MRI B0 Map Generation Using Varied Measurement Sequences
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Solution Overview
Problem
Existing methods for generating B0 maps in magnetic resonance imaging (MRI) suffer from artifacts and low SNR efficiency, making them unsuitable for clinical use, particularly due to hardware-dependent variables and tissue parameter dependencies.
Innovation Solution
A method using multiple measurement sequences, such as TrueFISP, FLASH, and FISP, to record image data sets with varied flip angles and repetition times, allowing for artifact-free B0 map generation and simultaneous determination of B0, B1, T1, and T2 values, with a reduced B0 value range for faster simulation and reduced computing time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If single measurement sequence is used for B0 map generation, then scan time is reduced, but artifacts and low SNR efficiency occur
Solution Approach 1:
The measurement process is segmented into multiple distinct measurement sequences (e.g., TrueFISP, FLASH, FISP), each with different parameter configurations. This segmentation allows the system to collect diverse signal evolutions that can be combined to generate artifact-free B0 maps while maintaining efficient scan times through optimized parameter selection in each sequence.
Solution Approach 2:
The patent employs dynamic variation of measurement parameters (flip angles, repetition times, echo times) across different measurement sequences. This dynamic approach enables the system to adaptively sample the signal evolution at multiple points, improving B0 map accuracy and SNR efficiency without requiring excessive total measurement time.
2Measurement precision
If multiple measurement sequences with varied parameters are used, then B0 map quality and SNR efficiency are improved, but device complexity increases
Solution Approach 1:
The patent designs measurement sequences that serve multiple functions simultaneously. For example, the same set of varied-parameter sequences is used for both B0 map generation and tissue parameter mapping (T1, T2, B1), reducing the need for separate dedicated sequences and thereby limiting the increase in device complexity despite the use of multiple sequences.
Solution Approach 2:
Instead of introducing entirely new measurement sequences, the patent achieves improved B0 map quality by systematically varying existing parameters (flip angle, repetition time, echo time) within standard sequence frameworks. This approach improves measurement precision while keeping the underlying sequence structure familiar and manageable, thus controlling device complexity.
3Measurement precision
If full B0 value range is simulated for dictionary matching, then measurement accuracy is improved, but computing time increases
Solution Approach 1:
The patent applies partial action by simulating and storing signal evolutions only for a reduced, clinically relevant B0 value range rather than the complete theoretical range. This partial simulation approach maintains sufficient accuracy for diagnostic purposes while dramatically reducing the size of the dictionary and associated computing time for matching.
Solution Approach 2:
The patent focuses computational resources on simulating signal evolutions for locally relevant B0 values (those most likely to be encountered in clinical practice) rather than uniformly covering the entire possible range. This local quality approach ensures high accuracy where it matters most while minimizing unnecessary computations in extreme or unlikely ranges.
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 results in high-quality, artifact-free B0 maps with improved SNR efficiency, enabling accurate tissue parameter mapping and reducing the need for extensive hardware calibration, thus enhancing diagnostic capabilities.
Implementation Method 1
The B0 field is the static, homogeneity basic magnetic field that is produced in a magnetic resonance (MR) scanner in order to establish an equilibrium position of nuclei (nuclear spins) in an examination subject
Implementation Method 2
Other quantifiable parameters are known. There are parameters that depend on the patient or region of interest, e.g. the relaxation times T1, T2 and T2*
Implementation Method 3
The term susceptibility in general describes the magnetizability of a substance or more specifically of a tissue. Step changes in susceptibility arise at the interfaces between tissues with different susceptibility
Implementation Method 4
At the interface between two tissues or substances with different χ-values, a gradient ΔB is therefore produced: ΔB=μ0(χ1−χ2)H
Data Source
AI summary
In a method and magnetic resonance apparatus for generating a B0 map of a region of interest, a magnetic resonance data set containing a number of image data sets is obtained and provided in a computer, wherein the image data sets are recorded using at least two measurement sequences and the mutually corresponding pixels of the image data sets each represent a time-dependent signal evolution. A B0 map of the region of interest is generated by the computer from the image data sets, wherein the B0 value of a pixel of the B0 map is determined from the associated signal evolution.