MRI GRE Fat Suppression Sequencing for Motion Artifact Reduction

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Solution Overview

Problem

Gradient recalled echo (GRE) sequences in magnetic resonance imaging (MRI) cause motion artifacts and inappropriate tissue contrast, particularly in abdominal scans, necessitating a solution to reduce scan time while maintaining image quality.

Innovation Solution

A magnetic resonance imaging method involving multiple NEXs with fat suppression pulses followed by gradient recalled echo sequences, where each NEX acquires multiple groups of initial image data, and the image is reconstructed using summed data from these NEXs, with optimized fat suppression pulses to minimize artifacts and improve signal-to-noise ratio (SNR).

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If GRE sequences are used to shorten scan time, then productivity is improved, but image quality deteriorates due to motion artifacts and inappropriate tissue contrast

Engineering Contradiction:
Improvescan timeVSAvoidimage quality
Core Design Contradiction:
ProductivityVSManufacturing precision

Solution Approach 1:

The imaging process is segmented into multiple NEXs (number of excitations) with multiple fat suppression pulses and multiple GRE sequences within each NEX. This segmentation allows the acquisition of multiple groups of initial image data that can be subsequently combined through summation, thereby maintaining fast scanning while improving image quality and reducing artifacts.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

Fat suppression pulses are applied preliminarily before each GRE sequence to suppress adipose tissue signal in advance. This preliminary action prevents the bright fat signal from causing motion artifacts and inappropriate contrast during the subsequent fast GRE imaging, thereby improving image quality without sacrificing scan speed.

Inventive Principle:
Principle #10Preliminary action

2Manufacturing precision

If multiple fat suppression pulses are applied with multiple GRE sequences, then image quality is improved, but device complexity increases

Engineering Contradiction:
Improveimage qualityVSAvoidsequence complexity
Core Design Contradiction:
Manufacturing precisionVSDevice complexity

Solution Approach 1:

Multiple groups of initial image data acquired from different NEXs and different GRE sequences are merged through summation to form summed image data. This merging process combines the advantages of multiple acquisitions to improve image quality and reduce artifacts while managing sequence complexity through systematic data combination.

Inventive Principle:
Principle #5Merging (Combining)

Solution Approach 2:

The imaging protocol employs periodic application of fat suppression pulses followed by periodic GRE sequences across multiple NEXs. This periodic structure provides a systematic and manageable approach to acquiring multiple data groups that can be summed, thereby improving image quality without creating unmanageable sequence complexity.

Inventive Principle:
Principle #19Periodic action

3Manufacturing precision

If frequency saturation pulse with offset is used, then fat suppression effectiveness is improved, but signal-to-noise ratio deteriorates

Engineering Contradiction:
Improvefat suppression effectivenessVSAvoidsignal-to-noise ratio
Core Design Contradiction:
Manufacturing precisionVSMeasurement precision

Solution Approach 1:

The frequency saturation pulse is designed with a frequency offset from the exact fat resonance frequency and with a pulse width smaller than the preset full-width pulse. This partial action approach provides sufficient fat suppression effectiveness while preserving more of the signal from other tissues, thereby maintaining an acceptable signal-to-noise ratio.

Inventive Principle:
Principle #16Partial or excessive action

Solution Approach 2:

The frequency saturation pulse parameters are changed by introducing a frequency offset and reducing the pulse width compared to the conventional full-width pulse centered at fat resonance frequency. These parameter changes optimize the balance between fat suppression effectiveness and signal-to-noise ratio preservation.

Inventive Principle:
Principle #35Parameter changes

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 effectively reduces respiratory motion artifacts and improves image contrast and SNR, achieving faster scan times without compromising image quality.

Implementation Method 1

a main magnet used to surround at least a portion of a scan subject and produce a static magnetic field

Methodology Applied
Scientific EffectMagnetic field: Magnetic Field

Implementation Method 2

a gradient coil assembly used to apply at least one gradient magnetic field to the static magnetic field

Methodology Applied
Scientific EffectMagnetic field gradient: Magnetic Field

Implementation Method 3

a radio frequency coil assembly used to apply a radio frequency field to the scan subject and receive a magnetic resonance signal from the scan subject

Methodology Applied
Scientific EffectMagnetic resonance: Resonance

Data Source

PatentUS12578406B2Magnetic resonance imaging system and method
Publication Date: 2026.03.17 GE PRECISION HEALTHCARE LLC
  • US12578406B2 patent drawing
  • US12578406B2 patent drawing
  • US12578406B2 patent drawing

AI summary

Provided in the present invention are a magnetic resonance imaging system and method. The magnetic resonance imaging method comprises: performing m NEXs, wherein in each NEX, a plurality of fat suppression pulses are applied, each of the plurality of fat suppression pulses has thereafter m gradient recalled echo sequences, and each NEX acquires q groups of initial image data, where q=m*n, n is the number of fat suppression pulses applied in each NEX, n is greater than 1, and m is greater than 1; and reconstructing a magnetic resonance image on the basis of at least a portion of the initial image data acquired in the m NEXs.