Evidence map›Paper›PMID 42279544›Full record

ReviewDiagnostics (Basel, Switzerland)2026

Multimodal Magnetic Resonance Imaging in Diabetic Kidney Disease: From Pathophysiological Insights to Clinical Applications.

Mengdan Ni, Bingcang Huang

Abstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 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

2 authors.

Mengdan NiPublic College of Medical Technology, University of Shanghai for Science and Technology, Shanghai 200093, China.
Bingcang HuangDepartment of Radiology, Gongli Hospital, Pudong, Shanghai 200135, China.ORCID 0000-0001-9792-5891

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiabetic kidney disease (DKD) is the leading cause of end-stage renal disease. Conventional clinical markers of renal function lack sufficient sensitivity for early diagnosis, whereas renal biopsy is unsuitable for routine monitoring because of its invasiveness.

objectiveThis narrative review aimed to evaluate recent advances in novel, non-invasive multimodal magnetic resonance imaging (MRI) biomarkers for the assessment of renal pathological alterations in DKD. RECENT

findingsRecent studies have demonstrated that multimodal MRI can non-invasively characterize several key pathological features of DKD, including renal hypoxia, microvascular dysfunction, ectopic fat deposition, and interstitial fibrosis. Furthermore, emerging evidence suggests that these imaging biomarkers may enhance risk stratification, monitor disease progression, and assess treatment efficacy, particularly in the presence of comorbidities and the advent of emerging therapies.

conclusionsMultimodal MRI shows considerable promise in translating advanced imaging biomarkers into clinical practice, facilitating the personalized management of DKD. However, future research must focus on establishing standardized imaging acquisition and analytical protocols, conducting prospective cohort studies to validate the association between imaging biomarkers and hard clinical endpoints, integrating artificial intelligence for automated analysis, and developing molecular imaging probes targeted at early disease pathways.

Indexed as

diabetes mellitusdiabetic kidney diseasemultimodal magnetic resonance imagingrenal dysfunctionrenal tissue characteristics

Identifiers

PMID42279544
PMCPMC13256882

What OpenQuestion holds

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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.