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Yu M, Lin L, Xu K, Xu M, Ren J, Niu X, Gao X, Zhang M, Yang Z, Dang J, Tao Q, Han S, Wang W, Cheng J, Zhang Y. Changes in aspartate metabolism in the medial-prefrontal cortex of nicotine addicts based on J-edited magnetic resonance spectroscopy. Hum Brain Mapp 2023; 44:6429-6438. [PMID: 37909379 PMCID: PMC10681642 DOI: 10.1002/hbm.26519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Revised: 09/05/2023] [Accepted: 10/04/2023] [Indexed: 11/03/2023] Open
Abstract
This study aims to explore the changes of the aspartate (Asp) level in the medial-prefrontal cortex (mPFC) of subjects with nicotine addiction (nicotine addicts [NAs]) using the J-edited 1 H MR spectroscopy (MRS), which may provide a positive imaging evidence for intervention of NA. From March to August 2022, 45 males aged 40-60 years old were recruited from Henan Province, including 21 in NA and 24 in nonsmoker groups. All subjects underwent routine magnetic resonance imaging (MRI) and J-edited MRS scans on a 3.0 T MRI scanner. The Asp level in mPFC was quantified with reference to the total creatine (Asp/Cr) and water (Aspwater-corr , with correction of the brain tissue composition) signals, respectively. Two-tailed independent samples t-test was used to analyze the differences in levels of Asp and other coquantified metabolites (including total N-acetylaspartate [tNAA], total cholinine [tCho], total creatine [tCr], and myo-Inositol [mI]) between the two groups. Finally, the correlations of the Asp level with clinical characteristic assessment scales were performed using the Spearman criteria. Compared with the control group (n = 22), NAs (n = 18) had higher levels of Asp (Asp/Cr: p = .005; Aspwater-corr : p = .004) in the mPFC, and the level of Asp was positively correlated with the daily smoking amount (Asp/Cr: p < .001; Aspwater-corr : p = .004). No significant correlation was found between the level of Asp and the years of nicotine use, Fagerstrom Nicotine Dependence (FTND), Russell Reason for Smoking Questionnaire (RRSQ), or Barratt Impulsivity Scale (BIS-11) score. The elevated Asp level was observed in mPFC of NAs in contrast to nonsmokers, and the Asp level was positively correlated with the amount of daily smoking, which suggests that nicotine addiction may result in elevated Asp metabolism in the human brain.
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Affiliation(s)
- Miaomiao Yu
- Department of Magnetic Resonance ImagingThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Liangjie Lin
- Clinical and Technical SupportPhilips HealthcareBeijingChina
| | - Ke Xu
- Department of Magnetic Resonance ImagingThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Man Xu
- Department of Magnetic Resonance ImagingThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Jianxin Ren
- Department of Magnetic Resonance ImagingThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Xiaoyu Niu
- Department of Magnetic Resonance ImagingThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Xinyu Gao
- Department of Magnetic Resonance ImagingThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Mengzhe Zhang
- Department of Magnetic Resonance ImagingThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Zhengui Yang
- Department of Magnetic Resonance ImagingThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Jinghan Dang
- Department of Magnetic Resonance ImagingThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Qiuying Tao
- Department of Magnetic Resonance ImagingThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Shaoqiang Han
- Department of Magnetic Resonance ImagingThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Weijian Wang
- Department of Magnetic Resonance ImagingThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Jingliang Cheng
- Department of Magnetic Resonance ImagingThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Yong Zhang
- Department of Magnetic Resonance ImagingThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
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Gudmundson AT, Davies-Jenkins CW, Özdemir İ, Murali-Manohar S, Zöllner HJ, Song Y, Hupfeld KE, Schnitzler A, Oeltzschner G, Stark CEL, Edden RAE. Application of a 1H Brain MRS Benchmark Dataset to Deep Learning for Out-of-Voxel Artifacts. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.08.539813. [PMID: 37215030 PMCID: PMC10197548 DOI: 10.1101/2023.05.08.539813] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Neural networks are potentially valuable for many of the challenges associated with MRS data. The purpose of this manuscript is to describe the AGNOSTIC dataset, which contains 259,200 synthetic 1H MRS examples for training and testing neural networks. AGNOSTIC was created using 270 basis sets that were simulated across 18 field strengths and 15 echo times. The synthetic examples were produced to resemble in vivo brain data with combinations of metabolite, macromolecule, residual water signals, and noise. To demonstrate the utility, we apply AGNOSTIC to train two Convolutional Neural Networks (CNNs) to address out-of-voxel (OOV) echoes. A Detection Network was trained to identify the point-wise presence of OOV echoes, providing proof of concept for real-time detection. A Prediction Network was trained to reconstruct OOV echoes, allowing subtraction during post-processing. Complex OOV signals were mixed into 85% of synthetic examples to train two separate CNNs for the detection and prediction of OOV signals. AGNOSTIC is available through Dryad and all Python 3 code is available through GitHub. The Detection network was shown to perform well, identifying 95% of OOV echoes. Traditional modeling of these detected OOV signals was evaluated and may prove to be an effective method during linear-combination modeling. The Prediction Network greatly reduces OOV echoes within FIDs and achieved a median log10 normed-MSE of -1.79, an improvement of almost two orders of magnitude.
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Affiliation(s)
- Aaron T Gudmundson
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute
| | - Christopher W Davies-Jenkins
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute
| | - İpek Özdemir
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute
| | - Saipavitra Murali-Manohar
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute
| | - Helge J Zöllner
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute
| | - Yulu Song
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute
| | - Kathleen E Hupfeld
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute
| | - Alfons Schnitzler
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute
| | - Craig E L Stark
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins School of Medicine
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute
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Shams Z, Klomp DWJ, Boer VO, Wijnen JP, Wiegers EC. Identifying the source of spurious signals caused by B 0 inhomogeneities in single-voxel 1 H MRS. Magn Reson Med 2022; 88:71-82. [PMID: 35344600 PMCID: PMC9311141 DOI: 10.1002/mrm.29222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 02/04/2022] [Accepted: 02/19/2022] [Indexed: 12/04/2022]
Abstract
Purpose Single‐voxel MRS (SV MRS) requires robust volume localization as well as optimized crusher and phase‐cycling schemes to reduce artifacts arising from signal outside the volume of interest. However, due to local magnetic field gradients (B0 inhomogeneities), signal that was dephased by the crusher gradients during acquisition might rephase, leading to artifacts in the spectrum. Here, we analyzed this mechanism, aiming to identify the source of signals arising from unwanted coherence pathways (spurious signals) in SV MRS from a B0 map. Methods We investigated all possible coherence pathways associated with imperfect localization in a semi‐localized by adiabatic selective refocusing (semi‐LASER) sequence for potential rephasing of signals arising from unwanted coherence pathways by a local magnetic field gradient. We searched for locations in the B0 map where the signal dephasing due to external (crusher) and internal (B0) field gradients canceled out. To confirm the mechanism, SV‐MR spectra (TE = 31 ms) and 3D‐CSI data with the same volume localization as the SV experiments were acquired from a phantom and 2 healthy volunteers. Results Our analysis revealed that potential sources of spurious signals were scattered over multiple locations throughout the brain. This was confirmed by 3D‐CSI data. Moreover, we showed that the number of potential locations where spurious signals could originate from monotonically decreases with crusher strength. Conclusion We proposed a method to identify the source of spurious signals in SV 1H MRS using a B0 map. This can facilitate MRS sequence design to be less sensitive to experimental artifacts.
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Affiliation(s)
- Zahra Shams
- Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Dennis W J Klomp
- Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Vincent O Boer
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
| | - Jannie P Wijnen
- Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Evita C Wiegers
- Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
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4
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Berrington A, Považan M, Barker PB. Estimation and removal of spurious echo artifacts in single-voxel MRS using sensitivity encoding. Magn Reson Med 2021; 86:2339-2352. [PMID: 34184324 DOI: 10.1002/mrm.28848] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 04/10/2021] [Accepted: 04/26/2021] [Indexed: 11/11/2022]
Abstract
PURPOSE In localized MRS, spurious echo artifacts commonly occur when unsuppressed signal outside the volume of interest is excited and refocused. In the spectral domain, these signals often overlap with metabolite resonances and hinder accurate quantification. Because the artifacts originate from regions separate from the target MRS voxel, this work proposes that sensitivity encoding based on receive-coil sensitivity profiles may be used to separate these signal contributions. METHODS Numerical simulations were performed to explore the effect of sensitivity-encoded separation for unknown artifact regions. An imaging-based approach was developed to identify regions that may contribute to spurious echo artifacts, and tested for sensitivity-based unfolding of signal on six data sets from three brain regions. Spectral data reconstructed using the proposed method ("ERASE") were compared with the standard coil combination. RESULTS The method was able to fully unfold artifact signals if regions were known a priori. Mismatch between estimated and true artifact regions reduced the efficiency of removal, yet metabolite signals were unaffected. Water suppression imaging was able to identify regions of unsuppressed signal, and ERASE (from up to eight regions) led to visible removal of artifacts relative to standard reconstruction. Fitting errors across major metabolites were also lower; for example, Cramér-Rao lower bounds of myo-inositol were 13.7% versus 17.5% for ERASE versus standard reconstruction, respectively. CONCLUSION The ERASE reconstruction tool was demonstrated to reduce spurious echo artifacts in single-voxel MRS. This tool may be incorporated into standard workflows to improve spectral quality when hardware limitations or other factors result in out-of-voxel signal contamination.
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Affiliation(s)
- Adam Berrington
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom
| | - Michal Považan
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Peter B Barker
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
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5
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Gao X, Kiselev VG, Lange T, Hennig J, Zaitsev M. Three-dimensional spatially resolved phase graph framework. Magn Reson Med 2021; 86:551-560. [PMID: 33608963 DOI: 10.1002/mrm.28732] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 12/23/2020] [Accepted: 01/25/2021] [Indexed: 11/12/2022]
Abstract
PURPOSE An open-source spatially resolved phase graph framework is proposed for simulating arbitrary pulse sequences in the presence of piece-wise constant gradients with arbitrary orientations in three dimensions. It generalizes the extended phase graph algorithm for analysis of nonperiodic sequences while preserving its efficiency, and is able to estimate the signal modulation in the 3D spatial domain. METHODS The framework extends the recursive magnetization-evolution algorithm to account for anisotropic diffusion and exploits a novel 3D k-space grid-merging method to balance the computational effort and memory requirements against acceptable simulation errors. A new postsimulation module is proposed to track and visualize the signal evolution both in the k-space and in the image domain, which can be used for simulating image artifacts or finding frequency-response profiles. To illustrate the developed technique, three examples are presented: (1) fast off-resonance calculation for dictionary building in MR fingerprinting, (2) validation of a steady-state sequence with quasi-isotropic diffusion weighting, and (3) investigation of the magnetization evolution in PRESS-based spectroscopic imaging. RESULTS The grid-merging algorithm of the proposed framework demonstrates high calculation efficiency exemplified by frequency-response simulation of pseudo steady-state or diffusion-weighted steady-state sequences. It further helps to visualize the signal evolution in PRESS-based sequences. CONCLUSIONS The proposed simulation framework has been validated based on several different example applications for analyzing signal evolution in the frequency and spatial domain.
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Affiliation(s)
- Xiang Gao
- Department of Radiology, Medical Physics, Medical Center University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Valerij G Kiselev
- Department of Radiology, Medical Physics, Medical Center University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Thomas Lange
- Department of Radiology, Medical Physics, Medical Center University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Jürgen Hennig
- Department of Radiology, Medical Physics, Medical Center University of Freiburg, University of Freiburg, Freiburg, Germany
| | - Maxim Zaitsev
- Department of Radiology, Medical Physics, Medical Center University of Freiburg, University of Freiburg, Freiburg, Germany.,High Field Magnetic Resonance Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
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6
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Kreis R, Boer V, Choi I, Cudalbu C, de Graaf RA, Gasparovic C, Heerschap A, Krššák M, Lanz B, Maudsley AA, Meyerspeer M, Near J, Öz G, Posse S, Slotboom J, Terpstra M, Tkáč I, Wilson M, Bogner W. Terminology and concepts for the characterization of in vivo MR spectroscopy methods and MR spectra: Background and experts' consensus recommendations. NMR IN BIOMEDICINE 2020; 34:e4347. [PMID: 32808407 PMCID: PMC7887137 DOI: 10.1002/nbm.4347] [Citation(s) in RCA: 64] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Revised: 05/20/2020] [Accepted: 05/21/2020] [Indexed: 05/04/2023]
Abstract
With a 40-year history of use for in vivo studies, the terminology used to describe the methodology and results of magnetic resonance spectroscopy (MRS) has grown substantially and is not consistent in many aspects. Given the platform offered by this special issue on advanced MRS methodology, the authors decided to describe many of the implicated terms, to pinpoint differences in their meanings and to suggest specific uses or definitions. This work covers terms used to describe all aspects of MRS, starting from the description of the MR signal and its theoretical basis to acquisition methods, processing and to quantification procedures, as well as terms involved in describing results, for example, those used with regard to aspects of quality, reproducibility or indications of error. The descriptions of the meanings of such terms emerge from the descriptions of the basic concepts involved in MRS methods and examinations. This paper also includes specific suggestions for future use of terms where multiple conventions have emerged or coexisted in the past.
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Affiliation(s)
- Roland Kreis
- Department of Radiology, Neuroradiology, and Nuclear Medicine and Department of Biomedical ResearchUniversity BernBernSwitzerland
| | - Vincent Boer
- Danish Research Centre for Magnetic Resonance, Funktions‐ og Billeddiagnostisk EnhedCopenhagen University Hospital HvidovreHvidovreDenmark
| | - In‐Young Choi
- Department of Neurology, Hoglund Brain Imaging CenterUniversity of Kansas Medical CenterKansas CityKansasUSA
| | - Cristina Cudalbu
- Centre d'Imagerie Biomedicale (CIBM)Ecole Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland
| | - Robin A. de Graaf
- Department of Radiology and Biomedical Imaging & Department of Biomedical EngineeringYale UniversityNew HavenConnecticutUSA
| | | | - Arend Heerschap
- Department of Radiology and Nuclear MedicineRadboud University Medical CenterNijmegenThe Netherlands
| | - Martin Krššák
- Division of Endocrinology and Metabolism, Department of Internal Medicine III & High Field MR Centre, Department of Biomedical Imaging and Image guided TherapyMedical University of ViennaViennaAustria
| | - Bernard Lanz
- Laboratory of Functional and Metabolic Imaging (LIFMET)Ecole Polytechnique Fédérale de LausanneLausanneSwitzerland
- Sir Peter Mansfield Imaging Centre, School of MedicineUniversity of NottinghamNottinghamUK
| | - Andrew A. Maudsley
- Department of Radiology, Miller School of MedicineUniversity of MiamiMiamiFloridaUSA
| | - Martin Meyerspeer
- Center for Medical Physics and Biomedical EngineeringMedical University of ViennaViennaAustria
- High Field MR CenterMedical University of ViennaViennaAustria
| | - Jamie Near
- Douglas Mental Health University Institute and Department of PsychiatryMcGill UniversityMontrealCanada
| | - Gülin Öz
- Center for Magnetic Resonance Research, Department of RadiologyUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Stefan Posse
- Department of NeurologyUniversity of New Mexico School of MedicineAlbuquerqueNew MexicoUSA
| | - Johannes Slotboom
- Department of Radiology, Neuroradiology, and Nuclear MedicineUniversity Hospital BernBernSwitzerland
| | - Melissa Terpstra
- Center for Magnetic Resonance Research, Department of RadiologyUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Ivan Tkáč
- Center for Magnetic Resonance Research, Department of RadiologyUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Martin Wilson
- Centre for Human Brain Health and School of PsychologyUniversity of BirminghamBirminghamUK
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
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Landheer K, Juchem C. Simultaneous optimization of crusher and phase cycling schemes for magnetic resonance spectroscopy: an extension of dephasing optimization through coherence order pathway selection. Magn Reson Med 2019; 83:391-402. [PMID: 31529647 DOI: 10.1002/mrm.27952] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2019] [Revised: 07/25/2019] [Accepted: 07/26/2019] [Indexed: 12/20/2022]
Abstract
PURPOSE To extend the dephasing optimization through coherence order pathway selection (DOTCOPS) algorithm, originally designed solely for gradient crusher schemes, to include tailored phase cycling schemes for arbitrary pulse sequences and arbitrary number of coupled spins. THEORY AND METHODS The effects all possible nested and cogwheel phase cycling schemes have on the coherence order pathways for an arbitrary experiment are considered. The DOTCOPS algorithm uses a cost function to maximally eliminate unwanted coherence pathways, with schemes preferentially eliminating unwanted coherence pathways that are less affected by the crusher scheme. Efficacy was demonstrated experimentally in 2 separate MR spectroscopy (MRS) sequences: semi-localized adiabatic selective refocusing (sLASER) and MEscher-GArwood sLASER both with phantom and in vivo experiments. RESULTS For all sequences investigated, cogwheel was found to theoretically outperform typical nested phase cycling schemes. The chosen cogwheel phase cycling schemes through DOTCOPS were found to outperform a typical 2-step phase cycling scheme in both phantom and in vivo experiments. Both crusher schemes and phase cycling schemes with 8, 16, or 32 steps are presented for 6 of the most common advanced MRS sequences. CONCLUSION The DOTCOPS algorithm has been extended to provide optimal crusher and phase cycling schemes considered in tandem. DOTCOPS can be applied to any pulse sequence of interest for any number of coupled spins. DOTCOPS is now able to alleviate the long-standing issue of designing effective crusher and phase cycling schemes for complex MRS modern sequences and, as a result, is expected to improve the data quality of virtually all applications.
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Affiliation(s)
- Karl Landheer
- Biomedical Engineering, Columbia University Fu Foundation School of Engineering and Applied Science, New York, New York
| | - Christoph Juchem
- Biomedical Engineering, Columbia University Fu Foundation School of Engineering and Applied Science, New York, New York.,Radiology, Columbia University College of Physicians and Surgeons, New York, New York
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8
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Landheer K, Juchem C. Dephasing optimization through coherence order pathway selection (DOTCOPS) for improved crusher schemes in MR spectroscopy. Magn Reson Med 2018; 81:2209-2222. [PMID: 30390346 DOI: 10.1002/mrm.27587] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Revised: 09/11/2018] [Accepted: 10/09/2018] [Indexed: 11/09/2022]
Abstract
PURPOSE To develop an algorithm which can robustly eliminate all unwanted coherence pathways for an arbitrary magnetic resonance spectroscopy experiment through the adjustment of the relative amplitudes of crusher gradients, thereby reducing the effects of spurious echoes and mislocalization. THEORY AND METHODS The effect of crushing gradients for all coherence pathways was modeled according to the associated physics, and a cost function was optimized which maximally crushes all unwanted coherence pathways, while unaffecting the desired coherence pathway(s). The efficacy of the method was tested versus literature schemes from 2 separate MR spectroscopy (MRS) sequences: sLASER and MEGA-sLASER with both phantom and in vivo experiments. RESULTS Improved crushing power for 2 separate MRS sequences was demonstrated for 2 crushing schemes adopted from the literature in both phantom and in vivo data. CONCLUSION A novel algorithm and associated software was developed based on rigorous treatment of all coherence pathways, which can be applied to any arbitrary magnetic resonance spectroscopic pulse sequence of interest and any arbitrary coupled spin system. This developed method solves a long-standing problem in in vivo MRS and is expected to critically improve the data quality of virtually all MRS applications.
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Affiliation(s)
- Karl Landheer
- Department of Biomedical Engineering, Columbia University Fu Foundation School of Engineering and Applied Science, New York, New York
| | - Christoph Juchem
- Department of Biomedical Engineering, Columbia University Fu Foundation School of Engineering and Applied Science, New York, New York.,Department of Radiology, Columbia University College of Physicians and Surgeons, New York, New York
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9
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Carlsson Å, Sohlin MC, Lagerstrand KM, Aronsson EF, Ljungberg M. The influence of cardiac triggering time and an optimization strategy for improved cardiac MR spectroscopy. Z Med Phys 2017; 27:310-317. [PMID: 28554547 DOI: 10.1016/j.zemedi.2017.04.006] [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: 11/04/2016] [Revised: 04/24/2017] [Accepted: 04/25/2017] [Indexed: 01/17/2023]
Abstract
PURPOSE To study how cardiac motion affects the spectral quality in cardiac MR spectroscopy and to establish an optimization strategy for the cardiac triggering time for improved quality and success rate of cardiac MRS. METHOD Water spectra were acquired while the cardiac triggering time was varied over the cardiac cycle, and five different spectral quality parameters were studied (frequency, phase, linewidth, amplitude and noise). Furthermore, three different optimization strategies for the cardiac triggering time were tested, and finally, a comparison was made between water suppressed lipid spectra acquired in systole and diastole. RESULTS The cardiac triggering time had a high impact on the spectral quality, especially on the mean signal amplitude and the standard deviation of the signal amplitude, phase and linewidth. Generally, the highest spectral quality was observed for spectra acquired in mid to end systole, at approximately 23% of the cardiac cycle. The exact optimal triggering time differed between subjects and needed to be individually optimized. To optimize the triggering time with our proposed MRS-method gave in average 13% higher signal than when the triggering time was determined through imaging. Lipid spectra acquired in systole demonstrated higher quality with improved SNR compared with acquisitions made in diastole. CONCLUSION This study shows that the spectral quality in cardiac MRS is strongly dependent on the cardiac triggering time, and that the spectral quality as well as the repeatability between acquisitions is greatly improved when the cardiac triggering time is individually optimized in mid to end systole using MRS.
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Affiliation(s)
- Åsa Carlsson
- Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden; Department of Radiation Physics, Gothenburg University, Gothenburg, Sweden.
| | - Maja C Sohlin
- Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden; Department of Radiation Physics, Gothenburg University, Gothenburg, Sweden
| | - Kerstin M Lagerstrand
- Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden; Department of Radiation Physics, Gothenburg University, Gothenburg, Sweden
| | - Eva Forsell Aronsson
- Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden; Department of Radiation Physics, Gothenburg University, Gothenburg, Sweden
| | - Maria Ljungberg
- Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden; Department of Radiation Physics, Gothenburg University, Gothenburg, Sweden
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10
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Landheer K, Sahgal A, Myrehaug S, Chen AP, Cunningham CH, Graham SJ. A rapid inversion technique for the measurement of longitudinal relaxation times of brain metabolites: application to lactate in high-grade gliomas at 3 T. NMR IN BIOMEDICINE 2016; 29:1381-1390. [PMID: 27455374 DOI: 10.1002/nbm.3580] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2016] [Revised: 05/30/2016] [Accepted: 06/13/2016] [Indexed: 06/06/2023]
Abstract
The aim of this study was to develop a time-efficient inversion technique to measure the T1 relaxation time of the methyl group of lactate (Lac) in the presence of contaminating lipids and to measure T1 at 3 T in a cohort of primary high-grade gliomas. Three numerically optimized inversion times (TIs) were chosen to minimize the expected error in T1 estimates for a given input total scan duration (set to be 30 min). A two-cycle spectral editing scheme was used to suppress contaminating lipids. The T1 values were then estimated from least-squares fitting of signal measurements versus TI. Lac T1 was estimated as 2000 ± 280 ms. After correcting for T1 (and T2 from literature values), the mean absolute Lac concentration was estimated as 4.3 ± 2.6 mm. The technique developed agrees with the results obtained by standard inversion recovery and can be used to provide rapid T1 estimates of other spectral components as required. Lac T1 exhibits similar variations to other major metabolites observable by MRS in high-grade gliomas. The T1 estimate provided here will be useful for future MRS studies wishing to report relaxation-corrected estimates of Lac concentration as an objective tumor biomarker. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Karl Landheer
- Department of Medical Biophysics, University of Toronto, ON, Canada.
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada.
| | - Arjun Sahgal
- Department of Radiation Oncology, Sunnybrook Odette Cancer Center, University of Toronto, ON, Canada
| | - Sten Myrehaug
- Department of Radiation Oncology, Sunnybrook Odette Cancer Center, University of Toronto, ON, Canada
| | | | - Charles H Cunningham
- Department of Medical Biophysics, University of Toronto, ON, Canada
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Simon J Graham
- Department of Medical Biophysics, University of Toronto, ON, Canada
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
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Weiss K, Summermatter S, Stoeck CT, Kozerke S. Compensation of signal loss due to cardiac motion in point-resolved spectroscopy of the heart. Magn Reson Med 2013; 72:1201-7. [DOI: 10.1002/mrm.25028] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2013] [Revised: 10/06/2013] [Accepted: 10/12/2013] [Indexed: 12/20/2022]
Affiliation(s)
- Kilian Weiss
- Institute for Biomedical Engineering; University and ETH Zurich; Switzerland
- Cardiology Division; Department of Medicine; Johns Hopkins University School of Medicine; Baltimore Maryland USA
| | | | - Christian T. Stoeck
- Institute for Biomedical Engineering; University and ETH Zurich; Switzerland
| | - Sebastian Kozerke
- Institute for Biomedical Engineering; University and ETH Zurich; Switzerland
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Carlsson Å, Ljungberg M, Starck G, Forssell-Aronsson E. Degraded water suppression in small volume 1H MRS due to localised shimming. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2011; 24:97-107. [DOI: 10.1007/s10334-010-0239-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2010] [Revised: 12/15/2010] [Accepted: 12/15/2010] [Indexed: 11/25/2022]
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