MRI Biomarker Assessment With Bootstrapping for Acquisition Variability
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Solution Overview
Problem
Existing methods for automatically assessing the longitudinal evolution of biomarkers are susceptible to variability due to differences in acquisition and processing techniques, leading to unreliable estimates of physical changes in biological tissues.
Innovation Solution
A method and system that account for the variability of acquisition techniques by calculating statistical parameters to generate synthetic data distributions, applying bootstrapping and fitting functions to evaluate the longitudinal evolution of biomarkers, and comparing against a reference value.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automatic estimation methods are used to assess longitudinal evolution of biomarkers, then productivity is improved, but measurement precision deteriorates due to variability in acquisition and processing techniques
Solution Approach 1:
The patent transforms the approach by changing from direct measurement comparison to statistical parameter estimation. Instead of directly comparing biomarker values across time points (which suffers from acquisition variability), the method estimates statistical parameters (mean, standard deviation, confidence intervals) for each time point and uses these parameters to assess longitudinal evolution, thereby correcting for measurement variability while maintaining automation
Solution Approach 2:
The patent introduces statistical parameters as intermediary elements between the raw biomarker measurements and the final longitudinal assessment. These statistical parameters (mean, standard deviation, confidence intervals) serve as mediators that summarize the measurement data while accounting for variability, enabling reliable longitudinal comparison without direct exposure to acquisition technique differences
2Measurement precision
If statistical parameters are calculated for each measurement to account for variability, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing statistical parameters (mean, standard deviation, confidence intervals) for each biomarker measurement at each time point before the longitudinal assessment is performed. This preliminary computation of statistical characteristics enables the subsequent longitudinal evaluation to proceed with simpler operations, as the variability information is already prepared and available for use
Data Source
AI summary
A system and a method for evaluating a longitudinal evolution of a quantitative biomarker measured for a biological object include receiving longitudinal measurements of the quantitative biomarker for the biological object. A statistical parameter, which characterizes a variability of the acquisition technique being used, is calculated for each measurement. The calculated statistical parameter is used for each obtained biomarker value for generating synthetic data having a distribution which follows the statistical distribution of possible values for the biomarker. The sampled values are fitted by using a fitting function for each bootstrapping fitting. A fitting parameter of the fitting function is extracted for each fitting. The longitudinal evolution of the quantitative biomarker is evaluated by statistically comparing the extracted fitting parameters against a reference value.