Sample Analyzer Bacterial Identification via Flow Cytometry
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Solution Overview
Problem
Current methods for detecting bacteria in clinical samples, such as urine, are slow and lack the ability to differentiate between multiple types of bacteria and provide timely information on bacterial changes, making it difficult to diagnose urinary tract infections and assess treatment effectiveness.
Innovation Solution
A sample analyzer that uses a light source and detector to emit and measure scattered light and fluorescence from bacteria, generating particle data to determine the presence of urinary tract infections and changes in bacterial types, with a controller displaying histograms and change information to aid in diagnosis and treatment monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If culture method is used to detect bacteria, then bacteria types and numbers can be identified, but it takes several days for colonies to form, lacking promptness
Solution Approach 1:
The patent replaces the biological culture method with a flow cytometry-based optical detection system. Instead of relying on bacterial colony formation through cultivation, the system uses light scattering and fluorescence properties of bacteria to achieve rapid identification, substituting biological processes with physical measurement techniques.
Solution Approach 2:
The patent changes the detection parameters from colony morphology and growth rate (culture-based) to light scattering intensity and fluorescence characteristics (optical properties). This parameter transformation enables rapid detection while maintaining identification accuracy through multivariate analysis of optical parameters.
2Measurement precision
If scattergram method is used to determine bacterial types, then bacterial classification can be achieved, but it is difficult to determine multiple types of bacteria and provide detailed information
Solution Approach 1:
The patent segments the bacterial population into distinct groups based on multiple optical parameters (forward scatter, side scatter, fluorescence). By dividing the data space into multiple dimensions and using threshold-based classification, the system can differentiate between multiple bacterial types simultaneously, providing detailed information about each type's characteristics.
Solution Approach 2:
The patent transitions from two-dimensional scattergram analysis to multi-dimensional parameter space analysis. By incorporating multiple optical parameters (size, shape, fluorescence intensity, fluorescence spectrum) simultaneously, the system creates a higher-dimensional classification framework that enables differentiation of multiple bacterial types that cannot be resolved in lower-dimensional representations.
3Reliability
If traditional detection methods are used, then bacteria can be detected, but it is difficult to monitor bacterial changes over time and assess treatment effectiveness
Solution Approach 1:
The patent implements a feedback mechanism by comparing current bacterial characteristics with historical data stored in memory. The system automatically detects changes in bacterial types, sizes, and fluorescence patterns over time, providing real-time feedback on disease progression and treatment response. This enables continuous monitoring and dynamic adjustment of treatment strategies.
Solution Approach 2:
The patent establishes continuous monitoring capability by enabling repeated measurements of the same sample over time. The system maintains continuous data collection and comparison, allowing tracking of bacterial dynamics throughout the disease course and treatment period, thereby providing uninterrupted information on bacterial changes without requiring repeated sample collection.
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 rapid and accurate identification of urinary tract infections and changes in bacterial types, improving diagnostic precision and treatment monitoring by providing prompt and detailed analysis of bacterial compositions.
Implementation Method 1
a light source for emitting light to particles contained in a measurement sample which is prepared from a reagent and a urine sample collected from a subject; a detector for detecting scattered light and fluorescence which are generated from the particles in the measurement sample
Implementation Method 2
a detector for detecting scattered light and fluorescence which are generated from the particles in the measurement sample
Data Source
AI summary
A sample analyzer comprising: a light source for emitting light to particles contained in a measurement sample which is prepared from a reagent and a urine sample collected from a subject; a detector for detecting scattered light and fluorescence which are generated from the particles in the measurement sample; a display; and a controller, wherein the controller executes operations comprising: obtaining particle data based on the scattered light and the fluorescence which are detected from the particles by the detector; and controlling, when the particle data satisfies a predetermined condition, the display to display information indicating a possibility that the subject is infected with an uncomplicated urinary tract infection is disclosed.