Evidence map›Paper›PMID 42824823›Full record

ArticleRadiology advances2026

Virtual MR elastography with diffusion-weighted imaging to evaluate chronic kidney disease fibrosis and dysfunction.

Ruirui Qi, Junfeng Li, Wenxi Liu, Peiyin Luo, Qiuyi Chen, Qiumei Liang, Fanqi Meng, Jinhua Qin, Feifei Qu, Haodong Qin and 5 more

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In one paragraph

Article in Radiology advances, 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
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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

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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

15 authors.

Ruirui QiDepartment of Radiology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine (Shenzhen Traditional Chinese Medicine Hospital), Shenzhen, Guangdong 518033, China.
Junfeng LiDepartment of Radiology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine (Shenzhen Traditional Chinese Medicine Hospital), Shenzhen, Guangdong 518033, China.
Wenxi LiuMedical AI Lab, School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, Guangdong 518055, China.
Peiyin LuoDepartment of Radiology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine (Shenzhen Traditional Chinese Medicine Hospital), Shenzhen, Guangdong 518033, China.
Qiuyi ChenDepartment of Radiology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine (Shenzhen Traditional Chinese Medicine Hospital), Shenzhen, Guangdong 518033, China.
Qiumei LiangDepartment of Radiology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine (Shenzhen Traditional Chinese Medicine Hospital), Shenzhen, Guangdong 518033, China.
Fanqi MengDepartment of Radiology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine (Shenzhen Traditional Chinese Medicine Hospital), Shenzhen, Guangdong 518033, China.
Jinhua QinDepartment of Radiology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine (Shenzhen Traditional Chinese Medicine Hospital), Shenzhen, Guangdong 518033, China.
Feifei QuMR Research Collaboration, Siemens Healthineers, Shanghai 200126, China.
Haodong QinMR Research Collaboration, Siemens Healthineers, Shanghai 200126, China.
Yanglei WuDepartment of Radiology, Charité-Universitätsmedizin Berlin, Berlin 10117, Germany.
Hanqing LyuDepartment of Radiology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine (Shenzhen Traditional Chinese Medicine Hospital), Shenzhen, Guangdong 518033, China.
Bingsheng HuangMedical AI Lab, School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen, Guangdong 518055, China.ORCID https://orcid.org/0000-0002-1183-7506
Youjia ZengDepartment of Nephrology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine (Shenzhen Traditional Chinese Medicine Hospital), Shenzhen, Guangdong 518033, China.
Yueyao ChenDepartment of Radiology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine (Shenzhen Traditional Chinese Medicine Hospital), Shenzhen, Guangdong 518033, China.ORCID https://orcid.org/0000-0002-6225-3359

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Renal stiffness declines with chronic kidney disease (CKD) progression. Magnetic resonance elastography (MRE) enables quantitative assessment of tissue stiffness but requires external hardware, limiting routine clinical use. Purpose: To develop a diffusion-derived virtual shear modulus (µ Materials and Methods: This prospective single-center study included 53 healthy volunteers and 114 CKD patients, stratified by estimated glomerular filtration rate (eGFR) into early-stage CKD (CKD Results: A significant correlation ( Conclusion: Diffusion-weighted imaging-derived µ

Indexed as

chronic kidney diseasediffusion-weighted imagingMR elastographystiffnessvirtual MR elastography

Identifiers

PMID42824823
PMCPMC13629548

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