Multiplexed Imaging Validation Using Cross-Correlation Alignment
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Solution Overview
Problem
Existing imaging methods lack a robust and reliable method to validate new imaging reagents and methods, often requiring multiple staining steps that alter the biological sample and complicate comparisons.
Innovation Solution
A quantitative method involving cross-correlation of imaging signals from different methods or reagents, adjusting for signal orientation, image parity, scale, and translation mismatch, to align and compare imaging zones in biological samples.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple staining steps are used to validate imaging methods, then comparison between methods can be performed, but the biological sample conditions are altered and effectiveness is reduced
Solution Approach 1:
The patent combines multiple imaging methods into a single multiplexed imaging workflow by using sequential hybridization of different imager strands to the same biological sample. This allows validation of multiple imaging methods simultaneously without requiring separate staining steps that would alter sample conditions between comparisons.
Solution Approach 2:
The patent creates a universal validation platform that can accommodate multiple imaging methods (fluorescence, brightfield, electron microscopy, mass spectrometry) using a common sample preparation and imaging workflow. The same biological sample can be validated against multiple reference methods through sequential imaging, making the validation process universally applicable across different imaging modalities.
2Reliability
If multiple staining steps are used to validate imaging methods, then comparison between methods can be performed, but the process complexity increases
Solution Approach 1:
The patent performs preliminary actions by first hybridizing target-specific binding partners to the biological sample and then sequentially hybridizing different imager strands in a standardized workflow. This preliminary setup creates a consistent platform that simplifies subsequent validation steps, as the same sample and protocol framework is used across all imaging method comparisons.
3Extent of automation
If quantitative comparison method is implemented, then automation capability is improved, but measurement and signal alignment complexity increases
Solution Approach 1:
The patent implements feedback mechanisms through cross-correlation analysis that automatically compares imaging zones from different imaging methods. The system provides quantitative feedback on signal similarity and alignment quality, enabling automated adjustment and validation of imaging methods without manual intervention for signal alignment.
Solution Approach 2:
The patent replaces manual signal alignment and comparison processes with automated computational methods including cross-correlation algorithms and image processing techniques. This substitution of mechanical/manual operations with computational systems enables high-throughput validation while managing the complexity of signal alignment through software-based solutions.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Provides a reliable and automated method to validate imaging reagents and methods, ensuring accurate comparison without altering the sample conditions, and allowing for the evaluation of multiple reagents or methods simultaneously.
Implementation Method 1
contacting a biological sample with one or more target-specific binding partners
Implementation Method 2
contacting the biological sample with labeled imager strands for a first imaging method, wherein the labeled imager strands are capable of binding a docking strand
Data Source
AI summary
A quantitative method of validating at least one candidate imaging method or candidate imaging reagent for use in evaluating a biological sample for the presence of one or more targets is described relying upon cross-correlation calculations.