Breath Sample Data Alignment for GC-MS Retention Time Correction
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Solution Overview
Problem
Current breath analysis techniques face challenges in accurately comparing breath fingerprints over time and across different equipment due to retention time shifts in GC-MS data, hindering integration into digital platforms for clinical applications.
Innovation Solution
A computer-implemented method synchronizes gas samples by identifying marker molecules, clustering, and performing polynomial fitting corrections to align retention times, followed by additional corrections using existing software toolboxes, allowing for accurate time synchronization and integration of breath data from various sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GC-MS analysis is used to obtain breath fingerprints, then diagnostic information can be obtained, but retention time shifts occur due to column aging causing inaccurate comparisons
Solution Approach 1:
The patent introduces an intermediary substance (retention time standard or internal standard compound) that is added to breath samples to serve as a reference marker. This intermediary allows for the calculation and correction of retention time shifts by comparing the retention time of the standard compound across different measurements, thereby enabling accurate comparison of breath fingerprints despite column aging and instrumental drift.
Solution Approach 2:
The patent applies parameter changes by dynamically adjusting retention time values based on observed shifts. Through mathematical transformations (such as retention time correction factors or alignment algorithms), the system transforms raw retention time data into corrected retention time data that compensates for instrumental drift, maintaining measurement precision over time and across different GC-MS systems.
2Productivity
If breath samples are analyzed across different equipment and time points, then more data can be collected for clinical applications, but data integration becomes problematic due to equipment-specific variations
Solution Approach 1:
The patent implements universality by developing a standardized data processing framework that can handle breath analysis data from multiple different GC-MS systems and time points. The retention time correction methodology using internal standards creates a universal reference system that enables data from heterogeneous sources to be integrated and compared, effectively making the analysis system multi-source compatible.
Solution Approach 2:
The patent applies preliminary action by performing retention time correction and normalization as a pre-processing step before data integration and analysis. By correcting retention time shifts and normalizing data early in the workflow using internal standard references, the system prepares data from different equipment and time points for seamless integration, avoiding the need for complex post-processing synchronization.
3Measurement precision
If traditional alignment methods are used, then some retention time correction can be achieved, but accurate alignment across large time periods and different equipment remains difficult
Solution Approach 1:
The patent uses an intermediary reference compound (internal standard) that is consistently added to all breath samples. This intermediary serves as a stable reference point that allows for the calculation of retention time correction factors across large time spans and different equipment. By tracking the retention time of this intermediary substance, the system can accurately align data regardless of when or on what equipment the analysis was performed.
Solution Approach 2:
The patent applies parameter changes through dynamic retention time correction factors that are calculated based on the observed shift of internal standard compounds. These correction factors transform raw retention time parameters into aligned parameters, enabling accurate comparison of breath fingerprints even when analyses are performed months or years apart or on different GC-MS systems.
Data Source
AI summary
A method for synchronizing data for gas samples with volatile organic compounds. The data includes chromatographic data indicative of molecule retention times. The method includes identifying or selecting marker molecules and clustering the plurality of gas samples into a plurality of clusters according to a clustering criterion. Next, a first correction of retention time deviations is performed on the data for the gas samples between clusters by using the marker molecules as anchor points to provide a coarse reduction of retention time deviations between the data. Finally, a second correction of retention time deviations is performed on the data, so as to further reduce retention time deviations between the data. The method reduces significant retention time deviations to allow, e.g., breath sample fingerprints obtained by different equipment at different times to be compared in one database for use on a digital platform.