MRI Fat Fraction Estimation via Phase Error Compensation
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Solution Overview
Problem
Current MRI methods for fat quantification in non-alcoholic fatty liver disease (NAFLD) face challenges with phase errors, which lead to biased fat fraction estimation and are not robust across different imaging platforms, due to the discarding of valuable phase information and reliance on time-consuming eddy current corrections.
Innovation Solution
A mixed fitting method is employed to separate signal contributions from different chemical species by selectively discarding or modifying phase information from echo signals with errors, using a signal model that accounts for phase, magnitude, and other errors, allowing for accurate separation of water and fat signals while reducing noise amplification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If phase information is discarded to eliminate phase errors, then measurement precision improves, but loss of information increases
Solution Approach 1:
The patent extracts and removes only the erroneous phase components from echo signals while preserving the valid phase information. This is achieved by identifying and eliminating phase errors selectively rather than discarding all phase information, thus resolving the contradiction between measurement precision and information loss.
Solution Approach 2:
The patent changes the state of phase information by transforming it from a potentially erroneous parameter to a corrected parameter. Through phase correction algorithms, the phase information is modified to remove errors while retaining its useful diagnostic value, allowing accurate fat fraction estimation without complete phase information discarding.
2Measurement precision
If eddy current corrections are applied to compensate for phase errors, then measurement precision improves, but loss of time increases
Solution Approach 1:
The patent applies preliminary phase correction to the acquired echo signals before performing fat fraction calculation. By correcting phase errors in advance during the signal processing stage rather than requiring repeated measurements or post-processing corrections, the method achieves accurate phase compensation efficiently without significant time loss.
3Measurement precision
If magnitude-based methods are used to eliminate phase errors, then measurement precision improves, but noise amplification increases
Solution Approach 1:
The patent changes the processing approach by using complex-based fitting with phase correction instead of magnitude-based methods. This parameter change in the mathematical model allows the preservation of phase information while correcting errors, thereby achieving unbiased fat fraction estimates without the severe noise amplification that characterizes magnitude-based approaches.
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 unbiased fat fraction estimates, reduces noise, and enhances the robustness and reproducibility of the biomarker, making it independent of imaging parameters and MRI systems, thereby improving the detection and classification of NAFLD.
Implementation Method 1
MRI uses the nuclear magnetic resonance ('NMR') phenomenon to produce images. When a substance such as human tissue is subjected to a uniform magnetic field, such as the so-called main magnetic field, B0, of an MRI system, the individual magnetic moments of the nuclei in the tissue attempt to align with this B0 field, but precess about it in random order at their characteristic Larmor frequency, ω.
Implementation Method 2
If the substance, or tissue, is subjected to a so-called excitation electromagnetic field, B1, that is in the plane transverse to the B0 field and that has a frequency near the Larmor frequency, the net aligned magnetic moment, referred to as longitudinal magnetization, may be rotated, or 'tipped,' into the transverse plane to produce a net transverse magnetic moment, referred to as transverse magnetization.
Data Source
AI summary
A method for producing an image of a subject with a magnetic resonance imaging (“MRI”) system, in which relative signal contributions from a plurality of different chemical species are separated, is provided. A plurality of different echo signals occurring at a respective plurality of different echo times are acquired with the MRI system and a signal model that accounts for relative signal components for each of a plurality of different chemical species is formed for each echo signal. Those echo signals containing errors, such as phase errors, magnitude errors, or errors indicative of a corrupted echo signal, are identified. The relative signal components for each of the plurality of different chemical species are then determined by fitting the echo signals with the signal model. Particularly, those echo signals identified as containing errors are fitted to the signal models in a manner that discards the error-containing information.