B1 and B0 Mapping in MRI via K-Space Filtering
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Solution Overview
Problem
Current MRI systems face challenges in accurately mapping the spatial distribution of RF B1 and static B0 magnetic fields, leading to image artifacts, degradation in image contrast, and limitations in quantitative measurements due to field non-uniformities, especially at higher magnetic field strengths.
Innovation Solution
The method involves acquiring and processing k-space data using spatial frequency domain filtering to generate multi-dimensional maps of B1 and B0 fields, employing SPAMM tagging patterns and k-space processing techniques to produce accurate and efficient B1 and B0 maps, which can be used to improve MRI system design and image correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional MRI mapping methods are used, then field distribution can be measured, but measurement precision and speed are insufficient due to field non-uniformities
Solution Approach 1:
The patent segments k-space into multiple regions and applies different filtering strategies to each region. The k-space data is divided into a central region and peripheral regions, with specific filtering applied to isolate tagging frequency components from background signals in each segment, enabling faster and more accurate B1 and B0 field mapping
Solution Approach 2:
The patent employs periodic tagging frequency modulation in the RF pulse sequence, where the tagging frequency is modulated at a known periodic rate. This periodic action creates distinct spectral signatures that can be filtered and processed to extract field information, improving both measurement precision and reducing acquisition time through efficient frequency domain sampling
2Reliability
If field mapping is performed to correct non-uniformities, then image quality improves, but system complexity increases
Solution Approach 1:
The patent extracts tagging frequency components from the k-space data by applying spatial frequency domain filtering. This extraction isolates the relevant field information from the complex MRI signal, separating the B1 and B0 field mapping information from other signal components, thereby improving image quality while managing processing complexity through targeted extraction
Solution Approach 2:
The patent introduces k-space spatial frequency domain filtering as an intermediary processing step between data acquisition and final image reconstruction. This intermediary filtering operation simplifies the overall processing by pre-processing the k-space data to remove unwanted frequency components, making subsequent field correction operations more efficient and manageable
3Productivity
If k-space filtering is applied, then mapping speed increases, but measurement precision may be compromised
Solution Approach 1:
The patent applies different filtering characteristics to different regions of k-space. The central region receives different filtering treatment compared to peripheral regions, with each region's filter parameters optimized for its specific signal characteristics. This local quality approach maintains measurement precision while enabling fast processing across the entire k-space domain
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 fast and accurate generation of B1 and B0 maps, reducing errors and improving image quality by accounting for field non-uniformities, enhancing MRI system performance, especially at higher field strengths and in moving subjects.
Implementation Method 1
nuclear magnetic resonance (NMR) wherein nuclei having a net magnetic moment
Implementation Method 2
immersed in a static background magnetic field B0. Ideally, this background static magnetic field is homogeneous throughout a volume to be imaged
Implementation Method 3
transmitting an RF magnetic field at the Larmor frequency into the volume that is to be imaged... so as to nutate the nuclear magnetic moment away from the nominal static magnetic field B0
Implementation Method 4
each relaxing nuclear magnetic moment emits a radio frequency response signal that can be detected as an RF signal
Data Source
AI summary
Frequency filtering of spatially modulated or “tagged” MRI data in the spatial frequency k-space domain with subsequent 2DFT to the spatial domain and pixel-by-pixel arithmetic calculations provide robust data that can be used to derive B1 and/or B0 maps for an MRI system.