Intra-blade Density Filter for Motion-Corrected MRI
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Solution Overview
Problem
Current MRI techniques are inadequate for correcting patient motion, particularly limiting the ability to perform T1-weighted imaging, as they often require long echo train lengths that restrict blade width and compromise motion correction.
Innovation Solution
The implementation of a density filter that preferentially weights k-space data to enhance T1-weighted or proton density-weighted acquisitions, allowing for robust motion correction by altering the weighting scheme to emphasize desired contrast over signal-to-noise, and the application of motion correction parameters to filtered k-space data using a motion correction algorithm.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If long echo train lengths are used for motion correction, then motion correction capability is improved, but blade width is restricted and T1-weighted imaging is compromised
Solution Approach 1:
The patent applies parameter changes by modifying the weighting scheme of k-space data through density filtering. Instead of uniformly weighting all echo lines, the system selectively weights echo lines based on their contribution to T1 contrast, thereby changing the effective parameters of the imaging sequence to achieve both motion correction and T1-weighted imaging with adequate blade width
Solution Approach 2:
The patent implements local quality by applying different weighting factors to different portions of the echo train. Specifically, echo lines that contribute more to T1 contrast receive higher weighting, while others are down-weighted or discarded. This localized optimization allows the system to maintain motion correction capability through blade rotation while preserving T1-weighted imaging quality
2Measurement precision
If conventional weighting schemes are used to emphasize signal-to-noise ratio, then signal quality is improved, but T1-weighted contrast is compromised
Solution Approach 1:
The patent changes the weighting parameter from conventional signal-to-noise optimization to T1-contrast optimization. By adjusting the density filter parameters and weighting factors, the system reprioritizes which echo lines contribute most to the final image, shifting the optimization goal from pure signal quality to T1-weighted contrast while maintaining acceptable noise levels
Solution Approach 2:
The patent applies local quality by differentiating the treatment of different echo lines based on their temporal position and contribution to T1 contrast. Early echo lines that provide strong T1 contrast are weighted heavily, while later echo lines are weighted less, creating a non-uniform weighting profile that optimizes T1-weighted imaging while managing noise
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
Enables the generation of T1-weighted images with improved motion correction capabilities, balancing contrast and signal-to-noise ratios, and facilitating the acquisition of motion-corrected images with enhanced image quality.
Implementation Method 1
magnetic resonance imaging (MRI) examinations are based on the interactions among a primary magnetic field, a radiofrequency (RF) magnetic field, and time varying magnetic gradient fields with gyromagnetic material having nuclear spins within a subject of interest
Implementation Method 2
a highly uniform, static magnetic field that is produced by a primary magnet
Implementation Method 3
An RF coil is employed to produce an RF magnetic field. This RF magnetic field perturbs the spins of some of the gyromagnetic nuclei from their equilibrium directions, causing the spins to precess around the axis of their equilibrium magnetization. During this precession, RF fields are emitted by the spinning, precessing nuclei
Implementation Method 4
A series of gradient fields are produced by a set of gradient coils located around the subject. The gradient fields encode positions of individual plane or volume elements (pixels or voxels) in two or three dimensions
Data Source
AI summary
In an embodiment, a method includes processing magnetic resonance (MR) data according to a process including applying a density filter to blades of k-space data rotated about a section of k-space. Each blade may include a first set of encode lines weighted in a first signal weighting and a second set of encode lines weighted in a second signal weighting. The density filter may be configured to preferentially weight each blade in the first signal weighting to produce blades of weighted k-space data.