Label-Free White Blood Cell Identification via Optical Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for differentiating white blood cells in biological samples require staining and labeling, which are time-consuming, costly, and prone to errors, especially in pathological samples.
Innovation Solution
An in-vitro method using a microscopy apparatus and a cell analysis device that determines the cell type of white blood cells without labeling by analyzing physical parameters and principal component analysis parameters from images of the cells.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If staining and labeling methods are used for white blood cell differentiation, then cell type identification accuracy is improved, but sample preparation time and cost increase
Solution Approach 1:
The patent extracts and utilizes the intrinsic optical properties of white blood cells (refractive index, scattering characteristics, absorption spectra) without adding external stains or labels. By taking out the need for chemical additives and focusing on the cells' natural optical signatures, the method eliminates time-consuming staining procedures while maintaining identification accuracy.
Solution Approach 2:
The method enables white blood cells to serve themselves for identification by utilizing their own optical properties. The cells' inherent characteristics (granularity, nuclear structure, cytoplasmic composition) naturally produce distinct optical signals that can be detected and classified, eliminating the need for external labeling services.
2Measurement precision
If staining methods are used for white blood cell differentiation, then cell type identification accuracy is improved, but the process becomes more costly and prone to errors
Solution Approach 1:
By extracting the identification capability from external stains and relocating it to the cells' intrinsic optical properties, the method removes the source of staining-related errors (inconsistent staining, artifact formation, chemical variability). The process becomes more reliable as it depends on stable, inherent cellular characteristics rather than variable chemical reactions.
Solution Approach 2:
The patent replaces the chemical staining system with an optical detection system. Instead of using chemical reactions to create visible differences, the method uses light scattering, absorption, and refractive index measurements to differentiate cell types, thereby eliminating chemical variability and improving process reliability.
3Productivity
If conventional hematology analyzers are used for automated analysis, then productivity is improved, but error messages and incorrect determinations increase for pathological samples
Solution Approach 1:
The patent creates a multi-functional optical analysis system that can handle both routine and pathological samples with a single methodology. Unlike conventional analyzers that rely on fixed algorithms optimized for normal samples, this system uses fundamental optical properties that remain valid across the full spectrum of sample types, enabling accurate analysis of pathological specimens without requiring separate validation protocols.
Solution Approach 2:
The method changes the measurement parameters from electrical impedance and stray light (conventional methods) to optical properties such as scattering intensity, absorption spectra, and refractive index. These optical parameters provide more discriminative power for pathological cells with altered morphology and composition, improving analysis accuracy while maintaining automated throughput.
4Measurement precision
If manual microscopy examination is performed for validation, then measurement precision is improved, but device complexity and operational complexity increase
Solution Approach 1:
The patent replaces manual microscopy with automated optical detection and image analysis. The system uses digital imaging combined with algorithmic processing to automatically classify cells based on their optical properties, eliminating the need for manual assessment while maintaining or improving precision through consistent, objective measurement criteria.
Solution Approach 2:
The system enables automated self-validation by integrating the validation function into the primary analysis workflow. The same optical detection system that performs initial cell classification also provides the data needed for validation, eliminating the need for separate manual microscopy steps and reducing operational complexity.
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 method allows for high sample throughput and accurate, qualitative, and quantitative determination of cells, reducing the need for conventional hematology analyzers and minimizing artifacts from staining and handling.
Implementation Method 1
On account of the processes employed (e.g., Mie scattering), a complicated sample preparation is necessary
Implementation Method 2
physical parameters of the cell are ascertained from the image representation of the cell
Implementation Method 3
physical parameters of the cell are ascertained from the image representation of the cell by means of an automated image analysis
Data Source
AI summary
An in-vitro method for determining a cell type of a white blood cell in a biological sample does so without labeling, wherein a microscopy apparatus images the cell, and physical parameters of the cell are ascertained from the image of the cell by an automated image analysis. The cell type of the white blood cell is determined on the basis of the physical parameters and on the basis of principal component analysis parameters (PCA parameters), wherein the principal component analysis parameters comprise linear combinations of at least some of the physical parameters.