Magnetic Resonance Fingerprinting Iterative Signal Comparison
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Solution Overview
Problem
Magnetic resonance fingerprinting (MRF) methods face limitations in determining parameter values, particularly the local magnetic field B0, due to artifacts such as banding and blurring, which affect spatial resolution and accuracy in clinical applications.
Innovation Solution
An iterative signal comparison method is employed to improve the determination of parameter values by correcting picture element time series based on initial parameter determinations, using comparison signal curves to refine measurements and account for measurement-specific parameters like B0, thereby increasing precision and reducing artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional MRF methods are used to determine parameter values, then measurement speed is improved, but measurement precision deteriorates due to artifacts like banding and blurring
Solution Approach 1:
The patent segments the determination process into multiple stages: first determining a preliminary parameter value, then using this to correct the picture element time series, and finally determining an improved parameter value. This multi-stage segmentation allows the method to maintain fast measurement speed while improving precision by addressing artifacts systematically in separate processing steps.
Solution Approach 2:
The patent performs preliminary determination of parameter values and preliminary correction of picture element time series before the final precise measurement. By performing these preliminary actions first, the method prepares the data to reduce artifacts like banding and blurring, enabling the subsequent precise measurement to achieve better accuracy without sacrificing measurement speed.
2Measurement precision
If quantitative MR imaging techniques are used to determine absolute properties, then measurement precision is improved, but measurement time increases
Solution Approach 1:
The patent applies partial action by performing selective corrections only on picture element time series that require it, based on the preliminary parameter determination. Rather than applying full quantitative imaging processing to all data, the method selectively corrects and re-determines parameters only where needed, reducing overall measurement time while maintaining precision for critical measurements.
Solution Approach 2:
The patent implements a feedback mechanism where the preliminary parameter determination results are used to correct the picture element time series, which then feeds into the final parameter determination. This feedback loop allows the method to iteratively improve precision without requiring multiple separate measurements, thereby reducing total measurement time while achieving accurate absolute property determination.
3Measurement precision
If picture element time series are corrected based on preliminary parameter determination, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent implements self-service by using the data and parameter determinations already obtained during the measurement process to correct and improve the same data. The preliminary parameter values derived from the picture element time series are used to correct those same time series, eliminating the need for external calibration data or additional correction measurements, thereby improving precision without proportionally increasing system complexity.
Solution Approach 2:
The patent merges the correction step with the parameter determination process by integrating the preliminary parameter determination, time series correction, and final parameter determination into a unified workflow. This merging allows the system to achieve improved precision through multiple processing stages without requiring separate complex subsystems, as the same processing unit handles all stages sequentially.
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 enhances the spatial resolution and precision of parameter value determination, allowing for more accurate assessment of tissue-specific and measurement-specific parameters, including the local magnetic field B0, and reduces artifacts like blurring, leading to improved diagnostic capabilities.
Implementation Method 1
To trigger nuclear spin resonances, radio-frequency excitation pulses (RF pulses) are irradiated into the examination object. The triggered nuclear spin resonances are measured as so-called k-space data
Implementation Method 2
For spatial encoding of the measurement data, rapidly switched magnetic gradient fields, which define the trajectories along which the detected MR signals are entered into k-space, are superimposed on the basic magnetic field
Implementation Method 3
the examination object is positioned in a magnetic resonance scanner in a strong static, homogeneous basic magnetic field, also called the B0 field, with field strengths of 0.2 Tesla to 7 Tesla and more, so that nuclear spins in the object are oriented along the basic magnetic field
Data Source
AI summary
In a magnetic resonance fingerprinting method and apparatus for improved determination of local parameter values of an examination object, in which at least two signal comparisons of acquired picture element time series are carried out with comparison signal curves for determination of parameter values. A further (subsequent) signal comparison takes into account results of a preceding signal comparison. This multi-stage determination of parameter values allows an increase of the spatial resolution and the precision with which the parameter values can be determined.