ArticleBMC medical imaging2026
Capability of multiparametric MRI to detect diabetic nephropathy in high-risk patients with type 2 diabetes: a prospective preliminary study.
Article in BMC medical 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.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
backgroundEarly diagnosis and treatment of diabetic nephropathy (DN) is important for improving prognosis of patients, but the noninvasive and reliable diagnostic tool is lacking. We aim to investigate the ability of multiparametric MRI for detecting early DN in high-risk patients with type 2 diabetes.
methodsBetween June 2023 and October 2024, we prospectively recruited 80 patients(diabetic patients group, n = 42, 53.4 ± 10.0 years old; DN patients group, n = 38, 47.9 ± 10.9 years old) and 16 healthy volunteers(control group, 49.5 ± 9.5 years old). All participants were examined using multiparametric MRI(IVIM, DKI, ASL and T1 mapping). The true diffusion coefficient(D), perfusion fraction(f), mean diffusivity(MD), mean kurtosis(MK), renal blood flow(RBF), T1 values in renal cortex were measured. Renal cortical MRI parameters among 3 groups were compared by one-way analysis of variance. Correlation between estimated glomerular filtration rate(eGFR), 24-hour urine albumin(24 h-UA) and renal cortical MRI parameters was evaluated using Spearman correlation analysis. The diagnostic performances of MRI parameters compared with biochemical indexes for detecting early DN were assessed using receiver operating characteristic curves.
resultsRenal cortical MRI parameters demonstrated statistically significant differences among 3 groups(P < 0.050). The eGFR, 24 h-UA significantly correlated with renal cortical MRI parameters(P < 0. 001). The areas under the curve(AUCs) for discriminating diabetic patients group from DN patients group were 0.706, 0.864, 0.732, 0.718, 0.910 and 0.718 for D, f, MD, MK, RBF and T1 values. AUCs of renal cortical f, RBF values were significantly larger than that of eGFR, serum creatinine, 24 h-UA, fasting blood glucose(P < 0.050).
conclusionsIntravoxel incoherent motion diffusion-weighted imaging and arterial spin labeling exhibited considerable promise as noninvasive tools for detecting DN in high-risk patients with type 2 diabetes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.