Whole-Slide Biomarker Analysis With Precomputed Pathology Visualization
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Solution Overview
Problem
Current digital pathology systems struggle with computationally intensive image analysis of large high-resolution digital images, requiring significant storage and limiting real-time diagnostic capabilities, and often force users to mentally approximate relevant areas of interest, leading to inefficiencies in quantitative analysis and visualization of entire tissue slides.
Innovation Solution
A digital pathology system with a workflow module that enables automated analysis and intuitive visualization of entire tissue slides, allowing users to manually or automatically select relevant areas, perform image analysis, and generate overlays for precise quantification of biomarker expressions, while excluding artefacts and unnecessary tissue content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional digital pathology systems analyze small fields of view to manage computational load, then processing time and memory usage are reduced, but the ability to perform quantitative analysis of entire tissue slides is compromised
Solution Approach 1:
The system segments the entire tissue slide into multiple smaller fields of view that can be processed individually by the digital pathology system. Each FOV is analyzed separately for biomarker expression, and the results are then aggregated to provide comprehensive quantitative analysis of the whole slide. This segmentation allows the system to manage computational load while ultimately covering the entire tissue area.
2Area of stationary object
If the system processes entire whole-slide images, then complete tissue coverage is achieved, but computational intensity and memory requirements increase significantly
Solution Approach 1:
The whole-slide image is divided into multiple smaller fields of view that can be processed sequentially or in parallel with reduced memory requirements. Each FOV is analyzed independently for biomarker expression levels, and the computational results are aggregated to provide comprehensive quantitative analysis of the entire tissue slide.
Solution Approach 2:
The system initially analyzes a representative subset of fields of view to estimate biomarker expression levels and provide preliminary diagnostic information. This partial analysis allows rapid assessment without processing the entire slide, and full quantitative analysis can be performed subsequently if needed.
3Measurement precision
If pathologists manually examine digital images to identify treatment options, then diagnostic accuracy is maintained, but significant time and mental effort are required
Solution Approach 1:
The digital pathology system automatically performs quantitative analysis of biomarker expressions in tissue slides without requiring manual examination by pathologists. The system independently processes whole-slide images, identifies relevant morphological features, quantifies biomarker expressions, and generates diagnostic reports, thereby eliminating the time-consuming manual review process while maintaining diagnostic accuracy.
Solution Approach 2:
The manual visual examination process is replaced with automated digital image analysis algorithms that process whole-slide images computationally. The system uses computer vision and machine learning techniques to identify tissue morphology, detect biomarker expressions, and quantify results, substituting the pathologist's manual visual inspection with automated computational analysis.
4Quantity of substance
If conventional systems limit field of view size to manage memory constraints, then memory usage is controlled, but the representative sampling of entire tissue slides becomes difficult
Solution Approach 1:
The system segments the entire tissue slide into multiple smaller fields of view that can be processed and stored with manageable memory requirements. By analyzing multiple FOVs across different regions of the slide, the system captures comprehensive tissue representation without requiring excessive memory resources.
Solution Approach 2:
The system merges the analysis results from multiple smaller fields of view to provide comprehensive quantitative analysis of the entire tissue slide. By combining data from multiple FOVs, the system achieves complete tissue coverage and accurate biomarker expression quantification without needing to load the entire high-resolution slide into memory simultaneously.
Data Source
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AI summary
A digital pathology system and associated method and computer program product provide a quantitative analysis of entire tissue slides as well as intuitive, effective, fast, and precise quantification of biomarker expressions across relevant areas of the entire tissue slides. The digital pathology system enables a novel workflow that allows the user to efficiently outline clinically relevant morphology in its entirety, including solid tumor areas. Quantitative analysis results are then efficiently and intuitively provided to the user for all tissue content (i.e., millions of cells) within seconds. This efficiency is made possible by a pre-computation step that computes and stores image analysis results for later retrieval. Visualizing vast amount of data effectively is another component of the system that provides information and confidence to the user about the biomarker expression levels.