MALDI-TOF Mass Spectrometer Time-of-Flight Data Processing
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Solution Overview
Problem
MALDI-TOF MS systems face challenges in data reproducibility due to variations in ionized particle velocities and incident angles, leading to inaccurate disease diagnostics, particularly in cancer detection, as the conversion of time-of-flight measurements to mass-to-charge ratios introduces statistical variations and compromises diagnostic accuracy.
Innovation Solution
The approach involves processing spectrometer test data by maintaining time-of-flight data in its original units and intensity, rather than converting it to mass-to-charge ratios, to minimize standard deviation and optimize data alignment with reference libraries, using techniques such as deep learning algorithms to enhance diagnostic accuracy and reproducibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If MALDI-TOF MS is used for rapid sample analysis with high sensitivity, then productivity is improved, but data spread over time occurs due to different incident angles of particles, worsening reliability
Solution Approach 1:
The patent changes the parameter domain from mass-to-charge ratio to time-of-flight measurement. By working directly with time measurements and their statistical distributions rather than converted mass values, the system maintains the rapid analysis capability while improving data reproducibility. The approach accounts for the intrinsic time variations caused by different incident angles without requiring conversion to mass-to-charge ratios.
2Difficulty of detecting and measuring
If mass-to-charge ratio conversion is performed for diagnostic analysis, then disease detection capability is enhanced, but statistical variation in time-of-flight measurements is amplified, worsening measurement precision
Solution Approach 1:
The patent inverts the conventional diagnostic approach by performing disease detection directly in the time-of-flight domain rather than converting to mass-to-charge ratios. This allows disease detection capability to be maintained through pattern recognition in time-domain spectra while avoiding the amplification of statistical variations that occurs during quadratic conversion.
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
This method improves the reproducibility and accuracy of disease diagnostics by minimizing the spread of peaks in time-of-flight data, allowing for more precise matching with reference profiles, thereby enhancing the reliability of disease diagnosis in MALDI-TOF MS systems.
Implementation Method 1
A laser may fire laser pulses at the sample. The matrix may absorb the energy from the laser and the molecules of the sample may be ionized
Implementation Method 2
When a spectrometer measures the time-of-flight of an ionized particle, the measured time-of-flight can be converted to a mass-to-charge ratio using a quadratic equation
Data Source
AI summary
An apparatus, method, or computer program. spectrometer test data of a sample may be received for processing. The spectrometer test data may include time-of-flight data in units of time and intensity of ionized particles travelling through a flight tube. The spectrometer test data may be matched to a reference library to determine characteristic information of the sample. The reference library may include spectrometer sample data in units of time and intensity of ionized particles of pre-stored reference samples detected by spectrometers in the past. The spectrometer reference data has known characteristics that the matching associates with the received spectrometer test data.