Metabolite Annotation Confidence Score (MACS): A Novel MSI Identification Scoring Tool

Mass spectrometry imaging (MSI) is an analytical techniquecapableof measuring and visualizing the spatial distribution of thousandsof ions across a sample. Measured ions can be putatively identifiedand annotated by comparing their mass-to-charge ratio (m/z) to a database of known compounds. For high-resolution,accurate mass (HRAM) imaging data sets, this is commonly performedby the annotation platform METASPACE. Annotations are reported witha metabolite-signal-match (MSM) score as a measure of the annotation'sconfidence level. However, the MSM scores reported by METASPACE oftendo not reflect a reasonable confidence level of an annotation andare not assigned consistently. The metabolite annotation confidencescore (MACS) is an alternative scoring system based on fundamentalmass spectrometry imaging metrics (mass measurement accuracy, spectralaccuracy, and spatial distribution) to generate values that reflectthe confidence of a specific annotation in HRAM-MSI data sets. Herein,the MACS system is characterized and compared to MSM scores from ionsannotated by METASPACE.

Automated summary

Mass spectrometry imaging (MSI) is a technique for measuring and visualizing the spatial distribution of ions in a sample. METASPACE is commonly used for annotation in high-resolution, accurate mass imaging data, but its reported confidence scores often do not accurately reflect the confidence level. The metabolite annotation confidence score (MACS) is an alternative system based on fundamental metrics to generate values that reflect the confidence of an annotation in HRAM-MSI data.