Radial Tissue Microstructure Profiling from Quantitative Imaging
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Solution Overview
Problem
Existing imaging techniques lack sensitivity and fail to efficiently characterize the spatial distribution of tissue microstructural properties, particularly in normal-appearing tissue surrounding lesions, limiting the clinical utility of quantitative metrics.
Innovation Solution
A method and system that characterize tissue microstructural properties by fitting a function to quantitative imaging data, associating each voxel with a distance from a center of interest, determining fitting parameters to represent spatial distribution, and outputting these parameters for comparison and classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a ring-based approach is used to characterize microstructural alterations, then the method is simple to implement, but the sensitivity and information extraction capability are insufficient
Solution Approach 1:
The patent segments the tissue region into multiple radial annuli centered on the lesion, with each annulus representing a specific distance range from the lesion center. This segmentation allows continuous characterization of microstructural properties across the entire radial profile, improving sensitivity while maintaining implementation simplicity through automated processing of each annular region
Solution Approach 2:
The patent transitions from conventional 2D planar analysis to 3D radial profiling by introducing the distance dimension from the lesion center. This dimensional expansion enables characterization of microstructural alterations along the radial gradient, capturing spatial distribution patterns that enhance sensitivity without significantly increasing implementation complexity
2Adaptability or versatility
If conventional clinical imaging techniques are used, then the equipment is accessible, but the microstructural properties cannot be quantified
Solution Approach 1:
The patent makes quantitative microstructural analysis universal by processing standard clinical MRI sequences (T1, T2, FLAIR) through a unified radial profiling framework. The same methodology can be applied to different MRI modalities and lesion types, enabling quantification of microstructural properties using accessible clinical equipment without requiring specialized hardware
Solution Approach 2:
The patent transforms qualitative imaging findings into quantitative metrics by calculating specific parameters (mean intensity, standard deviation, skewness, kurtosis) within radial annuli. This parameter transformation enables precise quantification of microstructural properties while maintaining compatibility with standard clinical imaging protocols and equipment
3Loss of information
If spatial distribution information is not condensed into scalar values, then the full spatial pattern is preserved, but the results are difficult to use clinically
Solution Approach 1:
The patent extracts key quantitative parameters (mean intensity, standard deviation, skewness, kurtosis) from the complex spatial distribution pattern within each radial annulus. These scalar values capture the essential microstructural characteristics while condensing the spatial information into clinically interpretable metrics that can be easily compared and used for diagnosis
Solution Approach 2:
The patent merges the spatial distribution pattern with quantitative parameter extraction by computing statistical moments across the radial profile. This combination preserves spatial pattern information through the radial annulus structure while condensing it into scalar parameters that maintain both information content and clinical usability
Data Source
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AI summary
The present invention concerns a system and a method for characterizing a spatial distribution of a tissue microstructural property from quantitative imaging data, the method (100) comprising: - acquiring (110), for a biological object and via a first interface, a property map for a tissue of said biological object (206), wherein said property map comprises voxels whose intensity represents a measured value V of said microstructural property; - determining (120), for at least a set of said voxels, a distance d separating each voxel of said set from a center of interest so that each voxel of said set be associated to a measured value V and a determined distance d; - fitting (130), for said set of voxels, a function f to the measured values V expressed in function of the determined distance d according to V(d) = f(β1, ... ,βN,d) in order to determine a set of fitting parameters (β1, ... ,βN); - determining (140), from said fit, the values of each fitting parameter (β1, ... ,βN); - outputting (150) the value of at least one of said fitting parameters.