Combined Quantitative Map Deviation Analysis for MRI Tissue Alteration
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Solution Overview
Problem
Current imaging techniques, such as quantitative MRI (qMRI), face challenges in accurately identifying and quantifying tissue alterations in biological objects due to the sensitivity of multiple physical mechanisms, which can lead to unclear identification of underlying pathological processes, especially when multiple biological processes occur simultaneously.
Innovation Solution
A method and system that acquire multiple quantitative MRI maps of different physical tissue properties, combine them into a combined quantitative map (CQM) using algebraic operations, and calculate a deviation map by comparing the CQM to a normative atlas, enabling better disentanglement of pathological mechanisms causing tissue alterations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple quantitative MRI maps are acquired to detect different physical tissue properties, then the sensitivity and information content improve, but the complexity of identifying underlying pathological mechanisms worsens due to multiple physical mechanisms affecting the same measure
Solution Approach 1:
The patent segments the analysis by creating separate deviation maps for each quantitative parameter (T1, T2, T2*, PD) compared against normative atlases. This segmentation allows each parameter's deviation to be independently visualized and interpreted, reducing the complexity of identifying which specific pathological mechanism is present while maintaining high detection sensitivity through multi-parameter assessment
Solution Approach 2:
The patent introduces deviation maps as intermediary visualizations between the raw quantitative MRI data and pathological interpretation. These deviation maps serve as mediators that highlight abnormal regions by comparing patient data against normative atlases, making it easier to identify pathological mechanisms without being overwhelmed by the complexity of multiple simultaneous physical mechanisms
2Loss of information
If multiple biological processes are monitored simultaneously through multiple qMRI measures, then comprehensive tissue characterization improves, but the ability to clearly identify specific underlying processes deteriorates due to neutralizing effects
Solution Approach 1:
The patent segments the tissue characterization into distinct quantitative parameters (T1, T2, T2*, PD), each sensitive to different physical mechanisms. By creating separate deviation maps for each parameter, the patent preserves complete tissue characterization information while enabling precise identification of specific pathological processes through pattern recognition across the segmented parameters
Solution Approach 2:
The patent applies local quality by providing voxel-wise deviation maps that show spatially specific alterations for each quantitative parameter. This allows different pathological processes to be identified in different local regions based on their characteristic patterns across multiple parameters, maintaining both comprehensive characterization and precise identification
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
This approach provides improved visualization and quantification of tissue alterations, allowing for more accurate detection and characterization of brain tissue pathologies by offering a voxel-wise representation of combined tissue properties, enhancing inter-subject comparability and sensitivity in identifying abnormal conditions.
Implementation Method 1
quantitative, physics-based parameters opposed to relative image contrasts as in conventional MRI... with respect to a physical parameter measured using the magnetic resonance (MR) phenomenon
Data Source
AI summary
A system and a method for detecting and quantifying a tissue alteration of a biological object. The method comprises the following steps: acquiring multiple quantitative maps of the biological object, wherein each of the multiple quantitative maps is a quantitative map of a different physical tissue property of the biological object; combining the acquired quantitative maps into a combined quantitative map (CQM); and calculating a deviation map by comparing the CQM to a normative atlas configured for providing expected values for the CQM.