Imaging Flow Cytometer Cell Parameter Calculation
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Solution Overview
Problem
Current flow-type particle sorting systems face challenges in accurately calculating cell parameters and efficiently sorting cells based on complex interactions and morphological features, such as phagocytosis, tumor cell killing, and mitotic phases, due to limitations in data processing and image analysis.
Innovation Solution
The method involves irradiating cells in a flow stream with frequency-modulated beams of light, generating image data, and calculating cell parameters using integrated circuit devices and algorithms to assess interactions, translocations, and morphological features, enabling precise classification and sorting of cells.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional flow-type particle sorting systems are used, then particles can be sorted based on measured characteristics, but the precision of cell parameter calculation is insufficient for complex interactions and morphological features
Solution Approach 1:
The patent transitions from traditional point-by-point light scattering measurement to a two-dimensional imaging detection dimension. The imaging detector captures spatial distribution information of light scattering and fluorescence across the cell, enabling precise measurement of morphological features, organelle positions, and cell interactions that cannot be obtained by conventional flow cytometry parameters
Solution Approach 2:
The patent replaces the traditional optical detection system with an imaging detection system. Instead of using photomultiplier tubes to measure light intensity at specific angles, the system uses an imaging detector (such as a CCD or CMOS camera) to capture the entire spatial distribution of light scattering and fluorescence, substituting mechanical/optical measurement with digital image capture and processing
2Productivity
If traditional detection methods are used, then basic particle sorting can be performed, but high-throughput sorting of cells with specific characteristics is limited
Solution Approach 1:
The system performs preliminary imaging and parameter calculation for all cells in the flow stream before sorting decisions are made. The imaging detector continuously captures cell images, and the processor pre-calculates relevant parameters (such as cell size, shape, organelle positions, and interaction features), so that when sorting is required, the decisions can be made rapidly based on already-processed information
Solution Approach 2:
The imaging detection system operates continuously as cells flow through the detection region, capturing images at high frame rates. The processor continuously analyzes images and calculates parameters in real-time, maintaining a continuous stream of useful data without interruption, enabling high-throughput sorting without sacrificing measurement precision
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 precision of cell characterization by 5% to 99% and allows for high-throughput sorting of cells with specific characteristics, improving the yield and purity of target cell populations.
Implementation Method 1
irradiating a sample comprising cells in a flow stream with frequency-modulated beams of light, measuring light from the cells in the sample
Implementation Method 2
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 calculating one or more cell parameters of cells in a sample. Methods according to certain embodiments include irradiating a sample comprising cells in a flow stream with frequency-modulated beams of light, measuring light from the cells in the sample, generating image data of the cells from the measured light and calculating one or more cell parameters based on the generated image data. Systems and integrated circuit devices (e.g., a field programmable gate array) for practicing the subject methods are also described. Non-transitory computer readable storage media are also provided.