted: 09/09/2024] [Indexed: 09/17/2024] Open
Abstract
Magnetic Resonance Spectroscopic Imaging (MRSI) is a powerful technique that can map the metabolic profile in the brain non-invasively. Extracranial lipid contamination and insufficient B0 homogeneity however hampers robustness, and as a result has hindered widespread use of MRSI in clinical and research settings. Over the last six years we have developed highly effective extracranial lipid suppression methods with a second order gradient insert (ECLIPSE) utilizing inner volume selection (IVS) and outer volume suppression (OVS) methods. While ECLIPSE provides > 100-fold in lipid suppression with modest radio frequency (RF) power requirements and immunity to B1+ field variations, axial coverage is reduced for non-elliptical head shapes. In this work we detail the design, construction, and utility of MC-ECLIPSE, a pulsed second order gradient coil with Z2 and X2Y2 fields, combined with a 54-channel multi-coil (MC) array. The MC-ECLIPSE platform allows arbitrary region of interest (ROI) shaped OVS for full-axial slice coverage, in addition to MC-based B0 field shimming, for robust human brain proton MRSI. In vivo experiments demonstrate that MC-ECLIPSE allows axial brain coverage of 92-95 % is achieved following arbitrary ROI shaped OVS for various head shapes. The standard deviation (SD) of the residual B0 field following SH2 and MC shimming were 25 ± 9 Hz and 18 ± 8 Hz over a 5 cm slab, and 18 ± 5 Hz and 14 ± 6 Hz over a 1.5 cm slab, respectively. These results demonstrate that B0 magnetic field shimming with the MC array supersedes second order harmonic capabilities available on standard MRI systems for both restricted and large ROIs. Furthermore, MC based B0 shimming provides comparable shimming performance to an unrestricted SH5 shim set for both restricted, and 5-cm slab shim challenges. Phantom experiments demonstrate the high level of localization performance achievable with MC-ECLIPSE, with ROI edge chemical shift displacements ranging from 1-3 mm with a median value of 2 mm, and transition width metrics ranging from 1-2.5 mm throughout the ROI edge. Furthermore, MC based B0 shimming is comparable to performance following a full set of unrestricted spherical harmonic fields up to order 5. Short echo time MRSI and GABA-edited MRSI acquisitions in the human brain following MC-shimming and arbitrary ROI shaping demonstrate full-axial slice coverage and extracranial lipid artifact free spectra. MC-ECLIPSE allows full-axial coverage and robust MRSI acquisitions, while allowing interrogation of cortical tissue proximal to the skull, which has significant value in a wide range of neurological and psychiatric conditions.
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Affiliation(s)
- Chathura Kumaragamage
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, USA.
| | - Scott McIntyre
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, USA
| | - Terence W Nixon
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, USA
| | - Henk M De Feyter
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, USA
| | - Robin A de Graaf
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, USA; Department of Biomedical Engineering, Yale University School of Medicine, New Haven, CT, USA
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2
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Deelchand DK. Simultaneous frequency and phase corrections of single-shot MRS data using cross-correlation. Magn Reson Med 2024. [PMID: 39155397 DOI: 10.1002/mrm.30252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Revised: 07/05/2024] [Accepted: 07/27/2024] [Indexed: 08/20/2024]
Abstract
PURPOSE The objective of this study was to propose a novel preprocessing approach to simultaneously correct for the frequency and phase drifts in MRS data using cross-correlation technique. METHODS The performance of the proposed method was first investigated at different SNR levels using simulation. Random frequency and phase offsets were added to a previously acquired STEAM human data at 7 T, simulating two different noise levels with and without baseline artifacts. Alongside the proposed spectral cross-correlation (SC) method, three other simultaneous alignment approaches were evaluated. Validation was performed on human brain data at 3 T and mouse brain data at 16.4 T. RESULTS The results showed that the SC technique effectively corrects for both small and large frequency and phase drifts, even at low SNR levels. Furthermore, the mean square measurement error of the SC algorithm was comparable to the other three methods used, with much faster processing time. The efficacy of the proposed technique was successfully demonstrated in both human brain MRS data and in a noisy MRS dataset acquired from a small volume-of-interest in the mouse brain. CONCLUSION The study demonstrated the availability of a fast and robust technique that accurately corrects for both small and large frequency and phase shifts in MRS.
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Affiliation(s)
- Dinesh K Deelchand
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA
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3
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Poli S, Emara AF, Lange NF, Ballabani E, Buser A, Schiavon M, Herzig D, Man CD, Bally L, Kreis R. Interleaved trinuclear MRS for single-session investigation of carbohydrate and lipid metabolism in human liver at 7T. NMR IN BIOMEDICINE 2024; 37:e5123. [PMID: 38423797 DOI: 10.1002/nbm.5123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Revised: 12/21/2023] [Accepted: 01/24/2024] [Indexed: 03/02/2024]
Abstract
The liver plays a central role in metabolic homeostasis, as exemplified by a variety of clinical disorders with hepatic and systemic metabolic disarrays. Of particular interest are the complex interactions between lipid and carbohydrate metabolism in highly prevalent conditions such as obesity, diabetes, and fatty liver disease. Limited accessibility and the need for invasive procedures challenge direct investigations in humans. Hence, noninvasive dynamic evaluations of glycolytic flux and steady-state assessments of lipid levels and composition are crucial for basic understanding and may open new avenues toward novel therapeutic targets. Here, three different MR spectroscopy (MRS) techniques that have been combined in a single interleaved examination in a 7T MR scanner are evaluated. 1H-MRS and 13C-MRS probe endogenous metabolites, while deuterium metabolic imaging (DMI) relies on administration of deuterated tracers, currently 2H-labelled glucose, to map the spatial and temporal evolution of their metabolic fate. All three techniques have been optimized for a robust single-session clinical investigation and applied in a preliminary study of healthy subjects. The use of a triple-channel 1H/2H/13C RF coil enables interleaved examinations with no need for repositioning. Short-echo-time STEAM spectroscopy provides well resolved spectra to quantify lipid content and composition. The relative benefits of using water saturation versus metabolite cycling and types of respiratory synchronization were evaluated. 2H-MR spectroscopic imaging allowed for registration of time- and space-resolved glucose levels following oral ingestion of 2H-glucose, while natural abundance 13C-MRS of glycogen provides a dynamic measure of hepatic glucose storage. For DMI and 13C-MRS, the measurement precision of the method was estimated to be about 0.2 and about 16 mM, respectively, for 5 min scanning periods. Excellent results were shown for the determination of dynamic uptake of glucose with DMI and lipid profiles with 1H-MRS, while the determination of changes in glycogen levels by 13C-MRS is also feasible but somewhat more limited by signal-to-noise ratio.
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Affiliation(s)
- Simone Poli
- MR Methodology, Department for Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland
- Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
- Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland
| | - Ahmed F Emara
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism UDEM, University Hospital Bern, Bern, Switzerland
| | - Naomi F Lange
- Department of Visceral Surgery and Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Graduate School for Health Sciences, University of Bern, Bern, Switzerland
| | - Edona Ballabani
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism UDEM, University Hospital Bern, Bern, Switzerland
| | - Angeline Buser
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism UDEM, University Hospital Bern, Bern, Switzerland
| | - Michele Schiavon
- Department of Information Engineering (DEI), University of Padova, Padua, Italy
| | - David Herzig
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism UDEM, University Hospital Bern, Bern, Switzerland
| | - Chiara Dalla Man
- Department of Information Engineering (DEI), University of Padova, Padua, Italy
| | - Lia Bally
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism UDEM, University Hospital Bern, Bern, Switzerland
| | - Roland Kreis
- MR Methodology, Department for Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland
- Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
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4
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Alves B, Simicic D, Mosso J, Lê TP, Briand G, Bogner W, Lanz B, Strasser B, Klauser A, Cudalbu C. Noise-reduction techniques for 1H-FID-MRSI at 14.1 T: Monte Carlo validation and in vivo application. NMR IN BIOMEDICINE 2024:e5211. [PMID: 39041293 DOI: 10.1002/nbm.5211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 03/28/2024] [Accepted: 06/14/2024] [Indexed: 07/24/2024]
Abstract
Proton magnetic resonance spectroscopic imaging (1H-MRSI) is a powerful tool that enables the multidimensional non-invasive mapping of the neurochemical profile at high resolution over the entire brain. The constant demand for higher spatial resolution in 1H-MRSI has led to increased interest in post-processing-based denoising methods aimed at reducing noise variance. The aim of the present study was to implement two noise-reduction techniques, Marchenko-Pastur principal component analysis (MP-PCA) based denoising and low-rank total generalized variation (LR-TGV) reconstruction, and to test their potential with and impact on preclinical 14.1 T fast in vivo 1H-FID-MRSI datasets. Since there is no known ground truth for in vivo metabolite maps, additional evaluations of the performance of both noise-reduction strategies were conducted using Monte Carlo simulations. Results showed that both denoising techniques increased the apparent signal-to-noise ratio (SNR) while preserving noise properties in each spectrum for both in vivo and Monte Carlo datasets. Relative metabolite concentrations were not significantly altered by either method and brain regional differences were preserved in both synthetic and in vivo datasets. Increased precision of metabolite estimates was observed for the two methods, with inconsistencies noted for lower-concentration metabolites. Our study provided a framework for how to evaluate the performance of MP-PCA and LR-TGV methods for preclinical 1H-FID MRSI data at 14.1 T. While gains in apparent SNR and precision were observed, concentration estimations ought to be treated with care, especially for low-concentration metabolites.
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Affiliation(s)
- Brayan Alves
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Animal Imaging and Technology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Dunja Simicic
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Animal Imaging and Technology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Laboratory of Functional and Metabolic Imaging, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Jessie Mosso
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Animal Imaging and Technology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Laboratory of Functional and Metabolic Imaging, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Thanh Phong Lê
- Laboratory of Functional and Metabolic Imaging, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Guillaume Briand
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Animal Imaging and Technology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Wolfgang Bogner
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University Vienna, Vienna, Austria
| | - Bernard Lanz
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Animal Imaging and Technology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Bernhard Strasser
- High-field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University Vienna, Vienna, Austria
| | - Antoine Klauser
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - Cristina Cudalbu
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Animal Imaging and Technology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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5
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Huang YL, Lin YR, Tsai SY. Comparison of convolutional-neural-networks-based method and LCModel on the quantification of in vivo magnetic resonance spectroscopy. MAGMA (NEW YORK, N.Y.) 2024; 37:477-489. [PMID: 37713007 DOI: 10.1007/s10334-023-01120-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 08/09/2023] [Accepted: 08/30/2023] [Indexed: 09/16/2023]
Abstract
BACKGROUND Quantification of metabolites concentrations in institutional unit (IU) is important for inter-subject and long-term comparisons in the applications of magnetic resonance spectroscopy (MRS). Recently, deep learning (DL) algorithms have found a variety of applications on the process of MRS data. A quantification strategy compatible to DL base MRS spectral processing method is, therefore, useful. MATERIALS AND METHODS This study aims to investigate whether metabolite concentrations quantified using a convolutional neural network (CNN) based method, coupled with a scaling procedure that normalizes spectral signals for CNN input and linear regression, can effectively reflect variations in metabolite concentrations in IU across different brain regions with varying signal-to-noise ratios (SNR) and linewidths (LW). An error index based on standard error (SE) is proposed to indicate the confidence levels associated with metabolite predictions. In vivo MRS spectra were acquired from three brain regions of 43 subjects using a 3T system. RESULTS The metabolite concentrations in IU of five major metabolites, quantified using CNN and LCModel, exhibit similar ranges with Pearson's correlation coefficients ranging from 0.24 to 0.78. The SE of the metabolites shows a positive correlation with Cramer-Rao lower bound (CRLB) (r=0.46) and absolute CRLB (r=0.81), calculated by multiplying CRLBs with the quantified metabolite content. CONCLUSION In conclusion, the CNN based method with the proposed scaling procedures can be employed to quantify in vivo MRS spectra and derive metabolites concentrations in IU. The SE can be used as error index, indicating predicted uncertainties for metabolites and sharing information similar to the absolute CRLB.
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Affiliation(s)
- Yu-Long Huang
- Department of Electronic and Computer Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan
| | - Yi-Ru Lin
- Department of Electronic and Computer Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan
| | - Shang-Yueh Tsai
- Graduate Institute of Applied Physics, National Chengchi University, No.64, Sec.2, ZhiNan Rd., Wenshan District, Taipei, 11605, Taiwan.
- Research Center for Mind, Brain and Learning, National Chengchi University, Taipei, Taiwan.
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Rakić M, Turco F, Weng G, Maes F, Sima DM, Slotboom J. Deep learning pipeline for quality filtering of MRSI spectra. NMR IN BIOMEDICINE 2024; 37:e5012. [PMID: 37518942 DOI: 10.1002/nbm.5012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 06/15/2023] [Accepted: 07/10/2023] [Indexed: 08/01/2023]
Abstract
With the rise of novel 3D magnetic resonance spectroscopy imaging (MRSI) acquisition protocols in clinical practice, which are capable of capturing a large number of spectra from a subject's brain, there is a need for an automated preprocessing pipeline that filters out bad-quality spectra and identifies contaminated but salvageable spectra prior to the metabolite quantification step. This work introduces such a pipeline based on an ensemble of deep-learning classifiers. The dataset consists of 36,338 spectra from one healthy subject and five brain tumor patients, acquired with an EPSI variant, which implemented a novel type of spectral editing named SLOtboom-Weng (SLOW) editing on a 7T MR scanner. The spectra were labeled manually by an expert into four classes of spectral quality as follows: (i) noise, (ii) spectra greatly influenced by lipid-related artifacts (deemed not to contain clinical information), (iii) spectra containing metabolic information slightly contaminated by lipid signals, and (iv) good-quality spectra. The AI model consists of three pairs of networks, each comprising a convolutional autoencoder and a multilayer perceptron network. In the classification step, the encoding half of the autoencoder is kept as a dimensionality reduction tool, while the fully connected layers are added to its output. Each of the three pairs of networks is trained on different representations of spectra (real, imaginary, or both), aiming at robust decision-making. The final class is assigned via a majority voting scheme. The F1 scores obtained on the test dataset for the four previously defined classes are 0.96, 0.93, 0.82, and 0.90, respectively. The arguably lower value of 0.82 was reached for the least represented class of spectra mildly influenced by lipids. Not only does the proposed model minimise the required user interaction, but it also greatly reduces the computation time at the metabolite quantification step (by selecting a subset of spectra worth quantifying) and enforces the display of only clinically relevant information.
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Affiliation(s)
- Mladen Rakić
- Research and Development, Icometrix, Leuven, Belgium
- Department of Electrical Engineering (ESAT), Processing Speech and Images (PSI) and Medical Imaging Research Center, KU Leuven, Leuven, Belgium
| | - Federico Turco
- Institute for Diagnostic and Interventional Radiology, Support Center for Advanced Neuroimaging (SCAN), University of Bern, Bern, Switzerland
| | - Guodong Weng
- Institute for Diagnostic and Interventional Radiology, Support Center for Advanced Neuroimaging (SCAN), University of Bern, Bern, Switzerland
| | - Frederik Maes
- Department of Electrical Engineering (ESAT), Processing Speech and Images (PSI) and Medical Imaging Research Center, KU Leuven, Leuven, Belgium
| | - Diana M Sima
- Research and Development, Icometrix, Leuven, Belgium
| | - Johannes Slotboom
- Institute for Diagnostic and Interventional Radiology, Support Center for Advanced Neuroimaging (SCAN), University of Bern, Bern, Switzerland
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Pan F, Liu X, Wan J, Guo Y, Sun P, Zhang X, Wang J, Bao Q, Yang L. Advances and prospects in deuterium metabolic imaging (DMI): a systematic review of in vivo studies. Eur Radiol Exp 2024; 8:65. [PMID: 38825658 PMCID: PMC11144684 DOI: 10.1186/s41747-024-00464-y] [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: 12/10/2023] [Accepted: 04/02/2024] [Indexed: 06/04/2024] Open
Abstract
BACKGROUND Deuterium metabolic imaging (DMI) has emerged as a promising non-invasive technique for studying metabolism in vivo. This review aims to summarize the current developments and discuss the futures in DMI technique in vivo. METHODS A systematic literature review was conducted based on the PRISMA 2020 statement by two authors. Specific technical details and potential applications of DMI in vivo were summarized, including strategies of deuterated metabolites detection, deuterium-labeled tracers and corresponding metabolic pathways in vivo, potential clinical applications, routes of tracer administration, quantitative evaluations of metabolisms, and spatial resolution. RESULTS Of the 2,248 articles initially retrieved, 34 were finally included, highlighting 2 strategies for detecting deuterated metabolites: direct and indirect DMI. Various deuterated tracers (e.g., [6,6'-2H2]glucose, [2,2,2'-2H3]acetate) were utilized in DMI to detect and quantify different metabolic pathways such as glycolysis, tricarboxylic acid cycle, and fatty acid oxidation. The quantifications (e.g., lactate level, lactate/glutamine and glutamate ratio) hold promise for diagnosing malignancies and assessing early anti-tumor treatment responses. Tracers can be administered orally, intravenously, or intraperitoneally, either through bolus administration or continuous infusion. For metabolic quantification, both serial time point methods (including kinetic analysis and calculation of area under the curves) and single time point quantifications are viable. However, insufficient spatial resolution remains a major challenge in DMI (e.g., 3.3-mL spatial resolution with 10-min acquisition at 3 T). CONCLUSIONS Enhancing spatial resolution can facilitate the clinical translation of DMI. Furthermore, optimizing tracer synthesis, administration protocols, and quantification methodologies will further enhance their clinical applicability. RELEVANCE STATEMENT Deuterium metabolic imaging, a promising non-invasive technique, is systematically discussed in this review for its current progression, limitations, and future directions in studying in vivo energetic metabolism, displaying a relevant clinical potential. KEY POINTS • Deuterium metabolic imaging (DMI) shows promise for studying in vivo energetic metabolism. • This review explores DMI's current state, limits, and future research directions comprehensively. • The clinical translation of DMI is mainly impeded by limitations in spatial resolution.
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Affiliation(s)
- Feng Pan
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Xinjie Liu
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, 430071, China
| | - Jiayu Wan
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Yusheng Guo
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Peng Sun
- MSC Clinical & Technical Solutions, Philips Healthcare, Beijing, 100600, China
| | - Xiaoxiao Zhang
- MSC Clinical & Technical Solutions, Philips Healthcare, Beijing, 100600, China
| | - Jiazheng Wang
- MSC Clinical & Technical Solutions, Philips Healthcare, Beijing, 100600, China
| | - Qingjia Bao
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, 430071, China.
| | - Lian Yang
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
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Shamaei A, Starcukova J, Rizzo R, Starcuk Z. Water removal in MR spectroscopic imaging with Casorati singular value decomposition. Magn Reson Med 2024; 91:1694-1706. [PMID: 38181180 DOI: 10.1002/mrm.29959] [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: 08/10/2023] [Revised: 11/04/2023] [Accepted: 11/17/2023] [Indexed: 01/07/2024]
Abstract
PURPOSE Water removal is one of the computational bottlenecks in the processing of high-resolution MRSI data. The purpose of this work is to propose an approach to reduce the computing time required for water removal in large MRS data. METHODS In this work, we describe a singular value decomposition-based approach that uses the partial position-time separability and the time-domain linear predictability of MRSI data to reduce the computational time required for water removal. Our approach arranges MRS signals in a Casorati matrix form, applies low-rank approximations utilizing singular value decomposition, removes residual water from the most prominent left-singular vectors, and finally reconstructs the water-free matrix using the processed left-singular vectors. RESULTS We have demonstrated the effectiveness of our proposed algorithm for water removal using both simulated and in vivo data. The proposed algorithm encompasses a pip-installable tool ( https://pypi.org/project/CSVD/), available on GitHub ( https://github.com/amirshamaei/CSVD), empowering researchers to use it in future studies. Additionally, to further promote transparency and reproducibility, we provide comprehensive code for result replication. CONCLUSIONS The findings of this study suggest that the proposed method is a promising alternative to existing water removal methods due to its low processing time and good performance in removing water signals.
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Affiliation(s)
- Amirmohammad Shamaei
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
- Department of Electrical and Software Engineering, Schulich School of Engineering, University of Calgary, Calgary, Alberta, Canada
| | - Jana Starcukova
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - Rudy Rizzo
- MR Methodology, Department of Interventional Neuroradiology, University of Bern, Bern, Switzerland
- Department of Biomedical Research, University of Bern, Bern, Switzerland
- Translational Imaging Center (TIC), Swiss Institute of Translational Entrepreneurial Medicine, Bern, Switzerland
| | - Zenon Starcuk
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
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Farley N, Susnjar A, Chiew M, Emir UE. Test-Retest Reproducibility of Reduced-Field-of-View Density-Weighted CRT MRSI at 3T. Tomography 2024; 10:493-503. [PMID: 38668396 PMCID: PMC11055142 DOI: 10.3390/tomography10040038] [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: 02/20/2024] [Revised: 03/25/2024] [Accepted: 03/26/2024] [Indexed: 04/29/2024] Open
Abstract
Quantifying an imaging modality's ability to reproduce results is important for establishing its utility. In magnetic resonance spectroscopic imaging (MRSI), new acquisition protocols are regularly introduced which improve upon their precursors with respect to signal-to-noise ratio (SNR), total acquisition duration, and nominal voxel resolution. This study has quantified the within-subject and between-subject reproducibility of one such new protocol (reduced-field-of-view density-weighted concentric ring trajectory (rFOV-DW-CRT) MRSI) by calculating the coefficient of variance of data acquired from a test-retest experiment. The posterior cingulate cortex (PCC) and the right superior corona radiata (SCR) were selected as the regions of interest (ROIs) for grey matter (GM) and white matter (WM), respectively. CVs for between-subject and within-subject were consistently around or below 15% for Glx, tCho, and Myo-Ins, and below 5% for tNAA and tCr.
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Affiliation(s)
- Nicholas Farley
- School of Health Sciences, Purdue University, West Lafayette, IN 47907, USA;
| | - Antonia Susnjar
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN 47907, USA;
| | - Mark Chiew
- Department of Medical Biophysics, University of Toronto, Toronto, ON M5G 1L7, Canada;
| | - Uzay E. Emir
- School of Health Sciences, Purdue University, West Lafayette, IN 47907, USA;
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN 47907, USA;
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10
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Just N, Chevillard PM, Batailler M, Dubois JP, Vaudin P, Pillon D, Migaud M. Multiparametric MR Evaluation of the Photoperiodic Regulation of Hypothalamic Structures in Sheep. Neuroscience 2023; 535:142-157. [PMID: 37913859 DOI: 10.1016/j.neuroscience.2023.10.022] [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: 08/25/2023] [Revised: 10/16/2023] [Accepted: 10/24/2023] [Indexed: 11/03/2023]
Abstract
Most organisms on earth, humans included, have developed strategies to cope with environmental day-night and seasonal cycles to survive. For most of them, their physiological and behavioral functions, including the reproductive function, are synchronized with the annual changes of day length, to ensure winter survival and subsequent reproductive success in the following spring. Sheep are sensitive to photoperiod, which also regulates natural adult neurogenesis in their hypothalamus. We postulate that the ovine model represents a good alternative to study the functional and metabolic changes occurring in response to photoperiodic changes in hypothalamic structures of the brain. Here, the impact of the photoperiod on the neurovascular coupling and the metabolism of the hypothalamic structures was investigated at 3T using BOLD fMRI, perfusion-MRI and proton magnetic resonance spectroscopy (1H-MRS). A longitudinal study involving 8 ewes was conducted during long days (LD) and short days (SD) revealing significant BOLD, rCBV and metabolic changes in hypothalamic structures of the ewe brain between LD and SD. More specifically, the transition between LD and SD revealed negative BOLD responses to hypercapnia at the beginning of SD period followed by significant increases in BOLD, rCBV, Glx and tNAA concentrations towards the end of the SD period. These observations suggest longitudinal mechanisms promoting the proliferation and differentiation of neural stem cells within the hypothalamic niche of breeding ewes. We conclude that multiparametric MRI studies including 1H-MRS could be promising non-invasive translational techniques to investigate the existence of natural adult neurogenesis in-vivo in gyrencephalic brains.
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Affiliation(s)
- Nathalie Just
- INRAE Centre Val de Loire, UMR Physiologie de la Reproduction et des Comportements CNRS, IFCE, INRAE, Université de Tours, 37380 Nouzilly France; Danish Research Centre for Magnetic Resonance (DRCMR), Hvidovre, Denmark.
| | - Pierre Marie Chevillard
- INRAE Centre Val de Loire, UMR Physiologie de la Reproduction et des Comportements CNRS, IFCE, INRAE, Université de Tours, 37380 Nouzilly France
| | - Martine Batailler
- INRAE Centre Val de Loire, UMR Physiologie de la Reproduction et des Comportements CNRS, IFCE, INRAE, Université de Tours, 37380 Nouzilly France
| | - Jean-Philippe Dubois
- INRAE Centre Val de Loire, UMR Physiologie de la Reproduction et des Comportements CNRS, IFCE, INRAE, Université de Tours, 37380 Nouzilly France
| | - Pascal Vaudin
- INRAE Centre Val de Loire, UMR Physiologie de la Reproduction et des Comportements CNRS, IFCE, INRAE, Université de Tours, 37380 Nouzilly France
| | - Delphine Pillon
- INRAE Centre Val de Loire, UMR Physiologie de la Reproduction et des Comportements CNRS, IFCE, INRAE, Université de Tours, 37380 Nouzilly France
| | - Martine Migaud
- INRAE Centre Val de Loire, UMR Physiologie de la Reproduction et des Comportements CNRS, IFCE, INRAE, Université de Tours, 37380 Nouzilly France
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11
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Sun L, Yan H, Zhang Y. Magnetic resonance spectroscopy (MRS) of multifidus muscle metabolites in chronic low back pain (CLBP). EUROPEAN SPINE JOURNAL : OFFICIAL PUBLICATION OF THE EUROPEAN SPINE SOCIETY, THE EUROPEAN SPINAL DEFORMITY SOCIETY, AND THE EUROPEAN SECTION OF THE CERVICAL SPINE RESEARCH SOCIETY 2023; 32:4397-4404. [PMID: 37721604 DOI: 10.1007/s00586-023-07933-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/25/2022] [Revised: 06/14/2023] [Accepted: 08/30/2023] [Indexed: 09/19/2023]
Abstract
PURPOSE The purpose of the study was to investigate several potential imaging biomarkers of CLBP that may be useful for diagnosis and treatment efficacy evaluation. Proton magnetic resonance spectroscopy (1H-MRS) was used to detect the content and ratio of creatine (Cr), choline (Cho), and lipid (Lip) in the multifidus muscle (Mm) in patients with CLBP and to test for relationships between these metabolites and pain severity and duration. METHODS Sixty patients with CLBP (experimental group) and sixty-nine asymptomatic volunteers (control group) underwent routine diagnostic magnetic resonance imaging of the lumbar spine. 1H-MRS was acquired with single-voxel MR spectroscopy. The MRS region of interest for measuring Cho, Cr, and Lip concentrations was determined at the L4/5 multifidus muscle (Mm), bilaterally. The contents and ratios of Cr, Cho, and Lip in bilateral and ipsilateral-to-pain (or matched control side) Mm were obtained, and the integral ratios of different metabolites obtained by using Cr as an internal reference were statistically analyzed. RESULTS There were no significant within-group differences in the contents and ratios of Lip, Cr, Cho, Lip/Cr, and Cho/Cr between the left and right Mm of the healthy control group (p > 0.05) or the CLBP group (p > 0.05). The CLBP group showed a much higher Lip and Lip/Cr ratio in the bilateral Mm compared to the healthy control group (p < 0.05) but there were no between-group differences in Cr, Cho, or the Cho/Cr ratio (p > 0.05). The severity of CLBP was correlated with Lip (p < 0.05). CONCLUSION Using 1H-MRS, we demonstrated higher Lip and Lip/Cr ratios in the Mm of patients with CLBP, compared to asymptomatic controls. Mm Lip was correlated with CLBP intensity. An increase in Lip in the Mm may be a characteristic finding in CLBP and may offer a useful prognostic marker for guiding rehabilitation strategies.
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Affiliation(s)
- Limeng Sun
- Department of Radiology, The Traditional Chinese Medicine Hospital of Taian, No. 58 Dongyue Street, Taian District, Taian, 271000, Shandong Province, China
| | - Hu Yan
- Department of Spine Surgery, The Traditional Chinese Medicine Hospital of Taian, No. 58 Dongyue Street, Taian District, Taian, 271000, Shandong Province, China.
| | - Ye Zhang
- Department of Radiology, Taian Maternal and Child Health Hospital, No. 386 Longtan Road, Gaoxin District, Taian, 27100, Shandong Province, China
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12
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Rizzo R, Kreis R. Multi-echo single-shot spectroscopy combined with simultaneous 2D model fitting for fast and accurate measurement of metabolite-specific concentrations and T 2 relaxation times. NMR IN BIOMEDICINE 2023; 36:e5016. [PMID: 37587062 DOI: 10.1002/nbm.5016] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 07/13/2023] [Accepted: 07/14/2023] [Indexed: 08/18/2023]
Abstract
The purpose of the current study was to develop a novel single-voxel MR spectroscopy acquisition scheme to simultaneously determine metabolite-specific concentrations and transverse relaxation times within realistic clinical scan times. Partly truncated multi-TE data are acquired as an echo train in a single acquisition (multi-echo single-shot [MESS]). A 2D multiparametric model fitting approach combines truncated, low-resolved short TE data with fully sampled, highly resolved, longer TE data to yield concentration and T2 estimates for major brain metabolites simultaneously. Cramer-Rao lower bounds (CRLB) are used as a measure of performance. The novel scheme was compared with traditional multi-echo multi-shot methods. In silico, in vitro, and in vivo experiments support the findings. MESS schemes, requiring only 2 min 12 s for the acquisition of three echo times, provide valid concentration and relaxation estimates for multiple metabolites and outperform traditional methods for simultaneous determinations of metabolite-specific T2 s and concentrations, with improvements ranging from 5% to 30% for T2 s and from 10% to 50% for concentrations. However, substantial unsuppressed residual water signals may hamper the method's reproducibility, as observed in an initial experiment setup that prioritizes short TEs with severely truncated acquisition for the benefit of signal-to-noise ratio (SNR). Nevertheless, CRLB have been confirmed to be well suited as design criteria, and within-session repeatability approaches CRLB when residual water is removed in postprocessing by exploiting longer and less truncated data recordings. MESS MRS combined with 2D model fitting promises comparable accuracy, increased precision, or inversely shorter experimental times compared with traditional approaches. However, the optimal design must be investigated as a trade-off between SNR, the truncation factor, and TE batch selections, all of which influence the robustness of estimations.
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Affiliation(s)
- Rudy Rizzo
- MR Methodology, Department for Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland
- Department for Biomedical Research, University of Bern, Bern, Switzerland
- Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine (sitem-insel), Bern, Switzerland
- Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland
| | - Roland Kreis
- MR Methodology, Department for Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland
- Department for Biomedical Research, University of Bern, Bern, Switzerland
- Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine (sitem-insel), Bern, Switzerland
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13
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Frank SM, Becker M, Malloni WM, Sasaki Y, Greenlee MW, Watanabe T. Protocol to conduct functional magnetic resonance spectroscopy in different age groups of human participants. STAR Protoc 2023; 4:102493. [PMID: 37572324 PMCID: PMC10448431 DOI: 10.1016/j.xpro.2023.102493] [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: 03/30/2023] [Revised: 06/02/2023] [Accepted: 07/17/2023] [Indexed: 08/14/2023] Open
Abstract
We present a protocol to conduct functional magnetic resonance spectroscopy (fMRS) in human participants before, during, and after training on a visual task. We describe steps for participant setup, volume-of-interest placement, fMRS measurement, and post-scan tests. We discuss the design, analysis, and interpretation of fMRS experiments. This protocol can be adapted to investigate the dynamics of chief excitatory and inhibitory neurotransmitters (glutamate and γ-aminobutyric acid, GABA, respectively) while participants perform or learn perceptual, motor, or cognitive tasks. For complete details on the use and execution of this protocol, please refer to Frank et al. (2022).1.
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Affiliation(s)
- Sebastian M Frank
- University of Regensburg, Institute for Experimental Psychology, Universitätsstraße 31, 93053 Regensburg, Germany.
| | - Markus Becker
- University of Regensburg, Institute for Experimental Psychology, Universitätsstraße 31, 93053 Regensburg, Germany
| | - Wilhelm M Malloni
- University of Regensburg, Institute for Experimental Psychology, Universitätsstraße 31, 93053 Regensburg, Germany
| | - Yuka Sasaki
- Brown University, Department of Cognitive, Linguistic and Psychological Sciences, 190 Thayer St., Providence, RI 02912, USA
| | - Mark W Greenlee
- University of Regensburg, Institute for Experimental Psychology, Universitätsstraße 31, 93053 Regensburg, Germany
| | - Takeo Watanabe
- Brown University, Department of Cognitive, Linguistic and Psychological Sciences, 190 Thayer St., Providence, RI 02912, USA.
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14
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Niess F, Strasser B, Hingerl L, Niess E, Motyka S, Hangel G, Krššák M, Gruber S, Spurny-Dworak B, Trattnig S, Scherer T, Lanzenberger R, Bogner W. Reproducibility of 3D MRSI for imaging human brain glucose metabolism using direct ( 2H) and indirect ( 1H) detection of deuterium labeled compounds at 7T and clinical 3T. Neuroimage 2023; 277:120250. [PMID: 37414233 PMCID: PMC11019874 DOI: 10.1016/j.neuroimage.2023.120250] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 05/25/2023] [Accepted: 06/23/2023] [Indexed: 07/08/2023] Open
Abstract
INTRODUCTION Deuterium metabolic imaging (DMI) and quantitative exchange label turnover (QELT) are novel MR spectroscopy techniques for non-invasive imaging of human brain glucose and neurotransmitter metabolism with high clinical potential. Following oral or intravenous administration of non-ionizing [6,6'-2H2]-glucose, its uptake and synthesis of downstream metabolites can be mapped via direct or indirect detection of deuterium resonances using 2H MRSI (DMI) and 1H MRSI (QELT), respectively. The purpose of this study was to compare the dynamics of spatially resolved brain glucose metabolism, i.e., estimated concentration enrichment of deuterium labeled Glx (glutamate+glutamine) and Glc (glucose) acquired repeatedly in the same cohort of subjects using DMI at 7T and QELT at clinical 3T. METHODS Five volunteers (4 m/1f) were scanned in repeated sessions for 60 min after overnight fasting and 0.8 g/kg oral [6,6'-2H2]-glucose administration using time-resolved 3D 2H FID-MRSI with elliptical phase encoding at 7T and 3D 1H FID-MRSI with a non-Cartesian concentric ring trajectory readout at clinical 3T. RESULTS One hour after oral tracer administration regionally averaged deuterium labeled Glx4 concentrations and the dynamics were not significantly different over all participants between 7T 2H DMI and 3T 1H QELT data for GM (1.29±0.15 vs. 1.38±0.26 mM, p=0.65 & 21±3 vs. 26±3 µM/min, p=0.22) and WM (1.10±0.13 vs. 0.91±0.24 mM, p=0.34 & 19±2 vs. 17±3 µM/min, p=0.48). Also, the observed time constants of dynamic Glc6 data in GM (24±14 vs. 19±7 min, p=0.65) and WM (28±19 vs. 18±9 min, p=0.43) dominated regions showed no significant differences. Between individual 2H and 1H data points a weak to moderate negative correlation was observed for Glx4 concentrations in GM (r=-0.52, p<0.001), and WM (r=-0.3, p<0.001) dominated regions, while a strong negative correlation was observed for Glc6 data GM (r=-0.61, p<0.001) and WM (r=-0.70, p<0.001). CONCLUSION This study demonstrates that indirect detection of deuterium labeled compounds using 1H QELT MRSI at widely available clinical 3T without additional hardware is able to reproduce absolute concentration estimates of downstream glucose metabolites and the dynamics of glucose uptake compared to 2H DMI data acquired at 7T. This suggests significant potential for widespread application in clinical settings especially in environments with limited access to ultra-high field scanners and dedicated RF hardware.
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Affiliation(s)
- Fabian Niess
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Lazarettgasse 14, Vienna A-1090, Austria.
| | - Bernhard Strasser
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Lazarettgasse 14, Vienna A-1090, Austria
| | - Lukas Hingerl
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Lazarettgasse 14, Vienna A-1090, Austria
| | - Eva Niess
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Lazarettgasse 14, Vienna A-1090, Austria; Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK), Austria
| | - Stanislav Motyka
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Lazarettgasse 14, Vienna A-1090, Austria; Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK), Austria
| | - Gilbert Hangel
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Lazarettgasse 14, Vienna A-1090, Austria; Department of Neurosurgery, Medical University of Vienna, Austria
| | - Martin Krššák
- Department of Medicine III, Division of Endocrinology and Metabolism, Medical University of Vienna, Austria
| | - Stephan Gruber
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Lazarettgasse 14, Vienna A-1090, Austria; Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK), Austria
| | - Benjamin Spurny-Dworak
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Austria
| | - Siegfried Trattnig
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Lazarettgasse 14, Vienna A-1090, Austria; Institute for Clinical Molecular MRI, Karl Landsteiner Society, Pölten 3100St, Austria
| | - Thomas Scherer
- Department of Medicine III, Division of Endocrinology and Metabolism, Medical University of Vienna, Austria
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Austria
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Lazarettgasse 14, Vienna A-1090, Austria; Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK), Austria
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15
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Koolschijn RS, Clarke WT, Ip IB, Emir UE, Barron HC. Event-related functional magnetic resonance spectroscopy. Neuroimage 2023; 276:120194. [PMID: 37244321 PMCID: PMC7614684 DOI: 10.1016/j.neuroimage.2023.120194] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 05/24/2023] [Indexed: 05/29/2023] Open
Abstract
Proton-Magnetic Resonance Spectroscopy (MRS) is a non-invasive brain imaging technique used to measure the concentration of different neurochemicals. "Single-voxel" MRS data is typically acquired across several minutes, before individual transients are averaged through time to give a measurement of neurochemical concentrations. However, this approach is not sensitive to more rapid temporal dynamics of neurochemicals, including those that reflect functional changes in neural computation relevant to perception, cognition, motor control and ultimately behaviour. In this review we discuss recent advances in functional MRS (fMRS) that now allow us to obtain event-related measures of neurochemicals. Event-related fMRS involves presenting different experimental conditions as a series of trials that are intermixed. Critically, this approach allows spectra to be acquired at a time resolution in the order of seconds. Here we provide a comprehensive user guide for event-related task designs, choice of MRS sequence, analysis pipelines, and appropriate interpretation of event-related fMRS data. We raise various technical considerations by examining protocols used to quantify dynamic changes in GABA, the primary inhibitory neurotransmitter in the brain. Overall, we propose that although more data is needed, event-related fMRS can be used to measure dynamic changes in neurochemicals at a temporal resolution relevant to computations that support human cognition and behaviour.
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Affiliation(s)
- Renée S Koolschijn
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, FMRIB, John Radcliffe Hospital, Oxford, United Kingdom; Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands.
| | - William T Clarke
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, FMRIB, John Radcliffe Hospital, Oxford, United Kingdom; Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom
| | - I Betina Ip
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, FMRIB, John Radcliffe Hospital, Oxford, United Kingdom
| | - Uzay E Emir
- School of Health Sciences, Purdue University, West Lafayette, United States
| | - Helen C Barron
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, FMRIB, John Radcliffe Hospital, Oxford, United Kingdom; Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom.
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16
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Weng G, Radojewski P, Slotboom J. α-D-Glucose as a non-radioactive MRS tracer for metabolic studies of the brain. Sci Rep 2023; 13:6159. [PMID: 37061615 PMCID: PMC10105689 DOI: 10.1038/s41598-023-33161-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 04/07/2023] [Indexed: 04/17/2023] Open
Abstract
Changes in brain glucose metabolism occur in many neurological disorders as well as during aging. Most studies on the uptake of glucose in the brain use positron emission tomography, which requires injection of a radioactive tracer. Our study shows that ultra-high-field 1H-MRS can be used to measure α-D-glucose at 5.22 ppm in vivo, and the α-D-glucose can be used as a radiation-free tracer in the human brain.
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Affiliation(s)
- Guodong Weng
- Institute for Diagnostic and Interventional Neuroradiology, Support Center for Advanced Neuroimaging (SCAN), Bern University Hospital, Inselspital, University of Bern, Bern, Switzerland
- Translational Imaging Center, Sitem-Insel, Bern, Switzerland
| | - Piotr Radojewski
- Institute for Diagnostic and Interventional Neuroradiology, Support Center for Advanced Neuroimaging (SCAN), Bern University Hospital, Inselspital, University of Bern, Bern, Switzerland
- Translational Imaging Center, Sitem-Insel, Bern, Switzerland
| | - Johannes Slotboom
- Institute for Diagnostic and Interventional Neuroradiology, Support Center for Advanced Neuroimaging (SCAN), Bern University Hospital, Inselspital, University of Bern, Bern, Switzerland.
- Translational Imaging Center, Sitem-Insel, Bern, Switzerland.
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17
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Harris AD, Amiri H, Bento M, Cohen R, Ching CRK, Cudalbu C, Dennis EL, Doose A, Ehrlich S, Kirov II, Mekle R, Oeltzschner G, Porges E, Souza R, Tam FI, Taylor B, Thompson PM, Quidé Y, Wilde EA, Williamson J, Lin AP, Bartnik-Olson B. Harmonization of multi-scanner in vivo magnetic resonance spectroscopy: ENIGMA consortium task group considerations. Front Neurol 2023; 13:1045678. [PMID: 36686533 PMCID: PMC9845632 DOI: 10.3389/fneur.2022.1045678] [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: 09/15/2022] [Accepted: 12/06/2022] [Indexed: 01/06/2023] Open
Abstract
Magnetic resonance spectroscopy is a powerful, non-invasive, quantitative imaging technique that allows for the measurement of brain metabolites that has demonstrated utility in diagnosing and characterizing a broad range of neurological diseases. Its impact, however, has been limited due to small sample sizes and methodological variability in addition to intrinsic limitations of the method itself such as its sensitivity to motion. The lack of standardization from a data acquisition and data processing perspective makes it difficult to pool multiple studies and/or conduct multisite studies that are necessary for supporting clinically relevant findings. Based on the experience of the ENIGMA MRS work group and a review of the literature, this manuscript provides an overview of the current state of MRS data harmonization. Key factors that need to be taken into consideration when conducting both retrospective and prospective studies are described. These include (1) MRS acquisition issues such as pulse sequence, RF and B0 calibrations, echo time, and SNR; (2) data processing issues such as pre-processing steps, modeling, and quantitation; and (3) biological factors such as voxel location, age, sex, and pathology. Various approaches to MRS data harmonization are then described including meta-analysis, mega-analysis, linear modeling, ComBat and artificial intelligence approaches. The goal is to provide both novice and experienced readers with the necessary knowledge for conducting MRS data harmonization studies.
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Affiliation(s)
- Ashley D. Harris
- Department of Radiology, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Houshang Amiri
- Neuroscience Research Center, Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran
| | - Mariana Bento
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada
| | - Ronald Cohen
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
| | - Christopher R. K. Ching
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, Los Angeles, CA, United States
| | - Christina Cudalbu
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Animal Imaging and Technology, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Emily L. Dennis
- TBI and Concussion Center, Department of Neurology, University of Utah, Salt Lake City, UT, United States
| | - Arne Doose
- Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Stefan Ehrlich
- Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Ivan I. Kirov
- Department of Radiology, Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY, United States
| | - Ralf Mekle
- Center for Stroke Research Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Eric Porges
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
| | - Roberto Souza
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Department of Electrical and Software Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada
| | - Friederike I. Tam
- Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Brian Taylor
- Division of Diagnostic Imaging, Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, Los Angeles, CA, United States
| | - Yann Quidé
- School of Psychology, University of New South Wales (UNSW), Sydney, NSW, Australia
| | - Elisabeth A. Wilde
- TBI and Concussion Center, Department of Neurology, University of Utah, Salt Lake City, UT, United States
| | - John Williamson
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
| | - Alexander P. Lin
- Center for Clinical Spectroscopy, Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States
| | - Brenda Bartnik-Olson
- Department of Radiology, Loma Linda University Medical Center, Loma Linda, CA, United States
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Abstract
Abstract
Purpose
Gliomas, the most common primary brain tumours, have recently been re-classified incorporating molecular aspects with important clinical, prognostic, and predictive implications. Concurrently, the reprogramming of metabolism, altering intracellular and extracellular metabolites affecting gene expression, differentiation, and the tumour microenvironment, is increasingly being studied, and alterations in metabolic pathways are becoming hallmarks of cancer. Magnetic resonance spectroscopy (MRS) is a complementary, non-invasive technique capable of quantifying multiple metabolites. The aim of this review focuses on the methodology and analysis techniques in proton MRS (1H MRS), including a brief look at X-nuclei MRS, and on its perspectives for diagnostic and prognostic biomarkers in gliomas in both clinical practice and preclinical research.
Methods
PubMed literature research was performed cross-linking the following key words: glioma, MRS, brain, in-vivo, human, animal model, clinical, pre-clinical, techniques, sequences, 1H, X-nuclei, Artificial Intelligence (AI), hyperpolarization.
Results
We selected clinical works (n = 51), preclinical studies (n = 35) and AI MRS application papers (n = 15) published within the last two decades. The methodological papers (n = 62) were taken into account since the technique first description.
Conclusions
Given the development of treatments targeting specific cancer metabolic pathways, MRS could play a key role in allowing non-invasive assessment for patient diagnosis and stratification, predicting and monitoring treatment responses and prognosis. The characterization of gliomas through MRS will benefit of a wide synergy among scientists and clinicians of different specialties within the context of new translational competences. Head coils, MRI hardware and post-processing analysis progress, advances in research, experts’ consensus recommendations and specific professionalizing programs will make the technique increasingly trustworthy, responsive, accessible.
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19
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Tomiyasu M, Harada M. In vivo Human MR Spectroscopy Using a Clinical Scanner: Development, Applications, and Future Prospects. Magn Reson Med Sci 2022; 21:235-252. [PMID: 35173095 PMCID: PMC9199975 DOI: 10.2463/mrms.rev.2021-0085] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
MR spectroscopy (MRS) is a unique and useful method for noninvasively evaluating biochemical metabolism in human organs and tissues, but its clinical dissemination has been slow and often limited to specialized institutions or hospitals with experts in MRS technology. The number of 3-T clinical MR scanners is now increasing, representing a major opportunity to promote the use of clinical MRS. In this review, we summarize the theoretical background and basic knowledge required to understand the results obtained with MRS and introduce the general consensus on the clinical utility of proton MRS in routine clinical practice. In addition, we present updates to the consensus guidelines on proton MRS published by the members of a working committee of the Japan Society of Magnetic Resonance in Medicine in 2013. Recent research into multinuclear MRS equipped in clinical MR scanners is explained with an eye toward future development. This article seeks to provide an overview of the current status of clinical MRS and to promote the understanding of when it can be useful. In the coming years, MRS-mediated biochemical evaluation is expected to become available for even routine clinical practice.
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Affiliation(s)
- Moyoko Tomiyasu
- Department of Molecular Imaging and Theranostics, National Institutes for Quantum Science and Technology.,Department of Radiology, Kanagawa Children's Medical Center
| | - Masafumi Harada
- Department of Radiology and Radiation Oncology, Graduate School of Biomedical Sciences, Tokushima University
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20
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Klauser A, Klauser P, Grouiller F, Courvoisier S, Lazeyras F. Whole-brain high-resolution metabolite mapping with 3D compressed-sensing SENSE low-rank 1 H FID-MRSI. NMR IN BIOMEDICINE 2022; 35:e4615. [PMID: 34595791 PMCID: PMC9285075 DOI: 10.1002/nbm.4615] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 08/16/2021] [Accepted: 08/20/2021] [Indexed: 05/07/2023]
Abstract
There is a growing interest in the neuroscience community to map the distribution of brain metabolites in vivo. Magnetic resonance spectroscopic imaging (MRSI) is often limited by either a poor spatial resolution and/or a long acquisition time, which severely restricts its applications for clinical and research purposes. Building on a recently developed technique of acquisition-reconstruction for 2D MRSI, we combined a fast Cartesian 1 H-FID-MRSI acquisition sequence, compressed-sensing acceleration, and low-rank total-generalized-variation constrained reconstruction to produce 3D high-resolution whole-brain MRSI with a significant acquisition time reduction. We first evaluated the acceleration performance using retrospective undersampling of a fully sampled dataset. Second, a 20 min accelerated MRSI acquisition was performed on three healthy volunteers, resulting in metabolite maps with 5 mm isotropic resolution. The metabolite maps exhibited the detailed neurochemical composition of all brain regions and revealed parts of the underlying brain anatomy. The latter assessment used previous reported knowledge and a atlas-based analysis to show consistency of the concentration contrasts and ratio across all brain regions. These results acquired on a clinical 3 T MRI scanner successfully combined 3D 1 H-FID-MRSI with a constrained reconstruction to produce detailed mapping of metabolite concentrations at high resolution over the whole brain, with an acquisition time suitable for clinical or research settings.
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Affiliation(s)
- Antoine Klauser
- Department of Radiology and Medical InformaticsUniversity of GenevaSwitzerland
- Center for Biomedical Imaging (CIBM)GenevaSwitzerland
| | - Paul Klauser
- Center for Psychiatric Neuroscience, Department of PsychiatryLausanne University HospitalSwitzerland
- Service of Child and Adolescent Psychiatry, Department of PsychiatryLausanne University HospitalSwitzerland
| | - Frédéric Grouiller
- Swiss Center for Affective SciencesUniversity of GenevaSwitzerland
- Laboratory of Behavioral Neurology and Imaging of Cognition, Department of Fundamental NeuroscienceUniversity of GenevaSwitzerland
| | - Sébastien Courvoisier
- Department of Radiology and Medical InformaticsUniversity of GenevaSwitzerland
- Center for Biomedical Imaging (CIBM)GenevaSwitzerland
| | - François Lazeyras
- Department of Radiology and Medical InformaticsUniversity of GenevaSwitzerland
- Center for Biomedical Imaging (CIBM)GenevaSwitzerland
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21
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Adany P, Choi IY, Lee P. Method for fast lipid reconstruction and removal processing in 1 H MRSI of the brain. Magn Reson Med 2021; 86:2930-2944. [PMID: 34337788 PMCID: PMC8568649 DOI: 10.1002/mrm.28949] [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: 02/10/2021] [Revised: 07/12/2021] [Accepted: 07/14/2021] [Indexed: 11/08/2022]
Abstract
PURPOSE To develop a new rapid spatial filtering method for lipid removal, fast lipid reconstruction and removal processing (FLIP), which selectively isolates and removes interfering lipid signals from outside the brain in a full-FOV 2D MRSI and whole-brain 3D echo planar spectroscopic imaging (EPSI). THEORY AND METHODS FLIP uses regularized least-squares regression based on spatial prior information from MRI to selectively remove lipid signals originating from the scalp and measure the brain metabolite signals with minimum cross contamination. FLIP is a noniterative approach, thus allowing a rapid processing speed, and uses only spatial information without any spectral priors. The performance of FLIP was compared with the Papoulis-Gerchberg algorithm (PGA), Hankel singular value decomposition (HSVD), and fast image reconstruction with L2 regularization (L2). RESULTS FLIP in both 2D and 3D MRSI resulted in consistent metabolite quantification in a greater number of voxels with less concentration variation than other algorithms, demonstrating effective and robust lipid-removal performance. The percentage of voxels that met quality criteria with FLIP, PGA, HSVD, and L2 processing were 90%, 57%, 29%, and 42% in 2D MRSI, and 80%, 75%, 76%, and 74% in 3D EPSI, respectively. The quantification results of full-FOV MRSI using FLIP were comparable to those of volume-localized MRSI, while allowing significantly increased spatial coverage. FLIP performed the fastest in 2D MRSI. CONCLUSION FLIP is a new lipid-removal algorithm that promises fast and effective lipid removal with improved volume coverage in MRSI.
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Affiliation(s)
- Peter Adany
- Hoglund Biomedical Imaging Center, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - In-Young Choi
- Hoglund Biomedical Imaging Center, University of Kansas Medical Center, Kansas City, KS 66160, USA
- Department of Neurology, University of Kansas Medical Center, Kansas City, KS 66160, USA
- Department of Radiology, University of Kansas Medical Center, Kansas City, KS 66160, USA
- Department of Molecular & Integrative Physiology, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Phil Lee
- Hoglund Biomedical Imaging Center, University of Kansas Medical Center, Kansas City, KS 66160, USA
- Department of Radiology, University of Kansas Medical Center, Kansas City, KS 66160, USA
- Department of Molecular & Integrative Physiology, University of Kansas Medical Center, Kansas City, KS 66160, USA
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22
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Caldwell S, Rothman DL. 1H Magnetic Resonance Spectroscopy to Understand the Biological Basis of ALS, Diagnose Patients Earlier, and Monitor Disease Progression. Front Neurol 2021; 12:701170. [PMID: 34512519 PMCID: PMC8429815 DOI: 10.3389/fneur.2021.701170] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 08/03/2021] [Indexed: 11/13/2022] Open
Abstract
At present, limited biomarkers exist to reliably understand, diagnose, and monitor the progression of amyotrophic lateral sclerosis (ALS), a fatal neurological disease characterized by motor neuron death. Standard MRI technology can only be used to exclude a diagnosis of ALS, but 1H-MRS technology, which measures neurochemical composition, may provide the unique ability to reveal biomarkers that are specific to ALS and sensitive enough to diagnose patients at early stages in disease progression. In this review, we present a summary of current theories of how mitochondrial energetics and an altered glutamate/GABA neurotransmitter flux balance play a role in the pathogenesis of ALS. The theories are synthesized into a model that predicts how pathogenesis impacts glutamate and GABA concentrations. When compared with the results of all MRS studies published to date that measure the absolute concentrations of these neurochemicals in ALS patients, results were variable. However, when normalized for neuronal volume using the MRS biomarker N-acetyl aspartate (NAA), there is clear evidence for an elevation of neuronal glutamate in nine out of thirteen studies reviewed, an observation consistent with the predictions of the model of increased activity of glutamatergic neurons and excitotoxicity. We propose that this increase in neuronal glutamate concentration, in combination with decreased neuronal volume, is specific to the pathology of ALS. In addition, when normalized to glutamate levels, there is clear evidence for a decrease in neuronal GABA in three out of four possible studies reviewed, a finding consistent with a loss of inhibitory regulation contributing to excessive neuronal excitability. The combination of a decreased GABA/Glx ratio with an elevated Glx/NAA ratio may enhance the specificity for 1H-MRS detection of ALS and ability to monitor glutamatergic and GABAergic targeted therapeutics. Additional longitudinal studies calculating the exact value of these ratios are needed to test these hypotheses and understand how ratios may change over the course of disease progression. Proposed modifications to the experimental design of the reviewed 1H MRS studies may also increase the sensitivity of the technology to changes in these neurochemicals, particularly in early stages of disease progression.
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Affiliation(s)
- Sarah Caldwell
- Departments of Radiology and Biomedical Engineering, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, CT, United States
| | - Douglas L Rothman
- Departments of Radiology and Biomedical Engineering, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, CT, United States
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23
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Hupfeld KE, Hyatt HW, Alvarez Jerez P, Mikkelsen M, Hass CJ, Edden RAE, Seidler RD, Porges EC. In Vivo Brain Glutathione is Higher in Older Age and Correlates with Mobility. Cereb Cortex 2021; 31:4576-4594. [PMID: 33959751 PMCID: PMC8408448 DOI: 10.1093/cercor/bhab107] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 03/25/2021] [Accepted: 03/28/2021] [Indexed: 12/12/2022] Open
Abstract
Brain markers of oxidative damage increase with advancing age. In response, brain antioxidant levels may also increase with age, although this has not been well investigated. Here, we used edited magnetic resonance spectroscopy to quantify endogenous levels of glutathione (GSH, one of the most abundant brain antioxidants) in 37 young [mean: 21.8 (2.5) years; 19 female] and 23 older adults [mean: 72.8 (8.9) years; 19 female]. Accounting for age-related atrophy, we identified higher frontal and sensorimotor GSH levels for the older compared with the younger adults. For the older adults only, higher sensorimotor (but not frontal) GSH was correlated with poorer balance and gait. This suggests a regionally specific relationship between higher brain oxidative stress levels and motor performance declines with age. We suggest these findings reflect an upregulation of GSH in response to increasing brain oxidative stress with normal aging. Together, these results provide insight into age differences in brain antioxidant levels and implications for motor function.
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Affiliation(s)
- K E Hupfeld
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL 32603, USA
| | - H W Hyatt
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL 32603, USA
| | - P Alvarez Jerez
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL 32603, USA
| | - M Mikkelsen
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - C J Hass
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL 32603, USA
| | - R A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - R D Seidler
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL 32603, USA
- Department of Neurology, University of Florida, Gainesville, FL 32611, USA
| | - E C Porges
- Department of Clinical and Health Psychology, University of Florida, Gainesville, FL 32603, USA
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24
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Cudalbu C, Bady P, Lai M, Xin L, Gusyatiner O, Hamou MF, Lepore M, Brouland JP, Daniel RT, Hottinger AF, Hegi ME. Metabolic and transcriptomic profiles of glioblastoma invasion revealed by comparisons between patients and corresponding orthotopic xenografts in mice. Acta Neuropathol Commun 2021; 9:133. [PMID: 34348785 PMCID: PMC8336020 DOI: 10.1186/s40478-021-01232-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Accepted: 07/21/2021] [Indexed: 02/07/2023] Open
Abstract
The invasive behavior of glioblastoma, the most aggressive primary brain tumor, is considered highly relevant for tumor recurrence. However, the invasion zone is difficult to visualize by Magnetic Resonance Imaging (MRI) and is protected by the blood brain barrier, posing a particular challenge for treatment. We report biological features of invasive growth accompanying tumor progression and invasion based on associated metabolic and transcriptomic changes observed in patient derived orthotopic xenografts (PDOX) in the mouse and the corresponding patients’ tumors. The evolution of metabolic changes, followed in vivo longitudinally by 1H Magnetic Resonance Spectroscopy (1H MRS) at ultra-high field, reflected growth and the invasive properties of the human glioblastoma transplanted into the brains of mice (PDOX). Comparison of MRS derived metabolite signatures, reflecting temporal changes of tumor development and invasion in PDOX, revealed high similarity to spatial metabolite signatures of combined multi-voxel MRS analyses sampled across different areas of the patients’ tumors. Pathway analyses of the transcriptome associated with the metabolite profiles of the PDOX, identified molecular signatures of invasion, comprising extracellular matrix degradation and reorganization, growth factor binding, and vascular remodeling. Specific analysis of expression signatures from the invaded mouse brain, revealed extent of invasion dependent induction of immune response, recapitulating respective signatures observed in glioblastoma. Integrating metabolic profiles and gene expression of highly invasive PDOX provided insights into progression and invasion associated mechanisms of extracellular matrix remodeling that is essential for cell–cell communication and regulation of cellular processes. Structural changes and biochemical properties of the extracellular matrix are of importance for the biological behavior of tumors and may be druggable. Ultra-high field MRS reveals to be suitable for in vivo monitoring of progression in the non-enhancing infiltration zone of glioblastoma.
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25
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Andronesi OC, Bhattacharyya PK, Bogner W, Choi IY, Hess AT, Lee P, Meintjes E, Tisdall MD, Zaitzev M, van der Kouwe A. Motion correction methods for MRS: experts' consensus recommendations. NMR IN BIOMEDICINE 2021; 34:e4364. [PMID: 33089547 PMCID: PMC7855523 DOI: 10.1002/nbm.4364] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2019] [Revised: 06/07/2020] [Accepted: 06/08/2020] [Indexed: 05/07/2023]
Abstract
Long acquisition times due to intrinsically low signal-to-noise ratio and the need for highly homogeneous B0 field make MRS particularly susceptible to motion or scanner instability compared with MRI. Motion-induced changes in both localization and shimming (ie B0 homogeneity) degrade MRS data quality. To mitigate the effects of motion three approaches can be employed: (1) subject immobilization, (2) retrospective correction, and (3) prospective real-time correction using internal and/or external tracking methods. Prospective real-time correction methods can simultaneously update localization and the B0 field to improve MRS data quality. While localization errors can be corrected with both internal (navigators) and external (optical camera, NMR probes) tracking methods, the B0 field correction requires internal navigator methods to measure the B0 field inside the imaged volume and the possibility to update the scanner shim hardware in real time. Internal and external tracking can rapidly update the MRS localization with submillimeter and subdegree precision, while scanner frequency and first-order shims of scanner hardware can be updated by internal methods every sequence repetition. These approaches are most well developed for neuroimaging, for which rigid transformation is primarily applicable. Real-time correction greatly improves the stability of MRS acquisition and quantification, as shown in clinical studies on subjects prone to motion, including children and patients with movement disorders, enabling robust measurement of metabolite signals including those with low concentrations, such as gamma-aminobutyric acid and glutathione. Thus, motion correction is recommended for MRS users and calls for tighter integration and wider availability of such methods by MR scanner manufacturers.
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Affiliation(s)
- Ovidiu C. Andronesi
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Corresponding Author: Ovidiu C. Andronesi, MD, PhD, Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Thirteenth Street, Charlestown, MA 02129, USA;
| | | | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University Vienna, Vienna, Austria
| | - In-Young Choi
- Department of Neurology, Hoglund Biomedical Imaging Center, University of Kansas Medical Center, Kansas City, KS, USA
| | - Aaron T. Hess
- University of Oxford Centre for Clinical Magnetic Resonance Research, Division of Cardiovascular Medicine, University of Oxford
| | - Phil Lee
- Department of Radiology, Hoglund Biomedical Imaging Center, University of Kansas Medical Center, Kansas City, KS, USA
| | - Ernesta Meintjes
- UCT Medical Imaging Research Unit, Division of Biomedical Engineering, Department of Human Biology, University of Cape Town
| | - M. Dylan Tisdall
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania
| | - Maxim Zaitzev
- Department of Radiology, Medical Physics, Medical Center, University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- High Field Magnetic Resonance Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - André van der Kouwe
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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26
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Lin A, Andronesi O, Bogner W, Choi I, Coello E, Cudalbu C, Juchem C, Kemp GJ, Kreis R, Krššák M, Lee P, Maudsley AA, Meyerspeer M, Mlynarik V, Near J, Öz G, Peek AL, Puts NA, Ratai E, Tkáč I, Mullins PG. Minimum Reporting Standards for in vivo Magnetic Resonance Spectroscopy (MRSinMRS): Experts' consensus recommendations. NMR IN BIOMEDICINE 2021; 34:e4484. [PMID: 33559967 PMCID: PMC8647919 DOI: 10.1002/nbm.4484] [Citation(s) in RCA: 115] [Impact Index Per Article: 38.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 11/24/2020] [Accepted: 01/12/2021] [Indexed: 05/08/2023]
Abstract
The translation of MRS to clinical practice has been impeded by the lack of technical standardization. There are multiple methods of acquisition, post-processing, and analysis whose details greatly impact the interpretation of the results. These details are often not fully reported, making it difficult to assess MRS studies on a standardized basis. This hampers the reviewing of manuscripts, limits the reproducibility of study results, and complicates meta-analysis of the literature. In this paper a consensus group of MRS experts provides minimum guidelines for the reporting of MRS methods and results, including the standardized description of MRS hardware, data acquisition, analysis, and quality assessment. This consensus statement describes each of these requirements in detail and includes a checklist to assist authors and journal reviewers and to provide a practical way for journal editors to ensure that MRS studies are reported in full.
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Affiliation(s)
- Alexander Lin
- Center for Clinical Spectroscopy, Department of Radiology, Brigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Ovidiu Andronesi
- Department of RadiologyMassachusetts General HospitalBostonMassachusettsUSA
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - In‐Young Choi
- Department of Neurology, Hoglund Biomedical Imaging CenterUniversity of Kansas Medical CenterKansas CityKansasUSA
| | - Eduardo Coello
- Center for Clinical Spectroscopy, Department of Radiology, Brigham and Women's HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Cristina Cudalbu
- Center for Biomedical Imaging (CIBM), Ecole Polytechnique Fédérale de LausanneLausanneSwitzerland
| | - Christoph Juchem
- Departments of Biomedical Engineering and RadiologyColumbia UniversityNew YorkNew YorkUSA
| | - Graham J. Kemp
- Department of Musculoskeletal and Ageing Science and Liverpool Magnetic Resonance Imaging Centre (LiMRIC)University of LiverpoolLiverpoolUK
| | - Roland Kreis
- Departments of Radiology and Biomedical ResearchUniversity of BernBernSwitzerland
| | - Martin Krššák
- Department of Medicine III and Department of Biomedical Imaging and Image guided TherapyMedical University of ViennaViennaAustria
| | - Phil Lee
- Department of Radiology, Hoglund Biomedical Imaging CenterUniversity of Kansas Medical CenterKansas CityKansasUSA
| | | | - Martin Meyerspeer
- High Field MR Center, Center for Medical Physics and Biomedical EngineeringMedical University of ViennaViennaAustria
| | - Vladamir Mlynarik
- Magnetic Resonance Centre of Excellence. Medical University of ViennaViennaAustria
| | - Jamie Near
- Brain Imaging Centre, Douglas Research Centre, Department of PsychiatryMcGill UniversityMontrealQuebecCanada
| | - Gülin Öz
- Center for Magnetic Resonance Research, Department of RadiologyUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Aimie L. Peek
- Faculty of Health SciencesUniversity of SydneySydneyAustralia
| | - Nicolaas A. Puts
- Department of Forensic and Neurodevelopmental SciencesSackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology, and Neuroscience, King's College LondonLondonUK
| | - Eva‐Maria Ratai
- A.A. Martinos Center for Biomedical Imaging, Neuroradiology Division, Department of RadiologyMassachusetts General HospitalBostonMassachusettsUSA
| | - Ivan Tkáč
- Faculty of Health SciencesUniversity of SydneySydneyAustralia
| | - Paul G. Mullins
- Bangor Imaging Unit, School of PsychologyBangor UniversityBangorGwyneddUK
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27
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Kumaragamage C, De Feyter HM, Brown P, McIntyre S, Nixon TW, de Graaf RA. ECLIPSE utilizing gradient-modulated offset-independent adiabaticity (GOIA) pulses for highly selective human brain proton MRSI. NMR IN BIOMEDICINE 2021; 34:e4415. [PMID: 33001485 PMCID: PMC9472321 DOI: 10.1002/nbm.4415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2020] [Revised: 08/16/2020] [Accepted: 09/07/2020] [Indexed: 06/11/2023]
Abstract
A multitude of extracranial lipid suppression methods exist for proton MRSI acquisitions. Popular and emerging lipid suppression methods each have their inherent set of advantages and disadvantages related to the achievable level of lipid suppression, RF power deposition, insensitivity to B1+ field and lipid T1 heterogeneity, brain coverage, spatial selectivity, chemical shift displacement (CSD) errors and the reliability of spectroscopic data spanning the observed 0.9-4.7 ppm band. The utility of elliptical localization with pulsed second order fields (ECLIPSE) was previously demonstrated with a greater than 100-fold in extracranial lipid suppression and low power requirements utilizing 3 kHz bandwidth AFP pulses. Like all gradient-based localization methods, ECLIPSE is sensitive to CSD errors, resulting in a modified metabolic profile in edge-of-ROI voxels. In this work, ECLIPSE is extended with 15 kHz bandwidth second order gradient-modulated RF pulses based on the gradient offset-independent adiabaticity (GOIA) algorithm to greatly reduce CSD and improve spatial selectivity. An adiabatic double spin-echo ECLIPSE inner volume selection (TE = 45 ms) MRSI method and an ECLIPSE outer volume suppression (TE = 3.2 ms) FID-MRSI method were implemented. Both GOIA-ECLIPSE MRSI sequences provided artifact-free metabolite spectra in vivo, with a greater than 100-fold in lipid suppression and less than 2.6 mm in-plane CSD and less than 3.3 mm transition width for edge-of-ROI voxels, representing an ~5-fold improvement compared with the parent, nongradient-modulated method. Despite the 5-fold larger bandwidth, GOIA-ECLIPSE only required a 1.9-fold increase in RF power. The highly robust lipid suppression combined with low CSD and sharp ROI edge transitions make GOIA-ECLIPSE an attractive alternative to commonly employed lipid suppression methods. Furthermore, the low RF power deposition demonstrates that GOIA-ECLIPSE is very well suited for high field (≥3 T) MRSI applications.
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Affiliation(s)
- Chathura Kumaragamage
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, CT, USA
| | - Henk M. De Feyter
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, CT, USA
| | - Peter Brown
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, CT, USA
| | - Scott McIntyre
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, CT, USA
| | - Terence W. Nixon
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, CT, USA
| | - Robin A. de Graaf
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, CT, USA
- Department of Biomedical Engineering, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, CT, USA
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28
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Lanz B, Abaei A, Braissant O, Choi IY, Cudalbu C, Henry PG, Gruetter R, Kara F, Kantarci K, Lee P, Lutz NW, Marjańska M, Mlynárik V, Rasche V, Xin L, Valette J. Magnetic resonance spectroscopy in the rodent brain: Experts' consensus recommendations. NMR IN BIOMEDICINE 2020; 34:e4325. [PMID: 33565219 PMCID: PMC9429976 DOI: 10.1002/nbm.4325] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Revised: 03/29/2020] [Accepted: 04/30/2020] [Indexed: 05/21/2023]
Abstract
In vivo MRS is a non-invasive measurement technique used not only in humans, but also in animal models using high-field magnets. MRS enables the measurement of metabolite concentrations as well as metabolic rates and their modifications in healthy animals and disease models. Such data open the way to a deeper understanding of the underlying biochemistry, related disturbances and mechanisms taking place during or prior to symptoms and tissue changes. In this work, we focus on the main preclinical 1H, 31P and 13C MRS approaches to study brain metabolism in rodent models, with the aim of providing general experts' consensus recommendations (animal models, anesthesia, data acquisition protocols). An overview of the main practical differences in preclinical compared with clinical MRS studies is presented, as well as the additional biochemical information that can be obtained in animal models in terms of metabolite concentrations and metabolic flux measurements. The properties of high-field preclinical MRS and the technical limitations are also described.
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Affiliation(s)
- Bernard Lanz
- Laboratory for Functional and Metabolic Imaging (LIFMET), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - Alireza Abaei
- Core Facility Small Animal Imaging, Ulm University, Ulm, Germany
| | - Olivier Braissant
- Service of Clinical Chemistry, University of Lausanne and University Hospital of Lausanne, Lausanne, Switzerland
| | - In-Young Choi
- Department of Neurology, University of Kansas Medical Center, Kansas City, Kansas, US
| | - Cristina Cudalbu
- Centre d'Imagerie Biomedicale (CIBM), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Pierre-Gilles Henry
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, US
| | - Rolf Gruetter
- Laboratory for Functional and Metabolic Imaging (LIFMET), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Firat Kara
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, US
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, US
| | - Phil Lee
- Department of Radiology, University of Kansas Medical Center, Kansas City, Kansas, US
| | - Norbert W Lutz
- CNRS, CRMBM, Aix-Marseille University, Marseille, France
| | - Małgorzata Marjańska
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, US
| | - Vladimír Mlynárik
- High Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Volker Rasche
- Core Facility Small Animal Imaging, Ulm University, Ulm, Germany
| | - Lijing Xin
- Centre d'Imagerie Biomedicale (CIBM), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Julien Valette
- Commissariat à l'Energie Atomique et aux Energies Alternatives, MIRCen, Fontenay-aux-Roses, France
- Neurodegenerative Diseases Laboratory, Centre National de la Recherche Scientifique, Université Paris-Sud, Université Paris-Saclay, UMR 9199, Fontenay-aux-Roses, France
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