Flow Cytometry Signal Saturation Handling for Accurate Cell Sorting
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Solution Overview
Problem
Flow-type particle sorting systems face challenges in accurately classifying particles due to saturated data signals from light detection, leading to inaccuracies in particle sorting decisions.
Innovation Solution
Methods and systems for adjusting particle classification indices by identifying and excluding saturated data signals, calculating adjusted spectral unmixing matrices, and implementing bitmap gating strategies to improve classification accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If light detection is used to detect particles in flow stream, then particle detection capability is improved, but signal saturation occurs leading to incorrect classification
Solution Approach 1:
The system performs preliminary detection of saturation conditions by monitoring detector output ranges before final classification decisions are made. When saturation is detected, the system preemptively adjusts classification parameters or excludes saturated signals from analysis, preventing incorrect sorting decisions from being made based on saturated data.
Solution Approach 2:
The system continuously monitors detector signals and uses feedback from saturation detection to adjust classification indices and sorting decisions in real-time. The saturated signal index is fed back into the classification process to modify particle identification, ensuring that saturated detectors do not lead to incorrect sorting decisions.
2Productivity
If saturated data signals are included in classification, then data utilization is maximized, but classification accuracy deteriorates
Solution Approach 1:
The system extracts and identifies saturated signals from the overall data set, then removes or excludes these saturated data points from the classification process. By separating saturated signals from valid signals, the system maintains high data utilization for valid measurements while preventing saturated signals from degrading classification accuracy.
Solution Approach 2:
The system changes the parameters used in classification by adjusting classification indices based on saturation detection. When saturation is detected in specific detector channels, the system modifies the spectral unmixing matrix or classification thresholds to compensate for or exclude the impact of saturated signals, thereby maintaining classification accuracy.
3Productivity
If spectral unmixing is performed with saturated signals, then fluorescence analysis is completed, but sorting purity is reduced
Solution Approach 1:
The system performs preliminary identification of saturated signals before completing the spectral unmixing process. By detecting saturation conditions in advance, the system can adjust the spectral unmixing matrix or exclude saturated channels from the analysis, ensuring that final sorting decisions are based on reliable fluorescence data rather than saturated measurements.
Solution Approach 2:
The system introduces a saturated signal index as an intermediary element that mediates between raw detector signals and final classification decisions. This intermediary structure allows the system to track which signals are saturated and use this information to adjust the spectral unmixing process, thereby maintaining sorting purity while still utilizing available fluorescence data.
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 particle sorting by improving the assignment of particles to correct populations and increasing the yield and purity of sorted particles.
Implementation Method 1
detecting light from particles in a flow stream
Implementation Method 2
calculating an adjusted spectral unmixing matrix for the fluorescence of the particle
Implementation Method 3
Droplets are passed through an electrostatic field and are deflected based on polarity and magnitude of charge on the droplet into one or more collection containers
Data Source
AI summary
Aspects of the present disclosure include methods for adjusting a particle classification index in response to one or more saturated data signals from light detected from particles in a flow stream. Methods according to certain embodiments include detecting light from particles in a flow stream; generating a plurality of data signals from the detected light; identifying one or more saturated data signals; generating a saturated signal index that corresponds to the identified saturated data signals; and applying the saturated signal index to a particle classification index to generate an adjusted particle classification index. In some embodiments, methods include determining one or more parameters of a particle (e.g., for use in a particle sort decision) by calculating an adjusted spectral unmixing matrix for the fluorescence of the particle that excludes one or more saturated data signals. Systems and integrated circuit devices (e.g., a field programmable gate array) for practicing the subject methods are also provided. Non-transitory computer readable storage mediums are also described.