Quantitative 1H-magnetic resonance spectroscopy of human brain: Influence of composition and parameterization of the basis set in linear combination model-fitting
Localized short‐echo‐time 1H‐MR spectra of human brain contain contributions of many low‐molecular‐weight metabolites and baseline contributions of macromolecules. Two approaches to model such spectra are compared and the data acquisition sequence, optimized for reproducibility, is presented. Modeli...
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| Published in | Magnetic resonance in medicine Vol. 48; no. 3; pp. 440 - 453 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Wiley Subscription Services, Inc., A Wiley Company
01.09.2002
Williams & Wilkins |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0740-3194 1522-2594 |
| DOI | 10.1002/mrm.10246 |
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| Abstract | Localized short‐echo‐time 1H‐MR spectra of human brain contain contributions of many low‐molecular‐weight metabolites and baseline contributions of macromolecules. Two approaches to model such spectra are compared and the data acquisition sequence, optimized for reproducibility, is presented. Modeling relies on prior knowledge constraints and linear combination of metabolite spectra. Investigated was what can be gained by basis parameterization, i.e., description of basis spectra as sums of parametric lineshapes. Effects of basis composition and addition of experimentally measured macromolecular baselines were investigated also. Both fitting methods yielded quantitatively similar values, model deviations, error estimates, and reproducibility in the evaluation of 64 spectra of human gray and white matter from 40 subjects. Major advantages of parameterized basis functions are the possibilities to evaluate fitting parameters separately, to treat subgroup spectra as independent moieties, and to incorporate deviations from straightforward metabolite models. It was found that most of the 22 basis metabolites used may provide meaningful data when comparing patient cohorts. In individual spectra, sums of closely related metabolites are often more meaningful. Inclusion of a macromolecular basis component leads to relatively small, but significantly different tissue content for most metabolites. It provides a means to quantitate baseline contributions that may contain crucial clinical information. Magn Reson Med 48:440–453, 2002. © 2002 Wiley‐Liss, Inc. |
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| AbstractList | Localized short-echo-time (1)H-MR spectra of human brain contain contributions of many low-molecular-weight metabolites and baseline contributions of macromolecules. Two approaches to model such spectra are compared and the data acquisition sequence, optimized for reproducibility, is presented. Modeling relies on prior knowledge constraints and linear combination of metabolite spectra. Investigated was what can be gained by basis parameterization, i.e., description of basis spectra as sums of parametric lineshapes. Effects of basis composition and addition of experimentally measured macromolecular baselines were investigated also. Both fitting methods yielded quantitatively similar values, model deviations, error estimates, and reproducibility in the evaluation of 64 spectra of human gray and white matter from 40 subjects. Major advantages of parameterized basis functions are the possibilities to evaluate fitting parameters separately, to treat subgroup spectra as independent moieties, and to incorporate deviations from straightforward metabolite models. It was found that most of the 22 basis metabolites used may provide meaningful data when comparing patient cohorts. In individual spectra, sums of closely related metabolites are often more meaningful. Inclusion of a macromolecular basis component leads to relatively small, but significantly different tissue content for most metabolites. It provides a means to quantitate baseline contributions that may contain crucial clinical information. Localized short‐echo‐time 1H‐MR spectra of human brain contain contributions of many low‐molecular‐weight metabolites and baseline contributions of macromolecules. Two approaches to model such spectra are compared and the data acquisition sequence, optimized for reproducibility, is presented. Modeling relies on prior knowledge constraints and linear combination of metabolite spectra. Investigated was what can be gained by basis parameterization, i.e., description of basis spectra as sums of parametric lineshapes. Effects of basis composition and addition of experimentally measured macromolecular baselines were investigated also. Both fitting methods yielded quantitatively similar values, model deviations, error estimates, and reproducibility in the evaluation of 64 spectra of human gray and white matter from 40 subjects. Major advantages of parameterized basis functions are the possibilities to evaluate fitting parameters separately, to treat subgroup spectra as independent moieties, and to incorporate deviations from straightforward metabolite models. It was found that most of the 22 basis metabolites used may provide meaningful data when comparing patient cohorts. In individual spectra, sums of closely related metabolites are often more meaningful. Inclusion of a macromolecular basis component leads to relatively small, but significantly different tissue content for most metabolites. It provides a means to quantitate baseline contributions that may contain crucial clinical information. Magn Reson Med 48:440–453, 2002. © 2002 Wiley‐Liss, Inc. Localized short-echo-time (1)H-MR spectra of human brain contain contributions of many low-molecular-weight metabolites and baseline contributions of macromolecules. Two approaches to model such spectra are compared and the data acquisition sequence, optimized for reproducibility, is presented. Modeling relies on prior knowledge constraints and linear combination of metabolite spectra. Investigated was what can be gained by basis parameterization, i.e., description of basis spectra as sums of parametric lineshapes. Effects of basis composition and addition of experimentally measured macromolecular baselines were investigated also. Both fitting methods yielded quantitatively similar values, model deviations, error estimates, and reproducibility in the evaluation of 64 spectra of human gray and white matter from 40 subjects. Major advantages of parameterized basis functions are the possibilities to evaluate fitting parameters separately, to treat subgroup spectra as independent moieties, and to incorporate deviations from straightforward metabolite models. It was found that most of the 22 basis metabolites used may provide meaningful data when comparing patient cohorts. In individual spectra, sums of closely related metabolites are often more meaningful. Inclusion of a macromolecular basis component leads to relatively small, but significantly different tissue content for most metabolites. It provides a means to quantitate baseline contributions that may contain crucial clinical information.Localized short-echo-time (1)H-MR spectra of human brain contain contributions of many low-molecular-weight metabolites and baseline contributions of macromolecules. Two approaches to model such spectra are compared and the data acquisition sequence, optimized for reproducibility, is presented. Modeling relies on prior knowledge constraints and linear combination of metabolite spectra. Investigated was what can be gained by basis parameterization, i.e., description of basis spectra as sums of parametric lineshapes. Effects of basis composition and addition of experimentally measured macromolecular baselines were investigated also. Both fitting methods yielded quantitatively similar values, model deviations, error estimates, and reproducibility in the evaluation of 64 spectra of human gray and white matter from 40 subjects. Major advantages of parameterized basis functions are the possibilities to evaluate fitting parameters separately, to treat subgroup spectra as independent moieties, and to incorporate deviations from straightforward metabolite models. It was found that most of the 22 basis metabolites used may provide meaningful data when comparing patient cohorts. In individual spectra, sums of closely related metabolites are often more meaningful. Inclusion of a macromolecular basis component leads to relatively small, but significantly different tissue content for most metabolites. It provides a means to quantitate baseline contributions that may contain crucial clinical information. |
| Author | Jung, B. Slotboom, J. Boesch, C. Hofmann, L. Maloca, P. Kreis, R. |
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| Keywords | Human Spectrometry Macromolecule Metabolite Reproducibility Medical imagery Parameterization Nuclear magnetic resonance imaging Quantitative analysis Brain (vertebrata) |
| Language | English |
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| References | Soher BJ, Hurd RE, Sailasuta N, Barker PB. Quantitation of automated single-voxel proton MRS using cerebral water as an internal reference. Magn Reson Med 1996; 36: 335-339. Mierisova S, van den Boogaart A, Tkac I, Van Hecke P, Vanhamme L, Liptaj T. New approach for quantitation of short echo time in vivo 1H MR spectra of brain using AMARES. NMR Biomed 1998; 11: 32-39. Banay-Schwartz M, Lajtha A, Palkovits M. Regional distribution of glutamate and aspartate in adult and old human brain. Brain Res 1992; 594: 343-346. Moonen CTW, van Zijl PCM. Highly effective water suppression for in vivo proton NMR spectroscopy (DRYSTEAM). J Magn Reson 1990; 88: 28-41. Provencher SW. Estimation of metabolite concentration from localized in vivo proton NMR spectra. Magn Reson Med 1993; 30: 672-679. Hennig J. The application of phase rotation for localized in vivo proton spectroscopy with short echo times. J Magn Reson 1992; 96: 40-49. Ernst T, Hennig J. Improved water suppression for localized in vivo 1H spectroscopy. J Magn Reson Series B 1995; 106: 181-186. Soher BJ, Young K, Govindaraju V, Maudsley AA. Automated spectral analysis. III. Application to in vivo proton MR spectroscopy and spectroscopic imaging. Magn Reson Med 1998; 40: 822-831. Ernst T, Kreis R, Ross BD. Absolute quantitation of water and metabolites in the human brain. I. Compartments and water. J Magn Reson Series B 1993; 102: 1-8. Vanhamme L, van den Boogaart A, van Huffel S. Improved method for accurate and efficient quantification of MRS data with use of prior knowledge. J Magn Reson 1997; 129: 35-43. Saunders DE, Howe FA, van den Boogaart A, Griffiths JR, Brown MM. Discrimination of metabolite from lipid and macromolecule resonances in cerebral infarction in humans using short echo proton spectroscopy. J Magn Reson Imag 1997; 7: 1116-1121. Kreis R. Quantitative localized 1H-MR spectroscopy for clinical use. Prog NMR Spectrosc 1997; 31: 155-195. Soher BJ, Young K, Maudsley AA. Representation of strong baseline contributions in 1H MR spectra. Magn Reson Med 2001; 45: 966-972. Cady EB, D'Souza PC. Analysis of proton brain spectra from human infants by fitting linear combinations of model spectra. J Magn Reson Anal 1997; 3: 5-14. Slotboom J, Boesch C, Kreis R. Versatile frequency domain fitting using time domain models and prior knowledge. Magn Reson Med 1998; 39: 899-911. Young K, Soher BJ, Maudsley AA. Automated spectral analysis. II. Application of wavelet shrinkage for characterization of non-parameterized signals. Magn Reson Med 1998; 40: 816-821. Bartha R, Drost DJ, Williamson PC. Factors affecting the quantification of short echo in-vivo 1H MR spectra: prior knowledge, peak elimination, and filtering. NMR Biomed 1999; 12: 205-216. Hakumaki JM, Kauppinen RA. 1H NMR visible lipids in the life and death of cells. Trends Biochem Sci 2000; 25: 357-362. Pouwels PJ, Brockmann K, Kruse B, Wilken B, Wick M, Hanefeld F, Frahm J. Regional age dependence of human brain metabolites from infancy to adulthood as detected by quantitative localized proton MRS. Pediatr Res 1999; 46: 474-485. Govindaraju V, Young K, Maudsley AA. Proton NMR chemical shifts and coupling constants for brain metabolites. NMR Biomed 2000; 13: 129-153. Hofmann L, Slotboom J, Boesch C, Kreis R. Characterization of the macromolecule baseline in localized 1H-MR spectra of human brain. Magn Reson Med 2001; 46: 855-863. de Graaf AA, Bovee WMMJ. Improved quantification of in vivo 1H NMR spectra by optimization of signal acquisition and processing and by incorporation of prior knowledge into the spectral fitting. Magn Reson Med 1990; 15: 305-319. Young K, Govindaraju V, Soher BJ, Maudsley AA. Automated spectral analysis. I. Formation of a priori information by spectral simulation. Magn Reson Med 1998; 40: 812-815. van der Veen JW, de Beer R, Luyten PR, van Ormondt D. Accurate quantification of in vivo 31P NMR signals using the variable projection method and prior knowledge. Magn Reson Med 1988; 6: 92-98. Mader I, Seeger U, Weissert R, Klose U, Naegele T, Melms A, Grodd W. Proton MR spectroscopy with metabolite-nulling reveals elevated macromolecules in acute multiple sclerosis. Brain 2001; 124: 953-961. Kreis R, Ross BD. Cerebral metabolic disturbances in patients with subacute and chronic diabetes mellitus: detection with proton MR spectroscopy. Radiology 1992; 184: 123-130. Pfeuffer J, Tkac I, Provencher SW, Gruetter R. Toward an in vivo neurochemical profile: quantification of 18 metabolites in short-echo-time (1)H NMR spectra of the rat brain. J Magn Reson 1999; 141: 104-120. Ala-Korpela M, Korhonen A, Liinamaa MJ, Savolainen MJ, Jokisaari J, Kesäniemi YA. 1H NMR and prior knowledge based lineshape fitting analysis: a powerful combination for quantitative biochemistry of plasma and lipoproteins. J Magn Reson Anal 1997; 3: 15-20. Cavassila S, Deval S, Huegen C, van Ormondt D, Graveron-Demilly D. Cramer-Rao bounds: an evaluation tool for quantitation. NMR Biomed 2001; 14: 278-283. Whittall KP, MacKay AL, Graeb DA, Nugent RA, Li DKB, Paty DW. In vivo measurement of T2 distributions and water contents in normal human brain. Magn Reson Med 1997; 37: 34-47. 2001; 124 1992; 184 1990; 15 2000; 25 1998 1999; 46 1999; 141 1996; 36 2001; 45 1998; 40 1993; 102 1997; 3 2001; 46 1997; 7 1999 1992; 96 1998; 39 1990; 88 1997; 129 2000 1997; 31 1992; 594 2000; 13 1988; 6 1997; 37 1993; 30 1995; 106 1999; 12 1984 2001; 14 1998; 11 |
| References_xml | – reference: Pouwels PJ, Brockmann K, Kruse B, Wilken B, Wick M, Hanefeld F, Frahm J. Regional age dependence of human brain metabolites from infancy to adulthood as detected by quantitative localized proton MRS. Pediatr Res 1999; 46: 474-485. – reference: van der Veen JW, de Beer R, Luyten PR, van Ormondt D. Accurate quantification of in vivo 31P NMR signals using the variable projection method and prior knowledge. Magn Reson Med 1988; 6: 92-98. – reference: de Graaf AA, Bovee WMMJ. Improved quantification of in vivo 1H NMR spectra by optimization of signal acquisition and processing and by incorporation of prior knowledge into the spectral fitting. Magn Reson Med 1990; 15: 305-319. – reference: Kreis R. Quantitative localized 1H-MR spectroscopy for clinical use. Prog NMR Spectrosc 1997; 31: 155-195. – reference: Mierisova S, van den Boogaart A, Tkac I, Van Hecke P, Vanhamme L, Liptaj T. New approach for quantitation of short echo time in vivo 1H MR spectra of brain using AMARES. NMR Biomed 1998; 11: 32-39. – reference: Cady EB, D'Souza PC. Analysis of proton brain spectra from human infants by fitting linear combinations of model spectra. J Magn Reson Anal 1997; 3: 5-14. – reference: Kreis R, Ross BD. Cerebral metabolic disturbances in patients with subacute and chronic diabetes mellitus: detection with proton MR spectroscopy. Radiology 1992; 184: 123-130. – reference: Hennig J. The application of phase rotation for localized in vivo proton spectroscopy with short echo times. J Magn Reson 1992; 96: 40-49. – reference: Hofmann L, Slotboom J, Boesch C, Kreis R. Characterization of the macromolecule baseline in localized 1H-MR spectra of human brain. Magn Reson Med 2001; 46: 855-863. – reference: Mader I, Seeger U, Weissert R, Klose U, Naegele T, Melms A, Grodd W. Proton MR spectroscopy with metabolite-nulling reveals elevated macromolecules in acute multiple sclerosis. Brain 2001; 124: 953-961. – reference: Ernst T, Hennig J. Improved water suppression for localized in vivo 1H spectroscopy. J Magn Reson Series B 1995; 106: 181-186. – reference: Provencher SW. Estimation of metabolite concentration from localized in vivo proton NMR spectra. Magn Reson Med 1993; 30: 672-679. – reference: Vanhamme L, van den Boogaart A, van Huffel S. Improved method for accurate and efficient quantification of MRS data with use of prior knowledge. J Magn Reson 1997; 129: 35-43. – reference: Bartha R, Drost DJ, Williamson PC. Factors affecting the quantification of short echo in-vivo 1H MR spectra: prior knowledge, peak elimination, and filtering. NMR Biomed 1999; 12: 205-216. – reference: Soher BJ, Young K, Govindaraju V, Maudsley AA. Automated spectral analysis. III. Application to in vivo proton MR spectroscopy and spectroscopic imaging. Magn Reson Med 1998; 40: 822-831. – reference: Cavassila S, Deval S, Huegen C, van Ormondt D, Graveron-Demilly D. Cramer-Rao bounds: an evaluation tool for quantitation. NMR Biomed 2001; 14: 278-283. – reference: Young K, Govindaraju V, Soher BJ, Maudsley AA. Automated spectral analysis. I. Formation of a priori information by spectral simulation. Magn Reson Med 1998; 40: 812-815. – reference: Soher BJ, Young K, Maudsley AA. Representation of strong baseline contributions in 1H MR spectra. Magn Reson Med 2001; 45: 966-972. – reference: Soher BJ, Hurd RE, Sailasuta N, Barker PB. Quantitation of automated single-voxel proton MRS using cerebral water as an internal reference. Magn Reson Med 1996; 36: 335-339. – reference: Banay-Schwartz M, Lajtha A, Palkovits M. Regional distribution of glutamate and aspartate in adult and old human brain. Brain Res 1992; 594: 343-346. – reference: Saunders DE, Howe FA, van den Boogaart A, Griffiths JR, Brown MM. Discrimination of metabolite from lipid and macromolecule resonances in cerebral infarction in humans using short echo proton spectroscopy. J Magn Reson Imag 1997; 7: 1116-1121. – reference: Slotboom J, Boesch C, Kreis R. Versatile frequency domain fitting using time domain models and prior knowledge. Magn Reson Med 1998; 39: 899-911. – reference: Govindaraju V, Young K, Maudsley AA. Proton NMR chemical shifts and coupling constants for brain metabolites. NMR Biomed 2000; 13: 129-153. – reference: Moonen CTW, van Zijl PCM. Highly effective water suppression for in vivo proton NMR spectroscopy (DRYSTEAM). J Magn Reson 1990; 88: 28-41. – reference: Ernst T, Kreis R, Ross BD. Absolute quantitation of water and metabolites in the human brain. I. Compartments and water. J Magn Reson Series B 1993; 102: 1-8. – reference: Pfeuffer J, Tkac I, Provencher SW, Gruetter R. Toward an in vivo neurochemical profile: quantification of 18 metabolites in short-echo-time (1)H NMR spectra of the rat brain. J Magn Reson 1999; 141: 104-120. – reference: Young K, Soher BJ, Maudsley AA. Automated spectral analysis. II. Application of wavelet shrinkage for characterization of non-parameterized signals. Magn Reson Med 1998; 40: 816-821. – reference: Whittall KP, MacKay AL, Graeb DA, Nugent RA, Li DKB, Paty DW. In vivo measurement of T2 distributions and water contents in normal human brain. Magn Reson Med 1997; 37: 34-47. – reference: Ala-Korpela M, Korhonen A, Liinamaa MJ, Savolainen MJ, Jokisaari J, Kesäniemi YA. 1H NMR and prior knowledge based lineshape fitting analysis: a powerful combination for quantitative biochemistry of plasma and lipoproteins. J Magn Reson Anal 1997; 3: 15-20. – reference: Hakumaki JM, Kauppinen RA. 1H NMR visible lipids in the life and death of cells. 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| SubjectTerms | 1H-magnetic resonance spectroscopy quantitation Adolescent Adult Aged Biological and medical sciences brain Brain - metabolism Brain Chemistry Female glutamate Humans Investigative techniques, diagnostic techniques (general aspects) Macromolecular Substances macromolecules Magnetic Resonance Spectroscopy - methods Male Medical sciences Middle Aged Nervous system Radiodiagnosis. Nmr imagery. Nmr spectrometry |
| Title | Quantitative 1H-magnetic resonance spectroscopy of human brain: Influence of composition and parameterization of the basis set in linear combination model-fitting |
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