MR Point Spread Function Calibration via Single K-Space Line
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Solution Overview
Problem
Current methods for determining the point spread function in magnetic resonance imaging, especially with techniques like Wave-CAIPI, are time-consuming and require additional measurement equipment or lengthy compute-intensive optimizations, making them impractical for rapid and high-quality image reconstruction during patient examinations.
Innovation Solution
A method that involves acquiring calibration data with and without additional gradient pulses for each gradient output direction, allowing for the precise calculation of the point spread function using a single k-space line, which can be done quickly and without additional hardware, enabling rapid trajectory characterization prior to each examination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods for determining the point spread function are used (multiple complete 3D k-space measurements), then measurement precision is improved, but loss of time increases significantly
Solution Approach 1:
The patent extracts only the essential information needed to determine the point spread function by acquiring data from a single k-space line instead of multiple complete 3D k-space measurements. This extraction approach obtains the necessary calibration data with minimal measurement time while maintaining sufficient accuracy for trajectory characterization.
Solution Approach 2:
The patent applies partial action by performing an incomplete measurement (single k-space line) that is sufficient for the specific purpose of determining the point spread function. This partial measurement avoids the excessive time required for complete 3D k-space measurements while providing adequate information for image reconstruction.
2Measurement precision
If compute-intensive nonlinear optimization is used to determine the point spread function, then measurement precision is improved, but loss of time increases due to lengthy computations
Solution Approach 1:
The patent replaces the mechanical computation process (iterative nonlinear optimization) with a direct calculation approach. By using the analytically derived relationship between the acquired signal and the point spread function, the system eliminates time-consuming numerical optimization while maintaining measurement precision.
Solution Approach 2:
The patent performs preliminary analytical preparation by deriving the direct calculation formula for the point spread function before actual measurement. This preliminary theoretical work enables rapid computation during the examination without requiring iterative optimization, as the calculation method is predetermined and optimized.
3Productivity
If additional gradient pulses are applied during readout to achieve slice shifts, then productivity is improved through faster imaging, but device complexity increases
Solution Approach 1:
The patent makes the additional gradient pulses serve multiple functions: they both create the desired slice shifts for accelerated imaging and simultaneously encode information about the actual k-space trajectory. This multi-functionality reduces the need for separate calibration measurements and simplifies the overall system requirements.
Solution Approach 2:
The additional gradient pulses automatically provide the information needed for point spread function determination through their effect on the acquired signal. The system uses the gradient pulses' own impact on the data to characterize the trajectory, eliminating the need for separate field camera equipment or additional dedicated measurement sequences.
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 significantly reduces examination time, eliminates the need for lengthy optimizations, and allows for high-quality image reconstruction without additional hardware, while being adaptable to changes in positioning and resolution without reacquiring calibration data.
Implementation Method 1
magnetic resonance imaging has meanwhile become established as a medical imaging modality
Implementation Method 2
a magnetic resonance sequence is used which applies an additional gradient pulse of a predefined gradient shape along at least one additional gradient output direction perpendicular to a readout direction during a readout time window
Implementation Method 3
a point spread function describing the actual sampling trajectory distorted by the additional gradient pulse is used in order to determine a magnetic resonance dataset from magnetic resonance signals
Data Source
AI summary
Method for MR imaging of an acquisition region during a patient examination. In order to determine a point spread function, in a prior measurement for each of additional gradient output directions, the method includes choosing, in the acquisition region, a slice lying outside of an isocenter of the MR device, which slice extends in a plane perpendicular to the additional gradient output direction under consideration; following a respective slice-selective excitation of the selected slice, acquiring first calibration data using the additional gradient pulse of the additional gradient output direction under consideration, and acquiring second calibration data omitting the additional gradient pulse in each case along a k-space line, wherein a same timing sequence of additional gradient pulse and readout time window is used as in the MR sequence; and calculating, from the first and second calibration data, the point spread function for the additional gradient output direction under consideration.