Flow Cytometry Data Fusion for Multidimensional Parameter Reconstruction

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Solution Overview

Problem

Current flow cytometry methods are limited in their ability to characterize cellular components due to the restricted number of parameters that can be simultaneously measured, which hinders the detailed identification and differentiation of normal and neoplastic cells within a sample.

Innovation Solution

The method involves fusing separate flow cytometry data files from different aliquots of the same sample, estimating missing parameter values with uncertainty measures, and reconstructing multidimensional data files to include all evaluated parameters, allowing for a higher number of parameters to be considered for each cellular event.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If multiple separate flow cytometry data files are fused to increase the number of parameters per event, then the characterization capability of cellular populations is improved, but the data processing complexity and computational requirements increase

Engineering Contradiction:

Improveparameter information completenessVSAvoiddata processing complexity

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The method segments the analysis by separating measured parameters from estimated parameters. Measured parameters come from actual flow cytometry data files, while estimated parameters are generated through computational modeling. This segmentation allows the system to handle incomplete data by filling gaps with statistically derived estimates, thereby completing the parameter information for each cellular event without requiring all parameters to be directly measured simultaneously.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces computational algorithms as an intermediary between raw flow cytometry data and final cellular characterization. These algorithms estimate missing parameter values by analyzing relationships between measured parameters and known cellular properties, acting as a mediator that transforms incomplete measured data into comprehensive parameter sets without requiring direct measurement of all parameters.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Loss of information

If the number of simultaneously measured parameters is increased to improve cell characterization, then the identification capability of cellular populations is improved, but the instrument capability and measurement capability are limited

Engineering Contradiction:

Improveparameter measurement completenessVSAvoidparameter measurement capability

Core Design Contradiction:

Loss of informationVSDifficulty of detecting and measuring

Solution Approach 1:

The method performs preliminary computational estimation of parameters that cannot be directly measured or are difficult to measure. By pre-calculating expected parameter values based on measured data and established cellular models, the system prepares complete parameter profiles before final cellular event characterization, effectively overcoming instrument measurement limitations.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent transforms the measurement problem by changing from direct physical measurement of all parameters to a hybrid approach where some parameters are measured and others are computationally derived. This parameter transformation allows the system to access information beyond direct measurement capabilities by using mathematical relationships between parameters.

Inventive Principle:

Principle #35Parameter changes

3Loss of information

If separate aliquots are measured to obtain additional parameters, then the number of parameters per event is increased, but the measurement time and analysis time are extended

Engineering Contradiction:

Improveparameter diversityVSAvoidmeasurement and analysis time

Core Design Contradiction:

Loss of informationVSLoss of time

Solution Approach 1:

The method merges multiple separate flow cytometry measurements into a unified dataset by fusing data from different aliquots. Each aliquot may contain measurements for different parameter sets, and the fusion process integrates these datasets with computational estimation to create complete parameter profiles for all cellular events, combining the benefits of multiple measurements without requiring sequential analysis of each aliquot separately.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The patent maintains continuous useful action by using computational estimation to fill parameter gaps continuously rather than requiring intermittent separate measurements. Once initial measurements are obtained, the system continuously generates estimated parameter values, maintaining the analytical process without interruption and reducing total measurement and analysis time.

Inventive Principle:

Principle #20Continuity of useful action

Data Source

PatentEP1770387B1Generation of the flow cytometry data files with a potentially infinite number of dimensions derived from the fusion of a group of separate flow cytometry data files and their multidimensional reconstruction with both actually measured and estimated flow cytometry data

Publication Date: 2011.02.09 UNIV DE SALAMANCA

AI summary

The present invention relates to a method that generates new flow cytometry data files with a potentially infinite number of dimensions, each event contained in these data files having associated information for each of the whole set of parameters evaluated, such information deriving from data which was either directly measured in the flow cytometer or estimated afterwards.