Concurrent Fat Iron Estimation via Reference Signal Library Matching
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Solution Overview
Problem
Conventional methods for estimating fat and iron in the liver using magnetic resonance (MR) imaging are cumbersome and error-prone due to iterative processes, where fat estimation is used to correct iron and vice versa, making concurrent estimation challenging, especially in conditions where both substances interfere with each other.
Innovation Solution
A method and system that generate a library of reference signals corresponding to different amounts of fat and iron, using matching criteria to concurrently estimate both fat and iron in MR signal data by identifying the best match through mathematical product calculations, allowing for simultaneous estimation without iteration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If iterative fat-corrected iron estimation and iron-corrected fat estimation methods are used, then measurement precision is improved, but device complexity and time consumption increase due to multiple iterations
Solution Approach 1:
The patent pre-calculates and stores a library of reference signals corresponding to different combinations of fat fractions and iron concentrations before actual measurement. This preliminary action eliminates the need for iterative corrections during the estimation process, as the measured signal can be directly compared against the pre-computed library to obtain both fat and iron values simultaneously, thus reducing device complexity while maintaining measurement precision
Solution Approach 2:
The patent creates a comprehensive library of reference signals that copy all possible combinations of fat and iron effects on MR signals. By storing these pre-computed reference patterns, the system replaces the complex iterative correction process with a direct matching operation, significantly simplifying the device complexity while preserving the ability to accurately estimate both parameters
2Measurement precision
If iterative correction methods are employed to account for mutual interference between fat and iron, then measurement precision is improved, but time consumption increases due to repeated calculations
Solution Approach 1:
The patent performs all necessary calculations for accounting for mutual interference between fat and iron in advance by pre-computing the reference signal library. This preliminary action shifts the computational burden from the measurement time to the preparation phase, allowing rapid direct comparison during actual estimation without iterative corrections, thus reducing time loss while maintaining precision
Solution Approach 2:
By creating a complete library of reference signals that incorporate all possible fat-iron interference scenarios, the patent enables direct matching during measurement. This copying approach eliminates the need for repeated calculations and iterative corrections, significantly reducing time consumption while preserving measurement precision through direct comparison with pre-computed reference patterns
3Ease of operation
If conventional separate estimation methods are used for fat and iron, then ease of operation is maintained, but measurement precision deteriorates due to unaccounted mutual interference
Solution Approach 1:
The patent merges the estimation of fat and iron into a single unified process by creating a reference signal library that incorporates both parameters simultaneously. The measured signal is compared against this combined library to directly obtain both fat fraction and iron concentration in one operation, maintaining ease of operation while eliminating mutual interference errors that plague separate estimation methods
Solution Approach 2:
The patent uses a composite reference signal library that combines the effects of different fat fractions and iron concentrations in all possible combinations. This composite approach allows the simple act of signal matching to simultaneously account for both substances and their mutual interference, preserving ease of operation while dramatically improving measurement precision over separate estimation methods
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 enables accurate and efficient concurrent estimation of fat and iron in anatomical tissue, reducing errors and improving the precision of measurements for hepatic disease treatment, by directly matching test signals with reference signals in the library.
Implementation Method 1
The MR signal simulation may include, for example, application of a Bloch function for magnetic resonance
Data Source
AI summary
A computer-implemented method for concurrently estimating the amount of fat and iron in anatomical tissue from magnetic resonance (MR) signal data includes receiving a test signal representative of the anatomical tissue acquired using a MR pulse sequence type. A repository of reference signal data is generated. The repository comprises a plurality of reference signals derived by an MR signal simulation for a plurality of different transverse relaxation rates, a plurality of different fat fractions, and the MR pulse sequence type. A first reference signal is identified in the plurality of reference signals. The first reference signal provides a best match to the test signal based on one or more matching criteria. The repository is searched to determine a first transverse relaxation rate and a first fat fraction associated with the first reference signal. Then, the amount of fat and iron in the anatomical tissue is estimated based on the first transverse relaxation rate and the first fat fraction.