Advertisement

Error images for spectroscopic imaging by LCModel using Cramer–Rao bounds

  • F. Jiru
  • A. Skoch
  • U. Klose
  • W. Grodd
  • M. HajekEmail author
Research Article

Abstract

The results of spectroscopic imaging (SI) measurements are often presented as metabolic images. If the spectra quality is not sufficient, the calculated concentrations are biased and the metabolic images show an incorrect metabolite distribution. To simplify the quality analysis of spectra measured by SI, an error image, reflecting the accuracy of the computed concentrations, can be displayed along with the metabolite image. In this paper the relevance of Cramer–Rao bounds (CRBs) calculated by the LCModel program to describe errors in estimated concentrations is validated using spectra simulations. The relation between the average CRBs and standard deviations (STD) of metabolite concentrations from 100 simulated spectra for various signal to noise ratio and line broadening conditions is evaluated. A parameter for calculating error images for metabolite ratios is proposed and an effective way to display error images is shown. The results suggest that the average CRBs are strongly correlated with the standard deviations and hence that CRB values reflect the relative uncertainty of the calculated concentrations. The error information can be integrated directly into a metabolite image by displaying only those areas of the metabolite image with corresponding CRBs below a selected threshold or by mapping CRBs as a transparency of the metabolite image. The concept of error images avoids extensive examination of each SI spectrum and helps to reject low quality spectra

Keywords

Spectroscopic imaging Error images LCModel Cramer–Rao bounds 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Brown TR, Kincaid BM, Ugurbil D (1982) NMR chemical shift imaging in three dimensions. Proc Natl Acad Sci 79:3523–3526PubMedCrossRefGoogle Scholar
  2. 2.
    Maudsley AA, Hilal SK, Perman WP, Simon HE (1983) Spatially resolved high resolution spectroscopy by four dimensional NMR. J Magn Reson 51:147–152Google Scholar
  3. 3.
    Maudsley AA, Lin E, Weiner MW (1992) Spectroscopic imaging display and analysis. Magn Reson Imag 10:471–485CrossRefGoogle Scholar
  4. 4.
    Ebel A, Soher BJ, Maudsley AA (2001) Assessment of 3D proton MR echo-planar spectroscopic imaging using automated spectral analysis. Magn Reson Med 46:1072–1078PubMedCrossRefGoogle Scholar
  5. 5.
    Young K, Khetselius D, Soher BJ, Maudsley AA (2000) Confidence images for MR spectroscopic imaging. Magn Reson Med 44:537–545PubMedCrossRefGoogle Scholar
  6. 6.
    Jiru F, Skoch A, Klose U, Grodd W, Hajek M (2004) Spectroscopic imaging of Glutamine and Glutamate using LCModel and error images. In: Proceedings of the 21th Annual Science Meeting ESMRMB, MAGMA – Suppl, Copenhagen, DenmarkGoogle Scholar
  7. 7.
    Kreis R (2004) Issues of spectral quality in clinical 1H-magnetic resonance spectroscopy and a gallery of artifacts NMR Biomed 17:361–381Google Scholar
  8. 8.
    Barkhuijsen H, de Beer R, van Ormondt D (1986) Error theory for time domain signal analysis with linear prediction and singular value decomposition. J Magn Reson 67:371–375Google Scholar
  9. 9.
    Cavassila S, Deval S, Huegen C, van Ormondt D, Graveron-Demilly D (2000) Cramer–Rao bound expressions for parametric estimation of overlapping peaks: influence of prior knowledge. J Magn Reson 143:311–320PubMedCrossRefGoogle Scholar
  10. 10.
    Cavassila S, Deval S, Huegen C, van Ormondt D, Graveron-Demilly D (2001) Cramer–Rao Bounds: an evaluation tool for quantitation. NMR Biomed. 14:278–283PubMedCrossRefGoogle Scholar
  11. 11.
    Provencher SW (1993) Estimation of metabolite concentrations from localized in vivo proton NMR spectra. Magn Reson Med 30:672–679PubMedCrossRefGoogle Scholar
  12. 12.
    McLean MA, Woermann FG, Barker GJ, Duncan JS (2000) Quantitative analysis of short echo time 1H-MRSI of cerebral gray and white matter. Magn Reson Med 44:401–411PubMedCrossRefGoogle Scholar
  13. 13.
    Jiru F, Burian M, Skoch A, Hajek M (2002) LCModel for spectroscopic imaging. In: Proceedings of the Annual Science Meeting ESMRMB, MAGMA Suppl 1, Cannes, p 368Google Scholar
  14. 14.
    Srinivasan R, Vigneron D, Sailasuta N, Hurd R, Nelson S (2004) A comparative study of myo-inositol quantification using LCmodel at 1.5 T and 3.0 T with 3 D 1H proton spectroscopic imaging of the human brain. Magn Reson Imag 22:523–528CrossRefGoogle Scholar
  15. 15.
    Provencher SW (1982) A constrained regularization method for inverting data represented by linear algebraic or integral equations. Comput Phys Commun 27:213–227CrossRefGoogle Scholar
  16. 16.
    Kanowski M, Kaufmann J, Braun J, Bernarding J, Tempelmann C (2004) Quantitation of simulated short echo time 1H human brain spectra by LCModel and AMARES. Magn Reson Med 51:904–912PubMedCrossRefGoogle Scholar
  17. 17.
    Hofmann L, Slotboom J, Jung B, Maloca P, Boesch C, Kreis R (2002) Quantitative 1H-magnetic resonance spectroscopy of human brain: influence of composition and parameterization of the basis set in linear combination model-fitting. Magn Reson Med 48:440–453PubMedCrossRefGoogle Scholar
  18. 18.
    Macri MA, Garreffa G, Giove F, Guardati M, Ambrosini A, Colonnese C, Maraviglia B (2004) In vivo quantitative 1H MRS of cerebellum and evaluation of quantitation reproducibility by simulation of different levels of noise and spectral resolution. Magn Reson Imaging 22:1385–1393Google Scholar
  19. 19.
    Seeger U, Klose U, Mader I, Grodd W, Nagele T (2003) Parameterized evaluation of macromolecules and lipids in proton MR spectroscopy of brain diseases. Magn Reson Med 49:19–28PubMedCrossRefGoogle Scholar
  20. 20.
    Taylor JR (1996) An introduction to error analysis: the study of uncertainties in physical measurements. University Science BooksGoogle Scholar
  21. 21.
    Pouwels PJ, Brockmann K, Kruse B, Wilken B, Wick M, Hanefeld F, Frahm J (1999) Regional age dependence of human brain metabolites from infancy to adulthood as detected by quantitative localized proton MRS. Pediatr Res 46:474–485PubMedCrossRefGoogle Scholar
  22. 22.
    Hajek M, Adamovicova M, Herynek V, Skoch A, Jiru F, Krepelova A, Dezortova M (2005) MR relaxometry and 1H MR spectroscopy for the determination of iron and metabolite concentrations in PKAN patients. Eur Radiol 15:1060–1068PubMedCrossRefGoogle Scholar
  23. 23.
    Ratiney H, Coenradie Y, Cavassila S, van Ormondt D, Graveron-Demilly D (2004) Time-domain quantitation of 1H short echo-time signals: background accommodation. MAGMA 16:284–296PubMedCrossRefGoogle Scholar

Copyright information

© ESMRMB 2006

Authors and Affiliations

  • F. Jiru
    • 1
    • 2
  • A. Skoch
    • 2
  • U. Klose
    • 1
  • W. Grodd
    • 1
  • M. Hajek
    • 2
    Email author
  1. 1.Section of Experimental MR of the CNS, Department of NeuroradiologyUniversity of TuebingenTue bingenGermany
  2. 2.MR UnitInstitute for Clinical and Experimental MedicinePrague 4Czech Republic

Personalised recommendations