Total liver fat quantification using three-dimensional respiratory self-navigated MRI sequence.

Area of Science:

• Medical Imaging
• Quantitative MRI
• Hepatology

Background:

• Magnetic Resonance Imaging (MRI) enables noninvasive quantification of liver fat fraction (FF), crucial for diagnosing fatty liver diseases.
• Current MRI methods often use 2D slices requiring breath-holds, posing challenges for patients with limited capacity.
• Existing 3D imaging motion correction techniques have drawbacks like external devices, acquisition interruption, or reduced spatial resolution.

Purpose of the Study:

• To present a proof-of-concept for a self-navigated 3D three-point Dixon MRI sequence for whole-liver fat quantification.
• To overcome limitations of breath-hold techniques and current 3D motion correction methods.
• To enable precise FF mapping in a single acquisition without compromising spatial resolution.

Main Methods:

• Integration of a respiratory self-gating strategy with a center k-space profile into a three-point Dixon sequence.
• Acquisition of 3D fat fraction (FF) maps using the novel sequence in a phantom and fifteen volunteers.
• Comparative analysis against multi-2D breath-hold and 3D free-breathing MRI approaches.

Main Results:

• The 3D self-navigated Dixon sequence effectively corrected for respiratory motion artifacts.
• The sequence provided more precise FF measurements compared to multi-2D breath-hold techniques.
• The 3D free-breathing approach was outperformed in terms of FF measurement precision.

Conclusions:

• The developed 3D respiratory self-gating fat quantification sequence corrects for respiratory motion.
• This novel sequence yields more precise liver fat fraction measurements.
• The method offers an improved approach for noninvasive liver fat assessment using MRI.