Imaging Mass Spectrometer Data Normalization
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Solution Overview
Problem
In imaging mass spectrometry, comparing data from multiple samples with different measurement point intervals and mass-to-charge ratio values is challenging due to variations in measurement conditions and ion intensity fluctuations, leading to inaccurate statistical analyses and subjective evaluations.
Innovation Solution
The method involves equalizing measurement point intervals and mass-to-charge ratio points across samples through interpolation or extrapolation, allowing for the combination and normalization of data, enabling accurate statistical analysis and simultaneous display of mass analysis result images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data from multiple samples with different measurement point intervals and mass-to-charge ratio values are directly compared, then the analysis process is simple, but the statistical analysis accuracy deteriorates due to variations in measurement conditions
Solution Approach 1:
The patent applies parameter changes by transforming the measurement point intervals and mass-to-charge ratio values to a common reference scale. Specifically, it converts the mass-to-charge ratio values to a standardized range and resamples the measurement points at uniform intervals, allowing direct comparison while maintaining statistical accuracy. This resolves the contradiction by changing the parameters of the raw data to enable accurate comparison without requiring complex sample-by-sample normalization procedures.
Solution Approach 2:
The patent introduces an intermediary reference frame with standardized measurement point intervals and mass-to-charge ratio values. All sample data are transformed to align with this reference frame before comparison, serving as a mediator that enables accurate statistical analysis. This intermediary structure allows multiple samples with different original parameters to be compared accurately without direct complex pairwise normalization.
2Manufacturing precision
If measurement point intervals are made smaller to improve spatial resolving power, then the spatial resolution improves, but the total data amount increases enormously
Solution Approach 1:
The patent performs preliminary data transformation and compression by converting all measurement data to a standardized reference frame with fixed measurement point intervals and mass-to-charge ratio ranges before analysis. This preliminary action reduces the effective data dimensionality and allows efficient storage and processing, preventing the exponential growth of data requirements that would otherwise result from high-resolution imaging of multiple samples.
3Reliability
If ion intensity signals are summed multiple times to compensate for fluctuations, then the signal stability improves, but the processing time increases
Solution Approach 1:
The patent introduces an intermediary reference frame that standardizes mass-to-charge ratio values and measurement point intervals across all samples. By transforming data to this common reference before comparison, the method enables direct statistical analysis without requiring time-consuming repeated measurements or complex normalization procedures for each sample pair, thus maintaining reliability while reducing processing time.
Data Source
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AI summary
In the case where the spatial measurement point intervals in imaging mass analysis data of two samples to be compared are different and where the degrees of spatial distribution spreading of substances are compared, one of the data is defined as a reference, the measurement point intervals in the other of the data are redefined so as to be equalized to the reference, and a mass spectrum at each virtual measurement point set as a result of the redefinition is obtained through interpolation or extrapolation based on a mass spectrum at an actual measurement points (S7). In the case where the arrays of the m/z values of mass spectra are different for each sample, the m/z value positions of the mass spectrum in one of the data are defined as a reference, and the intensity values corresponding to the reference m/z values are obtained through interpolation or extrapolation for the mass spectrum of the other of the data (S8). Because the measurement point intervals and the arrays of the m/z values are equalized in this way, the imaging mass analysis data can be combined with each other so as to be treated as one piece of data, whereby processing such as the creation of a peak matrix for a statistical analysis can be simply performed. Accordingly, a statistical analysis for comparing imaging mass analysis data respectively obtained from a plurality of samples can be simply performed, and the accuracy of the statistical analysis can be improved.