CTC Image Analysis With DNA Ploidy and Nuclear Morphology
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Solution Overview
Problem
Existing methods for identifying circulating tumor cells (CTCs) are limited by high false positives, damage to cells during preparation, loss of RNA, and difficulty in staining multiple biomarkers, leading to inaccurate detection and analysis.
Innovation Solution
A computer-implemented method using image processing and machine learning to identify CTCs by measuring pixel intensity and fluorescence, combined with specific staining and fixing techniques to preserve cell integrity and enhance contrast, along with a reagent system for fixing and blocking non-specific binding sites.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional physical properties and cell-surface markers are used to identify CTCs, then detection can be performed, but high false positives occur and relevant pathogenic CTCs are missed
Solution Approach 1:
The patent changes the detection parameters from conventional physical properties and cell-surface markers to nuclear morphology parameters (area, circularity, texture) and DNA ploidy levels. This parameter transformation enables more accurate identification of pathogenic CTCs while reducing false positives, as these nuclear characteristics are more specific to malignant transformation.
Solution Approach 2:
The patent replaces mechanical/physical detection methods (size filtering, density separation) with image processing and computational analysis of nuclear morphology. This substitution allows for more precise characterization of CTCs through digital measurement of nuclear features rather than crude physical separation.
2Ease of operation
If cell preparation methods are used to identify CTCs, then cell analysis can be performed, but cells are damaged and artifacts are created that obscure rare cell populations
Solution Approach 1:
The patent applies fixation and blocking treatments beforehand to preserve cell integrity and prevent artifacts during subsequent processing. The fixation step stabilizes cellular structures, while the blocking step prevents non-specific binding that would create background noise and obscure rare CTC populations.
Solution Approach 2:
The patent introduces blocking buffers as intermediary substances that bind to non-specific sites before antibody staining. This intermediary step prevents direct non-specific binding of detection reagents to cellular components, thereby reducing background artifacts and improving signal-to-noise ratio for rare cell detection.
3Stability of the object's composition
If cross-linking or precipitating fixatives are used, then cells can be fixed for analysis, but RNA is not preserved making genetic analysis difficult
Solution Approach 1:
The patent changes the chemical parameters of the fixation process by using milder fixation conditions and optimized blocking buffers that do not completely denature or cross-link cellular components. This modified chemical environment preserves RNA integrity while still providing sufficient structural stabilization for morphological analysis.
4Adaptability or versatility
If commonly used blocking buffers are used for multi-antibody stains, then staining can be performed, but signal-to-noise ratio is insufficient for rare cells requiring greater than four fluorophores
Solution Approach 1:
The patent uses composite blocking buffer formulations containing multiple components (serum proteins, synthetic blockers, and specific inhibitors) that work synergistically to block diverse non-specific binding sites. This composite approach provides superior background reduction compared to single-component blockers, enabling clear detection of rare CTCs stained with multiple fluorophores.
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
Enhances the ability to accurately detect and characterize CTCs at a molecular level, improving cancer screening and reducing the need for invasive procedures.
Implementation Method 1
These fixatives include cross-linking fixatives (e.g., formaldehyde, paraformaldehyde, etc.)
Implementation Method 2
or precipitating fixatives (e.g., ethanol, methanol, etc.)
Implementation Method 3
staining for multiple cellular biomarkers
Implementation Method 4
measuring a pixel intensity; determining a location of staining; identifying a first nuclear region of the first cell of interest
Data Source
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AI summary
Disclosed herein are compositions and methods of fixing and staining rare cells. Further, disclosed herein are methods of identifying circulating tumor cells (CTC). In some embodiments, the method includes: imaging a cell sample to identify a cell of interest; determining a first pixel intensity of a stained nuclear area; determining a second pixel intensity of a background area; calculating a ploidy status of the cell of interest by subtracting the second pixel intensity from the first pixel intensity; and determining whether the cell of interest is a CTC based on the ploidy status. The method may be computer implemented, such that the method uses a machine learning algorithm to identify a feature; process the feature to extract a parameter of interest; analyze the parameter of interest; and when the parameter of interest is greater than or less than a pre-determined threshold, classify the cell of interest as a CTC.