Immune Phenotype Image Generation for Pathology Slide Analysis
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Solution Overview
Problem
Current methods for predicting the response to immune checkpoint inhibitors in cancer patients are hindered by the difficulty in intuitively recognizing immune response information across numerous patches in pathology slide images, often including unnecessary analysis of regions.
Innovation Solution
A method and device that generate and output an image indicative of immune phenotype information for specific regions of interest (ROIs) in pathology slide images, using an ROI extraction model to determine relevant regions and provide visual representations of immune inflamed, excluded, or desert phenotypes, thereby focusing analysis on significant areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If immune response information is generated for each of numerous patches in pathology slide image, then comprehensive immune response information is obtained, but it becomes difficult for users to intuitively recognize immune response information
Solution Approach 1:
The pathology slide image is divided into multiple patches, and immune response information is generated for each patch. This segmentation allows comprehensive analysis of different regions while maintaining the ability to process and present information in manageable units.
Solution Approach 2:
Multiple patch-level immune response information results are merged into a unified visual representation. The system combines individual patch analyses into an overall immune phenotype assessment, enabling both detailed and comprehensive views of immune response.
2Reliability
If immune response information is generated for all patches in pathology slide image, then complete immune phenotype assessment is achieved, but computational resources are wasted on substantially unnecessary regions
Solution Approach 1:
The system extracts and identifies regions of interest (ROIs) from the pathology slide image that are most relevant for immune checkpoint inhibitor response prediction. By taking out only the substantially necessary patches for analysis, the system reduces computational waste while maintaining prediction reliability.
Solution Approach 2:
Different regions of the pathology slide image are treated with different analysis priorities. The system applies focused analysis to ROIs with higher predictive value while reducing or skipping analysis in less relevant regions, optimizing computational resource allocation based on local importance.
3Loss of information
If detailed immune response information is provided for numerous patches, then comprehensive immune phenotype data is obtained, but the complexity of information processing and presentation increases
Solution Approach 1:
The system transforms detailed patch-level immune response information into a visual representation that adds a spatial dimension. Instead of presenting raw data tables, the system creates visual maps showing immune phenotype distribution across different regions, making complex information more intuitively understandable.
Data Source
AI summary
The present disclosure relates to a method, performed by at least one computing device, for providing information associated with immune phenotype for pathology slide image. The method may include obtaining information associated with immune phenotype for one or more regions of interest (ROIs) in a pathology slide image, generating, based on the information associated with the immune phenotype for one or more ROIs, an image indicative of the information associated with the immune phenotype, and outputting the image indicative of the information associated with immune phenotype.