Evidence map›Paper›PMID 41585083›Full record

ReviewFrontiers in radiology2025

Diagnosing acute myocarditis in the emergency department-advancing cardiac MRI with a focus on low-field MR applications.

Ehsan Karimialavijeh, Latika Giri, Eduardo Baettig, Muhammad Umair

Abstract readReview
In one paragraph

Review in Frontiers in radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Ehsan KarimialavijehKaiser Permanent, Central Valley, CA, United States.
Latika GiriKathmandu University School of Medical Sciences, Dhulikhel, Nepal.
Eduardo BaettigDepartment of Radiology, Hospital Clínico Universitario de Valencia, Valencia, Spain.
Muhammad UmairColumbia University Irving Medical Center, New York, NY, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute myocarditis is an inflammatory condition of the myocardium, often triggered by viral infections, autoimmune diseases, or toxins. It can lead to arrhythmias, heart failure, and sudden cardiac death. Early and accurate diagnosis is crucial for timely management and preventing complications. It poses a significant diagnostic challenge in emergency departments (EDs) due to nonspecific symptoms, overlapping features with conditions like acute coronary syndrome, and limitations of conventional diagnostics. Cardiac magnetic resonance imaging (CMR) is the gold standard for noninvasive diagnosis, using the 2018 Modified Lake Louise Criteria (mLLC). However, high-field CMR (1.5-3T) faces barriers in EDs, such as longer scan times, higher cost, lack of accessibility, and contraindications in patients with implantable devices, severe kidney disease, or hemodynamic instability. Low-field MRI (<1.5T) offers advantages in portability, safety, and cost while reducing susceptibility artifacts. Recent advances in AI-driven image reconstruction (e.g., LoHiResGAN, U-net) address low signal-to-noise ratios, enabling cine imaging, strain analysis, and parametric mapping at 0.55T. Studies show that low-field CMR can detect subclinical myocarditis and predict outcomes, with ECV measurements at 0.55T strongly correlating with 1.5T (

Indexed as

abbreviated protocolacute myocarditisartificial intelligence (AI)cardiac magnetic resonance (CMR)emergency departmentlow-field MRIparametric mapping

Identifiers

PMID41585083
PMCPMC12823832

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Registered trials

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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 OpenQuestion graph.