Imaging Mass Spectrometry Normalization for Multiplicative Noise
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Solution Overview
Problem
Current mass spectrometry preprocessing methods, particularly in mass spectral imaging, face challenges in effectively removing multiplicative noise and accurately normalizing ion intensities across different spectra, leading to biased peak height comparisons and incomplete data normalization.
Innovation Solution
The Ionization Efficiency Correction (IEC) method employs non-negative matrix factorization to separate common and differential ion currents, using a rank-1 approximation to estimate the common ion current and scale spectra accordingly, thereby minimizing the impact of differential peaks and improving relative peak height comparisons.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional Total Ion Current (TIC) based normalization is used, then the preprocessing is simple and fast, but the peak height comparisons become biased due to multiplicative noise and differential peaks
Solution Approach 1:
The patent segments the total ion current into two distinct components: common ion current (present in all spectra) and differential ion current (varying between spectra). This segmentation is achieved through iterative subtraction of the common profile from each spectrum, allowing separate normalization of the common component while preserving differential information. This resolves the contradiction by enabling accurate peak height comparisons through selective normalization without requiring complex global normalization of all peaks.
Solution Approach 2:
The patent applies different normalization treatments to different parts of the spectrum: the common ion current component is normalized across all spectra, while the differential ion current component is preserved as-is. This local differentiation allows accurate comparison of common peaks while maintaining the unique characteristics of differential peaks, resolving the bias introduced by traditional global TIC normalization.
2Measurement precision
If area-under-the-curve based normalization (TIC) is applied, then the computation is straightforward, but the normalization is incomplete due to inability to distinguish common from differential ion content
Solution Approach 1:
The patent performs preliminary separation of common and differential ion currents before normalization. By iteratively identifying and subtracting the common profile from each spectrum, the method prepares the data in a form that enables accurate normalization. This preliminary action resolves the contradiction by automating the differentiation process, eliminating the need for manual peak selection while achieving complete and accurate normalization.
Solution Approach 2:
The patent employs an iterative feedback mechanism where the common profile is extracted, subtracted, and used to refine the normalization factors for subsequent iterations. This feedback loop continuously improves the separation of common and differential components, achieving high normalization accuracy through automated refinement without requiring user intervention.
3Extent of automation
If manual selection of mass range or elution time window is used, then the preprocessing requires user expertise and interaction, but the automation level is low
Solution Approach 1:
The patent implements a self-service automated system that automatically identifies, separates, and normalizes the common ion current component without requiring user selection of mass ranges or interaction with the data. The algorithm autonomously performs iterative profile extraction and normalization, completely eliminating the need for user expertise in preprocessing parameter selection while maintaining high normalization quality.
Data Source
Figure 1.1~1.1(b)
Figure 1.2~1.3
Figure 1.4~1.5
AI summary
The present invention relates generally to a species (analyte) separation and analysis system, for instance a spectrometry system, comprising a processor for receiving and processing signals from said its detector to remove undesirable variation or noise before further processing into a spectrum, whereby the processor is programmed by a novel program for a normalization preprocessing of the signals of said separation and analysis system.