bibliography.bib

@article{Mikkelsen2018,
author = {Mikkelsen, Mark and Saleh, Muhammad G. and Near, Jamie and Chan, Kimberly L. and Gong, Tao and Harris, Ashley D. and Oeltzschner, Georg and Puts, Nicolaas A.J. and Cecil, Kim M. and Wilkinson, Iain D. and Edden, Richard A.E.},
doi = {10.1002/mrm.27027},
file = {:Users/mmikkel5/Documents/Mendeley Desktop/Mikkelsen et al/Frequency and phase correction for multiplexed edited MRS of GABA and glutathione.pdf:pdf},
issn = {07403194},
journal = {Magnetic Resonance in Medicine},
keywords = {frequency,gaba,gsh,her-,mes,mrs,phase correction,spectral registration},
month = {jul},
number = {1},
pages = {21--28},
title = {{Frequency and phase correction for multiplexed edited MRS of GABA and glutathione}},
url = {https://onlinelibrary.wiley.com/doi/10.1002/mrm.27027},
volume = {80},
year = {2018}
}
@article{Mescher1998,
abstract = {Water suppression is typically performed in vivo by exciting the longitudinal magnetization in combination with dephasing, or by using frequency-selective coherence generation. MEGA, a frequency-selective refocusing technique, can be placed into any pulse sequence element designed to generate a Hahn spin-echo or stimulated echo, to dephase transverse water coherences with minimal spectral distortions. Water suppression performance was verified in vivo using stimulated echo acquisition mode (STEAM) localization, which provided water suppression comparable with that achieved with four selective pulses in 3,1-DRYSTEAM. The advantage of the proposed method was exploited for editing J-coupled resonances. Using a double-banded pulse that selectively inverts a J-coupling partner and simultaneously suppresses water, efficient metabolite editing was achieved in the point resolved spectroscopy (PRESS) and STEAM sequences in which MEGA was incorporated. To illustrate the efficiency of the method, the detection of gamma-aminobutyric acid (GABA) was demonstrated, with minimal contributions from macromolecules and overlying singlet peaks at 4 T. The estimated occipital GABA concentration was consistent with previous reports, suggesting that editing for GABA is efficient when based on MEGA at high field strengths.},
author = {Mescher, M and Merkle, H and Kirsch, J and Garwood, M and Gruetter, R},
doi = {10.1002/(SICI)1099-1492(199810)11:6<266::AID-NBM530>3.0.CO;2-J},
file = {:Users/mmikkel5/Documents/Mendeley Desktop/Mescher et al/Simultaneous in vivo spectral editing and water suppression.pdf:pdf},
isbn = {0952-3480 (Print)},
issn = {0952-3480},
journal = {NMR in Biomedicine},
keywords = {Frequency selective water suppression,GABA,Human brain,In vivo 1H MRS},
month = {oct},
number = {6},
pages = {266--272},
pmid = {9802468},
title = {{Simultaneous in vivo spectral editing and water suppression}},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/(SICI)1099-1492(199810)11:6%3C266::AID-NBM530%3E3.0.CO;2-J},
volume = {11},
year = {1998}
}
@article{Lu2005,
abstract = {PURPOSE: To establish image parameters for some routine clinical brain MRI pulse sequences at 3.0 T with the goal of maintaining, as much as possible, the well-characterized 1.5-T image contrast characteristics for daily clinical diagnosis, while benefiting from the increased signal to noise at higher field. MATERIALS AND METHODS: A total of 10 healthy subjects were scanned on 1.5-T and 3.0-T systems for T(1) and T(2) relaxation time measurements of major gray and white matter structures. The relaxation times were subsequently used to determine 3.0-T acquisition parameters for spin-echo (SE), T(1)-weighted, fast spin echo (FSE) or turbo spin echo (TSE), T(2)-weighted, and fluid-attenuated inversion recovery (FLAIR) pulse sequences that give image characteristics comparable to 1.5 T, to facilitate routine clinical diagnostics. Application of the routine clinical sequences was performed in 10 subjects, five normal subjects and five patients with various pathologies. RESULTS: T(1) and T(2) relaxation times were, respectively, 14% to 30% longer and 12% to 19% shorter at 3.0 T when compared to the values at 1.5 T, depending on the region evaluated. When using appropriate parameters, routine clinical images acquired at 3.0 T showed similar image characteristics to those obtained at 1.5 T, but with higher signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), which can be used to reduce the number of averages and scan times. Recommended imaging parameters for these sequences are provided. CONCLUSION: When parameters are adjusted for changes in relaxation rates, routine clinical scans at 3.0 T can provide similar image appearance as 1.5 T, but with superior image quality and/or increased speed.},
author = {Lu, Hanzhang and Nagae-Poetscher, Lidia M. and Golay, Xavier and Lin, Doris and Pomper, Martin and van Zijl, Peter C.M.},
doi = {10.1002/jmri.20356},
file = {:Users/mmikkel5/Documents/Mendeley Desktop/Lu et al/Routine clinical brain MRI sequences for use at 3.0 Tesla.pdf:pdf},
isbn = {1522-2586},
issn = {1053-1807},
journal = {Journal of Magnetic Resonance Imaging},
keywords = {Brain,Clinical MRI,FLAIR,High field,T1,T2},
month = {jul},
number = {1},
pages = {13--22},
pmid = {15971174},
title = {{Routine clinical brain MRI sequences for use at 3.0 Tesla}},
url = {http://doi.wiley.com/10.1002/jmri.20356},
volume = {22},
year = {2005}
}
@article{Piechnik2009,
abstract = {Cerebrospinal fluid (CSF) provides hydraulic suspension for the brain. The general concept of bulk CSF production, circulation, and reabsorption is well established, but the mechanisms of momentary CSF volume variation corresponding to vasoreactive changes are far less understood. Nine individuals were studied in a 3T MR scanner with a protocol that included visual stimulation using a 10-Hz reversing checkerboard and administration of a 5% CO(2) mix in air. We acquired PRESS-localized spin-echoes (TR = 12 sec, TE = 26 ms to 1.5 sec) from an 8-mL voxel located in the visual cortex. Echo amplitudes were fitted to a two-compartmental model of relaxation to estimate the partial volume of CSF and the T(2) relaxation times of the tissues. CSF signal contributed 10.7 +/- 3% of the total, with T(2,csf) = 503.0 +/- 64.3 [ms], T(2,brain) = 61.0 +/- 2 [ms]. The relaxation time of tissue increased during physiological stimulation, while the fraction of signal contributed by CSF decreased significantly by 5-6% with visual stimulation (P < 0.03) and by 3% under CO(2) inhalation (P < 0.08). The CSF signal fraction is shown to represent well the volume changes under viable physiological scenarios. In conclusion, CSF plays a significant role in buffering the changes in cerebral blood volume, especially during rapid functional stimuli.},
author = {Piechnik, S.K. and Evans, J. and Bary, L.H. and Wise, R.G. and Jezzard, P.},
doi = {10.1002/mrm.21897},
file = {:Users/mmikkel5/Documents/Mendeley Desktop/Piechnik et al/Functional changes in CSF volume estimated using measurement of water T2 relaxation.pdf:pdf},
isbn = {1522-2594 (Electronic)},
issn = {07403194},
journal = {Magnetic Resonance in Medicine},
keywords = {CO2 reactivity,Cerebral blood flow,Cerebrospinal fluid,Functional responses,Magnetic resonance imaging,Magnetic resonance spectroscopy,Vasodilatation},
month = {mar},
number = {3},
pages = {579--586},
pmid = {19132756},
title = {{Functional changes in CSF volume estimated using measurement of water T2 relaxation}},
url = {http://doi.wiley.com/10.1002/mrm.21897},
volume = {61},
year = {2009}
}
@article{Ernst1993,
abstract = {A method is presented to determine the compartmentation of a localized region in the human brain in terms of CSF, tissue water, and an NMR-invisible rest, using a PRESS or STEAM sequence. Discrimination between CSF and tissue water is based on differences in their T2 relaxation times. The NMR-invisible compartment is assessed using an external standard. The composition of three regions in the human brain is determined. The CSF content of specific regions can be used to quantify cortical atrophy. The method provides a means for measuring the water content of brain tissue in vivo with a precision of 1.5%. After appropriate corrections, the results are in close agreement with biochemical values. The method has major applications in localized quantitative spectroscopy. The compartmentation model can be used to correct for the CSF content of the selected volume and to properly define and interconvert all major concentration units.},
author = {Ernst, T. and Kreis, R. and Ross, B.D.},
doi = {10.1006/jmrb.1993.1055},
file = {:Users/mmikkel5/Documents/Mendeley Desktop/Ernst, Kreis, Ross/Absolute quantitation of water and metabolites in the human brain. I. Compartments and water.pdf:pdf},
issn = {10641866},
journal = {Journal of Magnetic Resonance, Series B},
month = {aug},
number = {1},
pages = {1--8},
title = {{Absolute quantitation of water and metabolites in the human brain. I. Compartments and water}},
url = {http://dx.doi.org/10.1006/jmrb.1993.1055 http://linkinghub.elsevier.com/retrieve/pii/S1064186683710551},
volume = {102},
year = {1993}
}
@article{Harris2017,
author = {Harris, Ashley D and Saleh, Muhammad G and Edden, Richard A.E.},
doi = {10.1002/mrm.26619},
file = {:Users/mmikkel5/Documents/Mendeley Desktop/Harris, Saleh, Edden/Edited 1 H magnetic resonance spectroscopy in vivo Methods and metabolites.pdf:pdf},
issn = {07403194},
journal = {Magnetic Resonance in Medicine},
keywords = {constant-time press,echo-time averaging,editing,j -coupling,j -difference,magnetic resonance spectroscopy,metabolites,mrs,quantum filtering},
month = {apr},
number = {4},
pages = {1377--1389},
title = {{Edited 1 H magnetic resonance spectroscopy in vivo: Methods and metabolites}},
url = {https://onlinelibrary.wiley.com/doi/10.1002/mrm.26619},
volume = {77},
year = {2017}
}
@article{Near2015,
abstract = {PURPOSE: Frequency and phase drifts are a common problem in the acquisition of in vivo magnetic resonance spectroscopy (MRS) data. If not accounted for, frequency and phase drifts will result in artifactual broadening of spectral peaks, distortion of spectral lineshapes, and a reduction in signal-to-noise ratio (SNR). We present herein a new method for estimating and correcting frequency and phase drifts in in vivo MRS data.\n\nMETHODS: We used a simple method of fitting each spectral average to a reference scan (often the first average in the series) in the time domain through adjustment of frequency and phase terms. Due to the similarity with image registration, this method is referred to as "spectral registration." Using simulated data with known frequency and phase drifts, the performance of spectral registration was compared with two existing methods at various SNR levels.\n\nRESULTS: Spectral registration performed well in comparison with the other methods tested in terms of both frequency and phase drift estimation.\n\nCONCLUSIONS: Spectral registration provides an effective method for frequency and phase drift correction. It does not involve the collection of navigator echoes, and does not rely on any specific resonances, such as residual water or creatine, making it highly versatile. Magn Reson Med, 2014. {\textcopyright} 2014 Wiley Periodicals, Inc.},
author = {Near, Jamie and Edden, Richard and Evans, C John and Paquin, Rapha{\"{e}}l and Harris, Ashley and Jezzard, Peter},
doi = {10.1002/mrm.25094},
file = {:Users/mmikkel5/Documents/Mendeley Desktop/Near et al/Frequency and phase drift correction of magnetic resonance spectroscopy data by spectral registration in the time domain.pdf:pdf},
issn = {07403194},
journal = {Magnetic Resonance in Medicine},
keywords = {B0 drift,Frequency drift,Magnetic resonance spectroscopy,Motion correction,Phase drift},
month = {jan},
number = {1},
pages = {44--50},
pmid = {24436292},
title = {{Frequency and phase drift correction of magnetic resonance spectroscopy data by spectral registration in the time domain}},
url = {http://www.ncbi.nlm.nih.gov/pubmed/24436292 http://doi.wiley.com/10.1002/mrm.25094},
volume = {73},
year = {2015}
}
@article{Mullins2014,
abstract = {There is increasing interest in the use of edited proton magnetic resonance spectroscopy for the detection of GABA in the human brain. At a recent meeting held at Cardiff University, a number of spectroscopy groups met to discuss the acquisition, analysis and interpretation of GABA-edited MR spectra. This paper aims to set out the issues discussed at this meeting, reporting areas of consensus around parameters and procedures in the field and highlighting those areas where differences remain. It is hoped that this paper can fulfill two needs, providing a summary of the current 'state-of-the-art' in the field of GABA-edited MRS at 3T using MEGA-PRESS and a basic guide to help researchers new to the field to avoid some of the pitfalls inherent in the acquisition and processing of edited MRS for GABA.},
author = {Mullins, Paul G and McGonigle, David J and O'Gorman, Ruth L and Puts, Nicolaas A.J. and Vidyasagar, Rishma and Evans, C John and Edden, Richard A.E.},
doi = {10.1016/j.neuroimage.2012.12.004},
file = {:Users/mmikkel5/Documents/Mendeley Desktop/Mullins et al/Current practice in the use of MEGA-PRESS spectroscopy for the detection of GABA.pdf:pdf},
issn = {10538119},
journal = {NeuroImage},
keywords = {Edited MRS,GABA,MEGA-PRESS,MRS analysis},
month = {feb},
pages = {43--52},
pmid = {23246994},
publisher = {Elsevier Inc.},
title = {{Current practice in the use of MEGA-PRESS spectroscopy for the detection of GABA}},
url = {http://www.ncbi.nlm.nih.gov/pubmed/23246994 http://linkinghub.elsevier.com/retrieve/pii/S1053811912011779 http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3825742 https://linkinghub.elsevier.com/retrieve/pii/S1053811912011779},
volume = {86},
year = {2014}
}
@article{Puts2013,
abstract = {PURPOSE: To measure the in vivo longitudinal relaxation time T1 of GABA at 3 Tesla (T).\n\nMATERIALS AND METHODS: J-difference edited single-voxel MR spectroscopy was used to isolate $\gamma$-aminobutyric acid (GABA) signals. An increased echo time (80 ms) acquisition was used, accommodating the longer, more selective editing pulses required for symmetric editing-based suppression of co-edited macromolecular signal. Acquiring edited GABA measurements at a range of relaxation times in 10 healthy participants, a saturation-recovery equation was used to model the integrated data.\n\nRESULTS: The longitudinal relaxation time of GABA was measured as T(1,GABA) = 1.31 ± 0.16 s.\n\nCONCLUSION: The method described has been successfully applied to measure the T1 of GABA in vivo at 3T.},
author = {Puts, Nicolaas A.J. and Barker, Peter B and Edden, Richard A.E.},
doi = {10.1002/jmri.23817},
file = {:Users/mmikkel5/Documents/Mendeley Desktop/Puts, Barker, Edden/Measuring the longitudinal relaxation time of GABA in vivo at 3 Tesla.pdf:pdf},
isbn = {1522-2586},
issn = {10531807},
journal = {Journal of Magnetic Resonance Imaging},
keywords = {3T,GABA,MEGA-PRESS,MRS,T1 relaxation,macromolecules},
month = {apr},
number = {4},
pages = {999--1003},
pmid = {23001644},
title = {{Measuring the longitudinal relaxation time of GABA in vivo at 3 Tesla}},
url = {http://www.ncbi.nlm.nih.gov/pubmed/23001644 http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3531569&tool=pmcentrez&rendertype=abstract http://doi.wiley.com/10.1002/jmri.23817},
volume = {37},
year = {2013}
}
@article{Klose1990,
abstract = {Spatially localized methods in spectroscopy often operate with magnetic field gradients for volume selection. The eddy currents induced by these gradients produce time-dependent shifts of the resonance frequency in the selected volume, which results in a distortion of the spectrum after Fourier transformation. In whole-body systems the complete compensation of eddy currents is a difficult procedure. To avoid this, a correction method is proposed for proton spectroscopy, which uses the signal of prominent water protons as a reference for the water-suppressed signal. The correction is performed in the time domain, dividing the water-suppressed signal by the phase factor of the water signal for each data point. The corrected spectra have a good resolution as shown by phantom measurements and brain and muscle spectra of volunteers.},
author = {Klose, Uwe},
doi = {10.1002/mrm.1910140104},
file = {:Users/mmikkel5/Documents/Mendeley Desktop/Klose/In vivo proton spectroscopy in presence of eddy currents.pdf:pdf},
issn = {07403194},
journal = {Magnetic Resonance in Medicine},
keywords = {Extracellular Space,Fourier Analysis,Humans,Magnetic Resonance Spectroscopy,Magnetic Resonance Spectroscopy: methods,Protons,Time Factors},
month = {apr},
number = {1},
pages = {26--30},
pmid = {2161984},
title = {{In vivo proton spectroscopy in presence of eddy currents}},
url = {http://www.ncbi.nlm.nih.gov/pubmed/2161984 http://doi.wiley.com/10.1002/mrm.1910140104},
volume = {14},
year = {1990}
}
@article{Kreis2004,
abstract = {In spite of the facts that magnetic resonance spectroscopy (MRS) is applied as clinical tool in non-specialized institutions and that semi-automatic acquisition and processing tools can be used to produce quantitative information from MRS exams without expert information, issues of spectral quality and quality assessment are neglected in the literature of MR spectroscopy. Even worse, there is no consensus among experts on concepts or detailed criteria of quality assessment for MR spectra. Furthermore, artifacts are not at all conspicuous in MRS and can easily be taken for true, interpretable features. This article aims to increase interest in issues of spectral quality and quality assessment, to start a larger debate on generally accepted criteria that spectra must fulfil to be clinically and scientifically acceptable, and to provide a sample gallery of artifacts, which can be used to raise awareness for potential pitfalls in MRS.},
author = {Kreis, Roland},
doi = {10.1002/nbm.891},
file = {:Users/mmikkel5/Documents/Mendeley Desktop/Kreis/Issues of spectral quality in clinical1H-magnetic resonance spectroscopy and a gallery of artifacts.pdf:pdf},
issn = {0952-3480},
journal = {NMR in Biomedicine},
keywords = {Algorithms,Artifacts,Biomedical,Biomedical: methods,Clinical Medicine,Clinical Medicine: methods,Computer-Assisted,Computer-Assisted: methods,Diagnosis,Equipment Failure,Equipment Failure Analysis,Equipment Failure Analysis: methods,Health Care,Humans,Magnetic Resonance Spectroscopy,Magnetic Resonance Spectroscopy: instrumentation,Magnetic Resonance Spectroscopy: methods,Protons,Quality Assurance,Reproducibility of Results,Sensitivity and Specificity,Technology Assessment},
month = {oct},
number = {6},
pages = {361--381},
pmid = {15468083},
title = {{Issues of spectral quality in clinical1H-magnetic resonance spectroscopy and a gallery of artifacts}},
url = {http://www.ncbi.nlm.nih.gov/pubmed/15468083 http://doi.wiley.com/10.1002/nbm.891 https://onlinelibrary.wiley.com/doi/10.1002/nbm.891},
volume = {17},
year = {2004}
}
@article{Wansapura1999,
abstract = {Relaxation time measurements at 3.0 T are reported for both gray and white matter in normal human brain. Measurements were made using a 3.0 T Bruker Biospec magnetic resonance imaging (MRI) scanner in normal adults with no clinical evidence of neurological disease. Nineteen subjects, 8 female and 11 male, were studied for T1 and T2 measurements, and 7 males were studied for T*2. Measurements were made using a saturation recovery method for T1, a multiple spin-echo experiment for T2, and a fast low-angle shot (FLASH) sequence with 14 different echo times for T*2. Results of the measurements are summarized as follows. Average T1 values measured for gray matter and white matter were 1331 and 832 msec, respectively. Average T2 values measured for gray matter and white matter were 80 and 110 msec, respectively. The average T*2 values for occipital and frontal gray matter were 41.6 and 51.8 msec, respectively. Average T*2 values for occipital and frontal white matter were 48.4 and 44.7 msec, respectively. ANOVA tests of the measurements revealed that for both gray and white matter there were no significant differences in T1 from one location in the brain to another. T2 in occipital gray matter was significantly higher (0.0001 < P < .0375) than the rest of the gray matter, while T2 in frontal white matter was significantly lower (P < 0.0001). Statistical analysis of cerebral hemispheric differences in relaxation time measurements showed no significant differences in T1 values from the left hemisphere compared with the right, except in insular gray matter, where this difference was significant at P = 0.0320. No significant difference in T2 values existed between the left and right cerebral hemispheres. Significant differences were apparent between male and female relaxation time measurements in brain. J. Magn. Reson. Imaging 1999;9:531–538. {\textcopyright} 1999 Wiley-Liss, Inc.},
author = {Wansapura, Janaka P and Holland, Scott K and Dunn, R Scott and Ball, William S},
doi = {10.1002/(SICI)1522-2586(199904)9:4<531::AID-JMRI4>3.0.CO;2-L},
file = {:Users/mmikkel5/Documents/Mendeley Desktop/Wansapura et al/NMR relaxation times in the human brain at 3.0 Tesla.pdf:pdf},
isbn = {1522-2586},
issn = {1053-1807},
journal = {Journal of Magnetic Resonance Imaging},
keywords = {3.0 T,Brain,Relaxation times,T1,T2},
month = {apr},
number = {4},
pages = {531--538},
pmid = {10232510},
title = {{NMR relaxation times in the human brain at 3.0 Tesla}},
url = {http://www.ncbi.nlm.nih.gov/pubmed/10232510 http://doi.wiley.com/10.1002/%28SICI%291522-2586%28199904%299%3A4%3C531%3A%3AAID-JMRI4%3E3.0.CO%3B2-L},
volume = {9},
year = {1999}
}
@article{Barkhuijsen1987,
abstract = {The authors are concerned with a new method of fitting a physical model function to a magnetic resonance signal, directly in the time domain. Their primary aim is analysis of the signal in quantitative terms, i.e., describing the signal in terms of physically meaningful parameters with their statistical errors. Before explaining the new method they make some remarks about the place of time-domain model fitting in spectral analysis},
author = {Barkhuijsen, H. and de Beer, R. and van Ormondt, D.},
doi = {10.1016/0022-2364(87)90023-0},
file = {:Users/mmikkel5/Documents/Mendeley Desktop/Barkhuijsen, de Beer, van Ormondt/Improved algorithm for noniterative time-domain model fitting to exponentially damped magnetic resonance signals.pdf:pdf},
isbn = {0022-2364},
issn = {00222364},
journal = {Journal of Magnetic Resonance},
month = {jul},
number = {3},
pages = {553--557},
title = {{Improved algorithm for noniterative time-domain model fitting to exponentially damped magnetic resonance signals}},
url = {http://linkinghub.elsevier.com/retrieve/pii/0022236487900230 https://linkinghub.elsevier.com/retrieve/pii/0022236487900230},
volume = {73},
year = {1987}
}
@article{Edden2012,
abstract = {PURPOSE: To develop an experimental approach for determining in vivo transverse relaxation rates (T(2)) of metabolites that are detected by spectral editing without using simulations, and to demonstrate this approach to measure the T(2) of $\gamma$-aminobutyric acid (GABA).\n\nMATERIALS AND METHODS: The proposed method first determines the TE-dependence of the edited signals using measurements in a pure phantom solution (10 mM $\gamma$-aminobutyric acid; GABA); the phantom T(2) is also determined. Once the editing echo time (TE)-modulation pattern is known, it can then be used to determine T(2) in vivo. The method was applied to measure GABA T(2) in the occipital lobe of five healthy adult subjects at 3T, using a J-difference editing method. Unwanted macromolecular contributions to the GABA signal were also measured.\n\nRESULTS: The in vivo T(2) of edited GABA signal was 88 ± 12 ms; this preliminary result is somewhat shorter than other metabolite T(2) values in the literature at this field strength.\n\nCONCLUSION: Spectral editing methods are now widely used to detect low concentration metabolites, such as GABA, but to date no edited acquisition methods have been proposed for the measurement of transverse relaxation times (T(2)). The method described has been successfully applied to measuring the T(2) of GABA.},
author = {Edden, Richard A.E. and Intrapiromkul, Jarunee and Zhu, He and Cheng, Ying and Barker, Peter B},
doi = {10.1002/jmri.22865},
file = {:Users/mmikkel5/Documents/Mendeley Desktop/Edden et al/Measuring T2 in vivo with J-difference editing Application to GABA at 3 Tesla.pdf:pdf},
isbn = {1522-2586 (Electronic)\r1053-1807 (Linking)},
issn = {10531807},
journal = {Journal of Magnetic Resonance Imaging},
keywords = {GABA,T 2,brain,edited MR spectroscopy,transverse relaxation},
month = {jan},
number = {1},
pages = {229--234},
pmid = {22045601},
title = {{Measuring T2 in vivo with J-difference editing: Application to GABA at 3 Tesla}},
url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3377980&tool=pmcentrez&rendertype=abstract http://doi.wiley.com/10.1002/jmri.22865},
volume = {35},
year = {2012}
}
@article{An2013,
abstract = {Purpose: To propose using the generalized least square (GLS) algorithm for combining multichannel single-voxel magnetic resonance spectroscopy (MRS) signals. Materials and Methods: Phantom and in vivo brain MRS experiments on a 7 T scanner equipped with a 32-channel receiver coil, as well as Monte Carlo simulations, were performed to compare the coefficient of variation (CV) of the GLS method with those of two recently reported spectral combination methods. Results: Compared to the two existing methods, the GLS method significantly reduced CV values for the simulation, phantom, and in vivo experiments. Conclusion: The GLS method can lead to improved precision of peak quantification. J. Magn. Reson. Imaging 2013;37:14451450. (c) 2012 Wiley Periodicals, Inc.},
archivePrefix = {arXiv},
arxivId = {NIHMS150003},
author = {An, Li and {Willem van der Veen}, Jan and Li, Shizhe and Thomasson, David M. and Shen, Jun},
doi = {10.1002/jmri.23941},
eprint = {NIHMS150003},
file = {:Users/mmikkel5/Documents/Mendeley Desktop/An et al/Combination of multichannel single-voxel MRS signals using generalized least squares.pdf:pdf},
isbn = {1053-1807},
issn = {10531807},
journal = {Journal of Magnetic Resonance Imaging},
keywords = {GLS,MRS,SNR,generalized least squares,multichannel coil,noise correlation},
month = {jun},
number = {6},
pages = {1445--1450},
pmid = {23172656},
title = {{Combination of multichannel single-voxel MRS signals using generalized least squares}},
url = {http://doi.wiley.com/10.1002/jmri.23941 https://onlinelibrary.wiley.com/doi/10.1002/jmri.23941},
volume = {37},
year = {2013}
}
@article{Gasparovic2006,
abstract = {A strategy for using tissue water as a concentration standard in (1)H magnetic resonance spectroscopic imaging studies on the brain is presented, and the potential errors that may arise when the method is used are examined. The sensitivity of the method to errors in estimates of the different water compartment relaxation times is shown to be small at short echo times (TEs). Using data from healthy human subjects, it is shown that different image segmentation approaches that are commonly used to account for partial volume effects (SPM2, FSL's FAST, and K-means) lead to different estimates of metabolite levels, particularly in gray matter (GM), owing primarily to variability in the estimates of the cerebrospinal fluid (CSF) fraction. While consistency does not necessarily validate a method, a multispectral segmentation approach using FAST yielded the lowest intersubject variability in the estimates of GM metabolites. The mean GM and white matter (WM) levels of N-acetyl groups (NAc, primarily N-acetylaspartate), choline (Ch), and creatine (Cr) obtained in these subjects using the described method with FAST multispectral segmentation are reported: GM [NAc] = 17.16 +/- 1.19 mM; WM [NAc] = 14.26 +/- 1.38 mM; GM [Ch] = 3.27 +/- 0.47 mM; WM [Ch] = 2.65 +/- 0.25 mM; GM [Cr] = 13.98 +/- 1.20 mM; and WM [Cr] = 7.10 +/- 0.67 mM.},
author = {Gasparovic, Charles and Song, Tao and Devier, Deidre and Bockholt, H Jeremy and Caprihan, Arvind and Mullins, Paul G and Posse, Stefan and Jung, Rex E and Morrison, Leslie A},
doi = {10.1002/mrm.20901},
file = {:Users/mmikkel5/Documents/Mendeley Desktop/Gasparovic et al/Use of tissue water as a concentration reference for proton spectroscopic imaging.pdf:pdf},
isbn = {0740-3194 (Print)\n0740-3194 (Linking)},
issn = {0740-3194},
journal = {Magnetic Resonance in Medicine},
keywords = {1H-MRS,Relaxation times,Spectroscopic imaging,Tissue water,Voxel},
month = {jun},
number = {6},
pages = {1219--1226},
pmid = {16688703},
title = {{Use of tissue water as a concentration reference for proton spectroscopic imaging}},
url = {http://www.ncbi.nlm.nih.gov/pubmed/16688703 http://doi.wiley.com/10.1002/mrm.20901},
volume = {55},
year = {2006}
}
@article{Evans2013,
abstract = {PURPOSE: To compare the repeatability of $\gamma$-aminobutyric acid (GABA) measurements using J-difference editing, before and after spectral realignment-a technique which has previously been demonstrated to improve the quality of J-difference GABA spectra.\n\nMATERIALS AND METHODS: We performed in vivo measurements in three brain regions (occipital, sensorimotor, and dorsolateral prefrontal cortex [DLPFC]), and analyzed these using alternative alignment approaches to evaluate the impact of alignment on repeatability: "Independent alignment" (aligning each subspectrum independently) and "Pairwise alignment" (aligning each on and off subspectrum as a pair) were compared.\n\nRESULTS: Pairwise alignment improved the group mean coefficient of variation in all regions; 0.4% in occipital, 1.1% in sensorimotor, and 1.1% in DLPFC. Independent alignment resulted in subtraction artifacts in the majority of cases, and increased the coefficient of variation in the DLPFC by 9.4%. Simulations demonstrate that the GABA quantification error in datasets with high B0 drift, is 4.5% without alignment, but <1% with optimal alignment.\n\nCONCLUSION: Pairwise alignment improves the repeatability of GABA spectroscopy data. However, independently aligning all on and off subspectra can lead to artifacts and worse repeatability when compared with nonaligned data.},
author = {Evans, C. John and Puts, Nicolaas A.J. and Robson, Si{\^{a}}n E. and Boy, Frederic and McGonigle, David J. and Sumner, Petroc and Singh, Krish D. and Edden, Richard A.E.},
doi = {10.1002/jmri.23923},
file = {:Users/mmikkel5/Documents/Mendeley Desktop/Evans et al/Subtraction artifacts and frequency (Mis-)alignment in J-difference GABA editing.pdf:pdf},
issn = {10531807},
journal = {Journal of Magnetic Resonance Imaging},
keywords = {GABA,MRS,frequency alignment,repeatability,subtraction artifact},
month = {oct},
number = {4},
pages = {970--975},
pmid = {23188759},
title = {{Subtraction artifacts and frequency (Mis-)alignment in J-difference GABA editing}},
url = {http://www.ncbi.nlm.nih.gov/pubmed/23188759 http://doi.wiley.com/10.1002/jmri.23923 https://onlinelibrary.wiley.com/doi/10.1002/jmri.23923},
volume = {38},
year = {2013}
}
@article{Hui2021a,
author = {Hui, Steve C.N. and Mikkelsen, Mark and Z{\"{o}}llner, Helge J. and Ahluwalia, Vishwadeep and Alcauter, Sarael and Baltusis, Laima and Barany, Deborah A and Barlow, Laura R and Becker, Robert and Berman, Jeffrey I and Berrington, Adam and Bhattacharyya, Pallab K and Blicher, Jakob Udby and Bogner, Wolfgang and Brown, Mark S and Calhoun, Vince D and Castillo, Ryan and Cecil, Kim M and Choi, Yeo Bi and Chu, Winnie C.W. and Clarke, William T and Craven, Alexander R and Cuypers, Koen and Dacko, Michael and de la Fuente-Sandoval, Camilo and Desmond, Patricia and Domagalik, Aleksandra and Dumont, Julien and Duncan, Niall W and Dydak, Ulrike and Dyke, Katherine and Edmondson, David A and Ende, Gabriele and Ersland, Lars and Evans, C John and Fermin, Alan S.R. and Ferretti, Antonio and Fillmer, Ariane and Gong, Tao and Greenhouse, Ian and Grist, James T and Gu, Meng and Harris, Ashley D and Hat, Katarzyna and Heba, Stefanie and Heckova, Eva and Hegarty, John P. and Heise, Kirstin-friederike and Honda, Shiori and Jacobson, Aaron and Jansen, Jacobus F.A. and Jenkins, Christopher W and Johnston, Stephen J and Juchem, Christoph and Kangarlu, Alayar and Kerr, Adam B and Landheer, Karl and Lange, Thomas and Lee, Phil and Levendovszky, Swati Rane and Limperopoulos, Catherine and Liu, Feng and Lloyd, William and Lythgoe, David J and Machizawa, Maro G and MacMillan, Erin L. and Maddock, Richard J and Manzhurtsev, Andrei V and Martinez-Gudino, Mar{\'{i}}a L. and Miller, Jack J and Mirzakhanian, Heline and Moreno-Ortega, Marta and Mullins, Paul G and Nakajima, Shinichiro and Near, Jamie and Noeske, Ralph and Nordh{\o}y, Wibeke and Oeltzschner, Georg and Osorio-Duran, Raul and Otaduy, Maria C.G. and Pasaye, Erick H and Peeters, Ronald and Peltier, Scott J and Pilatus, Ulrich and Polomac, Nenad and Porges, Eric C and Pradhan, Subechhya and Prisciandaro, James Joseph and Puts, Nicolaas A and Rae, Caroline D and Reyes-Madrigal, Francisco and Roberts, Timothy P.L. and Robertson, Caroline E and Rosenberg, Jens T and Rotaru, Diana-georgiana and {O'Gorman Tuura}, Ruth L and Saleh, Muhammad G and Sandberg, Kristian and Sangill, Ryan and Schembri, Keith and Schrantee, Anouk and Semenova, Natalia A and Singel, Debra and Sitnikov, Rouslan and Smith, Jolinda and Song, Yulu and Stark, Craig and Stoffers, Diederick and Swinnen, Stephan P. and Tain, Rongwen and Tanase, Costin and Tapper, Sofie and Tegenthoff, Martin and Thiel, Thomas and Thioux, Marc and Truong, Peter and van Dijk, Pim and Vella, Nolan and Vidyasagar, Rishma and Vovk, Andrej and Wang, Guangbin and Westlye, Lars T and Wilbur, Timothy K and Willoughby, William R and Wilson, Martin and Wittsack, Hans-J{\"{o}}rg and Woods, Adam J and Wu, Yen-Chien and Xu, Junqian and Lopez, Maria Yanez and Yeung, David K.W. and Zhao, Qun and Zhou, Xiaopeng and Zupan, Gasper and Edden, Richard A.E.},
doi = {10.1016/j.neuroimage.2021.118430},
file = {:Users/mmikkel5/Documents/Mendeley Desktop/Hui et al/Frequency drift in MR spectroscopy at 3T.pdf:pdf},
issn = {10538119},
journal = {NeuroImage},
month = {nov},
number = {21},
pages = {118430},
title = {{Frequency drift in MR spectroscopy at 3T}},
url = {https://linkinghub.elsevier.com/retrieve/pii/S1053811921007059},
volume = {241},
year = {2021}
}
@article{Harris2015,
author = {Harris, Ashley D. and Puts, Nicolaas A.J. and Edden, Richard A.E.},
doi = {10.1002/jmri.24903},
file = {:Users/mmikkel5/Documents/Mendeley Desktop/Harris, Puts, Edden/Tissue correction for GABA-edited MRS Considerations of voxel composition, tissue segmentation, and tissue relaxations.pdf:pdf;:Users/mmikkel5/Documents/Mendeley Desktop/Harris, Puts, Edden/Tissue correction for GABA-edited MRS Considerations of voxel composition, tissue segmentation, and tissue relaxations(2).pdf:pdf},
issn = {10531807},
journal = {Journal of Magnetic Resonance Imaging},
month = {nov},
number = {5},
pages = {1431--1440},
title = {{Tissue correction for GABA-edited MRS: Considerations of voxel composition, tissue segmentation, and tissue relaxations}},
url = {http://doi.wiley.com/10.1002/jmri.24903},
volume = {42},
year = {2015}
}
@article{Mikkelsen2017,
author = {Mikkelsen, Mark and Barker, Peter B and Bhattacharyya, Pallab K and Brix, Maiken K and Buur, Pieter F. and Cecil, Kim M and Chan, Kimberly L and Chen, David Y.-T. and Craven, Alexander R and Cuypers, Koen and Dacko, Michael and Duncan, Niall W and Dydak, Ulrike and Edmondson, David A and Ende, Gabriele and Ersland, Lars and Gao, Fei and Greenhouse, Ian and Harris, Ashley D and He, Naying and Heba, Stefanie and Hoggard, Nigel and Hsu, Tun-wei and Jansen, Jacobus F.A. and Kangarlu, Alayar and Lange, Thomas and Lebel, R Marc and Li, Yan and Lin, Chien-yuan E and Liou, Jy-kang and Lirng, Jiing-Feng and Liu, Feng and Ma, Ruoyun and Maes, Celine and Moreno-Ortega, Marta and Murray, Scott O and Noah, Sean and Noeske, Ralph and Noseworthy, Michael D and Oeltzschner, Georg and Prisciandaro, James J. and Puts, Nicolaas A.J. and Roberts, Timothy P.L. and Sack, Markus and Sailasuta, Napapon and Saleh, Muhammad G and Schallmo, Michael-paul and Simard, Nicholas and Swinnen, Stephan P. and Tegenthoff, Martin and Truong, Peter and Wang, Guangbin and Wilkinson, Iain D and Wittsack, Hans-J{\"{o}}rg and Xu, Hongmin and Yan, Fuhua and Zhang, Chencheng and Zipunnikov, Vadim and Z{\"{o}}llner, Helge J. and Edden, Richard A.E.},
doi = {10.1016/j.neuroimage.2017.07.021},
file = {:Users/mmikkel5/Documents/Mendeley Desktop/Mikkelsen et al/Big GABA Edited MR spectroscopy at 24 research sites.pdf:pdf},
issn = {10538119},
journal = {NeuroImage},
month = {oct},
pages = {32--45},
publisher = {Elsevier Inc.},
title = {{Big GABA: Edited MR spectroscopy at 24 research sites}},
url = {https://doi.org/10.1016/j.neuroimage.2017.07.021 https://linkinghub.elsevier.com/retrieve/pii/S105381191730589X},
volume = {159},
year = {2017}
}
@article{Mikkelsen2020,
author = {Mikkelsen, Mark and Tapper, Sofie and Near, Jamie and Mostofsky, Stewart H. and Puts, Nicolaas A. J. and Edden, Richard A. E.},
doi = {10.1002/nbm.4368},
file = {:Users/mmikkel5/Documents/Mendeley Desktop/Mikkelsen et al/Correcting frequency and phase offsets in MRS data using robust spectral registration.pdf:pdf},
issn = {0952-3480},
journal = {NMR in Biomedicine},
month = {oct},
number = {10},
pages = {e4368},
pmid = {32656879},
title = {{Correcting frequency and phase offsets in MRS data using robust spectral registration}},
url = {https://onlinelibrary.wiley.com/doi/10.1002/nbm.4368},
volume = {33},
year = {2020}
}