K-space Sectoring for Respiratory Motion Blur in MRI
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Solution Overview
Problem
Existing magnetic resonance imaging (MRI) techniques face challenges in reducing movement sensitivities, particularly in Cartesian 3D gradient echo sequences, leading to artifacts and inefficiencies due to respiratory variations, especially near the k-space center.
Innovation Solution
The method involves acquiring k-space data in multiple shots with a consistent number of views per shot, where views are distributed across sectors to maintain similar distances from the k-space center, and scanning these views in a manner that blurs movement along both Cartesian directions, reducing ghosting artifacts and increasing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If respiratory gating is used to reduce movement artifacts, then image quality is improved, but measurement time increases
Solution Approach 1:
The patent segments k-space into multiple sectors and distributes views across these sectors. Each sector contains views at similar distances from the k-space center, allowing independent processing and reconstruction. This segmentation enables more efficient use of acquired data and reduces the need for repeated measurements, thereby reducing measurement time while maintaining image quality.
Solution Approach 2:
The patent implements dynamic sorting of k-space views based on respiratory position. Views are sorted according to the respiratory signal and assigned to different bins corresponding to specific respiratory phases. This dynamic organization allows optimal selection of views for reconstruction at each respiratory phase, improving image quality without requiring excessive measurement time.
2Productivity
If multiple shots are used to acquire k-space data, then measurement time is reduced, but movement sensitivity increases
Solution Approach 1:
The patent applies local quality by distributing views from multiple shots across different sectors of k-space. Each sector is optimized to contain views at similar distances from the center, and views within each sector are processed with consideration of their specific respiratory phase. This local optimization reduces movement sensitivity while maintaining the efficiency benefits of multiple shots.
Solution Approach 2:
The patent dynamically sorts and bins views from multiple shots based on respiratory position. By organizing views according to their acquisition time and corresponding respiratory phase, the method reduces movement sensitivity even when using multiple shots for efficient data acquisition.
3Manufacturing precision
If views are concentrated near the k-space center, then image contrast is improved, but ghosting artifacts increase due to respiratory movement
Solution Approach 1:
The patent segments k-space into multiple sectors radially distributed around the center. This segmentation ensures that views at similar distances from the center are grouped together in the same sector, maintaining contrast while distributing the impact of respiratory movement across different sectors. The radial segmentation pattern helps minimize ghosting artifacts by ensuring that views affected by respiratory movement are properly sorted and reconstructed.
Solution Approach 2:
The patent dynamically sorts views within each sector based on respiratory position. By assigning views to different bins according to respiratory phase, the method reduces ghosting artifacts while preserving the contrast-enhancing concentration of views near the k-space center.
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 reduces movement sensitivity and artifacts, enhances image quality, and improves the efficiency of MRI scans by distributing k-space views to minimize the impact of respiratory movements, allowing for more flexible respiratory signal handling and shorter measurement times.
Implementation Method 1
Magnetic resonance (MR) is a known technology with which images from the interior of an examination subject can be generated. Expressed simply, the examination subject is placed in a magnetic resonance imaging scanner, in a strong, static, homogenous base magnetic field, also called a B0 field, having a field strength of 0.2 tesla-7 tesla and more, such that the nuclear spins of the subject orient themselves along the base magnetic field. In order to trigger magnetic resonance signals, the examination subject is irradiated with high frequency excitation pulses (RF pulses), the triggered magnetic resonance signals are detected
Implementation Method 2
For the spatial encoding of the measurement data, rapidly activated magnetic gradient fields are superimposed on the base magnetic field. The recorded measurement data are digitized and stored as complex number values in a k-space matrix.
Data Source
AI summary
In a method and apparatus to acquire a measurement data set of a breathing examination subject by magnetic resonance, the measurement data set is acquired in multiple shots each composed of a number of k-space trajectories (views), with the number Nv of views per shot being selected. The number of shots is determined in order to completely fill k-space to be scanned. The views of the shots are associated with sectors in k-space, with approximately the same number of views in each sector, and with all views in a sector have a similar distance from the k-space center. A respective view of each sector is associated with a respective one of the shots, corresponding to the orientation of the respective shot. The views that are associated with the same sector and different shots respectively assume the same time position within the shot.