Results and interpretation of a fitting challenge for MR spectroscopy set up by the MRS study group of ISMRM

the 2016 ISMRM MRS Study Group Fitting Challenge Team

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

Purpose: Fitting of MRS data plays an important role in the quantification of metabolite concentrations. Many different spectral fitting packages are used by the MRS community. A fitting challenge was set up to allow comparison of fitting methods on the basis of performance and robustness. Methods: Synthetic data were generated for 28 datasets. Short-echo time PRESS spectra were simulated using ideal pulses for the common metabolites at mostly near-normal brain concentrations. Macromolecular contributions were also included. Modulations of signal-to-noise ratio (SNR); lineshape type and width; concentrations of γ-aminobutyric acid, glutathione, and macromolecules; and inclusion of artifacts and lipid signals to mimic tumor spectra were included as challenges to be coped with. Results: Twenty-six submissions were evaluated. Visually, most fit packages performed well with mostly noise-like residuals. However, striking differences in fit performance were found with bias problems also evident for well-known packages. In addition, often error bounds were not appropriately estimated and deduced confidence limits misleading. Soft constraints as used in LCModel were found to substantially influence the fitting results and their dependence on SNR. Conclusions: Substantial differences were found for accuracy and precision of fit results obtained by the multiple fit packages.

Original languageEnglish (US)
Pages (from-to)11-32
Number of pages22
JournalMagnetic resonance in medicine
Volume87
Issue number1
Early online dateAug 2 2021
DOIs
StatePublished - Jan 2022

Bibliographical note

Funding Information:
The authors thank the following members of the 2016 ISMRM MRS Study Group Fitting Challenge Team: Jeffry R. Alger, Patrick J. Bolan, Tamas Borbath, Fawzi Boumezbeur, Carolina C. Fernandes, Eduardo Coello, Bharath Halandur Nagraja, Michal Považan, Hélène Ratiney, Diana Sima, Jana Starčuková, Brian J. Soher, Martin Wilson, Jack J.A. van Asten. Furthermore, we are also grateful to the further participants of the fitting challenge: Paul Chang, Nicolas Kunz, Ulrich Pilatus, Min Wang, and Yan Zhang. The authors would also like to thank Johannes Slotboom, Ph.D. for providing a spectrum from a patient with a brain tumor, Sreenath Kyathanahally, Ph.D. for help with creation of jMRUI format files, Christine Bolliger, Ph.D. for data used to create the macromolecular spectrum, Kendrick Kay, Ph.D. for visualization of the results, Patrick Bolan, Ph.D. for helpful discussion. MM and DKD acknowledge the support of the National Institutes of Health grants BTRC P41 EB027061 and P30 NS076408, while RK acknowledges support by the Swiss National Science Foundation (320030-175984).

Funding Information:
The authors would also like to thank Johannes Slotboom, Ph.D. for providing a spectrum from a patient with a brain tumor, Sreenath Kyathanahally, Ph.D. for help with creation of jMRUI format files, Christine Bolliger, Ph.D. for data used to create the macromolecular spectrum, Kendrick Kay, Ph.D. for visualization of the results, Patrick Bolan, Ph.D. for helpful discussion. MM and DKD acknowledge the support of the National Institutes of Health grants BTRC P41 EB027061 and P30 NS076408, while RK acknowledges support by the Swiss National Science Foundation (320030‐175984).

Publisher Copyright:
© 2021 International Society for Magnetic Resonance in Medicine.

Keywords

  • H MRS
  • analysis
  • brain
  • fitting
  • quantification
  • spectrum

Center for Magnetic Resonance Research (CMRR) tags

  • SMCT
  • P41

PubMed: MeSH publication types

  • Journal Article
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

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