Evidence map›Paper›PMID 42645965›Full record

ArticleJournal of imaging2026

Bibliometric Analysis of Whole-Body MRI from 2015 to 2025 Across Clinical Applications, Quantitative Imaging, and Artificial Intelligence.

Jonathan Lee, Christian Lee, Eric D Cyphers, Casey Bonzell, Simon Kim, Michael Repajic, Reza Assadsangabi, Thomas G Clifford, Vinay Duddalwar, Bryce D Beutler

Abstract read
In one paragraph

Article in Journal of imaging, 2026. 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

10 authors.

Jonathan LeeDepartment of Radiology, Los Angeles General Medical Center, Los Angeles, CA 90033, USA.ORCID 0000-0001-5220-1275
Christian LeeDepartment of Radiology, Los Angeles General Medical Center, Los Angeles, CA 90033, USA.
Eric D CyphersDepartment of Radiology, Los Angeles General Medical Center, Los Angeles, CA 90033, USA.
Casey BonzellDepartment of Radiology, Keck School of Medicine of USC, Los Angeles, CA 90033, USA.
Simon KimDepartment of Radiology, Keck School of Medicine of USC, Los Angeles, CA 90033, USA.
Michael RepajicDepartment of Radiology, Los Angeles General Medical Center, Los Angeles, CA 90033, USA.
Reza AssadsangabiDepartment of Radiology, Los Angeles General Medical Center, Los Angeles, CA 90033, USA.
Thomas G CliffordDepartment of Radiology, Los Angeles General Medical Center, Los Angeles, CA 90033, USA.
Vinay DuddalwarDepartment of Radiology, Los Angeles General Medical Center, Los Angeles, CA 90033, USA.
Bryce D BeutlerDepartment of Radiology, Los Angeles General Medical Center, Los Angeles, CA 90033, USA.ORCID 0000-0002-5071-1826

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Whole-body magnetic resonance imaging (WB-MRI) has become established for selected clinical indications and is increasingly studied across many fields including but not limited to oncologic, musculoskeletal, pediatric, and computational imaging applications. This study characterizes recent trends and the evolution of WB-MRI research using a bibliometric analysis reported using the PRISMA 2020 guidelines and identifies dominant clinical, quantitative, and artificial intelligence (AI) themes shaping the field. Publications were identified from Scopus, Web of Science, and PubMed using WB-MRI and its variant search terms and filtered to articles and reviews from 2015 through to 2025. Bibliometric analyses summarized publication output, contributors, citations, and keywords, and used exploratory keyword rules to classify major clinical and technical themes. Of 1511 included WB-MRI publications, annual output increased from 124 in 2015 to 180 in 2025. The journals with the highest publication counts were European Radiology, PLoS ONE, and the European Journal of Radiology. Parsed author affiliations most frequently represented the United States, Germany, and the United Kingdom. Research centered on oncologic applications, particularly myeloma and prostate cancer, alongside musculoskeletal disease, diffusion-weighted imaging, and AI-based segmentation. AI-related publications increased from 5 in 2015 to 20 in 2025. Broader clinical use of WB-MRI will require standardized acquisition, reproducible quantitative measures, and multicenter validation.

Indexed as

artificial intelligencebibliometricsdiffusion-weighted imagingmusculoskeletal imagingoncologic imagingpediatric imagingquantitative biomarkersradiomicsrare diseasewhole-body MRI

Identifiers

PMID42645965
PMCPMC13514230

What OpenQuestion holds

Textmetadata
Read underepoch 390

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 OpenQuestion graph.