Imaging Mass Spectrometry Peak Integration for Low-Intensity Compounds
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Solution Overview
Problem
Conventional imaging mass spectrometers face challenges in accurately detecting and displaying the distribution of compounds with low signal intensity, as their peaks can be buried under higher intensity peaks, and mass peaks from different compounds with close m/z values often overlap, leading to inaccurate representation of compound distribution.
Innovation Solution
The method involves dividing the measurement region into smaller analysis regions, averaging or summing profile spectra within each region, detecting and integrating peak information, and creating a peak list or mass spectrum that reflects the presence of compounds with accurate m/z values, preventing peak burial and enhancing mass accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If mass spectra from all micro regions are averaged or summed to create an average mass spectrum, then information about all compounds in the measurement region is reflected, but locally observed mass peaks with low signal intensity are buried under high intensity peaks from other regions
Solution Approach 1:
The measurement region is divided into multiple sub-regions, and mass spectra are averaged separately within each sub-region before integrating peak information across all sub-regions. This segmentation prevents high intensity peaks from one region from burying low intensity peaks from other regions, as each sub-region's average spectrum retains its unique peak characteristics.
Solution Approach 2:
Peak information (m/z values and signal intensities) is extracted from each sub-region's average mass spectrum separately, then integrated across all sub-regions. This extraction approach preserves peak information from each region rather than losing it in the overall average, allowing locally distributed compounds to be detected.
2Measurement precision
If mass peaks from different compounds with close m/z values are observed in an average mass spectrum, then the peaks may overlap and become indistinguishable, but separating them requires higher mass resolution
Solution Approach 1:
By dividing the measurement region into sub-regions and creating separate average spectra for each, the method reduces the number of overlapping peaks in each individual spectrum. This segmentation decreases the complexity of peak separation requirements, allowing accurate mass measurement without needing extremely high mass resolution to resolve all possible overlaps simultaneously.
Solution Approach 2:
The method uses iterative peak information integration where peak data from multiple sub-regions is combined and used to refine the identification of mass peaks. This feedback process helps distinguish overlapping peaks by cross-validating their presence across multiple sub-region spectra, improving mass accuracy without requiring proportionally higher resolution.
Data Source
AI summary
An imaging mass spectrometer according to the present invention includes: a measurement unit to acquire data by performing mass spectrometry for each micro regions in a measurement region; an analysis region determination unit to determine analysis regions each including the micro regions by dividing the measurement region or in accordance with user designation; a spectrum operation unit to acquire, in each analysis regions, an individual integrated mass spectrum by averaging or summing profile spectra based on data obtained by the measurement unit; a peak information integration unit to detect a peak on each individual integrated mass spectrum, to collect peak information including at least an m z value of the peak, to gather peak information, to integrate peaks that can be estimated to have substantially the same m/z value to obtain integrated peak information; and a display processing unit to create a peak list or a mass spectrum.