Dual-Polarity GRE Reference Data for EPI Artifact Reduction
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Solution Overview
Problem
Current methods for capturing reference measurement data in echo-planar imaging (EPI) techniques are inefficient, leading to artifacts in image data due to inconsistencies and long measurement times, especially when dealing with nonuniformities in the main magnetic field and physiological movements.
Innovation Solution
A method involving dual-polarity GRE acquisition techniques to capture reference measurement data with alternating read-out gradients, ensuring consistency and reducing measurement time by capturing data with identical gradients of different polarities, allowing for rapid and robust artifact correction using dual-polarity algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If reference measurement data is captured using conventional EPI techniques, then the data can be used for artifact correction, but the measurement time becomes excessively long and inconsistencies arise due to physiological movements and magnetic field nonuniformities
Solution Approach 1:
The patent changes the acquisition parameters by using GRE (gradient-recalled echo) instead of EPI (echo-planar imaging) for capturing reference measurement data. This parameter change reduces the measurement time significantly while maintaining the quality needed for artifact correction, as GRE sequences are inherently faster and less susceptible to motion artifacts and magnetic field nonuniformities.
2Device complexity
If conventional single-polarity gradient methods are used for reference data acquisition, then the setup is simple, but artifacts such as image ghosts and wrap-around artifacts persist
Solution Approach 1:
The patent applies asymmetry by using dual-polarity read-out gradients instead of conventional single-polarity gradients. By acquiring reference measurement data with both positive and negative gradient polarities and combining them appropriately, the method eliminates artifacts such as image ghosts and wrap-around artifacts that arise from gradient nonlinearities and eddy currents, while maintaining relative simplicity in the overall acquisition protocol.
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 artifacts in image data, such as image ghosts and wrap-around artifacts, while shortening the overall measurement time by ensuring high consistency between reference and imaging data, making it suitable for clinical diagnostics.
Implementation Method 1
an RF excitation pulse is followed by an oscillating, i.e., bipolar, read-out gradient which, on every change in polarity of the gradient, refocuses the transverse magnetization as far as T2* decay permits, and thus in each case generates a gradient echo
Implementation Method 2
the object under examination is to this end positioned in a magnetic resonance imager in a comparatively strong static, homogeneous main magnetic field, also known as B0 field, with field strengths of 0.2 tesla to 7 tesla and higher, such that the nuclear spins thereof are oriented along the main magnetic field
Implementation Method 3
In order to trigger nuclear spin resonances which are measurable as signals, radio-frequency excitation pulses (RF pulses) are irradiated into the object under examination
Data Source
AI summary
Techniques are described for complex preprocessing steps to ensure consistency of sorted sets of reference measurement data, which have conventionally been required when sorting reference measurement data sets for DPG algorithms captured using an EPI technique, to be omitted because items of reference measurement data captured via the described techniques are already consistent in themselves. Therefore, for each polarity of the read-out gradients, a set of fully sampled reference measurement data is available, which is already suitable for carrying out a dual-polarity (DP) algorithm without any further measures.