Digital Histopathology Cell Infiltration Analysis
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Solution Overview
Problem
Current methods for analyzing immune cell infiltration in tumors are limited by their inability to provide a global measure across the entire tumor, are not adaptable to various tumor types and sizes, and are difficult to use in preclinical studies, leading to non-reproducible and subjective results.
Innovation Solution
A process that generates a digital histopathological image of biological tissues, determines a distance map with iso-curves, and calculates a surface density curve of biological cells of interest, providing a global measure of infiltration that is reliable, reproducible, and adaptable to different tumor types and sizes, using image processing techniques such as Otsu binarization and K-means classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical sample analysis by punch biopsy is used, then detailed histopathological diagnosis can be made, but the sample requires physical possession, transport, and handling which complicates the process and reduces reproducibility
Solution Approach 1:
The patent creates a digital copy (virtual slide) of the physical histological preparation through digital imaging. This digital replica contains all necessary visual information for histopathological analysis without requiring physical sample transport or handling. The digital image can be stored, transmitted, and analyzed remotely, eliminating the complexity of physical sample management while preserving diagnostic accuracy.
2Measurement precision
If quantification rectangles with predetermined sizes are used, then cell density can be measured in specific areas, but the method is not adaptable to various tumor types and sizes
Solution Approach 1:
The patent replaces fixed predetermined rectangles with dynamic regions of interest that can be adaptively defined based on the specific tumor characteristics. The system allows flexible selection and adjustment of analysis regions according to tumor type, size, and morphology, enabling precise cell density measurements tailored to each case rather than applying a rigid uniform approach.
Solution Approach 2:
The patent creates a universal analysis framework that can handle various tumor types and sizes through a common digital image processing platform. The system provides multi-functional capabilities to analyze different biological objects (tumors, tissues) with varying characteristics using the same core technology, achieving both precision and adaptability.
3Measurement precision
If known software processes are used, then cell infiltration can be analyzed, but the process is difficult to use in preclinical studies and does not provide global measures of infiltration
Solution Approach 1:
The patent segments the tumor boundary into quantifiable regions using distance maps and iso-curves, dividing the complex infiltration pattern into manageable concentric zones. This segmentation enables systematic analysis of cell infiltration at different distances from the tumor boundary, providing both local and global infiltration measures that are easier to interpret and apply in preclinical studies.
Solution Approach 2:
The patent introduces a digital image processing system as an intermediary between the physical sample and the analysis. This intermediary layer provides automated, objective measurement tools that simplify the analysis process, making it more accessible and reproducible for preclinical studies while maintaining measurement precision.
4Measurement precision
If predetermined quantification rectangles are used, then specific area analysis is possible, but the method requires manual placement and is time-consuming
Solution Approach 1:
The patent replaces the manual mechanical process of placing and measuring within predetermined rectangles with automated digital image processing. The system automatically identifies regions of interest, calculates distance maps, generates iso-curves, and performs cell density measurements through computational algorithms, dramatically increasing productivity while maintaining measurement precision.
Solution Approach 2:
The patent performs preliminary automated processing steps (image acquisition, preprocessing, boundary detection, distance map calculation) before the actual cell density measurement. This preliminary automation prepares the data structure in advance, enabling rapid subsequent analysis without manual intervention, thus improving overall productivity.
Data Source
AI summary
The invention relates to a process for determining an infiltration profile of biological cells of interest in a biological object of interest from a digital histopathological image of biological tissues, a histological stain having previously been applied to the biological tissues,comprising generating a biological cell detection image, pixels associated with the histological stain on the histopathological image being of a predetermined color on said image,determining a distance map comprising distance iso-curves to the boundary of the biological object,and, from the distance map, calculating a curve representative of the surface density of biological cells of interest as a function of distance to the boundary, by counting, for each boundary distance value, pixels that are both of the predetermined color on the detection image and located between the iso-curve associated with said distance value and the consecutive iso-curve.