Biological Cell Tracking via Surface Coating and Algorithmic Filtering
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Solution Overview
Problem
Existing methods for label-free analysis of biological cells require time-consuming manual corrections and often misinterpret events due to cell interactions, leading to inaccurate tracking and analysis.
Innovation Solution
A device with a flow channel coated with molecules having affinity to specific cell categories, modifying cell movements, and a processor to identify and remove non-specific movements, ensuring accurate tracking and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image analysis is used to track individual cells, then cell information can be obtained, but time-consuming manual corrections are required and tracking accuracy deteriorates due to cell interactions
Solution Approach 1:
The patent replaces manual mechanical correction operations with an automated computer-based tracking system. The processor automatically identifies cells in sequential images, tracks their movements, and corrects tracking errors algorithmically without requiring manual intervention, thereby eliminating time loss while maintaining or improving tracking accuracy
Solution Approach 2:
The system employs feedback mechanisms where the processor continuously monitors cell positions across sequential images, detects tracking deviations caused by cell interactions, and automatically adjusts tracking paths based on detected cell behaviors. This closed-loop feedback system resolves tracking errors in real-time without manual correction
2Adaptability or versatility
If cells are tracked during movement, then dynamic cell behavior can be analyzed, but events are misinterpreted due to interactions with other cells or chamber surfaces
Solution Approach 1:
The patent applies local quality analysis by examining specific local events in the cell tracking data. The processor identifies and analyzes individual events (such as changes in movement speed or direction) in the context of their local environment, distinguishing between biologically relevant events and artifacts caused by cell-cell or cell-chamber interactions based on local patterns rather than global assumptions
Solution Approach 2:
The system dynamically adapts its analysis based on observed cell behaviors. The processor continuously adjusts tracking parameters and event detection thresholds based on real-time cell movements and interactions, allowing accurate differentiation between specific biological events and non-specific artifacts while maintaining dynamic analysis capability
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
Enables high-reliability, label-free analysis of biological cells by distinguishing specific from non-specific movements, improving accuracy and reducing errors in tracking.
Implementation Method 1
each zone of the flow channel comprises at least one surface coated with molecules having an affinity and specificity to the cell category associated with the zone, the at least one surface of the zone being configured to modify, by the molecules coating the at least one surface, a movement of a biological cell belonging to an associated biological cell category of the zone
Data Source
AI summary
According to an aspect of the present inventive concept there is provided a device for analyzing biological cells comprising: a flow channel passing a flow of liquid carrying the biological cells to be analyzed, the flow channel comprises at least one zone associated with a cell category; at least one detector to detect information representing the biological cells passing the at least one zone; a processor configured to receive and process the information by: identifying candidate biological cells; identifying tracks from the candidate biological cells; identifying candidate modified movements as events in each track; determining event related information associated with the event, the event related information comprises at least a sensed property of the candidate biological cells and/or a property defining a relation between events of at least two tracks from candidate biological cells; identifying candidate non-specific modified movements among the candidate modified movements; and removing the candidate non-specific modified movements from the candidate modified movements for each track.