Evidence map›Paper›PMID 41569085›Full record

ArticleJournal of magnetic resonance imaging : JMRI2026

Cardiac MR Fingerprinting at 0.55T Using a Deep Image Prior for Joint T

Zhongnan Liu, Zexuan Liu, Imran Rashid, Mauricio Stanzione Galizia, Christopher Scoma, William Truesdell, Prachi Agarwal, Nicole Seiberlich, Liyue Shen, Jesse Hamilton

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of magnetic resonance imaging : JMRI, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

Zhongnan LiuDepartment of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan, USA.ORCID 0009-0007-3492-0808
Zexuan LiuDepartment of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA.
Imran RashidSchool of Medicine, Case Western Reserve University, Cleveland, Ohio, USA.
Mauricio Stanzione GaliziaDepartment of Radiology, University of Michigan, Ann Arbor, Michigan, USA.
Christopher ScomaDivision of Cardiovascular Medicine, University of Michigan, Ann Arbor, Michigan, USA.
William TruesdellDepartment of Radiology, University of Michigan, Ann Arbor, Michigan, USA.
Prachi AgarwalDepartment of Radiology, University of Michigan, Ann Arbor, Michigan, USA.
Nicole SeiberlichDepartment of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA.
Liyue ShenDepartment of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan, USA.
Jesse HamiltonDepartment of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA.ORCID 0000-0002-4463-481X

Funding

DARPA HR00112520042MICDE Catalyst GrantMIDAS PODSNHI NHLBI R01HL163030NSF IIS-2435746Siemens Healthineers
6 · The paper itself

Abstract

background0.55T systems offer unique advantages and may support expanded access to cardiac MRI. PURPOSE: To assess the feasibility of 0.55T cardiac MR Fingerprinting (MRF), leveraging a deep image prior reconstruction to mitigate noise. STUDY TYPE: Phantom and prospective in vivo assessment. POPULATION: ISMRM/NIST MRI system phantom and 18 healthy subjects (11 female; ages 28 ± 8 years). FIELD STRENGTH AND SEQUENCES: MRF, modified Look-Locker inversion recovery (MOLLI), and T ASSESSMENT: MRF T STATISTICAL TESTS: Linear regression, Bland-Altman, intraclass correlation coefficient, and one-way ANOVA with p < 0.05 considered significant.

resultsMean measurements in the left ventricular septum were 671 ± 31 ms (MOLLI), 761 ± 147 ms (SLLR-MRF), and 686 ± 39 ms (DIP-MRF) for T DATA

conclusionThis study demonstrated the feasibility of cardiac MRF on a commercial 0.55T system, enabled by a deep image prior reconstruction for denoising. EVIDENCE LEVEL: 2. STAGE OF TECHNICAL EFFICACY: 1.

Indexed as

HeartImage Processing, Computer-AssistedMagnetic Resonance ImagingAdultAlgorithmsFeasibility StudiesFemaleHealthy VolunteersHumansImage Interpretation, Computer-AssistedMalePhantoms, ImagingProspective StudiesReproducibility of ResultsYoung Adultcardiacdeep learninglow fieldMR fingerprintingT1 mappingT2 mapping

Identifiers

PMID41569085
PMCPMC13066516

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.