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Blömer S, Hingerl L, Marjańska M, Bogner W, Motyka S, Hangel G, Klauser A, Andronesi OC, Strasser B. Proton-free induction decay MRSI at 7 T in the human brain using an egg-shaped modified rosette K-space trajectory. Magn Reson Med 2025; 93:1443-1457. [PMID: 39568225 PMCID: PMC11782714 DOI: 10.1002/mrm.30368] [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: 03/15/2024] [Revised: 09/26/2024] [Accepted: 10/20/2024] [Indexed: 11/22/2024]
Abstract
PURPOSE Proton (1H)-MRSI via spatial-spectral encoding poses high demands on gradient hardware at ultra-high fields and high-resolutions. Rosette trajectories help alleviate these problems, but at reduced SNR-efficiency because of their k-space densities not matching any desired k-space filter. We propose modified rosette trajectories, which more closely match a Hamming filter, and thereby improve SNR performance while still staying within gradient hardware limitations and without prolonging scan time. METHODS Analytical and synthetic simulations were validated with phantom and in vivo measurements at 7 T. The rosette and modified rosette trajectories were measured in five healthy volunteers in 6 min in a 2D slice in the brain. An elliptical phase-encoding sequence was measured in one volunteer in 22 min, and a 3D sequence was measured in one volunteer within 19 min. The SNR per-unit-time, linewidth, Cramer-Rao lower bounds (CRLBs), lipid contamination, and data quality of the proposed modified rosette trajectory were compared to the rosette trajectory. RESULTS Using the modified rosette trajectories, an improved k-space weighting function was achieved resulting in an SNR per-unit-time increase of up to 12% compared to rosette's and 23% compared to elliptical phase-encoding, dependent on the two additional trajectory parameters. Similar results were achieved for the theoretical SNR calculation based on k-space densities, as well as when using the pseudo-replica method for simulated, in vivo, and phantom data. The CRLBs of γ-aminobutyric acid and N-acetylaspartylglutamate improved non-significantly for the modified rosette trajectory, whereas the linewidths and lipid contamination remained similar. CONCLUSION By optimizing the shape of the rosette trajectory, the modified rosette trajectories achieved higher SNR per-unit-time and enhanced data quality at the same scan time.
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Affiliation(s)
- Simon Blömer
- German Center for Neurodegenerative Diseases (DZNE)
BonnGermany
| | - Lukas Hingerl
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University ViennaViennaAustria
| | - Małgorzata Marjańska
- Center for Magnetic Resonance Research, Department of RadiologyUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Wolfgang Bogner
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University ViennaViennaAustria
- Christian Doppler Laboratory for Clinical Molecular MR ImagingMedical University ViennaViennaAustria
| | - Stanislav Motyka
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University ViennaViennaAustria
- Christian Doppler Laboratory for Clinical Molecular MR ImagingMedical University ViennaViennaAustria
| | - Gilbert Hangel
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University ViennaViennaAustria
- Department of NeurosurgeryMedical University of ViennaViennaAustria
| | - Antoine Klauser
- Advanced Clinical Imaging TechnologySiemens Healthcare AGLausanneSwitzerland
| | - Ovidiu C. Andronesi
- A. A. Martinos Center for Biomedical Imaging, Department of RadiologyMassachusetts General HospitalCharlestownMassachusettsUSA
- Harvard Medical SchoolBostonMassachusettsUSA
| | - Bernhard Strasser
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University ViennaViennaAustria
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2
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de Graaf RA, Thomas M, De Feyter HM. Parallel detection of MRI and 1H MRSI for multi-contrast anatomical and metabolic imaging. Magn Reson Med 2025. [PMID: 40079484 DOI: 10.1002/mrm.30501] [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: 12/16/2024] [Revised: 02/25/2025] [Accepted: 02/25/2025] [Indexed: 03/15/2025]
Abstract
PURPOSE MRI and MRSI provide unique and complementary information on anatomy, structure, function, and metabolism. The default strategy for a combined MRI and MRSI study is a sequential acquisition of both modalities, leading to long scan times. As MRI and MRSI primarily detect water and metabolites, respectively, the small frequency difference between resonances can be exploited with frequency-selective RF pulses to achieve interleaved or parallel detection of MRI and MRSI, without an increase in total scan time. METHODS Here, we describe the pulse sequence modifications necessary to allow acquisition of T1 and T2-weighted MRI and B0/B1 mapping in parallel with MRSI. In general, the MRSI module, including water suppression, can be used unmodified. MRI methods are executed in 3D using 3- to 4-ms frequency-selective Gaussian RF pulses with acceleration along the third dimension through repetitive small-angle nutation or multi-spin-echo acquisitions. RESULTS Phantom experiments demonstrated artifact-free 3D MRIs. MRSIs in the absence or presence of MRI elements were identical in sensitivity and spectral resolution (line width) and showed consistent water suppression. Parallel MRI-MRSI was applied to the brains of tumor-bearing rats in vivo. High-contrast, high-sensitivity metabolic MRSI data at 8 μL nominal resolution was acquired in parallel with 3D T1-weighted, T2-weighted, and B0/B1-weighted MRIs for an overall scan duration of 30 min. CONCLUSION Multi-contrast MRIs and MRSI can be acquired in parallel by utilizing the small frequency difference between water and metabolites. This opens the possibility for shorter overall scans times, or the acquisition of higher-resolution or additional contrast MRIs.
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Affiliation(s)
- Robin A de Graaf
- Magnetic Resonance Research Center (MRRC), Department of Radiology and Biomedical Imaging, Yale University, New Haven, Connecticut, USA
- Magnetic Resonance Research Center (MRRC), Department of Biomedical Engineering, Yale University, New Haven, Connecticut, USA
| | - Monique Thomas
- Magnetic Resonance Research Center (MRRC), Department of Radiology and Biomedical Imaging, Yale University, New Haven, Connecticut, USA
| | - Henk M De Feyter
- Magnetic Resonance Research Center (MRRC), Department of Radiology and Biomedical Imaging, Yale University, New Haven, Connecticut, USA
- Magnetic Resonance Research Center (MRRC), Department of Biomedical Engineering, Yale University, New Haven, Connecticut, USA
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Huang Z, Emir U, Döring A, Klauser A, Xiao Y, Widmaier M, Xin L. Rosette Spectroscopic Imaging for Whole-Brain Slab Metabolite Mapping at 7T: Acceleration Potential and Reproducibility. Hum Brain Mapp 2025; 46:e70176. [PMID: 40056040 PMCID: PMC11889463 DOI: 10.1002/hbm.70176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2024] [Revised: 01/25/2025] [Accepted: 02/12/2025] [Indexed: 03/14/2025] Open
Abstract
Whole-brain proton magnetic resonance spectroscopic imaging (1H-MRSI) is a non-invasive technique for assessing neurochemical distribution in the brain, offering valuable insights into brain functions and neural diseases. It greatly benefits from the improved SNR at ultrahigh field strengths (≥ 7T). However, 1H-MRSI still faces several challenges, such as long acquisition time and severe signal contamination from water and lipids. In this study, 2D and 3D short TR/TE 1H-FID-MRSI sequences using rosette trajectories were developed with nominal spatial resolutions of 4.48 × 4.48 mm2 and 4.48 × 4.48 × 4.50 mm3, respectively. Water signals were suppressed using an optimized Five-variable-Angle-gaussian-pulses-with-ShorT-total-duration (FAST) water suppression scheme of 76 ms, and lipid signals were removed using the L2 regularization method. Metabolic maps of major 1H metabolites were obtained in 5:40 min with 16 averages and 1 average for the 2D and 3D acquisitions, respectively. Excellent intra-session reproducibility was shown, with the coefficients of variance (CV) being lower than 6% for N-Acetyl-L-aspartic acid (NAA), Glutamate (Glu), total Choline (tCho), Creatine and Phosphocreatine (tCr), and Glycine and Myo-inositol (Gly + Ins). To explore the potential of further acceleration, compressed sensing was applied retrospectively to the 3D datasets. The structural similarity index (SSIM) remained above 0.85 and 0.8 until R = 2 and 3 for the metabolite maps of Glu, NAA, tCr, and tCho, indicating the possibility for further reduction of acquisition time to around 2 min.
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Affiliation(s)
- Zhiwei Huang
- CIBM Center for Biomedical ImagingLausanneSwitzerland
- Animal Imaging and Technology, Ecole Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland
| | - Uzay Emir
- Department of RadiologyUniversity of North Carolina at Chapell HillChapell HillNorth CarolinaUSA
- Biomedical Research Imaging Center (BRIC), University of North Carolina at Chapell HillChapell HillNorth CarolinaUSA
- Joint Department of Biomedical EngineeringUniversity of North Carolina at Chapell HillChapell HillNorth CarolinaUSA
| | - André Döring
- CIBM Center for Biomedical ImagingLausanneSwitzerland
- Animal Imaging and Technology, Ecole Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland
| | - Antoine Klauser
- Advanced Clinical Imaging Technology, Siemens Healthineers International AGLausanneSwitzerland
| | - Ying Xiao
- CIBM Center for Biomedical ImagingLausanneSwitzerland
- Animal Imaging and Technology, Ecole Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland
- Institute of Physics (IPHYS), Ecole Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland
| | - Mark Widmaier
- CIBM Center for Biomedical ImagingLausanneSwitzerland
- Animal Imaging and Technology, Ecole Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland
- Institute of Physics (IPHYS), Ecole Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland
| | - Lijing Xin
- CIBM Center for Biomedical ImagingLausanneSwitzerland
- Animal Imaging and Technology, Ecole Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland
- Institute of Physics (IPHYS), Ecole Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland
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Karkouri J, Rodgers CT. Sequence building block for magnetic resonance spectroscopy on Siemens VE-series scanners. NMR IN BIOMEDICINE 2024; 37:e5165. [PMID: 38807311 DOI: 10.1002/nbm.5165] [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: 09/11/2023] [Revised: 03/19/2024] [Accepted: 03/28/2024] [Indexed: 05/30/2024]
Abstract
We present a sequence building block (SBB) that embeds magnetic resonance spectroscopy (MRS) into another sequence on the Siemens VE platform without any custom hardware. This enables dynamic studies such as functional MRS (fMRS), dynamic shimming and frequency correction, and acquisition of navigator images for motion correction. The SBB supports nonlocalised spectroscopy (free induction decay), STimulated Echo Acquisition Mode single voxel spectroscopy, and 1D, 2D and 3D phase-encoded chemical shift imaging. It can embed 1H or X-nuclear MRS into a 1H sequence; and 1H-MRS into an X-nuclear sequence. We demonstrate integration into the vendor's gradient-recalled echo sequence. We acquire test data in phantoms with three coils (31P/1H, 13C/1H and 2H/1H) and in two volunteers on a 7-T Terra MRI scanner. Fifteen lines of code are required to insert the SBB into a sequence. Spectra and images are acquired successfully in all cases in phantoms, and in human abdomen and calf muscle. Phantom comparison of signal-to-noise ratio and linewidth showed that the SBB has negligible effects on image and spectral quality, except that it sometimes produces a nuclear Overhauser effect (NOE) signal enhancement for multinuclear applications in line with conventional 1H NOE pulses. Our new SBB embeds MRS into a host imaging or spectroscopy sequence in 15 lines of code. It allows homonuclear and heteronuclear interleaving. The package is available through the standard C2P procedure. We hope this will lower the barrier for entry to studies applying dynamic fMRS and for online motion correction and B0-shim updating.
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Affiliation(s)
- Jabrane Karkouri
- Wolfson Brain Imaging Center, University of Cambridge, Cambridge, UK
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Wampl S, Körner T, Meyerspeer M, Zaitsev M, Wolf M, Trattnig S, Wolzt M, Bogner W, Schmid AI. A modular motion compensation pipeline for prospective respiratory motion correction of multi-nuclear MR spectroscopy. Sci Rep 2024; 14:10781. [PMID: 38734781 PMCID: PMC11088657 DOI: 10.1038/s41598-024-61403-w] [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: 11/10/2023] [Accepted: 05/06/2024] [Indexed: 05/13/2024] Open
Abstract
Magnetic resonance (MR) acquisitions of the torso are frequently affected by respiratory motion with detrimental effects on signal quality. The motion of organs inside the body is typically decoupled from surface motion and is best captured using rapid MR imaging (MRI). We propose a pipeline for prospective motion correction of the target organ using MR image navigators providing absolute motion estimates in millimeters. Our method is designed to feature multi-nuclear interleaving for non-proton MR acquisitions and to tolerate local transmit coils with inhomogeneous field and sensitivity distributions. OpenCV object tracking was introduced for rapid estimation of in-plane displacements in 2D MR images. A full three-dimensional translation vector was derived by combining displacements from slices of multiple and arbitrary orientations. The pipeline was implemented on 3 T and 7 T MR scanners and tested in phantoms and volunteers. Fast motion handling was achieved with low-resolution 2D MR image navigators and direct implementation of OpenCV into the MR scanner's reconstruction pipeline. Motion-phantom measurements demonstrate high tracking precision and accuracy with minor processing latency. The feasibility of the pipeline for reliable in-vivo motion extraction was shown on heart and kidney data. Organ motion was manually assessed by independent operators to quantify tracking performance. Object tracking performed convincingly on 7774 navigator images from phantom scans and different organs in volunteers. In particular the kernelized correlation filter (KCF) achieved similar accuracy (74%) as scored from inter-operator comparison (82%) while processing at a rate of over 100 frames per second. We conclude that fast 2D MR navigator images and computer vision object tracking can be used for accurate and rapid prospective motion correction. This and the modular structure of the pipeline allows for the proposed method to be used in imaging of moving organs and in challenging applications like cardiac magnetic resonance spectroscopy (MRS) or magnetic resonance imaging (MRI) guided radiotherapy.
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Affiliation(s)
- Stefan Wampl
- High Field MR Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Tito Körner
- High Field MR Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Martin Meyerspeer
- High Field MR Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Maxim Zaitsev
- Division of Medical Physics, Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Freiburg, Germany
| | - Marcos Wolf
- High Field MR Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Siegfried Trattnig
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Michael Wolzt
- Department of Clinical Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Albrecht Ingo Schmid
- High Field MR Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria.
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Motyka S, Weiser P, Bachrata B, Hingerl L, Strasser B, Hangel G, Niess E, Niess F, Zaitsev M, Robinson SD, Langs G, Trattnig S, Bogner W. Predicting dynamic, motion-related changes in B 0 field in the brain at a 7T MRI using a subject-specific fine-trained U-net. Magn Reson Med 2024; 91:2044-2056. [PMID: 38193276 DOI: 10.1002/mrm.29980] [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: 08/04/2023] [Revised: 11/28/2023] [Accepted: 11/30/2023] [Indexed: 01/10/2024]
Abstract
PURPOSE Subject movement during the MR examination is inevitable and causes not only image artifacts but also deteriorates the homogeneity of the main magnetic field (B0 ), which is a prerequisite for high quality data. Thus, characterization of changes to B0 , for example induced by patient movement, is important for MR applications that are prone to B0 inhomogeneities. METHODS We propose a deep learning based method to predict such changes within the brain from the change of the head position to facilitate retrospective or even real-time correction. A 3D U-net was trained on in vivo gradient-echo brain 7T MRI data. The input consisted of B0 maps and anatomical images at an initial position, and anatomical images at a different head position (obtained by applying a rigid-body transformation on the initial anatomical image). The output consisted of B0 maps at the new head positions. We further fine-trained the network weights to each subject by measuring a limited number of head positions of the given subject, and trained the U-net with these data. RESULTS Our approach was compared to established dynamic B0 field mapping via interleaved navigators, which suffer from limited spatial resolution and the need for undesirable sequence modifications. Qualitative and quantitative comparison showed similar performance between an interleaved navigator-equivalent method and proposed method. CONCLUSION It is feasible to predict B0 maps from rigid subject movement and, when combined with external tracking hardware, this information could be used to improve the quality of MR acquisitions without the use of navigators.
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Affiliation(s)
- Stanislav Motyka
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
- Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria
| | - Paul Weiser
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Beata Bachrata
- Department of Medical Engineering, Carinthia University of Applied Sciences, Klagenfurt, Austria
| | - Lukas Hingerl
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Bernhard Strasser
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Gilbert Hangel
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
- Department of Neurosurgery, Medical University of Vienna, Vienna, Austria
| | - Eva Niess
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
- Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria
| | - Fabian Niess
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Maxim Zaitsev
- Department of Radiology - Medical Physics, University of Freiburg, Freiburg, Germany
- Faculty of Medicine, University of Freiburg - Medical Centre, Freiburg, Germany
| | - Simon Daniel Robinson
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Georg Langs
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Siegfried Trattnig
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
- Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria
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Hewlett M, Oran O, Liu J, Drangova M. Prospective motion correction for brain MRI using spherical navigators. Magn Reson Med 2024; 91:1528-1540. [PMID: 38174443 DOI: 10.1002/mrm.29961] [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: 08/25/2023] [Revised: 10/24/2023] [Accepted: 11/20/2023] [Indexed: 01/05/2024]
Abstract
PURPOSE To demonstrate for the first time the feasibility of performing prospective motion correction using spherical navigators (SNAVs). METHODS SNAVs were interleaved in a 3D FLASH sequence with an additional short baseline scan (6.8 s) for fast rotation estimation. Assessment of SNAV-based prospective motion correction was performed in six volunteers. Participant motion was guided using randomly generated stepwise prompts as well as prompts derived from real motion cases. Experiments were performed on a 3 T MRI scanner using a 32-channel head coil. RESULTS When optimized for real-time application, SNAV-based motion estimates were computed in 25.8 ± 1.3 ms. Phantom-based quantification of rotation and translation accuracy indicated mean absolute errors of 0.10 ± 0.09° and 0.25 ± 0.14 mm, respectively. Implementing SNAV-based motion estimates for prospective motion correction led to a clear improvement in image quality with minimal increase in scan time (<5%). CONCLUSION Optimization of SNAV processing for real-time application enables prospective motion correction with low latency and minimal scan time requirements.
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Affiliation(s)
- Miriam Hewlett
- Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada
- Department of Medical Biophysics, The University of Western Ontario, London, Ontario, Canada
| | - Omer Oran
- Siemens Healthcare Limited, Oakville, Ontario, Canada
| | - Junmin Liu
- Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada
| | - Maria Drangova
- Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada
- Department of Medical Biophysics, The University of Western Ontario, London, Ontario, Canada
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Blömer S, Hingerl L, Marjańska M, Bogner W, Motyka S, Hangel G, Klauser A, Andronesi OC, Strasser B. Proton Free Induction Decay MRSI at 7T in the Human Brain Using an Egg-Shaped Modified Rosette K-Space Trajectory. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.26.24304840. [PMID: 38645249 PMCID: PMC11027556 DOI: 10.1101/2024.03.26.24304840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Purpose 1.1 Proton ( 1 H)-MRSI via spatial-spectral encoding poses high demands on gradient hardware at ultra-high fields and high-resolutions. Rosette trajectories help alleviate these problems, but at reduced SNR-efficiency due to their k-space densities not matching any desired k-space filter. We propose modified rosette trajectories, which more closely match a Hamming filter, and thereby improve SNR performance while still staying within gradient hardware limitations and without prolonging scan time. Methods 1.2Analytical and synthetic simulations were validated with phantom and in vivo measurements at 7 T. The rosette and modified rosette trajectories were measured in five healthy volunteers in six minutes in a 2D slice in the brain. A 3D sequence was measured in one volunteer within 19 minutes. The SNR, linewidth, CRLBs, lipid contamination and data quality of the proposed modified rosette trajectory were compared to the rosette trajectory. Results 1.3Using the modified rosette trajectories, an improved k-space weighting function was achieved resulting in an increase of up to 12% in SNR compared to rosette's dependent on the two additional trajectory parameters. Similar results were achieved for the theoretical SNR calculation based on k-space densities, as well as when using the pseudo-replica method for simulated, in-vivo and phantom data. The CRLBs improved slightly, but non-significantly for the modified rosette trajectories, while the linewidths and lipid contamination remained similar. Conclusion 1.4By improving the rosette trajectory's shape, modified rosette trajectories achieved higher SNR at the same scan time and data quality.
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Robinson SD, Bachrata B, Eckstein K, Bollmann S, Bollmann S, Hodono S, Cloos M, Tourell M, Jin J, O'Brien K, Reutens DC, Trattnig S, Enzinger C, Barth M. Improved dynamic distortion correction for fMRI using single-echo EPI and a readout-reversed first image (REFILL). Hum Brain Mapp 2023; 44:5095-5112. [PMID: 37548414 PMCID: PMC10502646 DOI: 10.1002/hbm.26440] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 06/01/2023] [Accepted: 07/12/2023] [Indexed: 08/08/2023] Open
Abstract
The boundaries between tissues with different magnetic susceptibilities generate inhomogeneities in the main magnetic field which change over time due to motion, respiration and system instabilities. The dynamically changing field can be measured from the phase of the fMRI data and corrected. However, methods for doing so need multi-echo data, time-consuming reference scans and/or involve error-prone processing steps, such as phase unwrapping, which are difficult to implement robustly on the MRI host. The improved dynamic distortion correction method we propose is based on the phase of the single-echo EPI data acquired for fMRI, phase offsets calculated from a triple-echo, bipolar reference scan of circa 3-10 s duration using a method which avoids the need for phase unwrapping and an additional correction derived from one EPI volume in which the readout direction is reversed. This Reverse-Encoded First Image and Low resoLution reference scan (REFILL) approach is shown to accurately measure B0 as it changes due to shim, motion and respiration, even with large dynamic changes to the field at 7 T, where it led to a > 20% increase in time-series signal to noise ratio compared to data corrected with the classic static approach. fMRI results from REFILL-corrected data were free of stimulus-correlated distortion artefacts seen when data were corrected with static field mapping. The method is insensitive to shim changes and eddy current differences between the reference scan and the fMRI time series, and employs calculation steps that are simple and robust, allowing most data processing to be performed in real time on the scanner image reconstruction computer. These improvements make it feasible to routinely perform dynamic distortion correction in fMRI.
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Affiliation(s)
- Simon Daniel Robinson
- Centre of Advanced ImagingUniversity of QueenslandBrisbaneAustralia
- Department of NeurologyMedical University of GrazGrazAustria
- High Field MR Centre, Department of Biomedical Imaging and Image‐Guided TherapyMedical University of ViennaViennaAustria
- Karl Landsteiner Institute for Clinical Molecular MR in Musculoskeletal ImagingViennaAustria
| | - Beata Bachrata
- High Field MR Centre, Department of Biomedical Imaging and Image‐Guided TherapyMedical University of ViennaViennaAustria
- Karl Landsteiner Institute for Clinical Molecular MR in Musculoskeletal ImagingViennaAustria
- Department of Medical EngineeringCarinthia University of Applied SciencesKlagenfurtAustria
| | - Korbinian Eckstein
- High Field MR Centre, Department of Biomedical Imaging and Image‐Guided TherapyMedical University of ViennaViennaAustria
| | - Saskia Bollmann
- Centre of Advanced ImagingUniversity of QueenslandBrisbaneAustralia
| | - Steffen Bollmann
- School of Information Technology and Electrical EngineeringThe University of QueenslandBrisbaneAustralia
| | - Shota Hodono
- Centre of Advanced ImagingUniversity of QueenslandBrisbaneAustralia
- ARC Training Centre for Innovation in Biomedical Imaging Technology (CIBIT)The University of QueenslandBrisbaneAustralia
| | - Martijn Cloos
- Centre of Advanced ImagingUniversity of QueenslandBrisbaneAustralia
- ARC Training Centre for Innovation in Biomedical Imaging Technology (CIBIT)The University of QueenslandBrisbaneAustralia
| | - Monique Tourell
- Centre of Advanced ImagingUniversity of QueenslandBrisbaneAustralia
- Siemens Healthcare Pty Ltd.BrisbaneAustralia
| | - Jin Jin
- Siemens Healthcare Pty Ltd.BrisbaneAustralia
| | | | - David C. Reutens
- Centre of Advanced ImagingUniversity of QueenslandBrisbaneAustralia
- ARC Training Centre for Innovation in Biomedical Imaging Technology (CIBIT)The University of QueenslandBrisbaneAustralia
| | - Siegfried Trattnig
- High Field MR Centre, Department of Biomedical Imaging and Image‐Guided TherapyMedical University of ViennaViennaAustria
| | | | - Markus Barth
- Centre of Advanced ImagingUniversity of QueenslandBrisbaneAustralia
- School of Information Technology and Electrical EngineeringThe University of QueenslandBrisbaneAustralia
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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: 6] [Impact Index Per Article: 3.0] [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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Niess F, Hingerl L, Strasser B, Bednarik P, Goranovic D, Niess E, Hangel G, Krššák M, Spurny-Dworak B, Scherer T, Lanzenberger R, Bogner W. Noninvasive 3-Dimensional 1 H-Magnetic Resonance Spectroscopic Imaging of Human Brain Glucose and Neurotransmitter Metabolism Using Deuterium Labeling at 3T : Feasibility and Interscanner Reproducibility. Invest Radiol 2023; 58:431-437. [PMID: 36735486 PMCID: PMC10184811 DOI: 10.1097/rli.0000000000000953] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 12/15/2022] [Indexed: 02/04/2023]
Abstract
OBJECTIVES Noninvasive, affordable, and reliable mapping of brain glucose metabolism is of critical interest for clinical research and routine application as metabolic impairment is linked to numerous pathologies, for example, cancer, dementia, and depression. A novel approach to map glucose metabolism noninvasively in the human brain has been presented recently on ultrahigh-field magnetic resonance (MR) scanners (≥7T) using indirect detection of deuterium-labeled glucose and downstream metabolites such as glutamate, glutamine, and lactate. The aim of this study was to demonstrate the feasibility to noninvasively detect deuterium-labeled downstream glucose metabolites indirectly in the human brain via 3-dimensional (3D) proton ( 1 H) MR spectroscopic imaging on a clinical 3T MR scanner without additional hardware. MATERIALS AND METHODS This prospective, institutional review board-approved study was performed in 7 healthy volunteers (mean age, 31 ± 4 years, 5 men/2 women) after obtaining written informed consent. After overnight fasting and oral deuterium-labeled glucose administration, 3D metabolic maps were acquired every ∼4 minutes with ∼0.24 mL isotropic spatial resolution using real-time motion-, shim-, and frequency-corrected echo-less 3D 1 H-MR spectroscopic Imaging on a clinical routine 3T MR system. To test the interscanner reproducibility of the method, subjects were remeasured on a similar 3T MR system. Time courses were analyzed using linear regression and nonparametric statistical tests. Deuterium-labeled glucose and downstream metabolites were detected indirectly via their respective signal decrease in dynamic 1 H MR spectra due to exchange of labeled and unlabeled molecules. RESULTS Sixty-five minutes after deuterium-labeled glucose administration, glutamate + glutamine (Glx) signal intensities decreased in gray/white matter (GM/WM) by -1.63 ± 0.3/-1.0 ± 0.3 mM (-13% ± 3%, P = 0.02/-11% ± 3%, P = 0.02), respectively. A moderate to strong negative correlation between Glx and time was observed in GM/WM ( r = -0.64, P < 0.001/ r = -0.54, P < 0.001), with 60% ± 18% ( P = 0.02) steeper slopes in GM versus WM, indicating faster metabolic activity. Other nonlabeled metabolites showed no significant changes. Excellent intrasubject repeatability was observed across scanners for static results at the beginning of the measurement (coefficient of variation 4% ± 4%), whereas differences were observed in individual Glx dynamics, presumably owing to physiological variation of glucose metabolism. CONCLUSION Our approach translates deuterium metabolic imaging to widely available clinical routine MR scanners without specialized hardware, offering a safe, affordable, and versatile (other substances than glucose can be labeled) approach for noninvasive imaging of glucose and neurotransmitter metabolism in the human brain.
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Affiliation(s)
- Fabian Niess
- From the High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Lukas Hingerl
- From the High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Bernhard Strasser
- From the High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Petr Bednarik
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, University Hospital Amager and Hvidovre, Hvidovre, Denmark
- Department of Radiology, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark
| | - Dario Goranovic
- From the High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Eva Niess
- From the High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Gilbert Hangel
- From the High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
- Department of Neurosurgery
| | - Martin Krššák
- Department of Medicine III, Division of Endocrinology and Metabolism
| | - Benjamin Spurny-Dworak
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria
| | - Thomas Scherer
- Department of Medicine III, Division of Endocrinology and Metabolism
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria
| | - Wolfgang Bogner
- From the High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
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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 ( 2 H) and indirect ( 1 H) detection of deuterium labeled compounds at 7T and clinical 3T. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.17.23288672. [PMID: 37131634 PMCID: PMC10153308 DOI: 10.1101/2023.04.17.23288672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
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'- 2 H 2 ]-glucose, its uptake and synthesis of downstream metabolites can be mapped via direct or indirect detection of deuterium resonances using 2 H MRSI (DMI) and 1 H 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 (4m/1f) were scanned in repeated sessions for 60 min after overnight fasting and 0.8g/kg oral [6,6'- 2 H 2 ]-glucose administration using time-resolved 3D 2 H FID-MRSI with elliptical phase encoding at 7T and 3D 1 H FID-MRSI with a non-Cartesian concentric ring trajectory readout at clinical 3T. Results One hour after oral tracer administration regionally averaged deuterium labeled Glx 4 concentrations and the dynamics were not significantly different over all participants between 7T 2 H DMI and 3T 1 H 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 Glc 6 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 2 H and 1 H data points a weak to moderate negative correlation was observed for Glx 4 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 Glc 6 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 1 H 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 2 H 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
| | - Bernhard Strasser
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna
| | - Lukas Hingerl
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna
| | - Eva Niess
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna
- Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK)
| | - Stanislav Motyka
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna
- Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK)
| | - Gilbert Hangel
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna
- Department of Neurosurgery, Medical University of Vienna
| | - Martin Krššák
- Department of Medicine III, Division of Endocrinology and Metabolism, Medical University of Vienna
| | - Stephan Gruber
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna
- Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK)
| | - Benjamin Spurny-Dworak
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna
| | - Siegfried Trattnig
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna
- Institute for Clinical Molecular MRI, Karl Landsteiner Society, 3100 St. Pölten, Austria
| | - Thomas Scherer
- Department of Medicine III, Division of Endocrinology and Metabolism, Medical University of Vienna
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna
- Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK)
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Spurny-Dworak B, Reed MB, Handschuh P, Vanicek T, Spies M, Bogner W, Lanzenberger R. The influence of season on glutamate and GABA levels in the healthy human brain investigated by magnetic resonance spectroscopy imaging. Hum Brain Mapp 2023; 44:2654-2663. [PMID: 36840505 PMCID: PMC10028653 DOI: 10.1002/hbm.26236] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 01/22/2023] [Accepted: 02/02/2023] [Indexed: 02/26/2023] Open
Abstract
Seasonal changes in neurotransmitter systems have been demonstrated in imaging studies and are especially noticeable in diseased states such as seasonal affective disorder (SAD). These modulatory neurotransmitters, such as serotonin, are influencing glutamatergic and GABAergic neurotransmission. Furthermore, central components of the circadian pacemaker are regulated by GABA (the suprachiasmatic nucleus) or glutamate (e.g., the retinohypothalamic tract). Therefore, we explored seasonal differences in the GABAergic and glutamatergic system in 159 healthy individuals using magnetic resonance spectroscopy imaging with a GABA-edited 3D-MEGA-LASER sequence at 3T. We quantified GABA+/tCr, GABA+/Glx, and Glx/tCr ratios (GABA+, GABA+ macromolecules; Glx, glutamate + glutamine; tCr, total creatine) in five different subcortical brain regions. Differences between time periods throughout the year, seasonal patterns, and stationarity were tested using ANCOVA models, curve fitting approaches, and unit root and stationarity tests, respectively. Finally, Spearman correlation analyses between neurotransmitter ratios within each brain region and cumulated daylight and global radiation were performed. No seasonal or monthly differences, seasonal patterns, nor significant correlations could be shown in any region or ratio. Unit root and stationarity tests showed stable patterns of GABA+/tCr, GABA+/Glx, and Glx/tCr levels throughout the year, except for hippocampal Glx/tCr. Our results indicate that neurotransmitter levels of glutamate and GABA in healthy individuals are stable throughout the year. Hence, despite the important correction for age and gender in the analyses of MRS derived GABA and glutamate, a correction for seasonality in future studies does not seem necessary. Future investigations in SAD and other psychiatric patients will be of high interest.
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Affiliation(s)
- B Spurny-Dworak
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria
| | - M B Reed
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria
| | - P Handschuh
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria
| | - T Vanicek
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria
| | - M Spies
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria
| | - W Bogner
- Department of Biomedical Imaging and Image-Guided Therapy, High Field MR Centre, Medical University of Vienna, Vienna, Austria
| | - R Lanzenberger
- Department of Psychiatry and Psychotherapy, Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria
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Lam F, Peng X, Liang ZP. High-Dimensional MR Spatiospectral Imaging by Integrating Physics-Based Modeling and Data-Driven Machine Learning: Current progress and future directions. IEEE SIGNAL PROCESSING MAGAZINE 2023; 40:101-115. [PMID: 37538148 PMCID: PMC10398845 DOI: 10.1109/msp.2022.3203867] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/05/2023]
Abstract
Magnetic resonance spectroscopic imaging (MRSI) offers a unique molecular window into the physiological and pathological processes in the human body. However, the applications of MRSI have been limited by a number of long-standing technical challenges due to high dimensionality and low signal-to-noise ratio (SNR). Recent technological developments integrating physics-based modeling and data-driven machine learning that exploit unique physical and mathematical properties of MRSI signals have demonstrated impressive performance in addressing these challenges for rapid, high-resolution, quantitative MRSI. This paper provides a systematic review of these progresses in the context of MRSI physics and offers perspectives on promising future directions.
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Affiliation(s)
- Fan Lam
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801 USA
- Beckman Institute for Advanced Science and Technology, Department of Electrical and Computer Engineering and Cancer Center at Illinois, University of Illinois Urbana-Champaign
| | - Xi Peng
- Department of Radiology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Zhi-Pei Liang
- Beckman Institute for Advanced Science and Technology, Department of Electrical and Computer Engineering and Cancer Center at Illinois, University of Illinois Urbana-Champaign
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Wallace TE, Kober T, Stockmann JP, Polimeni JR, Warfield SK, Afacan O. Real-time shimming with FID navigators. Magn Reson Med 2022; 88:2548-2563. [PMID: 36093989 PMCID: PMC9529812 DOI: 10.1002/mrm.29421] [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: 06/01/2022] [Revised: 07/22/2022] [Accepted: 08/02/2022] [Indexed: 11/12/2022]
Abstract
PURPOSE To implement a method for real-time field control using rapid FID navigator (FIDnav) measurements and evaluate the efficacy of the proposed approach for mitigating dynamic field perturbations and improvingT 2 * $$ {\mathrm{T}}_2^{\ast } $$ -weighted image quality. METHODS FIDnavs were embedded in a gradient echo sequence and a subject-specific linear calibration model was generated on the scanner to facilitate rapid shim updates in response to measured FIDnav signals. To confirm the accuracy of FID-navigated field updates, phantom and volunteer scans were performed with online updates of the scanner B0 shim settings. To evaluate improvement inT 2 * $$ {\mathrm{T}}_2^{\ast } $$ -weighted image quality with real-time shimming, 10 volunteers were scanned at 3T while performing deep-breathing and nose-touching tasks designed to modulate the B0 field. Quantitative image quality metrics were compared with and without FID-navigated field control. An additional volunteer was scanned at 7T to evaluate performance at ultra-high field. RESULTS Applying measured FIDnav shim updates successfully compensated for applied global and linear field offsets in phantoms and across all volunteers. FID-navigated real-time shimming led to a substantial reduction in field fluctuations and a consequent improvement inT 2 * $$ {\mathrm{T}}_2^{\ast } $$ -weighted image quality in volunteers performing deep-breathing and nose-touching tasks, with 7.57% ± 6.01% and 8.21% ± 10.90% improvement in peak SNR and structural similarity, respectively. CONCLUSION FIDnavs facilitate rapid measurement and application of field coefficients for slice-wise B0 shimming. The proposed approach can successfully counteract spatiotemporal field perturbations and substantially improvesT 2 * $$ {\mathrm{T}}_2^{\ast } $$ -weighted image quality, which is important for a variety of clinical and research applications, particularly at ultra-high field.
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Affiliation(s)
- Tess E Wallace
- Computational Radiology Laboratory, Department of Radiology, Boston Children’s Hospital, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Jason P Stockmann
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
| | - Jonathan R Polimeni
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
| | - Simon K Warfield
- Computational Radiology Laboratory, Department of Radiology, Boston Children’s Hospital, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
| | - Onur Afacan
- Computational Radiology Laboratory, Department of Radiology, Boston Children’s Hospital, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
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Lopez Kolkovsky AL, Carlier PG, Marty B, Meyerspeer M. Interleaved and simultaneous multi-nuclear magnetic resonance in vivo. Review of principles, applications and potential. NMR IN BIOMEDICINE 2022; 35:e4735. [PMID: 35352440 PMCID: PMC9542607 DOI: 10.1002/nbm.4735] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 03/03/2022] [Accepted: 03/28/2022] [Indexed: 06/14/2023]
Abstract
Magnetic resonance signals from different nuclei can be excited or received at the same time,rendering simultaneous or rapidly interleaved multi-nuclear acquisitions feasible. The advan-tages are a reduction of total scan time compared to sequential multi-nuclear acquisitions or that additional information from heteronuclear data is obtained at thesame time and anatomical position. Information content can be qualitatively increased by delivering a more comprehensive MR-based picture of a transient state (such as an exercise bout). Also, combiningnon-proton MR acquisitions with 1 Hinformation (e.g., dynamic shim updates and motion correction) can be used to improve data quality during long scans and benefits image coregistration. This work reviews the literature on interleaved and simultaneous multi-nuclear MRI and MRS in vivo. Prominent use cases for this methodology in clinical and research applications are brain and muscle, but studies have also been carried out in other targets, including the lung, knee, breast and heart. Simultaneous multi-nuclear measurements in the liver and kidney have also been performed, but exclusively in rodents. In this review, a consistent nomenclature is proposed, to help clarify the terminology used for this principle throughout the literature on in-vivo MR. An overview covers the basic principles, the technical requirements on the MR scanner and the implementations realised either by MR system vendors or research groups, from the early days until today. Considerations regarding the multi-tuned RF coils required and heteronuclear polarisation interactions are briefly discussed, and fields for future in-vivo applications for interleaved multi-nuclear MR pulse sequences are identified.
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Affiliation(s)
- Alfredo L. Lopez Kolkovsky
- NMR Laboratory, Neuromuscular Investigation CenterInstitute of MyologyParisFrance
- NMR laboratoryCEA, DRF, IBFJParisFrance
| | - Pierre G. Carlier
- NMR Laboratory, Neuromuscular Investigation CenterInstitute of MyologyParisFrance
- NMR laboratoryCEA, DRF, IBFJParisFrance
| | - Benjamin Marty
- NMR Laboratory, Neuromuscular Investigation CenterInstitute of MyologyParisFrance
- NMR laboratoryCEA, DRF, IBFJParisFrance
| | - Martin Meyerspeer
- High‐Field MR Center, Center for Medical Physics and Biomedical EngineeringMedical University of ViennaViennaAustria
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Strasser B, Arango NS, Stockmann JP, Gagoski B, Thapa B, Li X, Bogner W, Moser P, Small J, Cahill DP, Batchelor TT, Dietrich J, van der Kouwe A, White J, Adalsteinsson E, Andronesi OC. Improving D-2-hydroxyglutarate MR spectroscopic imaging in mutant isocitrate dehydrogenase glioma patients with multiplexed RF-receive/B 0 -shim array coils at 3 T. NMR IN BIOMEDICINE 2022; 35:e4621. [PMID: 34609036 PMCID: PMC8717863 DOI: 10.1002/nbm.4621] [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: 05/02/2021] [Revised: 08/27/2021] [Accepted: 08/30/2021] [Indexed: 06/13/2023]
Abstract
MR spectroscopic imaging (MRSI) noninvasively maps the metabolism of human brains. In particular, the imaging of D-2-hydroxyglutarate (2HG) produced by glioma isocitrate dehydrogenase (IDH) mutations has become a key application in neuro-oncology. However, the performance of full field-of-view MRSI is limited by B0 spatial nonuniformity and lipid artifacts from tissues surrounding the brain. Array coils that multiplex RF-receive and B0 -shim electrical currents (AC/DC mixing) over the same conductive loops provide many degrees of freedom to improve B0 uniformity and reduce lipid artifacts. AC/DC coils are highly efficient due to compact design, requiring low shim currents (<2 A) that can be switched fast (0.5 ms) with high interscan reproducibility (10% coefficient of variation for repeat measurements). We measured four tumor patients and five volunteers at 3 T and show that using AC/DC coils in addition to the vendor-provided second-order spherical harmonics shim provides 19% narrower spectral linewidth, 6% higher SNR, and 23% less lipid content for unrestricted field-of-view MRSI, compared with the vendor-provided shim alone. We demonstrate that improvement in MRSI data quality led to 2HG maps with higher contrast-to-noise ratio for tumors that coincide better with the FLAIR-enhancing lesions in mutant IDH glioma patients. Smaller Cramér-Rao lower bounds for 2HG quantification are obtained in tumors by AC/DC shim, corroborating with simulations that predicted improved accuracy and precision for narrower linewidths. AC/DC coils can be used synergistically with optimized acquisition schemes to improve metabolic imaging for precision oncology of glioma patients. Furthermore, this methodology has broad applicability to other neurological disorders and neuroscience.
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Affiliation(s)
- Bernhard Strasser
- A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Radiology, Boston, Massachusetts, USA
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Vienna, Austria
| | - Nicolas S. Arango
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Jason P. Stockmann
- A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Radiology, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Borjan Gagoski
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Boston, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Bijaya Thapa
- A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Radiology, Boston, Massachusetts, USA
| | - Xianqi Li
- A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Radiology, Boston, Massachusetts, USA
| | - Wolfgang Bogner
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Vienna, Austria
| | - Philipp Moser
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Vienna, Austria
| | - Julia Small
- Department of Neurosurgery, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Daniel P. Cahill
- Department of Neurosurgery, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Tracy T. Batchelor
- Department Neurology, Division of Neuro-Oncology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Jorg Dietrich
- Department Neurology, Division of Neuro-Oncology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Andre van der Kouwe
- A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Radiology, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Jacob White
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Elfar Adalsteinsson
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Ovidiu C. Andronesi
- A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Radiology, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
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18
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Thapa B, Mareyam A, Stockmann J, Strasser B, Keil B, Hoecht P, Carp S, Li X, Wang Z, Chang YV, Dietrich J, Uhlmann E, Cahill DP, Batchelor T, Wald L, Andronesi OC. In Vivo Absolute Metabolite Quantification Using a Multiplexed ERETIC-RX Array Coil for Whole-Brain MR Spectroscopic Imaging. J Magn Reson Imaging 2021; 56:121-133. [PMID: 34958166 DOI: 10.1002/jmri.28028] [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: 09/24/2021] [Revised: 12/01/2021] [Accepted: 12/03/2021] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND Absolute quantification of metabolites in MR spectroscopic imaging (MRSI) requires a stable reference signal of known concentration. The Electronic REference To access In vivo Concentrations (ERETIC) has shown great promise but has not been applied in patients and 3D MRSI. ERETIC hardware has not been integrated with receive arrays due to technical challenges, such as coil combination and unwanted coupling between multiple ERETIC and receive channels, for which we developed mitigation strategies. PURPOSE To develop absolute quantification for whole-brain MRSI in glioma patients. STUDY TYPE Prospective. POPULATION Five healthy volunteers and three patients with isocitrate dehydrogenase mutant glioma (27% female). Calibration and coil loading phantoms. FIELD STRENGTH/SEQUENCE A 3 T; Adiabatic spin-echo spiral 3D MRSI with real-time motion correction, Fluid Attenuated Inversion Recovery (FLAIR), Gradient Recalled Echo (GRE), Multi-echo Magnetization Prepared Rapid Acquisition of Gradient Echo (MEMPRAGE). ASSESSMENT Absolute quantification was performed for five brain metabolites (total N-acetyl-aspartate [NAA]/creatine/choline, glutamine + glutamate, myo-inositol) and the oncometabolite 2-hydroxyglutarate using a custom-built 4x-ERETIC/8x-receive array coil. Metabolite quantification was performed with both EREIC and internal water reference methods. ERETIC signal was transmitted via optical link and used to correct coil loading. Inductive and radiative coupling between ERETIC and receive channels were measured. STATISTICAL TESTS ERETIC and internal water methods for metabolite quantification were compared using Bland-Altman (BA) analysis and the nonparametric Mann-Whitney test. P < 0.05 was considered statistically significant. RESULTS ERETIC could be integrated in receive arrays and inductive coupling dominated (5-886 times) radiative coupling. Phantoms show proportional scaling of the ERETIC signal with coil loading. The BA analysis demonstrated very good agreement (3.3% ± 1.6%) in healthy volunteers, while there was a large difference (36.1% ± 3.8%) in glioma tumors between metabolite concentrations by ERETIC and internal water quantification. CONCLUSION Our results indicate that ERETIC integrated with receive arrays and whole-brain MRSI is feasible for brain metabolites quantification. Further validation is required to probe that ERETIC provides more accurate metabolite concentration in glioma patients. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Bijaya Thapa
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Azma Mareyam
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Jason Stockmann
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Bernhard Strasser
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Boris Keil
- Institute of Medical Physics and Radiation Protection, TH-Mittelhessen University of Applied Sciences (THM), Giessen, Germany
| | | | - Stefan Carp
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Xianqi Li
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Zhe Wang
- Siemens Medical Solutions USA, Boston, Massachusetts, USA
| | - Yulin V Chang
- Siemens Medical Solutions USA, Boston, Massachusetts, USA
| | - Jorg Dietrich
- Harvard Medical School, Boston, Massachusetts, USA.,Division of Neuro-Oncology, Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Erik Uhlmann
- Harvard Medical School, Boston, Massachusetts, USA.,Department of Neurology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - Daniel P Cahill
- Harvard Medical School, Boston, Massachusetts, USA.,Department of Neurosurgery, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Tracy Batchelor
- Harvard Medical School, Boston, Massachusetts, USA.,Department of Neurology, Brigham's and Women Hospital, Boston, Massachusetts, USA.,Dana Farber Cancer Institute, Boston, Massachusetts, USA
| | - Lawrence Wald
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Ovidiu C Andronesi
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
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19
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Hangel G, Spurny‐Dworak B, Lazen P, Cadrien C, Sharma S, Hingerl L, Hečková E, Strasser B, Motyka S, Lipka A, Gruber S, Brandner C, Lanzenberger R, Rössler K, Trattnig S, Bogner W. Inter-subject stability and regional concentration estimates of 3D-FID-MRSI in the human brain at 7 T. NMR IN BIOMEDICINE 2021; 34:e4596. [PMID: 34382280 PMCID: PMC11475238 DOI: 10.1002/nbm.4596] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 07/14/2021] [Accepted: 07/14/2021] [Indexed: 05/13/2023]
Abstract
PURPOSE Recently, a 3D-concentric ring trajectory (CRT)-based free induction decay (FID)-MRSI sequence was introduced for fast high-resolution metabolic imaging at 7 T. This technique provides metabolic ratio maps of almost the entire brain within clinically feasible scan times, but its robustness has not yet been thoroughly investigated. Therefore, we have assessed quantitative concentration estimates and their variability in healthy volunteers using this approach. METHODS We acquired whole-brain 3D-CRT-FID-MRSI at 7 T in 15 min with 3.4 mm nominal isometric resolution in 24 volunteers (12 male, 12 female, mean age 27 ± 6 years). Concentration estimate maps were calculated for 15 metabolites using internal water referencing and evaluated in 55 different regions of interest (ROIs) in the brain. Data quality, mean metabolite concentrations, and their inter-subject coefficients of variation (CVs) were compared for all ROIs. RESULTS Of 24 datasets, one was excluded due to motion artifacts. The concentrations of total choline, total creatine, glutamate, myo-inositol, and N-acetylaspartate in 44 regions were estimated within quality thresholds. Inter-subject CVs (mean over 44 ROIs/minimum/maximum) were 9%/5%/19% for total choline, 10%/6%/20% for total creatine, 11%/7%/24% for glutamate, 10%/6%/19% for myo-inositol, and 9%/6%/19% for N-acetylaspartate. DISCUSSION We defined the performance of 3D-CRT-based FID-MRSI for metabolite concentration estimate mapping, showing which metabolites could be robustly quantified in which ROIs with which inter-subject CVs expected. However, the basal brain regions and lesser-signal metabolites in particular remain as a challenge due susceptibility effects from the proximity to nasal and auditory cavities. Further improvement in quantification and the mitigation of B0 /B1 -field inhomogeneities will be necessary to achieve reliable whole-brain coverage.
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Affiliation(s)
- Gilbert Hangel
- High‐field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Department of NeurosurgeryMedical University of ViennaViennaAustria
| | - Benjamin Spurny‐Dworak
- Division of General Psychiatry, Department of Psychiatry and PsychotherapyMedical University of ViennaViennaAustria
| | - Philipp Lazen
- High‐field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Cornelius Cadrien
- High‐field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Department of NeurosurgeryMedical University of ViennaViennaAustria
| | - Sukrit Sharma
- High‐field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Lukas Hingerl
- High‐field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Eva Hečková
- High‐field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Bernhard Strasser
- High‐field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Stanislav Motyka
- High‐field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Alexandra Lipka
- High‐field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Institute for Clinical Molecular MRIKarl Landsteiner SocietySt. PöltenAustria
| | - Stephan Gruber
- High‐field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Christoph Brandner
- High‐field MR Center, Center for Medical Physics and Biomedical EngineeringMedical University of ViennaViennaAustria
| | - Rupert Lanzenberger
- Division of General Psychiatry, Department of Psychiatry and PsychotherapyMedical University of ViennaViennaAustria
| | - Karl Rössler
- Department of NeurosurgeryMedical University of ViennaViennaAustria
| | - Siegfried Trattnig
- High‐field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Institute for Clinical Molecular MRIKarl Landsteiner SocietySt. PöltenAustria
| | - Wolfgang Bogner
- High‐field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
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20
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Wang Z, Li Y, Lam F. High-resolution, 3D multi-TE 1 H MRSI using fast spatiospectral encoding and subspace imaging. Magn Reson Med 2021; 87:1103-1118. [PMID: 34752641 DOI: 10.1002/mrm.29015] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 08/30/2021] [Accepted: 08/30/2021] [Indexed: 12/22/2022]
Abstract
PURPOSE To develop a novel method to achieve fast, high-resolution, 3D multi-TE 1 H-MRSI of the brain. METHODS A new multi-TE MRSI acquisition strategy was developed that integrates slab selective excitation with adiabatic refocusing for better volume coverage, rapid spatiospectral encoding, sparse multi-TE sampling, and interleaved water navigators for field mapping and calibration. Special data processing strategies were developed to interpolate the sparsely sampled data, remove nuisance signals, and reconstruct multi-TE spatiospectral distributions with high SNR. Phantom and in vivo experiments have been carried out to demonstrate the capability of the proposed method. RESULTS The proposed acquisition can produce multi-TE 1 H-MRSI data with three TEs at a nominal spatial resolution of 3.4 × 3.4 × 5.3 mm3 in around 20 min. High-SNR brain metabolite spatiospectral reconstructions can be obtained from both a metabolite phantom and in vivo experiments by the proposed method. CONCLUSION High-resolution, 3D multi-TE 1 H-MRSI of the brain can be achieved within clinically feasible time. This capability, with further optimizations, could be translated to clinical applications and neuroscience studies where simultaneously mapping metabolites and neurotransmitters and TE-dependent molecular spectral changes are of interest.
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Affiliation(s)
- Zepeng Wang
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Yahang Li
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Fan Lam
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.,Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
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21
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Chan KL, Hock A, Edden RAE, MacMillan EL, Henning A. Improved prospective frequency correction for macromolecule-suppressed GABA editing with metabolite cycling at 3T. Magn Reson Med 2021; 86:2945-2956. [PMID: 34431549 DOI: 10.1002/mrm.28950] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 07/14/2021] [Accepted: 07/15/2021] [Indexed: 11/08/2022]
Abstract
PURPOSE To combine metabolite cycling with J-difference editing (MC MEGA) to allow for prospective frequency correction at each transient without additional acquisitions and compare it to water-suppressed MEGA-PRESS (WS MEGA) editing with intermittent prospective frequency correction. METHODS Macromolecule-suppressed gamma aminobutyric acid (GABA)-edited experiments were performed in a phantom and in the occipital lobe (OCC) (n = 12) and medial prefrontal cortex (mPFC) (n = 8) of the human brain. Water frequency consistency and average offset over acquisition time were compared. GABA multiplet patterns, signal intensities, and choline subtraction artifacts were evaluated. In vivo GABA concentrations were compared and related to frequency offset in the OCC. RESULTS MC MEGA was more stable with 21% and 32% smaller water frequency SDs in the OCC and mPFC, respectively. MC MEGA also had 39% and 40% smaller average frequency offsets in the OCC and mPFC, respectively. Phantom GABA multiplet patterns and signal intensities were similar. In vivo GABA concentrations were smaller in MC MEGA than in WS MEGA, with median (interquartile range) of 2.52 (0.27) and 2.29 (0.19) institutional units (i.u.), respectively in the OCC scans without prior DTI, and 0.99 (0.3) and 1.72 (0.5), respectively in the mPFC. OCC WS MEGA GABA concentrations, but not MC MEGA GABA concentrations were moderately correlated with frequency offset. mPFC WS MEGA spectra contained significantly more subtraction artifacts than MC MEGA spectra. CONCLUSION MC MEGA is feasible and allows for prospective frequency correction at every transient. MC MEGA GABA concentrations were not biased by frequency offsets and contained less subtraction artifacts compared to WS MEGA.
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Affiliation(s)
- Kimberly L Chan
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Andreas Hock
- MR Clinical Science, Philips Health Systems, Horgen, Switzerland
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Erin L MacMillan
- UBC MRI Research Centre, University of British Columbia, Vancouver, British Columbia, Canada.,SFU ImageTech Lab, Simon Fraser University, Surrey, British Columbia, Canada.,MR Clinical Science, Philips Healthcare, Markham, Ontario, Canada
| | - Anke Henning
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Max Planck Institute for Biological Cybernetics, Tübingen, Germany
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22
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Lee J, Andronesi OC, Torrado-Carvajal A, Ratai EM, Loggia ML, Weerasekera A, Berry MP, Ellingsen DM, Isaro L, Lazaridou A, Paschali M, Grahl A, Wasan AD, Edwards RR, Napadow V. 3D magnetic resonance spectroscopic imaging reveals links between brain metabolites and multidimensional pain features in fibromyalgia. Eur J Pain 2021; 25:2050-2064. [PMID: 34102707 DOI: 10.1002/ejp.1820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Revised: 06/01/2021] [Accepted: 06/04/2021] [Indexed: 11/08/2022]
Abstract
BACKGROUND Fibromyalgia is a centralized multidimensional chronic pain syndrome, but its pathophysiology is not fully understood. METHODS We applied 3D magnetic resonance spectroscopic imaging (MRSI), covering multiple cortical and subcortical brain regions, to investigate the association between neuro-metabolite (e.g. combined glutamate and glutamine, Glx; myo-inositol, mIno; and combined (total) N-acetylaspartate and N-acetylaspartylglutamate, tNAA) levels and multidimensional clinical/behavioural variables (e.g. pain catastrophizing, clinical pain severity and evoked pain sensitivity) in women with fibromyalgia (N = 87). RESULTS Pain catastrophizing scores were positively correlated with Glx and tNAA levels in insular cortex, and negatively correlated with mIno levels in posterior cingulate cortex (PCC). Clinical pain severity was positively correlated with Glx levels in insula and PCC, and with tNAA levels in anterior midcingulate cortex (aMCC), but negatively correlated with mIno levels in aMCC and thalamus. Evoked pain sensitivity was negatively correlated with levels of tNAA in insular cortex, MCC, PCC and thalamus. CONCLUSIONS These findings support single voxel placement targeting nociceptive processing areas in prior 1 H-MRS studies, but also highlight other areas not as commonly targeted, such as PCC, as important for chronic pain pathophysiology. Identifying target brain regions linked to multidimensional symptoms of fibromyalgia (e.g. negative cognitive/affective response to pain, clinical pain, evoked pain sensitivity) may aid the development of neuromodulatory and individualized therapies. Furthermore, efficient multi-region sampling with 3D MRSI could reduce the burden of lengthy scan time for clinical research applications of molecular brain-based mechanisms supporting multidimensional aspects of fibromyalgia. SIGNIFICANCE This large N study linked brain metabolites and pain features in fibromyalgia patients, with a better spatial resolution and brain coverage, to understand a molecular mechanism underlying pain catastrophizing and other aspects of pain transmission. Metabolite levels in self-referential cognitive processing area as well as pain-processing regions were associated with pain outcomes. These results could help the understanding of its pathophysiology and treatment strategies for clinicians.
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Affiliation(s)
- Jeungchan Lee
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Ovidiu C Andronesi
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Angel Torrado-Carvajal
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.,Medical Image Analysis and Biometry Laboratory, Universidad Rey Juan Carlos, Madrid, Spain
| | - Eva-Maria Ratai
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Marco L Loggia
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Akila Weerasekera
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Michael P Berry
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Dan-Mikael Ellingsen
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.,Department of Psychology, University of Oslo, Oslo, Norway
| | - Laura Isaro
- Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Asimina Lazaridou
- Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Myrella Paschali
- Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Arvina Grahl
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Ajay D Wasan
- Department of Anesthesiology and Perioperative Medicine, Center for Innovation in Pain Care, University of Pittsburgh, Pittsburgh, PA, USA
| | - Robert R Edwards
- Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Vitaly Napadow
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.,Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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23
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Bogner W, Otazo R, Henning A. Accelerated MR spectroscopic imaging-a review of current and emerging techniques. NMR IN BIOMEDICINE 2021; 34:e4314. [PMID: 32399974 PMCID: PMC8244067 DOI: 10.1002/nbm.4314] [Citation(s) in RCA: 73] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Revised: 03/24/2020] [Accepted: 03/30/2020] [Indexed: 05/14/2023]
Abstract
Over more than 30 years in vivo MR spectroscopic imaging (MRSI) has undergone an enormous evolution from theoretical concepts in the early 1980s to the robust imaging technique that it is today. The development of both fast and efficient sampling and reconstruction techniques has played a fundamental role in this process. State-of-the-art MRSI has grown from a slow purely phase-encoded acquisition technique to a method that today combines the benefits of different acceleration techniques. These include shortening of repetition times, spatial-spectral encoding, undersampling of k-space and time domain, and use of spatial-spectral prior knowledge in the reconstruction. In this way in vivo MRSI has considerably advanced in terms of spatial coverage, spatial resolution, acquisition speed, artifact suppression, number of detectable metabolites and quantification precision. Acceleration not only has been the enabling factor in high-resolution whole-brain 1 H-MRSI, but today is also common in non-proton MRSI (31 P, 2 H and 13 C) and applied in many different organs. In this process, MRSI techniques had to constantly adapt, but have also benefitted from the significant increase of magnetic field strength boosting the signal-to-noise ratio along with high gradient fidelity and high-density receive arrays. In combination with recent trends in image reconstruction and much improved computation power, these advances led to a number of novel developments with respect to MRSI acceleration. Today MRSI allows for non-invasive and non-ionizing mapping of the spatial distribution of various metabolites' tissue concentrations in animals or humans, is applied for clinical diagnostics and has been established as an important tool for neuro-scientific and metabolism research. This review highlights the developments of the last five years and puts them into the context of earlier MRSI acceleration techniques. In addition to 1 H-MRSI it also includes other relevant nuclei and is not limited to certain body regions or specific applications.
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Affiliation(s)
- Wolfgang Bogner
- High‐Field MR Center, Department of Biomedical Imaging and Image‐Guided TherapyMedical University of ViennaViennaAustria
| | - Ricardo Otazo
- Department of Medical PhysicsMemorial Sloan Kettering Cancer CenterNew York, New YorkUSA
| | - Anke Henning
- Max Planck Institute for Biological CyberneticsTübingenGermany
- Advanced Imaging Research Center, UT Southwestern Medical CenterDallasTexasUSA
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24
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Posse S, Sa De La Rocque Guimaraes B, Hutchins-Delgado T, Vakamudi K, Fotso Tagne K, Moeller S, Dager SR. On the acquisition of the water signal during water suppression: High-speed MR spectroscopic imaging with water referencing and concurrent functional MRI. NMR IN BIOMEDICINE 2021; 34:e4261. [PMID: 31999397 PMCID: PMC7390701 DOI: 10.1002/nbm.4261] [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: 05/10/2019] [Revised: 12/09/2019] [Accepted: 01/03/2020] [Indexed: 06/10/2023]
Abstract
This study evaluated the utility of concurrent water signal acquisition as part of the water suppression in MR spectroscopic imaging (MRSI), to allow simultaneous water referencing for metabolite quantification, and to concurrently acquire functional MRI (fMRI) data. We integrated a spatial-spectral binomial water excitation RF pulse and a short spatial-spectral echo-planar readout into the water suppression module of 2D and 3D proton-echo-planar-spectroscopic-imaging (PEPSI) with a voxel size as small as 4 x 4 x 6 mm3 . Metabolite quantification in reference to tissue water was validated in healthy controls for different prelocalization methods (spin-echo, PRESS and semi-LASER) and the clinical feasibility of a 3-minute 3D semi-Laser PEPSI scan (TR/TE: 1250/32 ms) with water referencing in patients with brain tumors was demonstrated. Spectral quality, SNR, Cramer-Rao-lower-bounds and water suppression efficiency were comparable with conventional PEPSI. Metabolite concentration values in reference to tissue water, using custom LCModel-based spectral fitting with relaxation correction, were in the range of previous studies and independent of the prelocalization method used. Next, we added a phase-encoding undersampled echo-volumar imaging (EVI) module during water suppression to concurrently acquire metabolite maps with water referencing and fMRI data during task execution and resting state in healthy controls. Integration of multimodal signal acquisition prolongated minimum TR by less than 50 ms on average. Visual and motor activation in concurrent fMRI/MRSI (TR: 1250-1500 ms, voxel size: 4 x 4 x 6 mm3 ) was readily detectable in single-task blocks with percent signal change comparable with conventional fMRI. Resting-state connectivity in sensory and motor networks was detectable in 4 minutes. This hybrid water suppression approach for multimodal imaging has the potential to significantly reduce scan time and extend neuroscience research and clinical applications through concurrent quantitative MRSI and fMRI acquisitions.
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Affiliation(s)
- Stefan Posse
- Department of Neurology, University of New Mexico, Albuquerque, NM, United States
- Department of Physics and Astronomy, University of New Mexico, Albuquerque, NM, United States
| | - Bruno Sa De La Rocque Guimaraes
- Department of Neurology, University of New Mexico, Albuquerque, NM, United States
- Department of Physics and Astronomy, University of New Mexico, Albuquerque, NM, United States
| | | | - Kishore Vakamudi
- Department of Neurology, University of New Mexico, Albuquerque, NM, United States
| | - Kevin Fotso Tagne
- Department of Neurology, University of New Mexico, Albuquerque, NM, United States
| | - Steen Moeller
- Center for Magnetic Resonance Research, Radiology, University of Minnesota, Minneapolis, MN, United States
| | - Stephen R Dager
- Departments of Radiology and Bioengineering, University of Washington, Seattle, WA, USA
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Andronesi OC, Bhattacharyya PK, Bogner W, Choi IY, Hess AT, Lee P, Meintjes E, Tisdall MD, Zaitzev M, van der Kouwe A. Motion correction methods for MRS: experts' consensus recommendations. NMR IN BIOMEDICINE 2021; 34:e4364. [PMID: 33089547 PMCID: PMC7855523 DOI: 10.1002/nbm.4364] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [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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Esmaeili M, Strasser B, Bogner W, Moser P, Wang Z, Andronesi OC. Whole-Slab 3D MR Spectroscopic Imaging of the Human Brain With Spiral-Out-In Sampling at 7T. J Magn Reson Imaging 2021; 53:1237-1250. [PMID: 33179836 PMCID: PMC8717862 DOI: 10.1002/jmri.27437] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Revised: 10/26/2020] [Accepted: 10/28/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Metabolic imaging using proton magnetic resonance spectroscopic imaging (MRSI) has increased the sensitivity and spectral resolution at field strengths of ≥7T. Compared to the conventional Cartesian-based spectroscopic imaging, spiral trajectories enable faster data collection, promising the clinical translation of whole-brain MRSI. Technical considerations at 7T, however, lead to a suboptimal sampling efficiency for the spiral-out (SO) acquisitions, as a significant portion of the trajectory consists of rewinders. PURPOSE To develop and implement a spiral-out-in (SOI) trajectory for sampling of whole-brain MRSI at 7T. We hypothesized that SOI will improve the signal-to-noise ratio (SNR) of metabolite maps due to a more efficient acquisition. STUDY TYPE Prospective. SUBJECTS/PHANTOM Five healthy volunteers (28-38 years, three females) and a phantom. FIELD STRENGTH/SEQUENCE Navigated adiabatic spin-echo spiral 3D MRSI at 7T. ASSESSMENT A 3D stack of SOI trajectories was incorporated into an adiabatic spin-echo MRSI sequence with real-time motion and shim correction. Metabolite spectral fitting, SNR, and Cramér-Rao lower bound (CRLB) were obtained. We compared the signal intensity and CRLB of three metabolites of tNAA, tCr, and tCho. Peak SNR (PSNR), structure similarity index (SSIM), and signal-to-artifact ratio were evaluated on water maps. STATISTICAL TESTS The nonparametric Mann-Whitney U-test was used for statistical testing. RESULTS Compared to SO, the SOI trajectory: 1) increased the k-space sampling efficiency by 23%; 2) is less demanding for the gradient hardware, requiring 36% lower Gmax and 26% lower Smax ; 3) increased PSNR of water maps by 4.94 dB (P = 0.0006); 4) resulted in a 29% higher SNR (P = 0.003) and lower CRLB by 26-35% (P = 0.02, tNAA), 35-55% (P = 0.03, tCr), and 22-23% (P = 0.04, tCho), which increased the number of well-fitted voxels (eg, for tCr by 11%, P = 0.03). SOI did not significantly change the signal-to-artifact ratio and SSIM (P = 0.65) compared to SO. DATA CONCLUSION SOI provided more efficient MRSI at 7T compared to SO, which improved the data quality and metabolite quantification. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY STAGE: 2.
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Affiliation(s)
- Morteza Esmaeili
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Department of Diagnostic Imaging, Akershus University Hospital, Lørenskog, Norway
| | - Bernhard Strasser
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- High-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Wolfgang Bogner
- High-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Philipp Moser
- High-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Zhe Wang
- Siemens Medical Solutions, Charlestown, Massachusetts, USA
| | - Ovidiu C. Andronesi
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
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Poblador Rodriguez E, Moser P, Auno S, Eckstein K, Dymerska B, van der Kouwe A, Gruber S, Trattnig S, Bogner W. Real-time motion and retrospective coil sensitivity correction for CEST using volumetric navigators (vNavs) at 7T. Magn Reson Med 2021; 85:1909-1923. [PMID: 33165952 PMCID: PMC7839562 DOI: 10.1002/mrm.28555] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Revised: 09/22/2020] [Accepted: 09/22/2020] [Indexed: 12/12/2022]
Abstract
PURPOSE To explore the impact of temporal motion-induced coil sensitivity changes on CEST-MRI at 7T and its correction using interleaved volumetric EPI navigators, which are applied for real-time motion correction. METHODS Five healthy volunteers were scanned via CEST. A 4-fold correction pipeline allowed the mitigation of (1) motion, (2) motion-induced coil sensitivity variations, ΔB1- , (3) motion-induced static magnetic field inhomogeneities, ΔB0 , and (4) spatially varying transmit RF field fluctuations, ΔB1+ . Four CEST measurements were performed per session. For the first 2, motion correction was turned OFF and then ON in absence of voluntary motion, whereas in the other 2 controlled head rotations were performed. During post-processing ΔB1- was removed additionally for the motion-corrected cases, resulting in a total of 6 scenarios to be compared. In all cases, retrospective ∆B0 and - ΔB1+ corrections were performed to compute artifact-free magnetization transfer ratio maps with asymmetric analysis (MTRasym ). RESULTS Dynamic ΔB1- correction successfully mitigated signal deviations caused by head motion. In 2 frontal lobe regions of volunteer 4, induced relative signal errors of 10.9% and 3.9% were reduced to 1.1% and 1.0% after correction. In the right frontal lobe, the motion-corrected MTRasym contrast deviated 0.92%, 1.21%, and 2.97% relative to the static case for Δω = 1, 2, 3 ± 0.25 ppm. The additional application of ΔB1- correction reduced these deviations to 0.10%, 0.14%, and 0.42%. The fully corrected MTRasym values were highly consistent between measurements with and without intended head rotations. CONCLUSION Temporal ΔB1- cause significant CEST quantification bias. The presented correction pipeline including the proposed retrospective ΔB1- correction significantly reduced motion-related artifacts on CEST-MRI.
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Affiliation(s)
- Esau Poblador Rodriguez
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University Vienna, Vienna, Austria
| | - Philipp Moser
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University Vienna, Vienna, Austria
| | - Sami Auno
- Neuroscience Center, University of Helsinki, Helsinki, Finland
| | - Korbinian Eckstein
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University Vienna, Vienna, Austria
| | - Barbara Dymerska
- Medical Physics and Bioengineering, University College London, London, United Kingdom
| | - Andre van der Kouwe
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Stephan Gruber
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University Vienna, Vienna, Austria
| | - Siegfried Trattnig
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University Vienna, Vienna, Austria.,Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University Vienna, Vienna, Austria
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Effects of SSRI treatment on GABA and glutamate levels in an associative relearning paradigm. Neuroimage 2021; 232:117913. [PMID: 33657450 PMCID: PMC7610796 DOI: 10.1016/j.neuroimage.2021.117913] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 02/01/2021] [Accepted: 02/23/2021] [Indexed: 11/21/2022] Open
Abstract
Impaired cognitive flexibility represents a widespread symptom in psychiatric disorders, including major depressive disorder (MDD), a disease, characterized by an imbalance of neuro-transmitter concentrations. While memory formation is mostly associated with glutamate, also gamma-Aminobutyric acid (GABA) and serotonin show attributions in a complex interplay between neurotransmitter systems. Treatment with selective serotonin reuptake inhibitors (SSRIs) does not solely affect the serotonergic system but shows downstream effects on GABA- and glutamatergic neurotransmission, potentially helping to restore cognitive function via neuroplastic effects. Hence, this study aims to elaborate the effects of associative relearning and SSRI treatment on GABAergic and glutamatergic function within and between five brain regions using magnetic resonance spectroscopy imaging (MRSI). In this study, healthy subjects were randomized into four groups which underwent three weeks of an associative relearning paradigm, with or without emotional connotation, under SSRI (10mg escitalopram) or placebo administration. MRSI measurements, using a spiral-encoded, 3D-GABA-edited MEGA-LASER sequence at 3T, were performed on the first and last day of relearning. Mean GABA+/tCr (GABA+ = GABA + macromolecules; tCr = total creatine) and Glx/tCr (Glx = glutamate + glutamine) ratios were quantified in a ROI-based approach for the hippocampus, insula, putamen, pallidum and thalamus, using LCModel. A total of 66 subjects ((37 female, mean age ± SD = 25.4±4.7) for Glx/tCr and 58 subjects (32 female, mean age ± SD = 25.1±4.7) for GABA+/tCr were included in the final analysis. A significant measurement by region and treatment (SSRI vs placebo) interaction on Glx/tCr ratios was found (pcor=0.017), with post hoc tests confirming differential effects on hippocampus and thalamus (pcor=0.046). Moreover, treatment by time comparison, for each ROI independently, showed a reduction of hippocampal Glx/tCr ratios after SSRI treatment (puncor=0.033). No significant treatment effects on GABA+/tCr ratios or effects of relearning condition on any neurotransmitter ratio could be found. Here, we showed a significant SSRI- and relearning-driven interaction effect of hippocampal and thalamic Glx/tCr levels, suggesting differential behavior based on different serotonin transporter and receptor densities. Moreover, an indication for Glx/tCr adaptions in the hippocampus after three weeks of SSRI treatment could be revealed. Our findings are in line with animal studies reporting glutamate adaptions in the hippocampus following chronic SSRI intake. Due to the complex interplay of serotonin and hippocampal function, involving multiple serotonin receptor subtypes on glutamatergic cells and GABAergic interneurons, the interpretation of underlying neurobiological actions remains challenging.
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Saleh MG, Edden RAE, Chang L, Ernst T. Motion correction in magnetic resonance spectroscopy. Magn Reson Med 2020; 84:2312-2326. [PMID: 32301174 PMCID: PMC8386494 DOI: 10.1002/mrm.28287] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2019] [Revised: 03/25/2020] [Accepted: 03/26/2020] [Indexed: 12/15/2022]
Abstract
In vivo proton magnetic resonance spectroscopy and spectroscopic imaging (MRS/MRSI) are valuable tools to study normal and abnormal human brain physiology. However, they are sensitive to motion, due to strong crusher gradients, long acquisition times, reliance on high magnetic field homogeneity, and particular acquisition methods such as spectral editing. The effects of motion include incorrect spatial localization, phase fluctuations, incoherent averaging, line broadening, and ultimately quantitation errors. Several retrospective methods have been proposed to correct motion-related artifacts. Recent advances in hardware also allow prospective (real-time) correction of the effects of motion, including adjusting voxel location, center frequency, and magnetic field homogeneity. This article reviews prospective and retrospective methods available in the literature and their implications for clinical MRS/MRSI. In combination, these methods can attenuate or eliminate most motion-related artifacts and facilitate the acquisition of high-quality data in the clinical research setting.
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Affiliation(s)
- Muhammad G. Saleh
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Maryland, USA
- F. M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Richard A. E. Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Maryland, USA
- F. M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Linda Chang
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland, Baltimore, USA
| | - Thomas Ernst
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland, Baltimore, USA
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30
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Esmaeili M, Stockmann J, Strasser B, Arango N, Thapa B, Wang Z, van der Kouwe A, Dietrich J, Cahill DP, Batchelor TT, White J, Adalsteinsson E, Wald L, Andronesi OC. An integrated RF-receive/B 0-shim array coil boosts performance of whole-brain MR spectroscopic imaging at 7 T. Sci Rep 2020; 10:15029. [PMID: 32929121 PMCID: PMC7490394 DOI: 10.1038/s41598-020-71623-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Accepted: 06/16/2020] [Indexed: 12/03/2022] Open
Abstract
Metabolic imaging of the human brain by in-vivo magnetic resonance spectroscopic imaging (MRSI) can non-invasively probe neurochemistry in healthy and disease conditions. MRSI at ultra-high field (≥ 7 T) provides increased sensitivity for fast high-resolution metabolic imaging, but comes with technical challenges due to non-uniform B0 field. Here, we show that an integrated RF-receive/B0-shim (AC/DC) array coil can be used to mitigate 7 T B0 inhomogeneity, which improves spectral quality and metabolite quantification over a whole-brain slab. Our results from simulations, phantoms, healthy and brain tumor human subjects indicate improvements of global B0 homogeneity by 55%, narrower spectral linewidth by 29%, higher signal-to-noise ratio by 31%, more precise metabolite quantification by 22%, and an increase by 21% of the brain volume that can be reliably analyzed. AC/DC shimming provide the highest correlation (R2 = 0.98, P = 0.001) with ground-truth values for metabolite concentration. Clinical translation of AC/DC and MRSI is demonstrated in a patient with mutant-IDH1 glioma where it enables imaging of D-2-hydroxyglutarate oncometabolite with a 2.8-fold increase in contrast-to-noise ratio at higher resolution and more brain coverage compared to previous 7 T studies. Hence, AC/DC technology may help ultra-high field MRSI become more feasible to take advantage of higher signal/contrast-to-noise in clinical applications.
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Affiliation(s)
- Morteza Esmaeili
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Diagnostic Imaging, Akershus University Hospital, Lørenskog, Norway
| | - Jason Stockmann
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Bernhard Strasser
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Nicolas Arango
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Bijaya Thapa
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Zhe Wang
- Siemens Medical Solutions, USA, Charlestown, MA, USA
| | - Andre van der Kouwe
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Jorg Dietrich
- Division of Neuro-Oncology, Department Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Daniel P Cahill
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Tracy T Batchelor
- Department Neurology, Brigham's and Women Hospital, Harvard Medical School, Boston, MA, USA
| | - Jacob White
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Elfar Adalsteinsson
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Lawrence Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Ovidiu C Andronesi
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
- Athinoula A. Martinos Center for Biomedical Imaging, Building 149, Room 2301 13th Street, Charlestown, MA, 02129, USA.
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Torrado-Carvajal A, Albrecht DS, Lee J, Andronesi OC, Ratai EM, Napadow V, Loggia ML. Inpainting as a Technique for Estimation of Missing Voxels in Brain Imaging. Ann Biomed Eng 2020; 49:345-353. [PMID: 32632531 DOI: 10.1007/s10439-020-02556-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Accepted: 06/19/2020] [Indexed: 10/23/2022]
Abstract
Issues with model fitting (i.e. suboptimal standard deviation, linewidth/full-width-at-half-maximum, and/or signal-to-noise ratio) in multi-voxel MRI spectroscopy, or chemical shift imaging (CSI) can result in the significant loss of usable voxels. A potential solution to minimize this problem is to estimate the value of unusable voxels by utilizing information from reliable voxels in the same image. We assessed an image restoration method called inpainting as a tool to restore unusable voxels, and compared it with traditional interpolation methods (nearest neighbor, trilinear interpolation and tricubic interpolation). In order to evaluate the performance across varying image contrasts and spatial resolutions, we applied the same techniques to a T1-weighted MRI brain dataset, and N-acetylaspartate (NAA) spectroscopy maps from a CSI dataset. For all image types, inpainting exhibited superior performance (lower normalized root-mean-square errors, NRMSE) compared to all other methods considered (p's < 0.001). Inpainting maintained an average NRMSE of less than 5% even with 50% missing voxels, whereas the other techniques demonstrated up to three times that value, depending on the nature of the image. For CSI maps, inpainting maintained its superiority whether the previously unusable voxels were randomly distributed, or located in regions most commonly affected by voxel loss in real-world data. Inpainting is a promising approach for recovering unusable or missing voxels in voxel-wise analyses, particularly in imaging modalities characterized by low SNR such as CSI. We hypothesize that this technique may also be applicable for datasets from other imaging modalities, such as positron emission tomography, or dynamic susceptibility contrast MRI.
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Affiliation(s)
- Angel Torrado-Carvajal
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA. .,Medical Image Analysis and Biometry Laboratory, Universidad Rey Juan Carlos, Madrid, Spain.
| | - Daniel S Albrecht
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Jeungchan Lee
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Ovidiu C Andronesi
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Eva-Maria Ratai
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Vitaly Napadow
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Marco L Loggia
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
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Boer VO, Andersen M, Lind A, Lee NG, Marsman A, Petersen ET. MR spectroscopy using static higher order shimming with dynamic linear terms (HOS-DLT) for improved water suppression, interleaved MRS-fMRI, and navigator-based motion correction at 7T. Magn Reson Med 2020; 84:1101-1112. [PMID: 32060951 PMCID: PMC7317823 DOI: 10.1002/mrm.28202] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Revised: 01/08/2020] [Accepted: 01/17/2020] [Indexed: 12/12/2022]
Abstract
PURPOSE To interleave global and local higher order shimming for single voxel MRS. Single voxel MR spectroscopy requires optimization of the B0 field homogeneity in the region of the voxel to obtain a narrow linewidth and provide high data quality. However, the optimization of local higher order fields on a localized MRS voxel typically leads to large field offsets outside that volume. This compromises interleaved MR sequence elements that benefit from global field homogeneity such as water suppression, interleaved MRS-fMRI, and MR motion correction. METHODS A shimming algorithm was developed to optimize the MRS voxel homogeneity and the whole brain homogeneity for interleaved sequence elements, using static higher order shims and dynamic linear terms (HOS-DLT). Shimming performance was evaluated using 6 brain regions and 10 subjects. Furthermore, the benefits of HOS-DLT was demonstrated for water suppression, MRS-fMRI, and motion corrected MRS using fat-navigators. RESULTS The HOS-DLT algorithm was shown to improve the whole brain homogeneity compared to an MRS voxel-based shim, without compromising the MRS voxel homogeneity. Improved water suppression over the brain, reduced image distortions in MRS-fMRI, and improved quality of motion navigators were demonstrated using the HOS-DLT method. CONCLUSION HOS-DLT shimming allowed for both local and global field homogeneity, providing excellent MR spectroscopy data quality, as well as good field homogeneity for interleaved sequence elements, even without the need for dynamic higher order shimming capabilities.
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Affiliation(s)
- Vincent O Boer
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Denmark
| | | | - Anna Lind
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Denmark
| | - Nam Gyun Lee
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Denmark.,Department of Biomedical Engineering, University of Southern California, Los Angeles, California
| | - Anouk Marsman
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Denmark
| | - Esben T Petersen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Denmark.,Center for Magnetic Resonance, Department of Health Technology, Technical University of Denmark, Kgs. Lyngby, Denmark
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Silberbauer LR, Spurny B, Handschuh P, Klöbl M, Bednarik P, Reiter B, Ritter V, Trost P, Konadu ME, Windpassinger M, Stimpfl T, Bogner W, Lanzenberger R, Spies M. Effect of Ketamine on Limbic GABA and Glutamate: A Human In Vivo Multivoxel Magnetic Resonance Spectroscopy Study. Front Psychiatry 2020; 11:549903. [PMID: 33101078 PMCID: PMC7507577 DOI: 10.3389/fpsyt.2020.549903] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Accepted: 08/18/2020] [Indexed: 12/12/2022] Open
Abstract
INTRODUCTION Converging evidence suggests that ketamine elicits antidepressant effects via enhanced neuroplasticity precipitated by a surge of glutamate and modulation of GABA. Magnetic resonance spectroscopic imaging (MRSI) illustrates changes to cerebral glutamate and GABA immediately following ketamine administration during dissociation. However, few studies assess subacute changes in the first hours following application, when ketamine's antidepressant effects emerge. Moreover, ketamine metabolites implicated in its antidepressant effects develop during this timeframe. Thus, this study aimed to investigate subacute changes in cerebral Glx (glutamate + glutamine), GABA and their ratio in seven brain regions central to depressive pathophysiology and treatment. METHODS Twenty-five healthy subjects underwent two multivoxel MRS scans using a spiral encoded, MEGA-edited LASER-localized 3D-MRSI sequence, at baseline and 2 h following intravenous administration of racemic ketamine (0.8 mg/kg bodyweight over 50 min). Ketamine, norketamine and dehydronorketamine plasma levels were determined at routine intervals during and after infusion. Automated region-of-interest (ROI)-based quantification of mean metabolite concentration was used to assess changes in GABA+/total creatine (tCr), Glx/tCr, and GABA+/Glx ratios in the thalamus, hippocampus, insula, putamen, rostral anterior cingulate cortex (ACC), caudal ACC, and posterior cingulate cortex. Effects of ketamine on neurotransmitter levels and association with ketamine- and metabolite plasma levels were tested with repeated measures analyses of variance (rmANOVA) and correlation analyses, respectively. RESULTS For GABA+/tCr rmANOVA revealed a measurement by region interaction effect (puncorr < 0.001) and post hoc pairwise comparisons showed a reduction in hippocampal GABA+/tCr after ketamine (pcorr = 0.02). For Glx/tCr and GABA+/Glx neither main effects of measurement nor measurement by region interactions were observed (all puncorr > 0.05). Furthermore, no statistically significant associations between changes in any of the neurotransmitter ratios and plasma levels of ketamine, norketamine, or dehydronorketamine were observed (pcorr > 0.05). CONCLUSION This study provides evidence for decreased hippocampal GABA+/tCr ratio 2 h following ketamine administration. As MRS methodology measures total levels of intra- and extracellular GABA, results might indicate drug induced alterations in GABA turnover. Our study in healthy humans suggests that changes in GABA levels, particularly in the hippocampus, should be further assessed for their relevance to ketamine´s antidepressant effects.
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Affiliation(s)
- Leo R Silberbauer
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Benjamin Spurny
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Patricia Handschuh
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Manfred Klöbl
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Petr Bednarik
- Department of Biomedical Imaging and Image-guided Therapy, High Field MR Centre, Medical University of Vienna, Vienna, Austria
| | - Birgit Reiter
- Department of Laboratory Medicine, Medical University of Vienna, Vienna, Austria
| | - Vera Ritter
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Patricia Trost
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Melisande E Konadu
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Marita Windpassinger
- Department of Anesthesia, Intensive Care Medicine and Pain Medicine, Medical University of Vienna, Vienna, Austria
| | - Thomas Stimpfl
- Department of Laboratory Medicine, Medical University of Vienna, Vienna, Austria
| | - Wolfgang Bogner
- Department of Biomedical Imaging and Image-guided Therapy, High Field MR Centre, Medical University of Vienna, Vienna, Austria
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Marie Spies
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
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Maul S, Giegling I, Rujescu D. Proton Magnetic Resonance Spectroscopy in Common Dementias-Current Status and Perspectives. Front Psychiatry 2020; 11:769. [PMID: 32848938 PMCID: PMC7424040 DOI: 10.3389/fpsyt.2020.00769] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Accepted: 07/20/2020] [Indexed: 12/13/2022] Open
Abstract
Dementia occurs mainly in the elderly and is associated with cognitive decline and impairment of activities of daily living. The most common forms of dementia are Alzheimer's disease (AD), vascular dementia (VD), dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD). To date, there are no causal options for therapy, but drug and non-drug treatments can positively modulate the course of the disease. Valid biomarkers are needed for the earliest possible and reliable diagnosis, but so far, such biomarkers have only been established for AD and require invasive and expensive procedures. In this context, proton magnetic resonance spectroscopy (1H-MRS) provides a non-invasive and widely available technique for investigating the biochemical milieu of brain tissue in vivo. Numerous studies have been conducted for AD, but for VD, DLB, and FTD the number of studies is limited. Nevertheless, MRS can detect measurable metabolic alterations in common dementias. However, most of the studies conducted are too heterogeneous to assess the potential use of MRS technology in clinical applications. In the future, technological advances may increase the value of MRS in dementia diagnosis and treatment. This review summarizes the results of MRS studies conducted in common dementias and discusses the reasons for the lack of transfer into clinical routine.
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Affiliation(s)
- Stephan Maul
- University Clinic and Outpatient Clinic for Psychiatry, Psychotherapy and Psychosomatics, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Ina Giegling
- University Clinic and Outpatient Clinic for Psychiatry, Psychotherapy and Psychosomatics, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Dan Rujescu
- University Clinic and Outpatient Clinic for Psychiatry, Psychotherapy and Psychosomatics, Martin Luther University Halle-Wittenberg, Halle, Germany
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Spurny B, Seiger R, Moser P, Vanicek T, Reed MB, Heckova E, Michenthaler P, Basaran A, Gryglewski G, Klöbl M, Trattnig S, Kasper S, Bogner W, Lanzenberger R. Hippocampal GABA levels correlate with retrieval performance in an associative learning paradigm. Neuroimage 2020; 204:116244. [PMID: 31606475 PMCID: PMC7610791 DOI: 10.1016/j.neuroimage.2019.116244] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Revised: 08/29/2019] [Accepted: 10/03/2019] [Indexed: 11/23/2022] Open
Abstract
Neural plasticity is a complex process dependent on neurochemical underpinnings. Next to the glutamatergic system which contributes to memory formation via long-term potentiation (LTP) and long-term depression (LTD), the main inhibitory neurotransmitter, GABA is crucially involved in neuroplastic processes. Hence, we investigated changes in glutamate and GABA levels in the brain in healthy participants performing an associative learning paradigm. Twenty healthy participants (10 female, 25 ± 5 years) underwent paired multi-voxel magnetic resonance spectroscopy imaging before and after completing 21 days of a facial associative learning paradigm in a longitudinal study design. Changes of GABA and glutamate were compared to retrieval success in the hippocampus, insula and thalamus. No changes in GABA and glutamate concentration were found after 21 days of associative learning. However, baseline hippocampal GABA levels were significantly correlated with initial retrieval success (pcor = 0.013, r = 0.690). In contrast to the thalamus and insula (pcor>0.1), higher baseline GABA levels in the hippocampus were associated with better retrieval performance in an associative learning paradigm. Therefore, our findings support the importance of hippocampal GABA levels in memory formation in the human brain in vivo.
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Affiliation(s)
- Benjamin Spurny
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria
| | - Rene Seiger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria
| | - Philipp Moser
- Department of Biomedical Imaging and Image-guided Therapy, High Field MR Centre, Medical University of Vienna, Austria
| | - Thomas Vanicek
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria
| | - Murray B Reed
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria
| | - Eva Heckova
- Department of Biomedical Imaging and Image-guided Therapy, High Field MR Centre, Medical University of Vienna, Austria
| | - Paul Michenthaler
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria
| | - Alim Basaran
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria
| | - Gregor Gryglewski
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria
| | - Manfred Klöbl
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria
| | - Siegfried Trattnig
- Department of Biomedical Imaging and Image-guided Therapy, High Field MR Centre, Medical University of Vienna, Austria; Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria
| | - Siegfried Kasper
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria
| | - Wolfgang Bogner
- Department of Biomedical Imaging and Image-guided Therapy, High Field MR Centre, Medical University of Vienna, Austria
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria.
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Chan KL, Barker PB. Retrospective motion compensation for edited MR spectroscopic imaging. Neuroimage 2019; 202:116141. [PMID: 31479753 DOI: 10.1016/j.neuroimage.2019.116141] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Revised: 08/23/2019] [Accepted: 08/28/2019] [Indexed: 12/12/2022] Open
Abstract
Edited magnetic resonance spectroscopic imaging (MRSI) is capable of mapping the distribution of low concentration metabolites such as gamma-aminobutyric acid (GABA) or and glutathione (GSH), but is prone to subtraction artifacts due to head motion or other instabilities. In this study, a retrospective motion compensation algorithm for edited MRSI is proposed. The algorithm identifies movement-affected signals by comparing residual water and lipid peaks between different transients recorded at the same point in k-space, and either phase corrects, replaces or removes affected spectra prior to spatial Fourier transformation. The method was tested on macromolecule-unsuppressed GABA-edited spin-echo MR spectroscopic imaging data acquired from 8 healthy adults scanned at 3T. Relative to non-motion compensated data sets, the motion compensated data had significantly less subtraction artifacts across subjects. The residual choline (Cho) peak in the spectrum (which is well resolved from as a different chemical shift from GABA and is completely absent in a spectrum without subtraction artifact) was used as a metric of motion artifact severity. The normalized Cho area was 5.14 times lower with motion compensation than without motion compensation. A 'removal-only' version of the technique is also shown to be promising in removing motion-corrupted artifacts in a GSH-edited MRSI acquisition acquired in 1 healthy subject. This study introduces a motion compensation technique and demonstrates that retrospective compensation in k-space is possible and significantly reduces the amount of subtraction artifacts in the resulting edited spectra.
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Affiliation(s)
- Kimberly L Chan
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA.
| | - Peter B Barker
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
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Moser P, Eckstein K, Hingerl L, Weber M, Motyka S, Strasser B, van der Kouwe A, Robinson S, Trattnig S, Bogner W. Intra-session and inter-subject variability of 3D-FID-MRSI using single-echo volumetric EPI navigators at 3T. Magn Reson Med 2019; 83:1920-1929. [PMID: 31721294 PMCID: PMC7065144 DOI: 10.1002/mrm.28076] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 09/25/2019] [Accepted: 10/22/2019] [Indexed: 01/25/2023]
Abstract
Purpose In this study, we demonstrate the first combination of 3D FID proton MRSI and spatial encoding via concentric‐ring trajectories (CRTs) at 3T. FID‐MRSI has many benefits including high detection sensitivity, in particular for J‐coupled metabolites (e.g., glutamate/glutamine). This makes it highly attractive, not only for clinical, but also for, potentially, functional MRSI. However, this requires excellent reliability and temporal stability. We have, therefore, augmented this 3D‐FID‐MRSI sequence with single‐echo, imaging‐based volumetric navigators (se‐vNavs) for real‐time motion/shim‐correction (SHMOCO), which is 2× quicker than the original double‐echo navigators (de‐vNavs), hence allowing more efficient integration also in short‐TR sequences. Methods The tracking accuracy (position and B0‐field) of our proposed se‐vNavs was compared to the original de‐vNavs in phantoms (rest and translation) and in vivo (voluntary head rotation). Finally, the intra‐session stability of a 5:40 min 3D‐FID‐MRSI scan was evaluated with SHMOCO and no correction (NOCO) in 5 resting subjects. Intra/inter‐subject coefficients of variation (CV) and intra‐class correlations (ICC) over the whole 3D volume and in selected regions of interest ROI were assessed. Results Phantom and in vivo scans showed highly consistent tracking performance for se‐vNavs compared to the original de‐vNavs, but lower frequency drift. Up to ~30% better intra‐subject CVs were obtained for SHMOCO (P < 0.05), with values of 9.3/6.9/6.5/7.8% over the full VOI for Glx/tNAA/tCho/m‐Ins ratios to tCr. ICCs were good‐to‐high (91% for Glx/tCr in motor cortex), whereas the inter‐subject variability was ~11–19%. Conclusion Real‐time motion/shim corrected 3D‐FID‐MRSI with time‐efficient CRT‐sampling at 3T allows reliable, high‐resolution metabolic imaging that is fast enough for clinical use and even, potentially, for functional MRSI.
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Affiliation(s)
- Philipp Moser
- High-Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Korbinian Eckstein
- High-Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Lukas Hingerl
- High-Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Michael Weber
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Stanislav Motyka
- High-Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Bernhard Strasser
- High-Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.,Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Andre van der Kouwe
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Simon Robinson
- High-Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Siegfried Trattnig
- High-Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.,Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria
| | - Wolfgang Bogner
- High-Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
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Moser P, Bogner W, Hingerl L, Heckova E, Hangel G, Motyka S, Trattnig S, Strasser B. Non-Cartesian GRAPPA and coil combination using interleaved calibration data - application to concentric-ring MRSI of the human brain at 7T. Magn Reson Med 2019; 82:1587-1603. [PMID: 31183893 PMCID: PMC6772100 DOI: 10.1002/mrm.27822] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Revised: 04/29/2019] [Accepted: 05/01/2019] [Indexed: 12/12/2022]
Abstract
PURPOSE Proton MR spectroscopic imaging (MRSI) benefits from B0 ≥ 7T and multichannel receive coils, promising substantial resolution improvements. However, MRSI acquisition with high spatial resolution requires efficient acceleration and coil combination. To speed up the already-fast sampling via concentric rings, we implemented additional, non-Cartesian, hybrid through-time/through-k-space (tt/tk)-generalized autocalibrating partially parallel acquisition (GRAPPA). A new multipurpose interleaved calibration scan (interleaved MUSICAL) acquires reference data for both coil combination and PI. This renders the reconstruction process (especially PI) less sensitive to instabilities. METHODS Six healthy volunteers were scanned at 7T. Three calibration datasets for coil combination and PI were recorded: a) iMUSICAL, b) static MUSICAL as prescan, c) moved MUSICAL as prescan with misaligned head position. The coil combination performance, including motion sensitivity, of iMUSICAL was compared to MUSICAL for single-slice free induction decay (FID)-MRSI. Through-time/through-k-space-GRAPPA with constant/variable-density undersampling was evaluated on the same data, comparing the three calibration datasets. Additionally, the proposed method was successfully applied to 3D whole-brain FID-MRSI. RESULTS Using iMUSICAL for coil combination yielded the highest signal-to-noise ratio (SNR) (+9%) and lowest Cramer-Rao lower bounds (CRLBs) (-6%) compared to both MUSICAL approaches, with similar metabolic map quality. Also, excellent mean g-factors of 1.07 and low residual lipid aliasing were obtained when using iMUSICAL as calibration data for two-fold, variable-density undersampling, while significantly degraded metabolic maps were obtained using the misaligned MUSICAL calibration data. CONCLUSION Through-time/through-k-space-GRAPPA can accelerate already time-efficient non-Cartesian spatial-spectral 2D/3D-MRSI encoding even further. Particularly promising results have been achieved using iMUSICAL as a robust, interleaved multipurpose calibration for MRSI reconstruction, without extra calibration prescan.
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Affiliation(s)
- Philipp Moser
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Lukas Hingerl
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Eva Heckova
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Gilbert Hangel
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Stanislav Motyka
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Siegfried Trattnig
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria.,Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria
| | - Bernhard Strasser
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria.,Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
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Poblador Rodriguez E, Moser P, Dymerska B, Robinson S, Schmitt B, van der Kouwe A, Gruber S, Trattnig S, Bogner W. A comparison of static and dynamic ∆B 0 mapping methods for correction of CEST MRI in the presence of temporal B 0 field variations. Magn Reson Med 2019; 82:633-646. [PMID: 30924210 PMCID: PMC6563466 DOI: 10.1002/mrm.27750] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Revised: 03/02/2019] [Accepted: 03/04/2019] [Indexed: 12/18/2022]
Abstract
PURPOSE To assess the performance, in the presence of scanner instabilities, of three dynamic correction methods which integrate ∆B0 mapping into the chemical exchange saturation transfer (CEST) measurement and three established static ∆B0 -correction approaches. METHODS A homogeneous phantom and five healthy volunteers were scanned with a CEST sequence at 7 T. The in vivo measurements were performed twice: first with unaltered system frequency and again applying frequency shifts during the CEST acquisition. In all cases, retrospective voxel-wise ∆B0 -correction was performed using one intrinsic and two extrinsic [prescans with dual-echo gradient-echo and water saturation shift referencing (WASSR)] static approaches. These were compared with two intrinsic [using phase data directly generated by single-echo or double-echo GRE (gradient-echo) CEST readout (CEST-GRE-2TE)] and one extrinsic [phase from interleaved dual-echo EPI (echo planar imaging) navigator (NAV-EPI-2TE)] dynamic ∆B0 -correction approaches [allowing correction of each Z-spectral point before magnetization transfer ratio asymmetry (MTRasym) analysis]. RESULTS All three dynamic methods successfully mapped the induced drift. The intrinsic approaches were affected by the CEST labeling near water (∆ω < |0.3| ppm). The MTRasym contrast was distorted by the frequency drift in the brain by up to 0.21%/Hz when static ∆B0 -corrections were applied, whereas the dynamic ∆B0 corrections reduced this to <0.01%/Hz without the need of external scans. The CEST-GRE-2TE and NAV-EPI-2TE resulted in highly consistent MTRasym values with/without drift for all subjects. CONCLUSION Reliable correction of scanner instabilities is essential to establish clinical CEST MRI. The three dynamic approaches presented improved the ∆B0 -correction performance significantly in the presence of frequency drift compared to established static methods. Among them, the self-corrected CEST-GRE-2TE was the most accurate and straightforward to implement.
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Affiliation(s)
- Esau Poblador Rodriguez
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Philipp Moser
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Barbara Dymerska
- Medical Physics and Bioengineering, University College London, London, United Kingdom
| | - Simon Robinson
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | | | - Andre van der Kouwe
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Stephan Gruber
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Siegfried Trattnig
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria.,Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
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40
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Deelchand DK, Joers JM, Auerbach EJ, Henry PG. Prospective motion and B 0 shim correction for MR spectroscopy in human brain at 7T. Magn Reson Med 2019; 82:1984-1992. [PMID: 31297889 DOI: 10.1002/mrm.27886] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2019] [Revised: 06/04/2019] [Accepted: 06/07/2019] [Indexed: 12/24/2022]
Abstract
PURPOSE To demonstrate feasibility and performance of prospective motion and B0 shim correction for MRS in human brain at 7T. METHODS Prospective motion correction using an optical camera and linear B0 shim correction using FASTMAP-like navigators were implemented into a semi-LASER sequence. The effect of motion on spectral quality was assessed without and with prospective correction in prefrontal cortex in 11 subjects. RESULTS Without prospective motion and shim correction, motion resulted in considerable degradation of MR spectra (broader linewidth, lower signal-to-noise ratio, degraded water suppression). With prospective motion and shim correction, spectral quality remained excellent despite motion. Prospective motion correction alone was not sufficient to prevent degradation of spectral quality. CONCLUSION Prospective motion and B0 shim correction is feasible at 7T and should help improve the robustness of MRS, particularly in motion-prone populations.
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Affiliation(s)
- Dinesh K Deelchand
- Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota, Minneapolis, Minnesota
| | - James M Joers
- Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota, Minneapolis, Minnesota
| | - Edward J Auerbach
- Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota, Minneapolis, Minnesota
| | - Pierre-Gilles Henry
- Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota, Minneapolis, Minnesota
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Chan KL, Oeltzschner G, Saleh MG, Edden RAE, Barker PB. Simultaneous editing of GABA and GSH with Hadamard-encoded MR spectroscopic imaging. Magn Reson Med 2019; 82:21-32. [PMID: 30793803 DOI: 10.1002/mrm.27702] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2018] [Revised: 01/28/2019] [Accepted: 01/30/2019] [Indexed: 12/23/2022]
Abstract
PURPOSE To evaluate the feasibility of simultaneous MR spectroscopic imaging (MRSI) of gamma-aminobutyric acid (GABA) and glutathione (GSH) in the human brain using Hadamard Encoding and Reconstruction of MEGA-Edited Spectroscopy (HERMES). METHODS Point RESolved Spectroscopy (PRESS)-localized MRSI was performed in GABA and GSH phantoms and in the human brain (n = 3) using HERMES editing and compared to conventional MEGA editing of each metabolite. Multiplet patterns, signal intensities, and metabolite crosstalk were compared between methods. GABA+ and GSH levels were compared between methods for bias and variability. Linear regression of HERMES-MRSI GABA+/H2 O and GSH/H2 O versus gray matter (GM) fraction were performed to assess differences between GM and white matter (WM). RESULTS Phantom HERMES-MRSI scans gave comparable GABA+ and GSH signals to MEGA-MRSI across the PRESS-localized volume. In vivo, HERMES-reconstructed GABA+ and GSH values had minimal measurement bias and variability relative to MEGA-MRSI. Intersubject coefficients of variation (CV) from two regions within the PRESS-localized volume for HERMES and MEGA were 6-12% for GABA+ and 6-19% for GSH. Interregion CVs were 5-15% for GABA+ and 3-17% for GSH. The GABA+/H2 O and GSH/H2 O ratios were ~1.8 times higher and ~1.9 times higher, respectively, in GM than in WM. CONCLUSION HERMES-MRSI of GABA+ and GSH was found to be practical in the human brain with minimal measurement bias and comparable variability to separate MEGA-edited acquisitions of each metabolite performed in double the scan time. The HERMES-MRSI is a promising method for simultaneously mapping the distribution of multiple low-concentration metabolites.
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Affiliation(s)
- Kimberly L Chan
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland.,Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Muhammad G Saleh
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Peter B Barker
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
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Spurny B, Heckova E, Seiger R, Moser P, Klöbl M, Vanicek T, Spies M, Bogner W, Lanzenberger R. Automated ROI-Based Labeling for Multi-Voxel Magnetic Resonance Spectroscopy Data Using FreeSurfer. Front Mol Neurosci 2019; 12:28. [PMID: 30837839 PMCID: PMC6382749 DOI: 10.3389/fnmol.2019.00028] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Accepted: 01/22/2019] [Indexed: 12/14/2022] Open
Abstract
Purpose: Advanced analysis methods for multi-voxel magnetic resonance spectroscopy (MRS) are crucial for neurotransmitter quantification, especially for neurotransmitters showing different distributions across tissue types. So far, only a handful of studies have used region of interest (ROI)-based labeling approaches for multi-voxel MRS data. Hence, this study aims to provide an automated ROI-based labeling tool for 3D-multi-voxel MRS data. Methods: MRS data, for automated ROI-based labeling, was acquired in two different spatial resolutions using a spiral-encoded, LASER-localized 3D-MRS imaging sequence with and without MEGA-editing. To calculate the mean metabolite distribution within selected ROIs, masks of individual brain regions were extracted from structural T1-weighted images using FreeSurfer. For reliability testing of automated labeling a comparison to manual labeling and single voxel selection approaches was performed for six different subcortical regions. Results: Automated ROI-based labeling showed high consistency [intra-class correlation coefficient (ICC) > 0.8] for all regions compared to manual labeling. Higher variation was shown when selected voxels, chosen from a multi-voxel grid, uncorrected for voxel composition, were compared to labeling methods using spatial averaging based on anatomical features within gray matter (GM) volumes. Conclusion: We provide an automated ROI-based analysis approach for various types of 3D-multi-voxel MRS data, which dramatically reduces hands-on time compared to manual labeling without any possible inter-rater bias.
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Affiliation(s)
- Benjamin Spurny
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Eva Heckova
- Department of Biomedical Imaging and Image-Guided Therapy, High Field MR Centre, Medical University of Vienna, Vienna, Austria
| | - Rene Seiger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Philipp Moser
- Department of Biomedical Imaging and Image-Guided Therapy, High Field MR Centre, Medical University of Vienna, Vienna, Austria
| | - Manfred Klöbl
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Thomas Vanicek
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Marie Spies
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Wolfgang Bogner
- Department of Biomedical Imaging and Image-Guided Therapy, High Field MR Centre, Medical University of Vienna, Vienna, Austria
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
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43
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Moser P, Hingerl L, Strasser B, Považan M, Hangel G, Andronesi OC, van der Kouwe A, Gruber S, Trattnig S, Bogner W. Whole-slice mapping of GABA and GABA + at 7T via adiabatic MEGA-editing, real-time instability correction, and concentric circle readout. Neuroimage 2019; 184:475-489. [PMID: 30243974 PMCID: PMC7212034 DOI: 10.1016/j.neuroimage.2018.09.039] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Revised: 08/20/2018] [Accepted: 09/15/2018] [Indexed: 01/29/2023] Open
Abstract
An adiabatic MEscher-GArwood (MEGA)-editing scheme, using asymmetric hyperbolic secant editing pulses, was developed and implemented in a B1+-insensitive, 1D-semiLASER (Localization by Adiabatic SElective Refocusing) MR spectroscopic imaging (MRSI) sequence for the non-invasive mapping of γ-aminobutyric acid (GABA) over a whole brain slice. Our approach exploits the advantages of edited-MRSI at 7T while tackling challenges that arise with ultra-high-field-scans. Spatial-spectral encoding, using density-weighted, concentric circle echo planar trajectory readout, enabled substantial MRSI acceleration and an improved point-spread-function, thereby reducing extracranial lipid signals. Subject motion and scanner instabilities were corrected in real-time using volumetric navigators optimized for 7T, in combination with selective reacquisition of corrupted data to ensure robust subtraction-based MEGA-editing. Simulations and phantom measurements of the adiabatic MEGA-editing scheme demonstrated stable editing efficiency even in the presence of ±0.15 ppm editing frequency offsets and B1+ variations of up to ±30% (as typically encountered in vivo at 7T), in contrast to conventional Gaussian editing pulses. Volunteer measurements were performed with and without global inversion recovery (IR) to study regional GABA levels and their underlying, co-edited, macromolecular (MM) signals at 2.99 ppm. High-quality in vivo spectra allowed mapping of pure GABA and MM-contaminated GABA+ (GABA + MM) along with Glx (Glu + Gln), with high-resolution (eff. voxel size: 1.4 cm3) and whole-slice coverage in 24 min scan time. Metabolic ratio maps of GABA/tNAA, GABA+/tNAA, and Glx/tNAA were correlated linearly with the gray matter fraction of each voxel. A 2.15-fold increase in gray matter to white matter contrast was observed for GABA when enabling IR, which we attribute to the higher abundance of macromolecules at 2.99 ppm in the white matter than in the gray matter. In conclusion, adiabatic MEGA-editing with 1D-semiLASER selection is as a promising approach for edited-MRSI at 7T. Our sequence capitalizes on the benefits of ultra-high-field MRSI while successfully mitigating the challenges related to B0/B1+ inhomogeneities, prolonged scan times, and motion/scanner instability artifacts. Robust and accurate 2D mapping has been shown for the neurotransmitters GABA and Glx.
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Affiliation(s)
- Philipp Moser
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090, Vienna, Austria; Christian Doppler Laboratory for Clinical Molecular MRI, Vienna, Austria.
| | - Lukas Hingerl
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090, Vienna, Austria.
| | - Bernhard Strasser
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090, Vienna, Austria; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| | - Michal Považan
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090, Vienna, Austria; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| | - Gilbert Hangel
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090, Vienna, Austria.
| | - Ovidiu C Andronesi
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| | - Andre van der Kouwe
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| | - Stephan Gruber
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090, Vienna, Austria.
| | - Siegfried Trattnig
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090, Vienna, Austria.
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090, Vienna, Austria.
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Hingerl L, Bogner W, Moser P, Považan M, Hangel G, Heckova E, Gruber S, Trattnig S, Strasser B. Density-weighted concentric circle trajectories for high resolution brain magnetic resonance spectroscopic imaging at 7T. Magn Reson Med 2018; 79:2874-2885. [PMID: 29106742 PMCID: PMC5873433 DOI: 10.1002/mrm.26987] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2017] [Revised: 09/09/2017] [Accepted: 10/07/2017] [Indexed: 12/18/2022]
Abstract
PURPOSE Full-slice magnetic resonance spectroscopic imaging at ≥7 T is especially vulnerable to lipid contaminations arising from regions close to the skull. This contamination can be mitigated by improving the point spread function via higher spatial resolution sampling and k-space filtering, but this prolongs scan times and reduces the signal-to-noise ratio (SNR) efficiency. Currently applied parallel imaging methods accelerate magnetic resonance spectroscopic imaging scans at 7T, but increase lipid artifacts and lower SNR-efficiency further. In this study, we propose an SNR-efficient spatial-spectral sampling scheme using concentric circle echo planar trajectories (CONCEPT), which was adapted to intrinsically acquire a Hamming-weighted k-space, thus termed density-weighted-CONCEPT. This minimizes voxel bleeding, while preserving an optimal SNR. THEORY AND METHODS Trajectories were theoretically derived and verified in phantoms as well as in the human brain via measurements of five volunteers (single-slice, field-of-view 220 × 220 mm2 , matrix 64 × 64, scan time 6 min) with free induction decay magnetic resonance spectroscopic imaging. Density-weighted-CONCEPT was compared to (a) the originally proposed CONCEPT with equidistant circles (here termed e-CONCEPT), (b) elliptical phase-encoding, and (c) 5-fold Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration accelerated elliptical phase-encoding. RESULTS By intrinsically sampling a Hamming-weighted k-space, density-weighted-CONCEPT removed Gibbs-ringing artifacts and had in vivo +9.5%, +24.4%, and +39.7% higher SNR than e-CONCEPT, elliptical phase-encoding, and the Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration accelerated elliptical phase-encoding (all P < 0.05), respectively, which lead to improved metabolic maps. CONCLUSION Density-weighted-CONCEPT provides clinically attractive full-slice high-resolution magnetic resonance spectroscopic imaging with optimal SNR at 7T. Magn Reson Med 79:2874-2885, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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Affiliation(s)
- Lukas Hingerl
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Wolfgang Bogner
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Christian Doppler Laboratory for Clinical Molecular MR ImagingMedical University of ViennaViennaAustria
| | - Philipp Moser
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Michal Považan
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Gilbert Hangel
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Eva Heckova
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Stephan Gruber
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
| | - Siegfried Trattnig
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Christian Doppler Laboratory for Clinical Molecular MR ImagingMedical University of ViennaViennaAustria
| | - Bernhard Strasser
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
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Lee CY, Choi IY, Lee P. Prospective frequency correction using outer volume suppression-localized navigator for MR spectroscopy and spectroscopic imaging. Magn Reson Med 2018; 80:2366-2373. [PMID: 29756324 PMCID: PMC6234100 DOI: 10.1002/mrm.27340] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2018] [Revised: 04/11/2018] [Accepted: 04/12/2018] [Indexed: 12/26/2022]
Abstract
PURPOSE New frequency correction methods are required to achieve the accurate measurement of frequency drifts in MRS and MRSI. We present a prospective frequency correction method with outer volume suppression (OVS)-based localization and selective water excitation for effective frequency correction with better SNR improvement compared to other techniques. METHODS An OVS-localized navigator was developed to prospectively correct frequency drifts during MRS and MRSI measurements. The performance of the navigator was tested on the human brain and a solution phantom for frequency drifts induced by head motion or gradient heating by a preceding DWI experiment at 3T. RESULTS The OVS-localized navigator could accurately track motion-induced frequency drifts with an RMS error of 0.5 Hz. The SNR of MRS signals was not affected by use of the OVS-localized navigator when compared with and without the navigator (P > 0.05). The frequency drifts induced by DWI experiments were 5.1 ± 0.3 Hz/min during MRSI measurements on humans, resulting in increased spectral linewidth, significant bias in metabolite concentrations, and significantly increased Cramér-Rao lower bounds (P < 0.05). After prospective frequency corrections, the quality of MRSI was recovered to the level of those without any DWI-induced frequency drifts, judged by the spectral linewidth, metabolite concentrations, and Cramér-Rao lower bounds. CONCLUSION The OVS-localized navigator demonstrated effective prospective frequency corrections for large frequency drifts (5 Hz/min) without introducing any saturation-induced SNR loss. These benefits can be particularly beneficial for the acquisition of MRS signals with long T1 and/or short TR, and spectral editing.
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Affiliation(s)
- Chu-Yu Lee
- Hoglund Brain Imaging Center, University of Kansas Medical Center, Kansas City, Kansas
| | - In-Young Choi
- Hoglund Brain Imaging Center, University of Kansas Medical Center, Kansas City, Kansas.,Department of Neurology, University of Kansas Medical Center, Kansas City, Kansas.,Department of Molecular & Integrative Physiology, University of Kansas Medical Center, Kansas City, Kansas
| | - Phil Lee
- Hoglund Brain Imaging Center, University of Kansas Medical Center, Kansas City, Kansas.,Department of Molecular & Integrative Physiology, University of Kansas Medical Center, Kansas City, Kansas
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Chang P, Nassirpour S, Eschelbach M, Scheffler K, Henning A. Constrained optimization for position calibration of an NMR field camera. Magn Reson Med 2017; 80:380-390. [PMID: 29159823 DOI: 10.1002/mrm.27010] [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: 06/22/2017] [Revised: 10/23/2017] [Accepted: 10/25/2017] [Indexed: 11/07/2022]
Abstract
PURPOSE Knowledge of the positions of field probes in an NMR field camera is necessary for monitoring the B0 field. The typical method of estimating these positions is by switching the gradients with known strengths and calculating the positions using the phases of the FIDs. We investigated improving the accuracy of estimating the probe positions and analyzed the effect of inaccurate estimations on field monitoring. METHODS The field probe positions were estimated by 1) assuming ideal gradient fields, 2) using measured gradient fields (including nonlinearities), and 3) using measured gradient fields with relative position constraints. The fields measured with the NMR field camera were compared to fields acquired using a dual-echo gradient recalled echo B0 mapping sequence. Comparisons were done for shim fields from second- to fourth-order shim terms. RESULTS The position estimation was the most accurate when relative position constraints were used in conjunction with measured (nonlinear) gradient fields. The effect of more accurate position estimates was seen when compared to fields measured using a B0 mapping sequence (up to 10%-15% more accurate for some shim fields). The models acquired from the field camera are sensitive to noise due to the low number of spatial sample points. CONCLUSION Position estimation of field probes in an NMR camera can be improved using relative position constraints and nonlinear gradient fields. Magn Reson Med 80:380-390, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Paul Chang
- Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- IMPRS for Cognitive and Systems Neuroscience, Eberhard-Karls University of Tuebingen, Germany
| | - Sahar Nassirpour
- Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- IMPRS for Cognitive and Systems Neuroscience, Eberhard-Karls University of Tuebingen, Germany
| | - Martin Eschelbach
- Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Department of Physics, Eberhard-Karls University of Tuebingen, Germany
| | - Klaus Scheffler
- Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Department of Biomedical Magnetic Resonance, Eberhard-Karls University of Tuebingen, Germany
| | - Anke Henning
- Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Department of Physics, University of Greifswald, Greifswald, Germany
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Heckova E, Považan M, Strasser B, Krumpolec P, Hnilicová P, Hangel GJ, Moser PA, Andronesi OC, van der Kouwe AJ, Valkovic P, Ukropcova B, Trattnig S, Bogner W. Real-time Correction of Motion and Imager Instability Artifacts during 3D γ-Aminobutyric Acid-edited MR Spectroscopic Imaging. Radiology 2017; 286:666-675. [PMID: 28957645 DOI: 10.1148/radiol.2017170744] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Purpose To compare the involuntary head motion, frequency and B0 shim changes, and effects on data quality during real-time-corrected three-dimensional γ-aminobutyric acid-edited magnetic resonance (MR) spectroscopic imaging in subjects with mild cognitive impairment (MCI), patients with Parkinson disease (PD), and young and older healthy volunteers. Materials and Methods In this prospective study, MR spectroscopic imaging datasets were acquired at 3 T after written informed consent was obtained. Translational and rotational head movement, frequency, and B0 shim were determined with an integrated volumetric navigator. Head motion patterns and imager instability were investigated in 33 young healthy control subjects (mean age ± standard deviation, 31 years ± 5), 34 older healthy control subjects (mean age, 67 years ± 8), 34 subjects with MCI (mean age, 72 years ± 5), and 44 patients with PD (mean age, 64 years ± 8). Spectral quality was assessed by means of region-of-interest analysis. Group differences were evaluated with Bonferroni-corrected Mann-Whitney tests. Results Three patients with PD and four subjects with MCI were excluded because of excessive head motion (ie, > 0.8 mm translation per repetition time of 1.6 seconds throughout >10 minutes). Older control subjects, patients with PD, and subjects with MCI demonstrated 1.5, 2, and 2.5 times stronger head movement, respectively, than did young control subjects (1.79 mm ± 0.77) (P < .001). Of young control subjects, older control subjects, patients with PD, and subjects with MCI, 6%, 35%, 38%, and 51%, respectively, moved more than 3 mm during the MR spectroscopic imaging acquisition of approximately 20 minutes. The predominant movements were head nodding and "sliding out" of the imager. Frequency changes were 1.1- and 1.4-fold higher in patients with PD (P = .007) and subjects with MCI (P < .001), respectively, and B0 shim changes were 1.3-, 1.5-, and 1.9-fold higher in older control subjects (P = .005), patients with PD (P < .001), and patients with MCI (P < .001), respectively, compared with those of young control subjects (12.59 Hz ± 2.49, 3.61 Hz · cm-1 ± 1.25). Real-time correction provided high spectral quality in all four groups (signal-to-noise ratio >15, Cramér-Rao lower bounds < 20%). Conclusion Real-time motion and B0 monitoring provides valuable information about motion patterns and B0 field variations in subjects with different predispositions for head movement. Immediate correction improves data quality, particularly in patients who have difficulty avoiding movement. © RSNA, 2017 Online supplemental material is available for this article.
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Affiliation(s)
- Eva Heckova
- From the High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria (E.H., M.P., B.S., G.J.H., P.A.M., S.T., W.B.); Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria (M.P., S.T., W.B.); Division of Neurosciences, Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia (P.H.); Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (O.C.A., A.J.v.d.K.); Institute of Experimental Endocrinology, Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovakia (P.K., B.U.); and 2nd Department of Neurology (P.V.) and Institute of Pathological Physiology (B.U.), Faculty of Medicine, Comenius University in Bratislava, Bratislava, Slovakia
| | - Michal Považan
- From the High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria (E.H., M.P., B.S., G.J.H., P.A.M., S.T., W.B.); Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria (M.P., S.T., W.B.); Division of Neurosciences, Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia (P.H.); Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (O.C.A., A.J.v.d.K.); Institute of Experimental Endocrinology, Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovakia (P.K., B.U.); and 2nd Department of Neurology (P.V.) and Institute of Pathological Physiology (B.U.), Faculty of Medicine, Comenius University in Bratislava, Bratislava, Slovakia
| | - Bernhard Strasser
- From the High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria (E.H., M.P., B.S., G.J.H., P.A.M., S.T., W.B.); Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria (M.P., S.T., W.B.); Division of Neurosciences, Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia (P.H.); Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (O.C.A., A.J.v.d.K.); Institute of Experimental Endocrinology, Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovakia (P.K., B.U.); and 2nd Department of Neurology (P.V.) and Institute of Pathological Physiology (B.U.), Faculty of Medicine, Comenius University in Bratislava, Bratislava, Slovakia
| | - Patrik Krumpolec
- From the High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria (E.H., M.P., B.S., G.J.H., P.A.M., S.T., W.B.); Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria (M.P., S.T., W.B.); Division of Neurosciences, Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia (P.H.); Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (O.C.A., A.J.v.d.K.); Institute of Experimental Endocrinology, Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovakia (P.K., B.U.); and 2nd Department of Neurology (P.V.) and Institute of Pathological Physiology (B.U.), Faculty of Medicine, Comenius University in Bratislava, Bratislava, Slovakia
| | - Petra Hnilicová
- From the High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria (E.H., M.P., B.S., G.J.H., P.A.M., S.T., W.B.); Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria (M.P., S.T., W.B.); Division of Neurosciences, Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia (P.H.); Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (O.C.A., A.J.v.d.K.); Institute of Experimental Endocrinology, Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovakia (P.K., B.U.); and 2nd Department of Neurology (P.V.) and Institute of Pathological Physiology (B.U.), Faculty of Medicine, Comenius University in Bratislava, Bratislava, Slovakia
| | - Gilbert J Hangel
- From the High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria (E.H., M.P., B.S., G.J.H., P.A.M., S.T., W.B.); Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria (M.P., S.T., W.B.); Division of Neurosciences, Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia (P.H.); Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (O.C.A., A.J.v.d.K.); Institute of Experimental Endocrinology, Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovakia (P.K., B.U.); and 2nd Department of Neurology (P.V.) and Institute of Pathological Physiology (B.U.), Faculty of Medicine, Comenius University in Bratislava, Bratislava, Slovakia
| | - Philipp A Moser
- From the High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria (E.H., M.P., B.S., G.J.H., P.A.M., S.T., W.B.); Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria (M.P., S.T., W.B.); Division of Neurosciences, Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia (P.H.); Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (O.C.A., A.J.v.d.K.); Institute of Experimental Endocrinology, Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovakia (P.K., B.U.); and 2nd Department of Neurology (P.V.) and Institute of Pathological Physiology (B.U.), Faculty of Medicine, Comenius University in Bratislava, Bratislava, Slovakia
| | - Ovidiu C Andronesi
- From the High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria (E.H., M.P., B.S., G.J.H., P.A.M., S.T., W.B.); Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria (M.P., S.T., W.B.); Division of Neurosciences, Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia (P.H.); Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (O.C.A., A.J.v.d.K.); Institute of Experimental Endocrinology, Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovakia (P.K., B.U.); and 2nd Department of Neurology (P.V.) and Institute of Pathological Physiology (B.U.), Faculty of Medicine, Comenius University in Bratislava, Bratislava, Slovakia
| | - Andre J van der Kouwe
- From the High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria (E.H., M.P., B.S., G.J.H., P.A.M., S.T., W.B.); Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria (M.P., S.T., W.B.); Division of Neurosciences, Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia (P.H.); Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (O.C.A., A.J.v.d.K.); Institute of Experimental Endocrinology, Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovakia (P.K., B.U.); and 2nd Department of Neurology (P.V.) and Institute of Pathological Physiology (B.U.), Faculty of Medicine, Comenius University in Bratislava, Bratislava, Slovakia
| | - Peter Valkovic
- From the High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria (E.H., M.P., B.S., G.J.H., P.A.M., S.T., W.B.); Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria (M.P., S.T., W.B.); Division of Neurosciences, Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia (P.H.); Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (O.C.A., A.J.v.d.K.); Institute of Experimental Endocrinology, Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovakia (P.K., B.U.); and 2nd Department of Neurology (P.V.) and Institute of Pathological Physiology (B.U.), Faculty of Medicine, Comenius University in Bratislava, Bratislava, Slovakia
| | - Barbara Ukropcova
- From the High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria (E.H., M.P., B.S., G.J.H., P.A.M., S.T., W.B.); Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria (M.P., S.T., W.B.); Division of Neurosciences, Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia (P.H.); Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (O.C.A., A.J.v.d.K.); Institute of Experimental Endocrinology, Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovakia (P.K., B.U.); and 2nd Department of Neurology (P.V.) and Institute of Pathological Physiology (B.U.), Faculty of Medicine, Comenius University in Bratislava, Bratislava, Slovakia
| | - Siegfried Trattnig
- From the High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria (E.H., M.P., B.S., G.J.H., P.A.M., S.T., W.B.); Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria (M.P., S.T., W.B.); Division of Neurosciences, Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia (P.H.); Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (O.C.A., A.J.v.d.K.); Institute of Experimental Endocrinology, Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovakia (P.K., B.U.); and 2nd Department of Neurology (P.V.) and Institute of Pathological Physiology (B.U.), Faculty of Medicine, Comenius University in Bratislava, Bratislava, Slovakia
| | - Wolfgang Bogner
- From the High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria (E.H., M.P., B.S., G.J.H., P.A.M., S.T., W.B.); Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria (M.P., S.T., W.B.); Division of Neurosciences, Biomedical Center Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia (P.H.); Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (O.C.A., A.J.v.d.K.); Institute of Experimental Endocrinology, Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovakia (P.K., B.U.); and 2nd Department of Neurology (P.V.) and Institute of Pathological Physiology (B.U.), Faculty of Medicine, Comenius University in Bratislava, Bratislava, Slovakia
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Joers JM, Deelchand DK, Kumar A, Moheet A, Seaquist E, Henry PG, Öz G. Measurement of Hypothalamic Glucose Under Euglycemia and Hyperglycemia by MRI at 3T. J Magn Reson Imaging 2017; 45:681-691. [PMID: 27402249 PMCID: PMC5575789 DOI: 10.1002/jmri.25383] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2016] [Accepted: 06/21/2016] [Indexed: 12/26/2022] Open
Abstract
PURPOSE To evaluate the feasibility of using a clinical magnetic resonance (MR) system and MR spectroscopy (MRS) to measure glucose concentration changes in the human hypothalamus, a structure central to whole-body glucose regulation. SUBJECTS AND METHODS A time series of MR spectra (semi-LASER, TE = 28 msec), localized to the bilateral hypothalamus (∼1.6 ml) were obtained at 3T in six healthy subjects at baseline (euglycemia) and during a ∼65-70-minute-long hyperglycemic clamp in 11-minute blocks with interleaved T1 FLASH images to retrospectively assess head motion, and track changes in cerebrospinal fluid (CSF) partial volume. The LCModel was used to quantify the sum of glucose and taurine concentrations, [Glc+Tau], along with their associated Cramér-Rao lower bounds (CRLB). RESULTS Spectral quality allowed quantification of [Glc+Tau] (sum reported due to high negative correlation between these metabolites) with CRLB <25% in 35/36 timepoints during hyperglycemia. Increased [Glc+Tau] was observed with hyperglycemia in all subjects, but most reliably in those with plasma glucose targets ≥300 mg/dl. For these subjects, [Glc+Tau]baseline (n = 4) was 1.5 (±0.3, SD) mM, and increased to 4.5 (±1.1) mM (n = 16) for timepoints acquired ≥25 minutes after onset of the clamp, with 15/16 timepoints having no overlap of 95% confidence intervals (CIs) between baseline and hyperglycemia. Preliminary analysis revealed a linear (1:5) relationship between hypothalamus-blood glucose concentrations. CONCLUSION It is feasible to measure glucose concentration changes in the human hypothalamus using a standard 3T scanner and a short-echo semi-LASER sequence by utilizing retrospective motion tracking, CSF correction, predetermined quality acceptance criteria, and hyperglycemic blood glucose levels ≥300 mg/dl. LEVEL OF EVIDENCE 2 J. Magn. Reson. Imaging 2017;45:681-691.
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Affiliation(s)
- James M. Joers
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Dinesh K. Deelchand
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Anjali Kumar
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, University of Minnesota, Minneapolis, Minnesota, USA
| | - Amir Moheet
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, University of Minnesota, Minneapolis, Minnesota, USA
| | - Elizabeth Seaquist
- Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, University of Minnesota, Minneapolis, Minnesota, USA
| | - Pierre-Gilles Henry
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Gülin Öz
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA
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49
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Al-Iedani O, Lechner-Scott J, Ribbons K, Ramadan S. Fast magnetic resonance spectroscopic imaging techniques in human brain- applications in multiple sclerosis. J Biomed Sci 2017; 24:17. [PMID: 28245815 PMCID: PMC5331701 DOI: 10.1186/s12929-017-0323-2] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2016] [Accepted: 02/08/2017] [Indexed: 01/04/2023] Open
Abstract
Multi voxel magnetic resonance spectroscopic imaging (MRSI) is an important imaging tool that combines imaging and spectroscopic techniques. MRSI of the human brain has been beneficially applied to different clinical applications in neurology, particularly in neurooncology but also in multiple sclerosis, stroke and epilepsy. However, a major challenge in conventional MRSI is the longer acquisition time required for adequate signal to be collected. Fast MRSI of the brain in vivo is an alternative approach to reduce scanning time and make MRSI more clinically suitable.Fast MRSI can be categorised into spiral, echo-planar, parallel and turbo imaging techniques, each with its own strengths. After a brief introduction on the basics of non-invasive examination (1H-MRS) and localization techniques principles, different fast MRSI techniques will be discussed from their initial development to the recent innovations with particular emphasis on their capacity to record neurochemical changes in the brain in a variety of pathologies.The clinical applications of whole brain fast spectroscopic techniques, can assist in the assessment of neurochemical changes in the human brain and help in understanding the roles they play in disease. To give a good example of the utilities of these techniques in clinical context, MRSI application in multiple sclerosis was chosen. The available up to date and relevant literature is discussed and an outline of future research is presented.
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Affiliation(s)
- Oun Al-Iedani
- School of Health Sciences, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW 2308, Australia
| | - Jeannette Lechner-Scott
- School of Medicine and Public Health, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW 2308, Australia.,Department of Neurology, John Hunter Hospital, Lookout Road, New Lambton, NSW 2305, Australia.,Hunter Medical Research Institute, Kookaburra Circuit, New Lambton, NSW 2305, Australia
| | - Karen Ribbons
- Department of Neurology, John Hunter Hospital, Lookout Road, New Lambton, NSW 2305, Australia
| | - Saadallah Ramadan
- School of Health Sciences, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW 2308, Australia.
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50
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Jain S, Sima DM, Sanaei Nezhad F, Hangel G, Bogner W, Williams S, Van Huffel S, Maes F, Smeets D. Patch-Based Super-Resolution of MR Spectroscopic Images: Application to Multiple Sclerosis. Front Neurosci 2017; 11:13. [PMID: 28197066 PMCID: PMC5281632 DOI: 10.3389/fnins.2017.00013] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2016] [Accepted: 01/09/2017] [Indexed: 01/16/2023] Open
Abstract
Purpose: Magnetic resonance spectroscopic imaging (MRSI) provides complementary information to conventional magnetic resonance imaging. Acquiring high resolution MRSI is time consuming and requires complex reconstruction techniques. Methods: In this paper, a patch-based super-resolution method is presented to increase the spatial resolution of metabolite maps computed from MRSI. The proposed method uses high resolution anatomical MR images (T1-weighted and Fluid-attenuated inversion recovery) to regularize the super-resolution process. The accuracy of the method is validated against conventional interpolation techniques using a phantom, as well as simulated and in vivo acquired human brain images of multiple sclerosis subjects. Results: The method preserves tissue contrast and structural information, and matches well with the trend of acquired high resolution MRSI. Conclusions: These results suggest that the method has potential for clinically relevant neuroimaging applications.
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Affiliation(s)
| | - Diana M Sima
- icometrix, R&DLeuven, Belgium; Department of Electrical Engineering-ESAT, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU LeuvenLeuven, Belgium
| | | | - Gilbert Hangel
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna Vienna, Austria
| | - Wolfgang Bogner
- High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of ViennaVienna, Austria; Christian Doppler Laboratory for Clinical Molecular MR ImagingVienna, Austria
| | - Stephen Williams
- Centre for Imaging Sciences, University of Manchester Manchester, UK
| | - Sabine Van Huffel
- Department of Electrical Engineering-ESAT, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU LeuvenLeuven, Belgium; ImecLeuven, Belgium
| | - Frederik Maes
- Department of Electrical Engineering-ESAT, PSI Medical Image Computing, KU Leuven Leuven, Belgium
| | - Dirk Smeets
- icometrix, R&DLeuven, Belgium; BioImaging Lab, Universiteit AntwerpenAntwerp, Belgium
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