Imaging Mass Spectrometry Data Processing for Compound Identification
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Solution Overview
Problem
Conventional imaging mass spectrometry techniques face challenges in accurately identifying compounds in biological samples due to overlapping peaks from multiple compounds, leading to low identification scores and unreliable results.
Innovation Solution
An imaging mass spectrometry data processing device and method that create mass spectrometry images, set regions of interest, acquire calculated MSn spectra by adding or subtracting average spectra, and perform compound identification using library search to enhance accuracy by isolating target compounds from overlapping signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If mass spectrometry is performed at each measurement point within a two-dimensional region on a sample to obtain distribution information, then spatial distribution visualization is achieved, but peak overlapping from multiple compounds occurs leading to low identification accuracy
Solution Approach 1:
The patent divides the two-dimensional measurement region into multiple small regions (regions of interest) and performs separate MSn analysis on each region. This segmentation allows the system to isolate target compounds in specific regions, reducing peak overlapping from compounds present in other regions. The identification unit then identifies compounds in each small region independently, significantly improving identification accuracy compared to analyzing the entire two-dimensional region as a single unit.
2Reliability
If library search is performed on MSn spectra from the entire two-dimensional region, then compound identification is attempted, but overlapping peaks from multiple compounds result in low scores and unreliable identification
Solution Approach 1:
The patent segments the data processing workflow by dividing the two-dimensional region into multiple small regions and performing separate library search on MSn spectra from each small region. This segmentation of the identification process eliminates the need to process overlapping peaks from the entire region simultaneously, thereby improving identification reliability while keeping data processing manageable through automated handling of multiple small datasets.
3Measurement precision
If MSn analysis is performed on the entire two-dimensional region, then comprehensive compound coverage is achieved, but peak overlapping reduces the quality of identification scores
Solution Approach 1:
The patent divides the large two-dimensional measurement region into multiple small regions and performs MSn analysis separately on each small region. This segmentation reduces peak overlapping within each analysis unit, thereby improving the quality of identification scores. The system comprehensively covers all compounds across the entire two-dimensional region by processing multiple small regions, achieving both comprehensive coverage and high score quality.
Solution Approach 2:
The patent introduces a new dimension of spatial resolution by dividing the two-dimensional measurement space into multiple discrete small regions. This dimensional segmentation allows the system to analyze compounds in each small region independently, transforming the problem from a single large two-dimensional analysis into multiple smaller two-dimensional analyses, thereby improving score quality while maintaining comprehensive coverage.
Data Source
AI summary
The user specifies regions of interest (ROIs) such as a region where a large amount of compound to be identified is estimated to be included and a region where the compound is overlapped with another compound on one or more specific MS images, and specifies addition or subtraction of the ROIs. For each of the specified ROIs, an average MS/MS spectrum is calculated from MS/MS spectrum data at measurement points in the regions, and the average MS/MS spectra at the ROIs are subjected to addition or subtraction, to obtain an MS/MS spectrum. By addition between the ROIs, the intensity of peak derived from the target compound can be increased. By subtraction between the ROIs, a peak derived from the other compound overlapped with the target compound can be removed. When the MS/MS spectrum after addition or subtraction is subjected to library search for identification, a score indicating the similarity of the spectrum is higher than the conventional score, and the identification accuracy can be improved.