Surface Coil Signal Saturation in Non-Uniform MR Fields
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Solution Overview
Problem
Conventional signal saturation methods in magnetic resonance imaging are highly sensitive to the non-uniformity of the main magnetic field, RF pulse intensity, and the size and position of the saturation region, making them impractical for use in non-uniform fields.
Innovation Solution
A method involving a magnetization preparation module based on the non-uniformity of the RF field and distance between a target saturation region and a surface coil, using adiabatic pulses to acquire and process datasets to achieve spatial selection, with phase cycling to eliminate interference signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional RF pulses are used for signal saturation, then signal saturation can be achieved in uniform fields, but the method becomes highly sensitive to non-uniformity of the main magnetic field and RF pulse intensity in non-uniform fields
Solution Approach 1:
The patent applies adiabatic pulses with continuously varying frequency and amplitude parameters instead of conventional fixed-parameter RF pulses. The frequency sweeps through a range while amplitude modulates according to a specific profile, making the pulse effects independent of B0 non-uniformity and B1 intensity variations. This parameter transformation resolves the contradiction by maintaining reliable signal saturation across different field conditions.
Solution Approach 2:
The patent introduces dynamic RF pulses where frequency and amplitude change continuously during the pulse duration rather than remaining static. The adiabatic condition requires dω/dt >> γB1², creating a dynamic system that adapts to local field conditions automatically, thereby achieving both reliability and adaptability in non-uniform fields.
2Manufacturing precision
If gradient pulses and saturation RF pulses are combined for spatial selection, then spatially selective signal saturation is achieved, but the method fails under non-uniform fields where both B0 and B1 exhibit significant non-uniformity
Solution Approach 1:
The patent replaces gradient-based spatial encoding with adiabatic pulses whose frequency and amplitude parameters are specifically designed to create spatially selective saturation in non-uniform fields. The adiabatic frequency sweep range and amplitude modulation profile are adjusted based on the expected field non-uniformity, achieving spatial selection without relying on linear gradients that fail under non-uniform conditions.
Solution Approach 2:
The patent introduces adiabatic pulses as an intermediary mechanism that mediates between the non-uniform field conditions and the desired spatial selection effect. These pulses act as a buffer that translates the complex non-uniform field distribution into controlled spatial saturation patterns, resolving the incompatibility between spatial selection requirements and non-uniform field conditions.
3Ease of manufacture
If conventional RF pulses are used in non-uniform fields, then some signal saturation effect can be observed, but the effect arises from signal cancellation rather than true saturation and shows high sensitivity to field non-uniformity
Solution Approach 1:
The patent transforms conventional fixed-parameter RF pulses into adiabatic pulses with continuously varying frequency and amplitude. This parameter change ensures that the saturation effect arises from genuine spin inversion rather than accidental signal cancellation, while maintaining implementation feasibility through standardized pulse sequence designs.
Solution Approach 2:
The patent converts the harmful effect of non-uniform fields (which causes signal cancellation in conventional methods) into a beneficial feature by designing adiabatic pulses that exploit the non-uniformity pattern. The frequency sweep and amplitude modulation are specifically tailored to work with the non-uniform field distribution, turning the problem of field non-uniformity into an advantage for achieving reliable spatial saturation.
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
The method demonstrates insensitivity to the non-uniformity of the main magnetic field and RF field intensity, allowing for stable and accurate signal saturation in non-uniform fields, enhancing practical applicability.
Implementation Method 1
a magnetization preparation module based on a distance between a target saturation region and a surface coil under a non-uniform field
Implementation Method 2
the present disclosure belongs to the technical field of magnetic resonance (MR)
Implementation Method 3
transmitting, by the surface coil, a first main pulse sequence
Implementation Method 4
saturation radio frequency (RF) pulses
Implementation Method 5
performing phase cycling on the first main pulse sequence or on the first magnetization preparation module and the first main pulse sequence, to eliminate an effect of a ring-down signal during an echo process and residual transverse magnetization
Data Source
AI summary
The provided is a signal saturation method for achieving spatial selection under a non-uniform field, and a medium. The method includes: setting a corresponding magnetization preparation module based on a distance between a target saturation region and a surface coil under a non-uniform field (S1); transmitting, by the surface coil, a first main pulse sequence, or sequentially transmitting a first magnetization preparation module and a first main pulse sequence, to acquire a first echo signal, and storing the first echo signal as a first dataset (S2); sequentially transmitting, by the surface coil, a second magnetization preparation module and a second main pulse sequence to acquire a second echo signal, and storing the second echo signal as a second dataset (S3); and processing the first dataset and the second dataset to saturate a signal in the target saturation region, thereby achieving spatial selection (S4).