Evidence map›Paper›PMID 39754665›Full record

ReviewEuropean journal of nuclear medicine and molecular imaging2025

Mapping the knowledge landscape of the PET/MR domain: a multidimensional bibliometric analysis.

Xiaofei Hu, Jianding Peng, Min Huang, Lin Huang, Qing Wang, Dingde Huang, Mei Tian

Abstract readReview
PubMed Publisher
In one paragraph

Review in European journal of nuclear medicine and molecular imaging, 2025. 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. Review
  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

7 authors.

Xiaofei Hu *Department of Nuclear Medicine, The First Hospital Affiliated of Army Medical University (Southwest Hospital), 30 Gaotanyanzheng St., Shapingba district, Chongqing, 400038, China.ORCID 0000-0001-5376-2779
Jianding Peng *School of Basic Medicine, Capital Medical University, Beijing, 100086, China.
Min HuangDepartment of Nuclear Medicine, The First Hospital Affiliated of Army Medical University (Southwest Hospital), 30 Gaotanyanzheng St., Shapingba district, Chongqing, 400038, China.
Lin HuangPeople's Hospital of Xingyi, Guizhou, 562400, China.
Qing WangInstitute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100086, China.
Dingde HuangDepartment of Nuclear Medicine, The First Hospital Affiliated of Army Medical University (Southwest Hospital), 30 Gaotanyanzheng St., Shapingba district, Chongqing, 400038, China. huangdingde@126.com.
Mei TianHuashan Hospital and Human Phenome Institute, Fudan University, 220 Handan Road, Shanghai, 200433, China. tianmei@fudan.edu.cn.ORCID 0000-0002-1587-2114

Funding

Beijing Postdoctoral Research Funding Project 2023-ZZ-002China Postdoctoral Science Foundation 2023M742438National Natural Science Foundation of China 82394430Natural Science Foundation of Chongqing cstc2021jcyj-msxmX0148
6 · The paper itself

Abstract

objectiveThis study aims to conduct a bibliometric analysis to explore research trends, collaboration patterns, and emerging themes in the PET/MR field based on published literature from 2010 to 2024.

methodsA detailed literature search was performed using the Web of Science Core Collection (WoSCC) database with keywords related to PET/MR. A total of 4,349 publications were retrieved and analyzed using various bibliometric tools, including VOSviewer and CiteSpace.

resultsThe analysis revealed an initial increase in PET/MR publications, peaking at 495 in 2021, followed by a slight decline. The USA, Germany, and China were the most prolific countries, with the USA demonstrating strong collaborative networks. Key institutions included the Stanford University, Technical University of Munich and University of Duisburg-Essen. Prominent authors were primarily from Germany, with significant contributions from University Hospital Essen. Major journals in the field included the European Journal of Nuclear Medicine, Journal of Nuclear Medicine, and Physics in Medicine and Biology. Emerging research areas focused on oncology, neurological disorders, and cardiovascular diseases, with keywords such as "prostate cancer," "Alzheimer's disease," and "breast cancer" showing high research activity. Recent trends also highlight the growing integration of AI, particularly deep learning, to improve imaging reconstruction and diagnostic accuracy.

conclusionThe findings emphasize the need for continuous investment, strategic planning, and technological innovations to expand PET/MR's clinical applications. Future research should focus on optimizing imaging techniques, fostering international collaborations, and integrating emerging technologies like artificial intelligence to enhance PET/MR's diagnostic and therapeutic potential in precision medicine.

Indexed as

BibliometricsMagnetic Resonance ImagingMultimodal ImagingPositron-Emission TomographyHumansBibliometric analysisHybrid imaging technologyInterdisciplinary collaborationPET/MRResearch trends

Identifiers

PMID39754665

What Socratic 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 Socratic graph.