Automated Tissue Analysis via Digital IHC Signature Maps
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Solution Overview
Problem
Current pathology analysis methods rely on manual, time-consuming processes by trained pathologists, prone to human errors, and lack automation for analyzing tissue samples using multiple biomarkers.
Innovation Solution
A computerized method for tissue analysis involving the preparation of thinly sectioned tissue samples, acquisition of diagnostic quality digital images, registration, overlaying a virtual grid, assigning IHC scores, and summating scores to generate an IHC signature map, which can be automated using programmed software.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual analysis by trained pathologists is used, then diagnostic accuracy can be maintained, but analysis time and human error increase significantly
Solution Approach 1:
The patent replaces the manual mechanical analysis process performed by pathologists with an automated computerized image analysis system. The system uses digital image processing algorithms to automatically detect, segment, and quantify tissue structures and biomarker expression, eliminating the need for manual microscopic examination while maintaining diagnostic accuracy through objective, reproducible measurements.
Solution Approach 2:
The patent creates a digital copy of the tissue slide through high-resolution scanning, allowing the analysis to be performed on the digital replica rather than the physical slide. This enables multiple analyses to be performed on the same sample without additional physical handling, and allows automated algorithms to process the image data efficiently while preserving all diagnostic information.
2Ease of operation
If single biomarker analysis is performed manually, then simplicity is maintained, but productivity and comprehensiveness decrease
Solution Approach 1:
The patent implements an analysis system that can handle multiple biomarkers and analysis types through a single unified platform. The software is designed to process various staining patterns, detect different tissue structures, and generate multiple types of quantitative outputs from the same digital image, allowing comprehensive multi-parameter analysis without requiring separate manual procedures for each biomarker.
Solution Approach 2:
The patent divides the complex multi-biomarker analysis task into separate processing modules that can independently analyze different biomarkers and tissue features. Each module can be configured for specific biomarker detection, and the results are integrated to provide comprehensive analysis. This modular approach maintains operational simplicity while enabling high-throughput multi-parameter assessment.
3Productivity
If automated computerized analysis is implemented, then productivity and consistency improve, but system complexity increases
Solution Approach 1:
The patent introduces a digital image as an intermediary between the physical tissue sample and the analysis process. The high-resolution scan creates a standardized digital representation that can be processed by automated algorithms without requiring complex mechanical manipulation of physical slides. This intermediary layer simplifies the automation process by converting physical variability into standardized digital data that is easier to process consistently.
4Extent of automation
If digital image acquisition is performed, then automation capability is enabled, but initial setup time and resource requirements increase
Solution Approach 1:
The patent performs preliminary digital scanning and image processing to create a comprehensive digital archive of the tissue samples before analysis begins. This preliminary action captures all necessary diagnostic information in digital format, enabling subsequent automated analyses to proceed without repeated physical slide handling or additional setup time. The digital archive serves as a permanent reference that can be analyzed repeatedly with different algorithms.
Data Source
AI summary
A computerized method for immunohistochemistry analysis of tissue utilizes digital images of multiple adjacent tissue sections aligned within a computerized software and processed with an algorithm to quantify a two-dimensional IHC signature score for each respective slide image. In various embodiments, the IHC score is performed over several adjacent sections and further processed to produce a three-dimensional IHC quantification referred to as an IHC signature map.