# Highly Reproducible, Vendor‐Agnostic, Motion‐Insensitive Liver PDFF Mapping at 0.55T, 1.5T, and 3T

**Authors:** Jiayi Tang, Daiki Tamada, Jon‐Fredrik Nielsen, Jitka Starekova, Julius F. Heidenreich, Felix Schön, Alexandra A. Anagnostopoulos, Amirhossein Roshanshad, Lu Mao, Shohei Fujita, Pengcheng Xu, Christopher Keen, Imam Ahmed Shaik, Eugene Milshteyn, Seonghwan Yee, Andrew J. Ellison, David Rutkowski, Jeff Kammerman, Jean H. Brittain, Xiaodong Zhong, William A. Grissom, Maxim Zaitsev, Aaron L. Carrel, Yogesh Rathi, Yun Jiang, Berkin Bilgic, Scott B. Reeder, Diego Hernando

PMC · DOI: 10.1002/mrm.70223 · 2025-12-12

## TL;DR

This study introduces a new MRI method for measuring liver fat that works across different machines and is less affected by motion.

## Contribution

A vendor-agnostic, motion-insensitive PDFF quantification method was developed and validated across multiple MR systems and field strengths.

## Key findings

- Pulseq-FAM showed reduced T1-bias and variability compared to commercial methods in phantom studies.
- Pulseq-FAM improved image quality and reduced motion artifacts in volunteer studies.
- The method demonstrated excellent repeatability and reproducibility across field strengths.

## Abstract

To develop and validate a vendor‐agnostic, motion‐insensitive proton‐density fat‐fraction (PDFF) quantification method.

Flip‐angle‐modulated (FAM) 2D chemical‐shift‐encoded (CSE) MRI for PDFF quantification was implemented in both the vendor‐agnostic platform Pulseq (“Pulseq‐FAM”) and one vendor‐specific platform (“GE‐specific FAM”). These implementations were distributed to four sites with twelve MR systems of three vendors (Siemens/GE/Philips) and field strengths (0.55T/1.5T/3T). A sequentially‐shipped 16‐vial phantom (PDFF = 0%–30%/T1water = 200–1400 ms) underwent confounder‐corrected PDFF mapping with commercial 3D‐CSE methods and GE‐specific FAM as available on each system, and Pulseq‐FAM on every system. To assess bias, phantom PDFF measurements were compared to reference. Between‐system variance was evaluated with linear mixed‐effects modeling. Different volunteers were also imaged at each site to assess free‐breathing PDFF mapping feasibility.

A prospective single‐site volunteer study was also conducted. Adult patients and children were imaged with breath‐held 3D‐CSE and free‐breathing GE‐specific and Pulseq‐FAM. Radiologists evaluated images for overall quality and motion artifacts. To assess bias, Pulseq‐FAM PDFF measurements were compared to 3D‐CSE and GE‐specific FAM. Test–retest repeatability was assessed by re‐imaging after repositioning. Between‐field‐strength reproducibility was assessed at 1.5T and 3.0T.

In the multi‐center study, Pulseq‐FAM showed reduced T1‐bias and between‐system variability versus 3D‐CSE in phantom PDFF measurements, and free‐breathing feasibility in volunteers. In the single‐site volunteer study (N = 57), Pulseq‐FAM improved image quality and motion artifacts versus 3D‐CSE (p < 0.01). Pulseq‐FAM showed excellent agreement with 3D‐CSE (95% limits‐of‐agreement (LoA) = 3.4% PDFF) and GE‐specific FAM (LoA = 2.0%). Pulseq‐FAM showed excellent repeatability (repeatability coefficient (RC) = 1.6% PDFF) and between‐field‐strength reproducibility (reproducibility coefficient (RDC) = 2.4%) versus 3D‐CSE (RC = 2.7%/RDC = 3.4%; differences p < 0.05).

Pulseq‐FAM enables accurate, reproducible, vendor‐agnostic, and motion‐insensitive PDFF quantification in adults and children.

## Full-text entities

- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

7 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12962202/full.md

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Source: https://tomesphere.com/paper/PMC12962202