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Related Concept Videos

Double Resonance Techniques: Overview01:12

Double Resonance Techniques: Overview

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Double resonance techniques in Nuclear Magnetic Resonance (NMR) spectroscopy involve the simultaneous application of two different frequencies or radiofrequency pulses to manipulate and observe two distinct nuclear spins. One important application of double resonance is spin decoupling, which selectively suppresses coupling with one type of nucleus while observing the NMR signal from another nucleus, simplifying the spectrum and enhancing resolution.
Spin decoupling is usually achieved by...
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Related Experiment Video

Updated: Dec 28, 2025

The Use of Magnetic Resonance Spectroscopy as a Tool for the Measurement of Bi-hemispheric Transcranial Electric Stimulation Effects on Primary Motor Cortex Metabolism
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Preprocessing, analysis and quantification in single-voxel magnetic resonance spectroscopy: experts' consensus

Jamie Near1,2, Ashley D Harris3,4,5, Christoph Juchem6

  • 1Douglas Mental Health University Institute and Department of Psychiatry, McGill University, Montreal, Canada.

NMR in Biomedicine
|February 22, 2020
PubMed
Summary

This review details the essential post-acquisition steps for magnetic resonance spectroscopy (MRS) data analysis. It provides best practice recommendations for preprocessing, metabolite signal estimation, and quantification to ensure accurate metabolite concentration measures.

Keywords:
MRSanalysispreprocessingprocessingquantificationquantitationwater referencing

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Area of Science:

  • Neuroimaging and Spectroscopy
  • Biomedical Data Analysis

Background:

  • Magnetic Resonance Spectroscopy (MRS) is crucial for non-invasively measuring brain metabolites.
  • Accurate metabolite concentration quantification requires rigorous post-acquisition data processing.

Purpose of the Study:

  • To review and provide best practice recommendations for the post-acquisition workflow of single-voxel MRS experiments.
  • To guide researchers in obtaining reliable metabolite concentration measures from MRS data.

Main Methods:

  • Review of the three core post-acquisition steps: data preprocessing, signal intensity estimation, and quantification.
  • Discussion of essential techniques and considerations for each stage of the MRS analysis pipeline.

Main Results:

  • Detailed examination of data preprocessing requirements for MRS datasets.
  • Methods for accurate estimation of metabolite signal intensities.
  • Strategies for converting raw signal intensities into scaled concentration units using a quantitative reference.

Conclusions:

  • Adherence to recommended best practices in preprocessing, analysis, and quantification is vital for valid MRS results.
  • Standardized workflows enhance the reliability and interpretability of metabolite concentration measurements in MRS studies.