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Fast and Accurate Abdominal PDFF and R2* Mapping With Model-Fitted Flip Angle Modulation and Simultaneous Multi-Slice

Chuanli Cheng1,2, Liwen Wan1,2, Hao Peng1,2

  • 1Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.

Magnetic Resonance in Medicine
|November 25, 2025
PubMed
Summary
This summary is machine-generated.

A new 2D Flip Angle Modulated (FAM) MRI method with model-fitted flip angle calculation and simultaneous multi-slice (SMS) acceleration offers fast and accurate liver fat fraction (PDFF) and R2* quantification. This approach demonstrates superior noise performance compared to traditional GRAPPA methods.

Keywords:
R2*free‐breathing CSEmodel‐fitted FAMproton density fat fractionsimultaneous multi‐slice

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Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Medical Physics
  • Biomedical Engineering

Background:

  • Accurate quantification of liver proton-density fat fraction (PDFF) and R2* is crucial for diagnosing and monitoring liver diseases.
  • Current MRI techniques can be time-consuming and may be affected by motion artifacts.
  • Simultaneous multi-slice (SMS) imaging offers potential for accelerated MRI acquisition.

Purpose of the Study:

  • To develop and validate an online model fitting-based flip angle calculation method for Flip Angle Modulated (FAM) Chemical Shift-Encoded (CSE) MRI.
  • To integrate FAM-CSE MRI with SMS imaging for accelerated and accurate abdominal PDFF and R2* quantification.
  • To evaluate the performance of the proposed method against existing techniques.

Main Methods:

  • A novel online model fitting approach using Gaussian functions was employed to determine optimal flip angle (FA) profiles, avoiding iterative optimization.
  • Inter-slice SMS acceleration was integrated to enhance acquisition efficiency.
  • Phantom and volunteer studies at 3.0T were conducted to validate PDFF and R2* quantification using FAM-SMS, FAM-GRAPPA, and FAM-Hybrid methods, compared to low-FA 3D acquisitions.

Main Results:

  • Model-fitted FA profiles closely matched optimized profiles in phantom studies, yielding unbiased PDFF and R2* quantification.
  • FAM-SMS demonstrated high correlation with 3D reference scans for both PDFF (0.994-0.995) and R2* (0.978-0.988).
  • In vivo, FAM-SMS achieved comparable noise levels to 3D acquisition and showed significantly lower standard deviations for PDFF (18.7%) and R2* (18.5%) compared to FAM-GRAPPA.

Conclusions:

  • The proposed 2D FAM method with model-fitted FA calculation and SMS acceleration provides fast, accurate, and motion-robust liver PDFF and R2* imaging.
  • This technique offers superior noise performance compared to GRAPPA, simplifying MRI protocol design.
  • The method holds promise for improved clinical assessment of liver fat content and iron overload.