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Klauser A, Klauser P, Grouiller F, Courvoisier S, Lazeyras F. Whole-brain high-resolution metabolite mapping with 3D compressed-sensing SENSE low-rank 1 H FID-MRSI. NMR IN BIOMEDICINE 2022; 35:e4615. [PMID: 34595791 PMCID: PMC9285075 DOI: 10.1002/nbm.4615] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 08/16/2021] [Accepted: 08/20/2021] [Indexed: 05/07/2023]
Abstract
There is a growing interest in the neuroscience community to map the distribution of brain metabolites in vivo. Magnetic resonance spectroscopic imaging (MRSI) is often limited by either a poor spatial resolution and/or a long acquisition time, which severely restricts its applications for clinical and research purposes. Building on a recently developed technique of acquisition-reconstruction for 2D MRSI, we combined a fast Cartesian 1 H-FID-MRSI acquisition sequence, compressed-sensing acceleration, and low-rank total-generalized-variation constrained reconstruction to produce 3D high-resolution whole-brain MRSI with a significant acquisition time reduction. We first evaluated the acceleration performance using retrospective undersampling of a fully sampled dataset. Second, a 20 min accelerated MRSI acquisition was performed on three healthy volunteers, resulting in metabolite maps with 5 mm isotropic resolution. The metabolite maps exhibited the detailed neurochemical composition of all brain regions and revealed parts of the underlying brain anatomy. The latter assessment used previous reported knowledge and a atlas-based analysis to show consistency of the concentration contrasts and ratio across all brain regions. These results acquired on a clinical 3 T MRI scanner successfully combined 3D 1 H-FID-MRSI with a constrained reconstruction to produce detailed mapping of metabolite concentrations at high resolution over the whole brain, with an acquisition time suitable for clinical or research settings.
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Affiliation(s)
- Antoine Klauser
- Department of Radiology and Medical InformaticsUniversity of GenevaSwitzerland
- Center for Biomedical Imaging (CIBM)GenevaSwitzerland
| | - Paul Klauser
- Center for Psychiatric Neuroscience, Department of PsychiatryLausanne University HospitalSwitzerland
- Service of Child and Adolescent Psychiatry, Department of PsychiatryLausanne University HospitalSwitzerland
| | - Frédéric Grouiller
- Swiss Center for Affective SciencesUniversity of GenevaSwitzerland
- Laboratory of Behavioral Neurology and Imaging of Cognition, Department of Fundamental NeuroscienceUniversity of GenevaSwitzerland
| | - Sébastien Courvoisier
- Department of Radiology and Medical InformaticsUniversity of GenevaSwitzerland
- Center for Biomedical Imaging (CIBM)GenevaSwitzerland
| | - François Lazeyras
- Department of Radiology and Medical InformaticsUniversity of GenevaSwitzerland
- Center for Biomedical Imaging (CIBM)GenevaSwitzerland
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2
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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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Klauser A, Strasser B, Thapa B, Lazeyras F, Andronesi O. Achieving high-resolution 1H-MRSI of the human brain with compressed-sensing and low-rank reconstruction at 7 Tesla. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2021; 331:107048. [PMID: 34438355 PMCID: PMC8717865 DOI: 10.1016/j.jmr.2021.107048] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 06/29/2021] [Accepted: 08/08/2021] [Indexed: 06/02/2023]
Abstract
Low sensitivity MR techniques such as magnetic resonance spectroscopic imaging (MRSI) greatly benefit from the gain in signal-to-noise provided by ultra-high field MR. High-resolution and whole-slab brain MRSI remains however very challenging due to lengthy acquisition, low signal, lipid contamination and field inhomogeneity. In this study, we propose an acquisition-reconstruction scheme that combines 1H free-induction-decay (FID)-MRSI sequence, short TR acquisition, compressed sensing acceleration and low-rank modeling with total-generalized-variation constraint to achieve metabolite imaging in two and three dimensions at 7 Tesla. The resulting images and volumes reveal highly detailed distributions that are specific to each metabolite and follow the underlying brain anatomy. The MRSI method was validated in a high-resolution phantom containing fine metabolite structures, and in five healthy volunteers. This new application of compressed sensing acceleration paves the way for high-resolution MRSI in clinical setting with acquisition times of 5 min for 2D MRSI at 2.5 mm and of 20 min for 3D MRSI at 3.3 mm isotropic.
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Affiliation(s)
- Antoine Klauser
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Department of Radiology and Medical Informatics, University of Geneva, Switzerland; Center for Biomedical Imaging (CIBM), Geneva, Switzerland.
| | - Bernhard Strasser
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Bijaya Thapa
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Francois Lazeyras
- Department of Radiology and Medical Informatics, University of Geneva, Switzerland; Center for Biomedical Imaging (CIBM), Geneva, Switzerland
| | - Ovidiu Andronesi
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
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Andronesi OC, Bhattacharyya PK, Bogner W, Choi IY, Hess AT, Lee P, Meintjes E, Tisdall MD, Zaitzev M, van der Kouwe A. Motion correction methods for MRS: experts' consensus recommendations. NMR IN BIOMEDICINE 2021; 34:e4364. [PMID: 33089547 PMCID: PMC7855523 DOI: 10.1002/nbm.4364] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2019] [Revised: 06/07/2020] [Accepted: 06/08/2020] [Indexed: 05/07/2023]
Abstract
Long acquisition times due to intrinsically low signal-to-noise ratio and the need for highly homogeneous B0 field make MRS particularly susceptible to motion or scanner instability compared with MRI. Motion-induced changes in both localization and shimming (ie B0 homogeneity) degrade MRS data quality. To mitigate the effects of motion three approaches can be employed: (1) subject immobilization, (2) retrospective correction, and (3) prospective real-time correction using internal and/or external tracking methods. Prospective real-time correction methods can simultaneously update localization and the B0 field to improve MRS data quality. While localization errors can be corrected with both internal (navigators) and external (optical camera, NMR probes) tracking methods, the B0 field correction requires internal navigator methods to measure the B0 field inside the imaged volume and the possibility to update the scanner shim hardware in real time. Internal and external tracking can rapidly update the MRS localization with submillimeter and subdegree precision, while scanner frequency and first-order shims of scanner hardware can be updated by internal methods every sequence repetition. These approaches are most well developed for neuroimaging, for which rigid transformation is primarily applicable. Real-time correction greatly improves the stability of MRS acquisition and quantification, as shown in clinical studies on subjects prone to motion, including children and patients with movement disorders, enabling robust measurement of metabolite signals including those with low concentrations, such as gamma-aminobutyric acid and glutathione. Thus, motion correction is recommended for MRS users and calls for tighter integration and wider availability of such methods by MR scanner manufacturers.
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Affiliation(s)
- Ovidiu C. Andronesi
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Corresponding Author: Ovidiu C. Andronesi, MD, PhD, Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Thirteenth Street, Charlestown, MA 02129, USA;
| | | | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University Vienna, Vienna, Austria
| | - In-Young Choi
- Department of Neurology, Hoglund Biomedical Imaging Center, University of Kansas Medical Center, Kansas City, KS, USA
| | - Aaron T. Hess
- University of Oxford Centre for Clinical Magnetic Resonance Research, Division of Cardiovascular Medicine, University of Oxford
| | - Phil Lee
- Department of Radiology, Hoglund Biomedical Imaging Center, University of Kansas Medical Center, Kansas City, KS, USA
| | - Ernesta Meintjes
- UCT Medical Imaging Research Unit, Division of Biomedical Engineering, Department of Human Biology, University of Cape Town
| | - M. Dylan Tisdall
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania
| | - Maxim Zaitzev
- Department of Radiology, Medical Physics, Medical Center, University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- High Field Magnetic Resonance Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - André van der Kouwe
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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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: 1.7] [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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6
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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: 2.8] [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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7
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Li X, Strasser B, Jafari-Khouzani K, Thapa B, Small J, Cahill DP, Dietrich J, Batchelor TT, Andronesi OC. Super-Resolution Whole-Brain 3D MR Spectroscopic Imaging for Mapping D-2-Hydroxyglutarate and Tumor Metabolism in Isocitrate Dehydrogenase 1-mutated Human Gliomas. Radiology 2020; 294:589-597. [PMID: 31909698 PMCID: PMC7053225 DOI: 10.1148/radiol.2020191529] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Revised: 10/04/2019] [Accepted: 11/05/2019] [Indexed: 12/11/2022]
Abstract
Background Isocitrate dehydrogenase (IDH) mutations are highly frequent in glioma, producing high levels of the oncometabolite D-2-hydroxyglutarate (D-2HG). Hence, D-2HG represents a valuable imaging marker for IDH-mutated human glioma. Purpose To develop and evaluate a super-resolution three-dimensional (3D) MR spectroscopic imaging strategy to map D-2HG and tumor metabolism in IDH-mutated human glioma. Materials and Methods Between March and September 2018, participants with IDH1-mutated gliomas and healthy participants were prospectively scanned with a 3-T whole-brain 3D MR spectroscopic imaging protocol optimized for D-2HG. The acquired D-2HG maps with a voxel size of 5.2 × 5.2 × 12 mm were upsampled to a voxel size of 1.7 × 1.7 × 3 mm using a super-resolution method that combined weighted total variation, feature-based nonlocal means, and high-spatial-resolution anatomic imaging priors. Validation with simulated healthy and patient data and phantom measurements was also performed. The Mann-Whitney U test was used to check that the proposed super-resolution technique yields the highest peak signal-to-noise ratio and structural similarity index. Results Three participants with IDH1-mutated gliomas (mean age, 50 years ± 21 [standard deviation]; two men) and three healthy participants (mean age, 32 years ± 3; two men) were scanned. Twenty healthy participants (mean age, 33 years ± 5; 16 men) underwent a simulation of upsampled MR spectroscopic imaging. Super-resolution upsampling improved peak signal-to-noise ratio and structural similarity index by 62% (P < .05) and 7.3% (P < .05), respectively, for simulated data when compared with spline interpolation. Correspondingly, the proposed method significantly improved tissue contrast and structural information for the acquired 3D MR spectroscopic imaging data. Conclusion High-spatial-resolution whole-brain D-2-hydroxyglutarate imaging is possible in isocitrate dehydrogenase 1-mutated human glioma by using a super-resolution framework to upsample three-dimensional MR spectroscopic images acquired at lower resolution. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Huang and Lin in this issue.
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Affiliation(s)
- Xianqi Li
- From the A. A. Martinos Center for Biomedical Imaging, Department of
Radiology, Massachusetts General Hospital, 149 13th St, Suite 2301, Charlestown,
MA 02129 (X.L., B.S., B.T., O.C.A.); iCAD, Nashua, NH (K.J.); Departments of
Neurosurgery (J.S., D.P.C.) and Neurology (J.D.), Massachusetts General
Hospital, Boston, Mass; Department of Neurology, Brigham and Women’s
Hospital, Boston, Mass (T.T.B.); and Dana-Farber Cancer Institute, Boston, Mass
(T.T.B.)
| | - Bernhard Strasser
- From the A. A. Martinos Center for Biomedical Imaging, Department of
Radiology, Massachusetts General Hospital, 149 13th St, Suite 2301, Charlestown,
MA 02129 (X.L., B.S., B.T., O.C.A.); iCAD, Nashua, NH (K.J.); Departments of
Neurosurgery (J.S., D.P.C.) and Neurology (J.D.), Massachusetts General
Hospital, Boston, Mass; Department of Neurology, Brigham and Women’s
Hospital, Boston, Mass (T.T.B.); and Dana-Farber Cancer Institute, Boston, Mass
(T.T.B.)
| | - Kourosh Jafari-Khouzani
- From the A. A. Martinos Center for Biomedical Imaging, Department of
Radiology, Massachusetts General Hospital, 149 13th St, Suite 2301, Charlestown,
MA 02129 (X.L., B.S., B.T., O.C.A.); iCAD, Nashua, NH (K.J.); Departments of
Neurosurgery (J.S., D.P.C.) and Neurology (J.D.), Massachusetts General
Hospital, Boston, Mass; Department of Neurology, Brigham and Women’s
Hospital, Boston, Mass (T.T.B.); and Dana-Farber Cancer Institute, Boston, Mass
(T.T.B.)
| | - Bijaya Thapa
- From the A. A. Martinos Center for Biomedical Imaging, Department of
Radiology, Massachusetts General Hospital, 149 13th St, Suite 2301, Charlestown,
MA 02129 (X.L., B.S., B.T., O.C.A.); iCAD, Nashua, NH (K.J.); Departments of
Neurosurgery (J.S., D.P.C.) and Neurology (J.D.), Massachusetts General
Hospital, Boston, Mass; Department of Neurology, Brigham and Women’s
Hospital, Boston, Mass (T.T.B.); and Dana-Farber Cancer Institute, Boston, Mass
(T.T.B.)
| | - Julia Small
- From the A. A. Martinos Center for Biomedical Imaging, Department of
Radiology, Massachusetts General Hospital, 149 13th St, Suite 2301, Charlestown,
MA 02129 (X.L., B.S., B.T., O.C.A.); iCAD, Nashua, NH (K.J.); Departments of
Neurosurgery (J.S., D.P.C.) and Neurology (J.D.), Massachusetts General
Hospital, Boston, Mass; Department of Neurology, Brigham and Women’s
Hospital, Boston, Mass (T.T.B.); and Dana-Farber Cancer Institute, Boston, Mass
(T.T.B.)
| | - Daniel P. Cahill
- From the A. A. Martinos Center for Biomedical Imaging, Department of
Radiology, Massachusetts General Hospital, 149 13th St, Suite 2301, Charlestown,
MA 02129 (X.L., B.S., B.T., O.C.A.); iCAD, Nashua, NH (K.J.); Departments of
Neurosurgery (J.S., D.P.C.) and Neurology (J.D.), Massachusetts General
Hospital, Boston, Mass; Department of Neurology, Brigham and Women’s
Hospital, Boston, Mass (T.T.B.); and Dana-Farber Cancer Institute, Boston, Mass
(T.T.B.)
| | - Jorg Dietrich
- From the A. A. Martinos Center for Biomedical Imaging, Department of
Radiology, Massachusetts General Hospital, 149 13th St, Suite 2301, Charlestown,
MA 02129 (X.L., B.S., B.T., O.C.A.); iCAD, Nashua, NH (K.J.); Departments of
Neurosurgery (J.S., D.P.C.) and Neurology (J.D.), Massachusetts General
Hospital, Boston, Mass; Department of Neurology, Brigham and Women’s
Hospital, Boston, Mass (T.T.B.); and Dana-Farber Cancer Institute, Boston, Mass
(T.T.B.)
| | - Tracy T. Batchelor
- From the A. A. Martinos Center for Biomedical Imaging, Department of
Radiology, Massachusetts General Hospital, 149 13th St, Suite 2301, Charlestown,
MA 02129 (X.L., B.S., B.T., O.C.A.); iCAD, Nashua, NH (K.J.); Departments of
Neurosurgery (J.S., D.P.C.) and Neurology (J.D.), Massachusetts General
Hospital, Boston, Mass; Department of Neurology, Brigham and Women’s
Hospital, Boston, Mass (T.T.B.); and Dana-Farber Cancer Institute, Boston, Mass
(T.T.B.)
| | - Ovidiu C. Andronesi
- From the A. A. Martinos Center for Biomedical Imaging, Department of
Radiology, Massachusetts General Hospital, 149 13th St, Suite 2301, Charlestown,
MA 02129 (X.L., B.S., B.T., O.C.A.); iCAD, Nashua, NH (K.J.); Departments of
Neurosurgery (J.S., D.P.C.) and Neurology (J.D.), Massachusetts General
Hospital, Boston, Mass; Department of Neurology, Brigham and Women’s
Hospital, Boston, Mass (T.T.B.); and Dana-Farber Cancer Institute, Boston, Mass
(T.T.B.)
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8
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Vidya Shankar R, Chang JC, Hu HH, Kodibagkar VD. Fast data acquisition techniques in magnetic resonance spectroscopic imaging. NMR IN BIOMEDICINE 2019; 32:e4046. [PMID: 30637822 DOI: 10.1002/nbm.4046] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2015] [Revised: 10/30/2018] [Accepted: 10/31/2018] [Indexed: 06/09/2023]
Abstract
Magnetic resonance spectroscopic imaging (MRSI) is an important technique for assessing the spatial variation of metabolites in vivo. The long scan times in MRSI limit clinical applicability due to patient discomfort, increased costs, motion artifacts, and limited protocol flexibility. Faster acquisition strategies can address these limitations and could potentially facilitate increased adoption of MRSI into routine clinical protocols with minimal addition to the current anatomical and functional acquisition protocols in terms of imaging time. Not surprisingly, a lot of effort has been devoted to the development of faster MRSI techniques that aim to capture the same underlying metabolic information (relative metabolite peak areas and spatial distribution) as obtained by conventional MRSI, in greatly reduced time. The gain in imaging time results, in some cases, in a loss of signal-to-noise ratio and/or in spatial and spectral blurring. This review examines the current techniques and advances in fast MRSI in two and three spatial dimensions and their applications. This review categorizes the acceleration techniques according to their strategy for acquisition of the k-space. Techniques such as fast/turbo-spin echo MRSI, echo-planar spectroscopic imaging, and non-Cartesian MRSI effectively cover the full k-space in a more efficient manner per TR . On the other hand, techniques such as parallel imaging and compressed sensing acquire fewer k-space points and employ advanced reconstruction algorithms to recreate the spatial-spectral information, which maintains statistical fidelity in test conditions (ie no statistically significant differences on voxel-wise comparisions) with the fully sampled data. The advantages and limitations of each state-of-the-art technique are reviewed in detail, concluding with a note on future directions and challenges in the field of fast spectroscopic imaging.
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Affiliation(s)
- Rohini Vidya Shankar
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - John C Chang
- Banner M D Anderson Cancer Center, Gilbert, AZ, USA
- School for Engineering of Matter, Transport and Energy, Arizona State University, Tempe, AZ, USA
| | - Houchun H Hu
- Department of Radiology and Medical Imaging, Phoenix Children's Hospital, Phoenix, AZ, USA
| | - Vikram D Kodibagkar
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA
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9
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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: 6.4] [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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10
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Klauser A, Courvoisier S, Kasten J, Kocher M, Guerquin-Kern M, Van De Ville D, Lazeyras F. Fast high-resolution brain metabolite mapping on a clinical 3T MRI by accelerated 1 H-FID-MRSI and low-rank constrained reconstruction. Magn Reson Med 2018; 81:2841-2857. [PMID: 30565314 DOI: 10.1002/mrm.27623] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Revised: 10/18/2018] [Accepted: 11/12/2018] [Indexed: 12/18/2022]
Abstract
PURPOSE Epitomizing the advantages of ultra short echo time and no chemical shift displacement error, high-resolution-free induction decay magnetic resonance spectroscopic imaging (FID-MRSI) sequences have proven to be highly effective in providing unbiased characterizations of metabolite distributions. However, its merits are often overshadowed in high-resolution settings by reduced signal-to-noise ratios resulting from the smaller voxel volumes procured by extensive phase encoding and the related acquisition times. METHODS To address these limitations, we here propose an acquisition and reconstruction scheme that offers both implicit dataset denoising and acquisition acceleration. Specifically, a slice selective high-resolution FID-MRSI sequence was implemented. Spectroscopic datasets were processed to remove fat contamination, and then reconstructed using a total generalized variation (TGV) regularized low-rank model. We further measured reconstruction performance for random undersampled data to assess feasibility of a compressed-sensing SENSE acceleration scheme. Performance of the lipid suppression was assessed using an ad hoc phantom, while that of the low-rank TGV reconstruction model was benchmarked using simulated MRSI data. To assess real-world performance, 2D FID-MRSI acquisitions of the brain in healthy volunteers were reconstructed using the proposed framework. RESULTS Results from the phantom and simulated data demonstrate that skull lipid contamination is effectively removed and that data reconstruction quality is improved with the low-rank TGV model. Also, we demonstrated that the presented acquisition and reconstruction methods are compatible with a compressed-sensing SENSE acceleration scheme. CONCLUSIONS An original reconstruction pipeline for 2D 1 H-FID-MRSI datasets was presented that places high-resolution metabolite mapping on 3T MR scanners within clinically feasible limits.
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Affiliation(s)
- Antoine Klauser
- Department of Radiology and Medical, Informatics, University of Geneva, Geneva, Switzerland
| | - Sebastien Courvoisier
- Department of Radiology and Medical, Informatics, University of Geneva, Geneva, Switzerland
| | - Jeffrey Kasten
- Department of Radiology and Medical, Informatics, University of Geneva, Geneva, Switzerland
| | - Michel Kocher
- Department of Radiology and Medical, Informatics, University of Geneva, Geneva, Switzerland
| | | | - Dimitri Van De Ville
- Department of Radiology and Medical, Informatics, University of Geneva, Geneva, Switzerland.,Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Francois Lazeyras
- Department of Radiology and Medical, Informatics, University of Geneva, Geneva, Switzerland
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11
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Tsai SY, Lin YR, Lin HY, Lin FH. Reduction of lipid contamination in MR spectroscopy imaging using signal space projection. Magn Reson Med 2018; 81:1486-1498. [PMID: 30277271 DOI: 10.1002/mrm.27496] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2018] [Revised: 06/22/2018] [Accepted: 07/25/2018] [Indexed: 12/27/2022]
Abstract
PURPOSE Lipid contamination can complicate the metabolite quantification in MR spectroscopic imaging (MRSI). In addition to various experimental methods demonstrated to be feasible for lipid suppression, the postprocessing method is beneficial in the flexibility of applications. In this study, the signal space projection (SSP) algorithm is proposed to suppress the lipid signal in the MRSI. METHODS The performance of lipid suppression using SSP and SSP combined with the Papoulis-Gerchberg (PG) algorithm (PG+SSP) is examined in 2D MRSI data and the results were compared with outer volume saturation (OVS) methods. Up to 10 lipid spatial components were extracted by SSP from lipid signals in the range of 0.8~1.5 ppm. RESULTS Our results show that most lipid signals were found in the first 4 to 5 components and that lipid signals on the spectra can be suppressed using 4 to 5 components. Metabolites concentrations were quantified using LCModel. Two regions of interest (ROIs) were manually selected on the peripheral and inner brain regions. The quantification of metabolites in terms of fitting reliability (CRLB) and spatial variations within ROIs (SpaVar) is improved using SSP. When 5 to 6 components were used in SSP and PG+SSP, the metabolite concentrations and the associated SpaVar and CRLB are at the same level as those from the OVS. CONCLUSION We have demonstrated that the SSP method can be used to suppress the lipid signals of MRSI and SSP with 5 to 6 components is suggested to have a similar suppression performance as the OVS method.
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Affiliation(s)
- Shang-Yueh Tsai
- Graduate Institute of Applied Physics, National Chengchi University, Taipei, Taiwan.,Research Center for Mind, Brain and Learning, National Chengchi University, Taipei, Taiwan
| | - Yi-Ru Lin
- Department of Electronic and Computer Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan
| | - Hsin-Yu Lin
- Department of Electronic and Computer Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan
| | - Fa-Hsuan Lin
- Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan
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12
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de Graaf RA, Brown PB, De Feyter HM, McIntyre S, Nixon TW. Elliptical localization with pulsed second-order fields (ECLIPSE) for robust lipid suppression in proton MRSI. NMR IN BIOMEDICINE 2018; 31:e3949. [PMID: 29985532 PMCID: PMC6108906 DOI: 10.1002/nbm.3949] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Revised: 04/02/2018] [Accepted: 04/27/2018] [Indexed: 05/21/2023]
Abstract
Proton MRSI has great clinical potential for metabolic mapping of the healthy and pathological human brain. Unfortunately, the promise has not yet been fully achieved due to numerous technical challenges related to insufficient spectral quality caused by magnetic field inhomogeneity, insufficient RF transmit power and incomplete lipid suppression. Here a robust, novel method for lipid suppression in 1 H MRSI is presented. The method is based on 2D spatial localization of an elliptical region of interest using pulsed second-order spherical harmonic (SH) magnetic fields. A dedicated, high-amplitude second-order SH gradient setup was designed and constructed, containing coils to generate Z2, X2Y2 and XY magnetic fields. Simulations and phantom MRI results are used to demonstrate the principles of the method and illustrate the manifestation of chemical shift displacement. 1 H MRSI on human brain in vivo demonstrates high quality, robust suppression of extracranial lipids. The method allows a wide range of inner or outer volume selection or suppression and should find application in MRSI, reduced-field-of-view MRI and single-volume MRS.
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Affiliation(s)
- Robin A. de Graaf
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, Connecticut, USA
- Department of Biomedical Engineering, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Peter B. Brown
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Henk M. De Feyter
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Scott McIntyre
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Terence W. Nixon
- Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University School of Medicine, New Haven, Connecticut, USA
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13
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Karlberg A, Berntsen EM, Johansen H, Myrthue M, Skjulsvik AJ, Reinertsen I, Esmaeili M, Dai HY, Xiao Y, Rivaz H, Borghammer P, Solheim O, Eikenes L. Multimodal 18 F-Fluciclovine PET/MRI and Ultrasound-Guided Neurosurgery of an Anaplastic Oligodendroglioma. World Neurosurg 2017; 108:989.e1-989.e8. [DOI: 10.1016/j.wneu.2017.08.085] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2017] [Revised: 08/10/2017] [Accepted: 08/12/2017] [Indexed: 11/28/2022]
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