Biomarker Quantification via Saturation Residence Time Analysis
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Solution Overview
Problem
Current tissue analysis methods for biomarker quantification are computationally intensive, laborious, and prone to inaccuracies due to variations in signal intensity caused by factors like illumination and staining protocols, making them expensive and subjective, with limitations in distinguishing biomarker amounts beyond saturation levels.
Innovation Solution
A computer-implemented method using an image analysis system that determines the saturation residence time (SRT) by analyzing intensity values and exposure intervals of digital images from tissue samples stained with a μIHC system, allowing for accurate biomarker quantification and prediction of tumor stage or treatment recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If signal strength is used as an indicator of biomarker expression level, then quantification can be achieved, but accuracy deteriorates due to saturation effects and variability from illumination and staining protocols
Solution Approach 1:
The patent transforms the measurement parameter from signal strength (intensity) to saturation residence time (SRT). Instead of measuring how strong the signal is, the system measures how long it takes for the signal to reach saturation, which is determined by the amount of biomarker present. This parameter transformation eliminates the problems of illumination variability and staining protocol differences, as SRT is inherently independent of these factors.
Solution Approach 2:
The patent replaces the traditional optical measurement system (which relies on light intensity detection) with a temporal measurement system (which relies on time-based saturation detection). This substitution moves from measuring the magnitude of a physical quantity (signal intensity) to measuring a temporal characteristic (time to saturation), thereby eliminating the influence of optical variability on measurement accuracy.
2Measurement precision
If conventional staining and signal intensity analysis is used, then biomarker detection is possible, but the process becomes computationally intensive and laborious
Solution Approach 1:
The patent extracts the essential information needed for quantification (the time to reach saturation) from the complex signal intensity data. By focusing only on the temporal aspect of signal development rather than analyzing the full spectrum of intensity variations, the system simplifies the computational requirements while maintaining accurate quantification capability.
3Ease of manufacture
If DAB stain is used for signal detection, then cost is reduced compared to expensive antibodies and detection systems, but signal intensity becomes weak and inaccurate due to light scattering
Solution Approach 1:
The patent replaces intensity-based measurement with time-based measurement, which works effectively with DAB stain. Since the measurement criterion is the time to reach saturation rather than the absolute intensity level, the light-scattering properties of DAB become irrelevant, allowing cost-effective staining to achieve accurate quantification.
4Strength
If signal intensity exceeds saturation level, then strong signal is obtained, but the ability to distinguish differences in biomarker amount is lost
Solution Approach 1:
The patent performs the measurement during the transient phase before saturation is reached. By capturing the time it takes to reach saturation rather than measuring the saturated signal level, the system preserves information about biomarker amount. Different biomarker amounts result in different saturation times, maintaining discriminability even when all samples eventually reach the same saturation intensity level.
Data Source
AI summary
Embodiments of the invention relate to a computer-implemented method for quantifying a biomarker in a tissue sample of an organism. An image analysis system receives images of a stained tissue sample. Each received digital image depicts the tissue sample region at the end of an exposure interval. The system analyzes the intensity values and exposure intervals of the received digital images for determining the time when the intensity values corresponding to the plurality of exposure intervals ordered according to ascending exposure interval lengths reach a plateau (saturation residence time—SRT). The system determines the amount of a biomarker in the tissue sample and/or predicts a tumor stage and/or a treatment recommendation as a function of the SRT.


