Mass Spectrometry Peak Deconvolution for Higher Sample Throughput
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Solution Overview
Problem
High-throughput sample analysis in mass spectrometry is limited by the ability to accurately integrate peak areas when signals from adjacent peaks are partially overlapped, particularly in acoustic ejection mass spectrometry, where lower intensity peaks are convolved with higher intensity peaks, and conventional algorithms designed for chromatographic peaks are ineffective.
Innovation Solution
A system and method for calculating peak areas using a processor to fit a mixture of distribution functions to the peak profile, accounting for expected peak times and integrating convolved peaks in acoustic ejection mass spectrometry traces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If delay time between sample injections is increased to prevent peak interference, then peak integration accuracy is improved, but sample throughput decreases
Solution Approach 1:
The system performs preliminary deconvolution processing on overlapping peaks using a mathematical model that accounts for the specific peak shape characteristics of acoustic ejection mass spectrometry. By pre-calculating and separating convolved peaks through algorithmic decomposition rather than waiting for temporal separation, the system achieves accurate integration without requiring extended delay times between injections.
2Ease of operation
If conventional chromatographic peak integration algorithms are used, then ease of operation is maintained, but measurement precision deteriorates due to asymmetric peak shapes with steep gradients
Solution Approach 1:
The system changes the fundamental parameters of the peak integration approach by adopting a deconvolution-based method tailored to acoustic ejection mass spectrometry peak characteristics. Instead of using standard chromatographic integration algorithms, the system implements a mathematical model that specifically accounts for the asymmetric shape and steep gradients of AEMS peaks, thereby achieving accurate integration despite the complexity increase.
3Productivity
If sample introduction speed is increased to improve throughput, then productivity is improved, but peak overlap increases causing measurement precision to deteriorate
Solution Approach 1:
The system replaces the mechanical/temporal separation approach (increasing delay times) with a computational/mathematical approach (deconvolution algorithms). By substituting the physical separation mechanism with signal processing mathematics, the system can maintain high introduction speeds while achieving accurate peak separation through algorithmic decomposition of overlapping signals.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances the accuracy of peak area calculation in high-throughput sample analysis, allowing for improved integration of asymmetric peaks and maintaining throughput without increasing delay times between sample injections.
Implementation Method 1
acoustic ejection mass spectrometry systems
Implementation Method 2
The sample introduction system ionizes each ejected sample of the series of samples, producing an ion beam
Implementation Method 3
The mass spectrometer receives the ion beam and mass analyzes the ion beam over time
Data Source
AI summary
A trace of intensity versus time values is received for a series of samples produced by a mass spectrometer. Also, a series of ejections times corresponding to the series of samples produced by a sample introduction system is received. A series of expected peak times corresponding to the series of ejection times are calculated using a known delay time from ejection to mass analysis. At least one isolated peak of the trace is identified using the series of expected peak times. A peak profile is calculated by fitting a mixture of at least two different distribution functions to the at least one isolated peak. For at least one time of the series of expected peak times, an area of a peak at the one time is calculated by fitting the peak profile to the trace at the one time and calculating an area of the fitted peak profile.