Mathematical Framework for Quantifying Delocalization in MALDI-MSI via a Composite Scoring Approach

Area of Science:

• Biomedical imaging
• Analytical chemistry
• Molecular pathology

Background:

• Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is crucial for visualizing biomolecule distribution in tissues.
• Analyte delocalization, the spreading of molecules beyond their original location, is a significant challenge impacting MALDI-MSI sensitivity and spatial resolution.
• This phenomenon is often exacerbated by sample preparation techniques, including matrix application.

Purpose of the Study:

• To develop and evaluate metrics for quantifying analyte delocalization in MALDI-MSI data.
• To establish a robust delocalization score for assessing image quality and data reliability.
• To investigate the correlation of delocalization patterns among different analytes within mouse brain sections.

Main Methods:

• Utilized MALDI-MSI data from mouse brain sections to assess various delocalization metrics.
• Evaluated metrics such as distances between centers of mass, off-tissue signal distances from the border, and background signal area.
• Defined a novel delocalization score as a tunable linear combination of background area and mean off-tissue distance.

Main Results:

• A linear combination of background area and mean distance effectively quantified analyte delocalization.
• The proposed delocalization score demonstrated practical utility, with higher weighting on area proving effective.
• Strong correlations in delocalization scores across different analytes were observed, indicating consistent delocalization behaviors.

Conclusions:

• The developed delocalization score provides a quantitative method to assess and potentially mitigate issues in MALDI-MSI.
• The score's tunability allows adaptation to specific experimental needs and applications.
• Consistent delocalization patterns across analytes suggest shared underlying mechanisms or sensitivities to sample handling in MALDI-MSI.