Imaging Mass Spectrometer Isomer Classification via MSn Multivariate Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional imaging mass spectrometers struggle to distinguish between structural isomers of compounds that are identical in mass but differ in structure, leading to incorrect determination of spatial distribution information.
Innovation Solution
An imaging mass spectrometer equipped with a measurement section capable of performing MSn analysis across a two-dimensional area, utilizing a reference spectrum acquirer, analysis controller, spectrum classifier, and image creator to classify product-ion spectra through multivariate analysis, allowing for the visualization of spatial distribution for each compound candidate based on structural differences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional imaging mass spectrometry using MS/MS analysis is employed to distinguish ions with close mass-to-charge ratios, then the specificity of compound detection is improved, but structural isomers with identical mass-to-charge ratios cannot be distinguished
Solution Approach 1:
The patent segments the mass spectrometry analysis into multiple stages: initial MS detection, followed by multiple MSn analysis stages with different collision energies. Each stage produces fragment ion spectra that are processed independently through multivariate analysis, allowing structural differentiation of isomers that cannot be distinguished by a single mass-to-charge ratio measurement.
Solution Approach 2:
The patent changes the analysis parameters by performing MSn analysis with multiple different collision energies. This parameter variation produces different fragment ion patterns for different structural isomers, enabling their distinction. The multivariate analysis processor compares spectra obtained under different collision energy conditions to identify and separate signals from structural isomers.
2Measurement precision
If MSn analysis with multiple collision energies is performed for each measurement point, then spatial distribution of each compound can be determined, but the measurement time and complexity increase
Solution Approach 1:
The patent performs preliminary multivariate analysis processing on the fragment ion spectra to create reference data structures before final image reconstruction. The system pre-processes spectra from multiple collision energies, identifies characteristic fragment patterns for different compounds, and stores this information for efficient comparison during image generation, reducing the computational burden during actual measurement.
Solution Approach 2:
The patent uses multivariate analysis to create virtual reference spectra and compound profiles from the measured data. These copied spectral patterns serve as templates for identifying and mapping compound distributions, allowing the system to efficiently recognize and quantify compounds without requiring exhaustive measurement of every possible spectral variation at each pixel location.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate visualization of spatial distribution for each structural isomer, providing detailed structural information rather than just mass-to-charge ratio-based distribution, improving the accuracy of compound identification and spatial mapping.
Implementation Method 1
an imaging mass spectrometer equipped with a measurement section capable of performing an MSn analysis (where n is an integer equal to or greater than two) for each measurement point
Data Source
AI summary
A user enters structures of a plurality of metabolite candidates contained in a sample. A dissociation pattern predictor predicts a dissociation pattern for each metabolite candidate. An MS/MS spectrum estimator estimates an MS/MS spectrum and stores it in a teaching data storage. An imaging mass spectrometry unit acquires measured MS/MS spectra for each measurement point within a measurement range on a sample by performing an MS/MS analysis in which a precursor ion based on mass information of each metabolite candidate is used as an analysis target. A multivariate analysis processor performs a multivariate analysis in which the peak information based on the MS/MS spectra stored in the teaching data storage is used as teaching data, to classify measured MS/MS spectra at each measurement point into a plurality of metabolite candidates. Based on the classification result, a spatial distribution creator creates an image showing a spatial distribution for each metabolite candidate.