The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Time‐domain semi‐parametric estimation based on a metabolite basis set
Abstract
A novel and fast time‐domain quantitation algorithm—quantitation based on semi‐parametric quantum estimation (QUEST)—invoking optimal prior knowledge is proposed and tested. This nonlinear least‐squares algorithm fits a time‐domain model function, made up from a basis set of quantum‐mechanically simulated whole‐metabolite signals, to low‐SNR in vivo data. A basis set of in vitro measured signals can be used too. The simulated basis set was created with the software package NMR‐SCOPE which can invoke various experimental protocols. Quantitation of 1 H short echo‐time signals is often hampered by a background signal originating mainly from macromolecules and lipids. Here, we propose and compare three novel semi‐parametric approaches to handle such signals in terms of bias‐variance trade‐off. The performances of our methods are evaluated through extensive Monte‐Carlo studies. Uncertainty caused by the background is accounted for in the Cramér–Rao lower bounds calculation. Valuable insight about quantitation precision is obtained from the correlation matrices. Quantitation with QUEST of 1 H in vitro data, 1 H in vivo short echo‐time and 31 P human brain signals at 1.5 T, as well as 1 H spectroscopic imaging data of human brain at 1.5 T, is demonstrated. Copyright © 2005 John Wiley & Sons, Ltd.
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Cites
Estimation of metabolite concentrations from localized in vivo proton NMR spectra
Provencher, S. W. (1993) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910300604 · Cited by 3,655
Magnetic Resonance Imaging: Physical Principles and Sequence Design
Brown, R. W., Cheng, Y. N., Haacke, E. M., Thompson, M. R., & Venkatesan, R. (2014) · doi:10.1002/9781118633953 · Cited by 2,688
Proton NMR chemical shifts and coupling constants for brain metabolites
Govindaraju, V., Young, K., & Maudsley, A. A. (2000) · NMR in Biomedicine · doi:10.1002/1099-1492(200005)13:3<129::aid-nbm619>3.0.co;2-v · Cited by 1,689
Dynamics of blood flow and oxygenation changes during brain activation: the Balloon model
Buxton, R. B., Wong, E. C., & Frank, L. R. (1998) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910390602 · Cited by 1,665
Automatic quantitation of localized in vivo1H spectra with LCModel
Provencher, S. W. (2001) · NMR in Biomedicine · doi:10.1002/nbm.698 · Cited by 1,634
Improved Method for Accurate and Efficient Quantification of MRS Data with Use of Prior Knowledge
Vanhamme, L., van den Boogaart, A., & Van Huffel, S. (1997) · Journal of Magnetic Resonance · doi:10.1006/jmre.1997.1244 · Cited by 1,627
Efficient and Adaptive Estimation for Semiparametric Models.
Do, K. A., Bickel, P. J., Klaassen, C. A. J., Ritov, Y., & Wellner, J. A. (1994) · Biometrics · doi:10.2307/2533465 · Cited by 1,403
Efficient and Adaptive Estimation for Semiparametric Models.
Schick, A., Bickel, P. J., Klaassen, C. A. J., Ritov, Y., & Wellner, J. A. (1994) · Journal of the American Statistical Association · doi:10.2307/2291028 · Cited by 1,109
Java-based graphical user interface for the MRUI quantitation package
Naressi, A., Couturier, C., Devos, J. M., Janssen, M., Mangeat, C., Beer, R. D., & Graveron-Demilly, D. (2001) · Magnetic Resonance Materials in Physics, Biology and Medicine · doi:10.1007/bf02668096 · Cited by 1,003
Self-citationAnalysis of macromolecule resonances in 1H NMR spectra of human brain
Behar, K. L., Rothman, D. L., Spencer, D. D., & Petroff, O. A. C. (1994) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910320304 · Cited by 467
Cited by
Methodological consensus on clinical proton MRS of the brain: Review and recommendations
Wilson, M., Andronesi, O., Barker, P. B., Bartha, R., Bizzi, A., Bolan, P. J., Brindle, K. M., Choi, I., Cudalbu, C., Dydak, U., et al. (2019) · Magnetic Resonance in Medicine · doi:10.1002/mrm.27742 · Cited by 470
Wilson, M., Reynolds, G., Kauppinen, R. A., Arvanitis, T. N., & Peet, A. C. (2011) · Magnetic Resonance in Medicine · doi:10.1002/mrm.22579 · Cited by 332
Altered Reward Circuitry in the Norepinephrine Transporter Knockout Mouse
Gallagher, J. J., Zhang, X., Hall, F. S., Uhl, G. R., Bearer, E. L., & Jacobs, R. E. (2013) · PLoS ONE · doi:10.1371/journal.pone.0057597 · Cited by 25
Metadata
- Authors
- Ratiney, H., Sdika, M., Coenradie, Y., Cavassila, S., Ormondt, D. V., & Graveron‐Demilly, D.
- Venue
- NMR in Biomedicine
- Publisher
- Wiley
- Published
- 2005-01-19
- Volume
- 18
- Issue
- 1
- Pages
- 1-13
- ISSN
- 0952-3480 (ISSN-L)
- 1099-1492
- OpenAlex
- W2051783722
- Cited by
- 295
- References
- 35
- FWCI
- 10.71
- Type
- journal article
- Language
- en
- Open access
- closed
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- Ratiney, H., Sdika, M., Coenradie, Y., Cavassila, S., Ormondt, D. V., & Graveron‐Demilly, D. (2005). Time‐domain semi‐parametric estimation based on a metabolite basis set. NMR in Biomedicine. https://doi.org/10.1002/nbm.895
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