Quality Control Standards for Batch Effect Evaluation and Correction in Mass Spectrometry Imaging

Area of Science:

• Analytical Chemistry
• Biotechnology
• Mass Spectrometry Imaging

Background:

• Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) enables spatial molecular profiling but faces challenges in reproducibility.
• Technical variations from sample preparation and instrument performance hinder accurate assessment and data quality in MALDI-MSI.
• A standardized method for quality control and batch effect correction is needed to enhance the reliability of MALDI-MSI results.

Purpose of the Study:

• To develop and validate a novel quality control standard (QCS) for MALDI-MSI.
• To introduce a data analysis pipeline for evaluating and correcting technical variations in MALDI-MSI.
• To improve the reproducibility and data quality of spatial molecular profiling using MALDI-MSI.

Main Methods:

• Designed a tissue-mimicking QCS using propranolol in a gelatin matrix to simulate ion suppression.
• Conducted a three-day batch experiment to assess the QCS's sensitivity to longitudinal technical variations.
• Applied three computational approaches for batch effect correction to MALDI-MSI data, including principal component analysis (PCA).

Main Results:

• The developed QCS effectively mimicked ion suppression observed in tissue samples.
• The QCS demonstrated sensitivity to longitudinal technical variations, serving as an effective indicator of batch effects.
• Batch effect correction significantly reduced QCS variation and improved sample clustering in PCA, enhancing data quality.

Conclusions:

• The designed QCS provides a reliable tool for evaluating batch effects in MALDI-MSI.
• The data analysis pipeline effectively corrects for technical variations, improving MALDI-MSI data reproducibility.
• This integrated approach offers MALDI-MSI users a robust method for quality control and enhanced data analysis.