Canceration Detection Device Segmentation Flow Cytometry
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Solution Overview
Problem
Existing cancer detection methods, such as those described in US Patent Application Publication No. 2008/108103, face challenges in accurately distinguishing between 'CIN1' and 'Cancer' stages, leading to false alarms and reduced reliability in detecting cancerous cells.
Innovation Solution
A method and device that analyze the number of normal cells, DNA content, and nucleus-to-cell size ratio in epidermal tissue specimens to accurately determine the progression to cancerous cell levels, using flow cytometry and DNA staining to differentiate between normal and cancerous cells.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the analyzer tries to reliably detect Cancer by analyzing cell characteristics, then the detection reliability improves, but false alarm increases because atypical cells in CIN1 are also detected as Cancer
Solution Approach 1:
The invention segments the cell population analysis by specifically counting normal cells in the surface layer (CIN1 region) separately from other cells. By dividing the analysis into distinct cell population groups (normal surface layer cells vs. other cells), the method can differentiate between CIN1 and Cancer stages more accurately, reducing false alarms while maintaining detection reliability
Solution Approach 2:
The invention changes the measurement parameter from general cell characteristic analysis to specific DNA content measurement of normal cells in the surface layer. By using DNA content as a quantitative parameter and establishing threshold values, the method achieves more precise discrimination between CIN1 and Cancer stages, resolving the contradiction between detection reliability and measurement precision
2Adaptability or versatility
If the analyzer uses general cell characteristic analysis to detect atypical cells, then the detection coverage improves, but the ability to distinguish between different canceration stages deteriorates
Solution Approach 1:
The invention applies local quality by focusing analysis on a specific region (surface layer normal cells) rather than analyzing all cells uniformly. By targeting the specific population of normal cells in the surface layer and measuring their DNA content, the method achieves precise stage discrimination while maintaining comprehensive detection capability through the flow cytometry approach
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
The approach enhances the reliability of cancer detection by accurately distinguishing between normal and cancerous cell stages, reducing false alarms and improving the detection of cancerous cells, particularly in the 'CIN1' to 'Cancer' transition.
Implementation Method 1
irradiates the measurement specimen flowing through the flow cell with light to acquire a scattered light signal for the individual cell
Implementation Method 2
acquiring first data related to an amount of DNA of the cell contained in the prepared measurement specimen
Data Source
AI summary
Provided is a canceration information providing method capable of presenting information related to canceration of cells with high reliability. A cell in which an amount of DNA is greater than or equal to an amount of DNA of a normal cell in a S period is extracted from a cell group of V11≦N/C ratio≦V12 (first counting step). If a number of cells obtained in the first counting step is greater than or equal to a threshold value S1 (S107: YES), “Cancer” is set to a flag 1. A cell in which an amount of DNA is 2C is extracted from a cell group of V13≦N/C ratio<V11 (second counting step). A ratio of a number of cells obtained in the first counting step and a number of cells obtained in the second counting step is calculated, and “Cancer” is set to a flag 2 if the ratio is greater than or equal to a threshold value S2 (S111: YES). If either one of the flags 1, 2 is “Cancer” (S113: YES), retest necessary is displayed.