Multi-parametric liver tissue characterization using MR fingerprinting: Simultaneous T₁ , T₂ , T₂ *, and fat fraction...

Area of Science:

• Magnetic Resonance Imaging
• Medical Physics
• Hepatology

Background:

• Quantitative imaging biomarkers like T1, T2, T2*, and fat fraction (FF) are crucial for assessing liver disease.
• Current methods often require sequential scans, increasing acquisition time and patient burden.

Purpose of the Study:

• To develop and evaluate an extended MR fingerprinting (MRF) framework for simultaneous quantitative mapping of liver T1, T2, T2*, and FF.
• To enable multi-parametric liver tissue characterization within a single, short breath-hold scan (~14 seconds).

Main Methods:

• A gradient echo (GRE) liver MRF sequence with nine readouts, low flip angles, and golden angle radial trajectory was implemented at 1.5T.
• A low-rank tensor constrained reconstruction was used for nine-echo time-series analysis.
• Dictionary matching and M0 map analysis were employed for water- and fat-specific parameter estimation, including FF.

Main Results:

• Phantom studies demonstrated high accuracy (r² > 0.97) for T1, T2, T2*, and FF mapping compared to reference methods.
• In vivo measurements in 12 subjects showed comparable results to conventional techniques with minimal bias.
• Preliminary feasibility was demonstrated in four patients.

Conclusions:

• The proposed nine-echo liver MRF sequence allows for efficient, quantitative multi-parametric liver tissue characterization.
• This technique offers a promising approach for liver disease assessment, with future validation in patient cohorts planned.