Evidence map›Paper›PMID 40344610›Full record

ReviewJournal of magnetic resonance imaging : JMRI2025

Magnetic Resonance Imaging in the Clinical Evaluation of Lung Disorders: Current Status and Future Prospects.

Linyu Wu, Chen Gao, Ting Wu, Ning Kong, Ziwei Zhang, Jie Li, Li Fan, Maosheng Xu

Abstract readReview
In one paragraph

Review in Journal of magnetic resonance imaging : JMRI, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
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

8 authors.

Linyu WuDepartment of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.
Chen GaoDepartment of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.
Ting WuDepartment of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.
Ning KongDepartment of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.
Ziwei ZhangDepartment of Radiology, Second Affiliated Hospital of Naval Medical University, Shanghai, China.
Jie LiDepartment of Radiology, Second Affiliated Hospital of Naval Medical University, Shanghai, China.
Li FanDepartment of Radiology, Second Affiliated Hospital of Naval Medical University, Shanghai, China.ORCID https://orcid.org/0000-0003-4722-3933
Maosheng XuDepartment of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.ORCID https://orcid.org/0000-0002-2396-1600

Funding

Medical and health Science and Technology Project of Zhejiang Province 2022KY230Medical and health Science and Technology Project of Zhejiang Province 2024KY129Medical and health Science and Technology Project of Zhejiang Province 2024KY132National Natural Science Foundation of China 82102128"Pioneer" and "Leading Goose" R&D Program of Zhejiang 2022C03046Research Project of Zhejiang Chinese Medical University 2022FSYYZY08Zhejiang Provincial Natural Science Foundation of China LTGY23H180001Zhejiang Provincial Natural Science Foundation of China LTGY24H180006
6 · The paper itself

Abstract

The low proton density and high signal decay rate of pulmonary tissue have previously hampered the application of magnetic resonance imaging (MRI) in the clinical evaluation of lung disorders. With the continuing technical advances in scanners, coils, pulse sequences, and image postprocessing, pulmonary MRI can provide structural and functional information with faster imaging speed and improved image quality, which has shown potential to be an alternative and complementary diagnostic method to chest computed tomography (CT). Compared with CT, MRI does not involve ionizing radiation, making it particularly suitable for pediatric patients, pregnant women, and individuals requiring longitudinal monitoring. This narrative review focuses on recent advances in techniques and clinical applications for pulmonary MRI in lung diseases, including lung parenchymal and pulmonary vascular diseases. Future developments, including artificial intelligence-driven technological optimization and assisted diagnosis, hardware advancements, and clinical biomarkers validation, hold the potential to further enhance the clinical utility of pulmonary MRI. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

Indexed as

Lung DiseasesMagnetic Resonance ImagingFemaleHumansLungTomography, X-Ray Computedadvancementapplicationlung diseasesMRI

Identifiers

PMID40344610
PMCPMC12507151

What OpenQuestion holds

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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 OpenQuestion graph.