Evidence map›Paper›PMID 41387985›Full record

ArticleMagnetic resonance in medicine2026

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

Jiayi Tang, Daiki Tamada, Jon-Fredrik Nielsen, Jitka Starekova, Julius F Heidenreich, Felix Schön, Alexandra A Anagnostopoulos, Amirhossein Roshanshad, Lu Mao, Shohei Fujita and 18 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Magnetic resonance in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

28 authors.

Jiayi TangMedical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID https://orcid.org/0009-0000-8565-6575
Daiki TamadaDepartment of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID https://orcid.org/0000-0003-3615-459X
Jon-Fredrik NielsenFunctional MRI Laboratory, Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA.ORCID https://orcid.org/0000-0002-2058-3579
Jitka StarekovaDepartment of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID https://orcid.org/0000-0002-4285-3090
Julius F HeidenreichDepartment of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID https://orcid.org/0000-0002-0683-7982
Felix SchönDepartment of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID https://orcid.org/0000-0003-4377-2345
Alexandra A AnagnostopoulosDepartment of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID https://orcid.org/0009-0003-3362-9673
Amirhossein RoshanshadDepartment of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID https://orcid.org/0000-0001-6725-0045
Lu MaoBiostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID https://orcid.org/0000-0002-8626-9822
Shohei FujitaAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.ORCID https://orcid.org/0000-0003-4276-6226
Pengcheng XuAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.ORCID https://orcid.org/0009-0002-3911-7188
Christopher KeenBiomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA.ORCID https://orcid.org/0000-0001-9049-2851
Imam Ahmed ShaikBrigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.ORCID https://orcid.org/0009-0000-2849-8849
Eugene MilshteynGE HealthCare, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0003-0213-7003
Seonghwan YeeRadiology, Harvard Medical School, Boston, Massachusetts, USA.ORCID https://orcid.org/0009-0004-6001-9106
Andrew J EllisonBiomedical Imaging Center, Chobanian and Avedisian School of Medicine, Boston University, Boston, Massachusetts, USA.ORCID https://orcid.org/0009-0008-2056-7182
David RutkowskiCalimetrix, LLC, Madison, Wisconsin, USA.ORCID https://orcid.org/0000-0002-1168-5004
Jeff KammermanCalimetrix, LLC, Madison, Wisconsin, USA.ORCID https://orcid.org/0000-0003-4780-9360
Jean H BrittainCalimetrix, LLC, Madison, Wisconsin, USA.ORCID https://orcid.org/0000-0002-1314-8114
Xiaodong ZhongRadiological Sciences, University of California, Los Angeles, Los Angeles, California, USA.ORCID https://orcid.org/0000-0001-8355-5279
William A GrissomBiomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.ORCID https://orcid.org/0000-0002-3289-1827
Maxim ZaitsevDivision of Medical Physics, Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.ORCID https://orcid.org/0000-0001-7530-1228
Aaron L CarrelPediatrics, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID https://orcid.org/0000-0001-7575-2539
Yogesh RathiBrigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0002-9946-2314
Yun JiangRadiology, University of Michigan, Ann Arbor, Michigan, USA.ORCID https://orcid.org/0000-0002-0713-9641
Berkin BilgicAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.ORCID https://orcid.org/0000-0002-9080-7865
Scott B ReederMedical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID https://orcid.org/0000-0003-4728-8171
Diego HernandoMedical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID https://orcid.org/0000-0002-0016-0317

Funding

A harmonized vendor-agnostic environment for multi-site functional MRI studiesU24NS120056 · NINDS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2023 to 2025
$1.5M
Harmonizing data acquisition, reconstruction, and analysis for reproducible, cross-vendor, open source MRIR01EB032378 · BRIGHAM AND WOMEN'S HOSPITAL · 2025 to 2025
$644k
Fully Automated High-Throughput Quantitative MRI of the LiverR01EB031886 · UNIVERSITY OF WISCONSIN-MADISON · 2025 to 2025
$584k
Department of Radiology, University of Wisconsin-Madison 2307-003NIBIB NIH HHS R01EB031886NIBIB NIH HHS R01 EB032378NIBIB NIH HHS R01EB032378NIBIB NIH HHS R44EB025729NINDS NIH HHS U24 NS120056
6 · The paper itself

Abstract

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

methodsFlip-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%/T1

resultsIn 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).

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

Indexed as

Adipose TissueImage Processing, Computer-AssistedLiverMagnetic Resonance ImagingAdultArtifactsFemaleHumansImaging, Three-DimensionalMaleMiddle AgedMotionPhantoms, ImagingProspective StudiesReproducibility of Resultscross‐vendorfat quantificationliverMASLDPDFFproton density fat fractionPulseqvendor‐agnostic

Identifiers

PMID41387985
PMCPMC12962202

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.