GRAPPA Operator Gridding for MRI Trajectory Correction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Gradient timing delays in MRI systems cause mismatches between intended and actual trajectories, leading to artifacts in reconstructed images, as conventional methods require additional acquisitions that may not account for gradient coupling and patient motion, and assume consistent shifts.
Innovation Solution
The use of GRAPPA Operator Gridding (GROG) to determine base weights for shifting trajectories, allowing for the correction of gradient delays without additional acquisitions by identifying on-angle portions of trajectories, calculating GROG weights, and iteratively adjusting the center of k-space to ensure accurate projection alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods are used to correct trajectory shifts, then additional acquisitions are required, but this increases scan time and may not account for gradient coupling and patient motion
Solution Approach 1:
The method uses the acquired k-space data itself to determine trajectory shifts and calculate correction factors, rather than requiring separate calibration acquisitions. The system self-calibrates by analyzing the actual trajectory deviations from the intended path during the imaging acquisition, eliminating the need for additional time-consuming calibration scans.
Solution Approach 2:
The system continuously monitors the actual trajectory during acquisition and compares it against the intended trajectory. Correction factors are calculated based on the observed deviations and applied to realign the k-space data, providing feedback-based trajectory correction that adapts to gradient coupling and patient motion effects.
2Measurement precision
If additional acquisitions are performed to account for trajectory shifts, then measurement precision improves, but device complexity increases
Solution Approach 1:
The method performs multiple functions within a single acquisition: it simultaneously obtains imaging data and uses the same data to determine trajectory shifts and calculate correction factors. This multi-functional approach eliminates the need for separate calibration acquisitions and reduces overall system complexity.
Solution Approach 2:
The system performs preliminary trajectory analysis during the acquisition process itself, calculating correction factors as the data is collected. This preliminary action is integrated into the acquisition protocol rather than requiring separate pre-calibration steps, simplifying the overall device complexity.
3Productivity
If gradient coils operate at high slew rates, then echo spacing decreases and imaging speed improves, but trajectory deviations increase due to delay times
Solution Approach 1:
The system changes the parameter approach by not trying to eliminate gradient delays but rather by measuring the actual trajectory deviations caused by these delays and using the measured information to correct the k-space data. This allows high slew rates to be maintained while compensating for the resulting trajectory inaccuracies through data processing.
Solution Approach 2:
The method replaces mechanical/physical trajectory correction (which would require complex gradient timing adjustments) with a computational approach. Instead of trying to mechanically synchronize gradient responses, the system uses signal processing and trajectory-based correction factors to achieve the desired imaging accuracy.
Data Source
AI summary
Apparatus, methods, and other embodiments associated with magnetic resonance (MR) trajectory correcting using GRAPPA operator gridding (GROG) are described. One example method includes identifying an on angle or regular portion of a projection in an MR trajectory and then computing base GROG weights for that portion. The example method includes identifying a shift direction and a shift amount for the projection. The shift direction is configured to shift the projection towards a desired point in k-space and the shift amount is configured to shift the projection by a desired amount in the shift direction. With a shift direction and amount available, the example method corrects for a gradient delay by manipulating the MR source signal data using the shift direction and the shift amount. In one embodiment, a gradient delay can be determined and used to calibrate an MRI apparatus.