Flow Cytometer Drop Delay Calculation Using Imaging Sensors
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Solution Overview
Problem
Flow cytometers face inaccuracies in predicting droplets containing particles of interest due to perturbations in the flow stream, leading to imprecise cell sorting and contamination, especially when turbulence is caused by variability in particle size or drift in cytometer components.
Innovation Solution
The method involves determining the drop delay of a flow stream by obtaining and comparing different frequencies of drop perturbation, using imaging sensors and processors to capture and analyze images of the flow stream, allowing for automated adjustment of parameters like electrical charge timing and flow rate without the need for calibration particles or manual input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional hydrodynamic estimation is used to predict droplet contents, then the system is simple to operate, but the prediction accuracy deteriorates due to flow stream perturbations and turbulence
Solution Approach 1:
The patent replaces conventional hydrodynamic mechanical estimation with an optical measurement system using imaging sensors to directly observe and measure flow stream position and droplet characteristics, thereby achieving higher prediction accuracy without relying on simplified hydrodynamic models
Solution Approach 2:
The patent introduces an imaging sensor as an intermediary device that captures images of the flow stream and droplets, allowing indirect measurement of droplet contents and flow position through image analysis rather than direct mechanical measurement
2Productivity
If manual calibration and parameter adjustment are used, then the system requires less computational resources, but the time consumption and labor intensity increase
Solution Approach 1:
The system performs automated self-calibration by using the imaging sensor to capture flow stream characteristics and automatically calculating drop delay and timing parameters, eliminating the need for manual calibration operations and enabling the system to adjust itself based on real-time observations
Solution Approach 2:
The patent implements a feedback mechanism where images of the flow stream are continuously captured, analyzed to determine actual droplet positions and timing, and used to automatically adjust charging and deflection timing parameters, creating a closed-loop system that optimizes performance in real-time
3Adaptability or versatility
If flow stream turbulence is present due to particle variability, then the system can handle diverse samples, but the droplet prediction reliability deteriorates
Solution Approach 1:
The patent replaces hydrodynamic modeling that assumes laminar flow with direct optical measurement of actual droplet positions and flow stream characteristics, allowing the system to accurately predict droplet contents even when turbulence and flow variations occur due to diverse particle sizes and sample types
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 approach enhances the predictability and accuracy of cell sorting by reducing turbulence-related errors, improving the precision and reliability of flow cytometry analyses by automatically determining optimal operating conditions for the flow cytometer.
Implementation Method 1
the flow cell is rapidly vibrated by an acoustic device, such as a piezoelectric transducer
Implementation Method 2
rapidly vibrated by an acoustic device
Implementation Method 3
light from the irradiation source (e.g., laser) is scattered
Implementation Method 4
The light can also excite components in the cell stream that have fluorescent properties, such as fluorescent markers
Implementation Method 5
the flow stream is subjected to an electrical charge upstream from the deflection plate such that the first frequency and second frequency are determined from one or more captured images of the deflected flow stream
Data Source
AI summary
Aspects of the present disclosure include methods and systems for determining drop delay of a flow stream in a flow cytometer. Methods according to certain embodiments include obtaining a first frequency (f1) of drop perturbation of a flow stream subjected to an oscillating vibration, capturing one or more images of the flow stream in a detection field, obtaining a second frequency (f2) of drop perturbation of the flow stream based on one or more of the captured images and determining the drop delay of the flow stream based on the first frequency and the second frequency. Systems for practicing the subject methods having an imaging sensor for capturing one or more images of the flow stream and a processor configured to calculate drop delay using one or more of the captured images are also provided. Non-transitory computer readable storage mediums are also described.