What is the optimal schedule for multiparametric MRS? A magnetic resonance fingerprinting perspective

Alexey Kulpanovich, Assaf Tal

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Clinical magnetic resonance spectroscopy (MRS) mainly concerns itself with the quantification of metabolite concentrations. Metabolite relaxation values, which reflect the microscopic state of specific cellular and sub-cellular environments, could potentially hold additional valuable information, but are rarely acquired within clinical scan times. By varying the flip angle, repetition time and echo time in a preset way (termed a schedule), and matching the resulting signals to a pre-generated dictionary – an approach dubbed magnetic resonance fingerprinting – it is possible to encode the spins' relaxation times into the acquired signal, simultaneously quantifying multiple tissue parameters for each metabolite. Herein, we optimized the schedule to minimize the averaged root mean square error (RMSE) across all estimated parameters: concentrations, longitudinal and transverse relaxation time, and transmitter inhomogeneity. The optimal schedules were validated in phantoms and, subsequently, in a cohort of healthy volunteers, in a 4.5 mL parietal white matter single voxel and an acquisition time under 5 minutes. The average intra-subject, inter-scan coefficients of variation (CVs) for metabolite concentrations, T1 and T2 relaxation times were found to be 3.4%, 4.6% and 4.7% in-vivo, respectively, averaged over all major singlets. Coupled metabolites were quantified using the short echo time schedule entries and spectral fitting, and reliable estimates of glutamate+glutamine, glutathione and myo-inositol were obtained.

Original languageEnglish
Article numbere4196
JournalNMR in Biomedicine
Volume34
Issue number5
DOIs
StatePublished - May 2021
Externally publishedYes

Bibliographical note

Funding Information:
Assaf Tal acknowledges the support of the Minerva Foundation, Monroy-Marks Career Development Fund, and the historic generosity of the Harold Perlman Family. This work was supported by NIH grant R21 NS112853?01. By optimizing the schedule, MRSF can be used to acquire the relaxation values of the major singlets, without significantly impairing the quantification of metabolite concentrations of both coupled and uncoupled resonances. Monitoring the unsuppressed water signal as the system is driven into dynamic equilibrium produces estimates of water's T1 and T2 constants as well. The ability to acquire per-subject multiparametric spectroscopic data provides more accurate and robust absolute quantification of metabolite concentrations. Furthermore, ample evidence exists that metabolite relaxation times change in multiple neuropathologies, making them potential biomarkers. The multiparametric framework proposed herein thus also enhances the clinical relevance of single voxel MRS, all within a clinical timeframe of under five minutes. Assaf Tal acknowledges the support of the Minerva Foundation, Monroy-Marks Career Development Fund, and the historic generosity of the Harold Perlman Family. This work was supported by NIH grant R21 NS112853?01.

Funding Information:
Assaf Tal acknowledges the support of the Minerva Foundation, Monroy‐Marks Career Development Fund, and the historic generosity of the Harold Perlman Family. This work was supported by NIH grant R21 NS112853–01.

Publisher Copyright:
© 2019 John Wiley & Sons, Ltd.

Keywords

  • MRF
  • MRS
  • MRSF
  • T1 relaxation
  • T2 relaxation
  • magnetic resonance fingerprinting
  • magnetic resonance spectroscopy
  • multiparametric MRS

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