Spatial Pathology Analysis for Tumor-Lymphocyte Distribution
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Solution Overview
Problem
Current image-level analysis in digital pathology strips away detailed spatial information of biological objects, impeding the detection of their microenvironment-dependent activities and interactions, which are crucial for accurate diagnoses, prognoses, and treatment evaluations.
Innovation Solution
A digital pathology image processing system detects sets of biological object depictions and generates spatial-distribution metrics characterizing their relative locations, using techniques like spatial-point-process and geostatistical analysis, to predict biological states and treatment responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If image-level analysis is used to simplify metadata storage and improve ease of understanding, then ease of operation is improved, but spatial information and measurement precision are lost
Solution Approach 1:
The patent segments the image analysis into multiple levels: image-level results (simple counts and ratios) and object-level results (detailed spatial coordinates and distributions). This segmentation allows users to choose the appropriate level of detail for their needs, preserving spatial information when required while maintaining simplicity when sufficient
Solution Approach 2:
The patent adds a spatial dimension to traditional image-level analysis by generating object-level results that include precise coordinates, distances, and spatial relationships. This transforms the analysis from a single-level summary to a multi-dimensional characterization that preserves both simplicity and detail
2Device complexity
If image-level analysis is used to simplify processing, then device complexity is reduced, but measurement precision and diagnostic accuracy deteriorate
Solution Approach 1:
The system dynamically adjusts the level of analysis based on diagnostic needs. It can operate at a simpler image-level when sufficient, or transition to more complex object-level analysis when spatial precision is required for accurate diagnosis and treatment evaluation
Solution Approach 2:
The analysis is segmented into distinct processing stages that can be independently applied. The system can perform only image-level processing for simple cases, or add object-level processing stages when enhanced precision is needed, allowing flexible complexity management
3Measurement precision
If spatial distribution analysis is implemented to capture microenvironment interactions, then measurement precision and diagnostic accuracy are improved, but device complexity and processing requirements increase
Solution Approach 1:
The complex spatial analysis is segmented into distinct computational stages: object detection, coordinate extraction, distance calculation, and distribution metric generation. This segmentation allows the system to implement sophisticated spatial analysis while managing complexity through modular, step-by-step processing
Solution Approach 2:
The patent introduces intermediate spatial metrics (such as mean distances, spatial distributions, and relative positions) that serve as mediators between raw image data and final diagnostic conclusions. These intermediaries simplify the interpretation of complex spatial relationships while preserving measurement precision
Data Source
AI summary
Systems and methods relate to processing digital pathology images. More specifically, depictions of objects of a first class (e.g., lymphocytes) and depictions of objects of a second class (e.g., tumor cells) are detected. Locations of each biological object depiction are identified, which are used to generate multiple spatial-distribution metrics that characterize where depictions of objects of a first class are located relative to objects of a second class. The spatial-distribution metrics are used to generate a result corresponding to a predicted biological state of or a potential treatment of a subject. For example, the result may predict whether and/or an extent to which lymphocytes have infiltrated a tumor, whether checkpoint blockade therapy would be an effective treatment for the subject, and/or whether a subject is eligible for a clinical trial.