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This study introduces a novel multilabel approach for quantitative mass spectrometry imaging (MSI). This method improves accuracy by creating individual calibration curves for each pixel, outperforming the traditional single-label standard for heterogeneous samples.

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Area of Science:

  • Analytical Chemistry
  • Biomedical Imaging
  • Mass Spectrometry

Background:

  • Quantitative mass spectrometry imaging (MSI) typically uses a single internal standard for calibration.
  • This standard method overlooks local variations in noise and ion suppression, affecting accuracy.
  • Ion suppression effects can be concentration-dependent, further complicating quantification.

Purpose of the Study:

  • To develop and validate a novel multilabel approach for improved quantitative MSI.
  • To address the limitations of single internal standards in MSI, particularly concerning ion suppression heterogeneity.
  • To enable pixel-specific calibration curves for more accurate quantification of endogenous compounds.

Main Methods:

  • Application of multiple isotopically labeled versions of a target compound at varying concentrations to the sample.
  • Development of per-pixel internal calibration curves using the multilabel approach.
  • Quantification of an endogenous peptide (histone H4) using matrix-assisted laser desorption/ionization-Q-MSI (MALDI-Q-MSI) and comparison with a single-label method.

Main Results:

  • The multilabel approach demonstrated superior accuracy compared to the single-label method, especially for inhomogeneously distributed compounds.
  • Significant heterogeneity in ion suppression was observed across tissue samples, with varying regression slopes (up to a factor of 4).
  • Results were validated by liquid chromatography-mass spectrometry (LC-MS), showing high agreement (Pearson correlation r = 0.87).

Conclusions:

  • The proposed multilabel approach provides more accurate quantification in MSI than the conventional single-label method.
  • This method is particularly advantageous when target compounds exhibit wide concentration ranges and inhomogeneous distribution within tissues.
  • Pixel-specific calibration using multiple internal standards effectively accounts for local variations in ion suppression and noise.