Flow Cytometer Aggregate Discrimination via Spatial Light Scatter
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Solution Overview
Problem
Flow-type particle sorting systems face challenges in accurately distinguishing and sorting cell aggregates from single cells due to clumping issues, which affect the accuracy and purity of sorted cells, particularly in therapeutic applications.
Innovation Solution
The system detects light from a sample in a flow stream, generates spatial data, and determines whether objects are aggregates based on image moments and light scatter properties, using processors and integrated circuit devices to differentiate between single cells and aggregates and sort them accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional particle sorting systems use basic light detection methods, then the system structure remains simple, but the ability to distinguish aggregates from single cells is insufficient
Solution Approach 1:
The patent transitions from conventional single-point light detection to two-dimensional spatial light detection by capturing light scatter patterns across a spatial domain. This dimensional expansion enables the system to distinguish aggregates from single cells based on their unique spatial light distribution patterns, achieving superior discrimination accuracy while managing complexity through digital image processing.
Solution Approach 2:
The system utilizes variations in light scatter intensity and distribution patterns (analogous to color changes) to differentiate between single cells and aggregates. By analyzing the spatial pattern of light scatter rather than just intensity, the system can identify characteristic patterns that indicate aggregate formation, improving measurement precision without requiring complex physical modifications.
2Manufacturing precision
If the system sorts all detected particles without discrimination, then processing speed is maintained, but purity of sorted cells deteriorates due to inclusion of aggregates
Solution Approach 1:
The system performs preliminary spatial characterization of particles using light scatter imaging before the sorting decision is made. By capturing and analyzing the spatial light distribution pattern of each particle, the system pre-identifies aggregates versus single cells, enabling high-purity sorting without sacrificing throughput. This preliminary spatial assessment allows the sorting mechanism to selectively divert aggregates while maintaining rapid processing speed.
3Stability of the object's composition
If mechanical or enzymatic breakdown is used to prevent clumping, then single cell suspension is improved, but incomplete disruption leads to remaining aggregates
Solution Approach 1:
The patent implements a feedback mechanism where the spatial light scatter imaging system continuously monitors the cell suspension for aggregate formation. When aggregates are detected through their characteristic spatial light patterns, the system can trigger additional mechanical or enzymatic disruption cycles. This closed-loop feedback ensures complete tissue disruption and maintains stable single-cell suspension without requiring overly complex pre-processing equipment.
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 and purity of cell sorting by effectively identifying and separating single cells from aggregates, improving the yield and quality of sorted cell compositions.
Implementation Method 1
detecting light absorption, light scatter, light emission (e.g., fluorescence) from the sample in the flow stream
Implementation Method 2
detecting light absorption, light scatter, light emission (e.g., fluorescence) from the sample in the flow stream
Implementation Method 3
detecting light absorption, light scatter, light emission (e.g., fluorescence) from the sample in the flow stream
Data Source
AI summary
Aspects of the present disclosure include methods for characterizing particles of a sample in a flow stream. Methods according to certain embodiments include detecting light from a sample having cells in a flow stream, generating an image of an object in the flow stream in an interrogation region and determining whether the object in the flow stream is an aggregate based on the generated image. Systems having a processor with memory operably coupled to the processor having instructions stored thereon, which when executed by the processor, cause the processor to generate an image of an object in a flow stream and to determine whether the object is an aggregate are also described. Integrated circuit devices (e.g., field programmable gate arrays) having programming for practicing the subject methods are also provided.