Automated Immune Cell Quantification in Tumoral Tissues
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Solution Overview
Problem
Current methods for quantifying immune cells in tumoral tissues face challenges with reproducibility and automation, particularly when using tissue microarrays, which can lead to inconsistent results due to spatial heterogeneity in cancer tissues and manual errors in selecting tumour areas.
Innovation Solution
A method involving automated slide-staining systems, high-resolution digital scanning, and software-assisted analysis to detect and quantify immune cells in tumoral tissues, using specific antibodies for immune cell markers like CD3, CD8, and CD20, and implementing a grid system for accurate density assessment, ensuring standardization and inter-laboratory comparability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual methods are used for selecting and analyzing tumour areas in tissue microarrays, then pathologists can visually examine Haematoxylin-Eosin counterstaining to identify regions of interest, but differences between pathologists and manual errors lead to poor reproducibility and reliability of measurements
Solution Approach 1:
The patent replaces manual mechanical selection of tumour areas with an automated digital image analysis system. The system uses computer algorithms to automatically identify and segment tumour regions, immune cell infiltrates, and stromal areas based on digital whole slide images, eliminating inter-observer variability and manual errors in region selection while maintaining diagnostic accuracy
Solution Approach 2:
The patent creates digital copies (whole slide images) of the physical tissue sections and performs all analysis on these digital replicas. This allows multiple analyses of the same tissue sample without physical manipulation, enabling automated algorithms to repeatedly measure the same features with identical results while preserving the original tissue for potential re-analysis
2Productivity
If tissue microarrays are used for high-throughput analysis, then productivity increases, but spatial heterogeneity of target molecules in cancer tissue leads to sampling errors and loss of diagnostic information
Solution Approach 1:
The patent transitions from analyzing small 2D tissue microarray cores to analyzing the entire 3D tissue architecture captured in whole slide images. This dimensional expansion allows comprehensive sampling of spatial heterogeneity across the entire tumour section while maintaining high throughput by processing multiple whole slides efficiently with automated algorithms
Solution Approach 2:
The patent segments the tumour tissue into distinct functional regions (tumour core, invasive margin, lymphoid aggregates, stromal areas) using automated image analysis. This segmentation allows separate quantification of immune cells in each region, preserving spatial heterogeneity information while enabling systematic high-throughput analysis across multiple samples
3Extent of automation
If automated slide-staining systems and digital scanning are implemented, then automation and reproducibility improve, but device complexity and initial investment increase
Solution Approach 1:
The patent employs a digital image analysis system that can analyze multiple types of immunohistochemical stains (CD3, CD8, CD20, and other immune cell markers) on the same tissue sections. This multi-functional approach consolidates what would otherwise require separate manual analysis processes into a single automated platform, reducing overall system complexity while maintaining high automation levels
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 enhances reproducibility and automation, providing a reliable and standardized approach for predicting cancer patient survival and treatment response, improving upon existing methods by reducing human error and heterogeneity issues.
Implementation Method 1
by using antibodies binding specifically to antigens expressed by immune cells
Data Source
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AI summary
A method for assessment of a number or density of immune cells in tumoral tissues comprising the steps consisting in: a. providing one or more immunostained slices of tissue section obtained by an automated slide-staining system by using antibodies binding specifically to antigens (markers) expressed by immune cells. b. proceeding to digitalisation of the slides of step a. by high resolution scan capture, whereby a high definition (4.6 μm/pixel or better) digital picture of the slide to be analysed is obtained, c. detecting the slice of tissue section on the digital picture d. analyzing the slice of tissue section for defining (i) the tumour (CT) and (ii) the invasive margin of the tumour (IM), e. providing a size reference grid with uniformly distributed units having a same surface, said grid being adapted to the size of the tumour to be analyzed, e1. checking the quality of immunostaining, f. detecting and quantifying stained cells of each unit whereby the number or the density of immune cells stained of each unit is assessed.