Imaging Mass Spectrometry ROI Specification via Optical Overlay
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Solution Overview
Problem
The challenge lies in setting appropriate regions of interest (ROIs) for analysis in mass spectrometric imaging graphics, as visual differences in ion intensity may not be recognizable, leading to inefficient trial-and-error processes, especially when detecting disease markers or analyzing biological tissues.
Innovation Solution
An imaging mass spectrometric data analyzer is developed, featuring a reference image display processor to create and display two-dimensional intensity distribution images from non-mass spectrometric imaging techniques, an ROI specification processor to allow users to specify ROIs, and an analysis processor to extract and perform multivariate analysis on mass spectrometric data from these regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If mass spectrometric imaging graphic is used to set ROI, then ion intensity distribution can be visualized, but visual recognition of site differences is insufficient when ion intensity difference is small
Solution Approach 1:
The patent merges mass spectrometric imaging data with optical microscope images to create a composite image. The optical microscope image provides clear morphological structure that enables visual recognition of tissue sites, while the mass spectrometric data provides ion intensity information. This combination allows users to accurately identify and set ROIs based on visible morphological features rather than relying solely on subtle ion intensity differences.
Solution Approach 2:
The patent introduces an intermediary processing step that overlays mass spectrometric imaging data onto optical microscope images. This intermediary composite image serves as a bridge between the two data types, allowing the clear visual information from optical microscopy to mediate the identification of regions that would otherwise be difficult to distinguish in mass spectrometric images alone.
2Difficulty of detecting and measuring
If optical microscope image is used to set ROI, then morphological structure is clearly visible, but sites with unclear visual features are excluded from ROI candidates
Solution Approach 1:
The patent combines optical microscope images with mass spectrometric imaging graphics to create a composite image. This allows users to leverage the clear morphological visualization of optical microscopy while simultaneously accessing information from mass spectrometry that may reveal sites not visually distinguishable in optical images alone.
Solution Approach 2:
The patent adds a new dimension of information by overlaying mass spectrometric data onto the optical image. This additional dimensional information from mass spectrometry allows detection of sites based on ion intensity characteristics rather than relying solely on optical visual features, effectively adding a new channel for identifying ROIs.
3Measurement precision
If trial and error method is used to set ROI for disease marker detection, then appropriate ROI can be identified, but analysis efficiency is reduced
Solution Approach 1:
The patent performs preliminary action by pre-processing and overlaying mass spectrometric imaging data onto optical microscope images before the user sets ROIs. This preliminary preparation creates a composite image that clearly indicates potential ROIs based on ion intensity distribution, eliminating the need for users to perform trial-and-error adjustments and significantly speeding up the ROI setting process.
Data Source
AI summary
A reference image data input section reads, from a Raman spectroscopic analyzer, a set of data constituting a Raman spectroscopic imaging graphic for a target sample. An ROI specification processor) displays a Raman spectroscopic imaging graphic based on those data on a display unit. An operator viewing the image operates an input unit to set a plurality of ROIs. Then, the ROI specification processor determines position information of the ROIs. An analysis processor extracts the data of measurement points corresponding to the set ROIs from MS imaging data acquired by an analysis performed by an imaging mass spectrometry unit for the same target sample. The processor also calculates an average mass spectrum from the data of a large number of measurement points for each ROI, and performs a multivariate analysis on the plurality of average mass spectrum data to compare the ROIs with each other or divide them into groups.