Digital Image Analysis of Inflammatory Cells in Tumor Tissue
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Solution Overview
Problem
Current methods for assessing the immune system state in tumor tissues are subjective, prone to human error, and unable to quantify complex inflammatory cell distributions, limiting their effectiveness in predicting patient responses to cancer therapies.
Innovation Solution
A method involving tissue acquisition, staining, digitization, and software-based image analysis to extract and characterize inflammatory cells and modulators, deriving an immune system state score for patient stratification and therapy selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual evaluation of histologic tissue sections by a pathologist is used, then the assessment of inflammatory cells and modulators of inflammation can be performed, but the evaluation is subjective and prone to observer bias and human error
Solution Approach 1:
The patent replaces the manual mechanical evaluation system with an automated digital image analysis system. Whole slide scanning and sophisticated image analysis programs objectively detect and characterize cells across entire tissue sections, eliminating observer bias and human error while maintaining assessment capability.
Solution Approach 2:
The patent creates a digital copy of the histologic tissue section through whole slide scanning. This digital replica allows for repeated, consistent analysis without the variability inherent in manual pathologist evaluation, enabling precise and reliable measurements of inflammatory cells and modulators.
2Quantity of substance
If manual counting of inflammatory cells is performed, then the quantity of cells can be determined, but the method cannot practically assess a whole tissue section
Solution Approach 1:
The patent replaces manual counting with automated image analysis that can process entire whole slide images. The sophisticated image analysis programs detect and characterize cells across the complete tissue section, enabling assessment of large areas that are impractical for manual evaluation.
Solution Approach 2:
The patent transitions from two-dimensional manual field-by-field assessment to comprehensive whole-slide digital imaging. This dimensional expansion allows simultaneous analysis of entire tissue sections, capturing cell quantity and distribution across the complete tissue architecture rather than limited microscopic fields.
3Quantity of substance
If manual evaluation is used, then simple cell counts can be obtained, but quantitation of complex inflammation modulator distribution metrics is not possible
Solution Approach 1:
The patent replaces manual evaluation with automated image analysis capable of calculating complex spatial metrics. The system quantifies distribution patterns, distances between cells and tissue features, fractal patterns, and lacunarity—metrics that are computationally intensive and impossible to determine through manual counting.
Solution Approach 2:
The patent expands from simple cell count parameters to multiple complex spatial and distribution parameters. The image analysis system simultaneously measures cell quantity, spatial distribution, architectural patterns, and relationships between different cell types and tissue features, providing a comprehensive quantitative profile.
4Loss of information
If manual counting methods are used, then individual marker assessments can be performed, but quantitative assessments of associations between markers using serial tissue sections are not possible
Solution Approach 1:
The patent merges analysis of multiple serial tissue sections into a unified digital framework. The image analysis system integrates data from consecutive sections stained with different markers, enabling quantitative assessment of spatial associations and correlations between different inflammatory cell types and modulators across the tissue architecture.
Data Source
AI summary
This disclosure concerns methods for evaluating inflammatory cells and modulators of the inflammatory response in tumor tissue and other relevant tissue types. The methods entail: obtaining a tissue sample and processing said tissue sample to produce histologic slides of tissue sections; staining of the tissue sections to identify inflammatory cells and modulators of the inflammatory response; digitizing slides to produce an image of the stained tissue sections; digitally stratifying the tissue sample into tumor and other relevant tissue compartments; and using digital image analysis to quantify cell-based and cell population-based features. The quantification of cell-based and cell population-based features within a tissue compartment of interest is used to develop a summary score of the immune system-tissue compartment of interest interaction. Patient stratification and selection as candidates for a therapeutic approach is ultimately based on the summary score value.