Flow Cytometer Drop Delay Determination via Image Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Flow cytometers face challenges in accurately determining the drop delay, leading to imprecise cell sorting and contamination due to variability in particle size and drift in cytometer components, requiring significant human intervention and calibration.
Innovation Solution
The method involves capturing images of the flow stream to identify disturbances at the break-off point, calculating the drop delay that produces the maximal amplitude of disturbance, and adjusting parameters such as electrical charge timing and flow rate using a processor-controlled system, reducing the need for manual input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration and determination of drop delay is performed, then the system can operate with basic components, but the sorting precision deteriorates due to variability in particle size and drift in cytometer components
Solution Approach 1:
The flow cytometer system performs self-calibration by automatically determining drop delay through image processing of the flow stream. The processor analyzes disturbances at the break-off point to calculate drop delay without requiring manual intervention, enabling the system to adapt to component drift and particle size variability autonomously.
Solution Approach 2:
The patent replaces manual mechanical calibration procedures with an automated optical measurement system. Instead of physically adjusting components based on operator experience, the system uses imaging sensors and computational algorithms to precisely determine drop delay, substituting mechanical adjustment with optical detection and digital processing.
2Manufacturing precision
If automated determination of drop delay is implemented, then sorting precision improves, but device complexity increases due to additional imaging and processing requirements
Solution Approach 1:
The imaging system serves multiple functions: it captures flow stream images for drop delay determination, monitors flow conditions, and provides data for sorting decisions. The processor performs both image analysis for calibration and control functions, making the system multi-functional and reducing the need for separate dedicated components for each function.
Solution Approach 2:
The patent introduces an intermediary imaging system that bridges the gap between the physical flow stream and the digital control system. The images serve as an intermediate representation that allows the processor to accurately determine drop delay and adjust sorting parameters without direct mechanical interaction with the flow stream.
3Measurement precision
If frequent calibration is performed to maintain precision, then sorting accuracy improves, but productivity decreases due to time loss from calibration procedures
Solution Approach 1:
The automated drop delay determination system enables continuous operation without interruption for calibration. The processor continuously monitors the flow stream and adjusts drop delay in real-time, eliminating the need to stop the flow cytometer for periodic calibration and maintaining both precision and productivity simultaneously.
Solution Approach 2:
The system implements a feedback loop where the processor continuously analyzes flow stream images, determines current drop delay, compares it to optimal values, and automatically adjusts parameters. This closed-loop control maintains sorting accuracy throughout operation without requiring manual recalibration, as the system self-corrects for drift and variations.
4Reliability
If manual intervention is required for calibration and operation, then device complexity remains low, but the predictability of particle detection deteriorates
Solution Approach 1:
The flow cytometer system performs self-calibration by automatically determining drop delay through image processing of the flow stream. The processor analyzes disturbances at the break-off point to calculate drop delay without requiring manual intervention, enabling the system to adapt to component drift and particle size variability autonomously.
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 accuracy of cell sorting by automating the determination of drop delay, minimizing human intervention, and improving the predictability of particle detection and sorting, thereby reducing contamination and increasing the efficiency of flow cytometer operations.
Implementation Method 1
As particles of interest (e.g., cells) move through the interrogation point, light from the irradiation source (e.g., laser) is scattered.
Implementation Method 2
The light can also excite components in the cell stream that have fluorescent properties, such as fluorescent markers that have been added to the fluid sample and adhered to certain cells of interest.
Implementation Method 3
The flow cell hydrodynamically focuses the particles (e.g., cells) within the stream to pass through the center of an irradiation source
Implementation Method 4
In flow cytometers that sort cells by an electrostatic method, the desired cells are contained within an electrically charged droplet. To charge the droplet, the flow cell includes a charging element.
Data Source
Figure 1
AI summary
Methods and systems for determining a drop delay of a flow stream in a flow cytometer are provided. Aspects of the methods according to certain embodiments include capturing an image of the flow stream to obtain an imaged flow stream, identifying a disturbance at a break off point in the imaged flow stream and calculating the drop delay of the flow stream based on the identified disturbance. 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 identify a disturbance at a break off in the imaged flow stream and calculating the drop delay using the imaged flow stream are also provided. Non-transitory computer readable storage mediums are also described.