Evidence map›Paper›PMID 40123968›Full record

ArticleClinical kidney journal2025

T1 mapping magnetic resonance imaging predicts decline of kidney function.

Aurélie Huber, Ibtisam Aslam, Lindsey Crowe, Menno Pruijm, Thomas de Perrot, Sophie de Seigneux, Jean-Paul Vallée, Lena Berchtold

Abstract read
In one paragraph

Article in Clinical kidney journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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  3. Review
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  5. Navigator-gated free-breathing joint TMagma (New York, N.Y.) · 2026
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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.

Aurélie HuberDepartment of Medicine, Division of Nephrology and Hypertension, University Hospitals of Geneva, Geneva, Switzerland.ORCID https://orcid.org/0009-0005-6640-1012
Ibtisam AslamDepartment of Diagnostics, Division of Radiology, University Hospitals of Geneva and Faculty of Medicine of the Geneva University, Geneva, Switzerland.
Lindsey CroweDepartment of Diagnostics, Division of Radiology, University Hospitals of Geneva and Faculty of Medicine of the Geneva University, Geneva, Switzerland.
Menno PruijmDepartment of Medicine, Division of Nephrology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.ORCID https://orcid.org/0000-0003-1027-1851
Thomas de PerrotDepartment of Diagnostics, Division of Radiology, University Hospitals of Geneva and Faculty of Medicine of the Geneva University, Geneva, Switzerland.
Sophie de SeigneuxDepartment of Medicine, Division of Nephrology and Hypertension, University Hospitals of Geneva, Geneva, Switzerland.
Jean-Paul ValléeDepartment of Diagnostics, Division of Radiology, University Hospitals of Geneva and Faculty of Medicine of the Geneva University, Geneva, Switzerland.ORCID https://orcid.org/0000-0001-7546-2013
Lena BerchtoldDepartment of Medicine, Division of Nephrology and Hypertension, University Hospitals of Geneva, Geneva, Switzerland.ORCID https://orcid.org/0000-0001-8815-4263

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Renal cortical interstitial fibrosis, typically assessed by biopsy, is crucial for kidney function prognosis. Magnetic resonance imaging (MRI) is a promising method to assess fibrosis non-invasively. Diffusion-weighted (DW) MRI correlates with renal fibrosis and predicts kidney function decline in chronic kidney disease (CKD) and kidney allograft patients. This study evaluates whether T1 and T2 mapping predict kidney function decline and if their simultaneous use enhances the predictive power of a DW-MRI-based model. Methods: We prospectively included 197 patients (42 CKD, 155 allograft kidneys). Each underwent a biopsy followed by multiparametric MRI without contrast within 1 week. Over a median follow-up of 2.2 years, laboratory parameters were recorded. The primary endpoint was a rapid decline in kidney function [glomerular filtration rate (GFR) reduction >30%] or replacement therapy initiation. The ability of T1 and T2 mapping sequences to predict poor renal outcome was examined using multivariable Cox regression models, incorporating MRI-derived parameters, estimated GFR (eGFR) and proteinuria. Results: Renal outcome occurred in 54 patients after a median of 1.1 years (interquartile range 0.9-2.1). Univariable survival analysis showed cortical T1 was associated with poor renal outcome {hazard ratio [HR] 3.02 [95% confidence interval (CI) 1.44-6.33]}, while T2 sequences had no significant predictive value. Adding cortical T1 to the established model (ΔADC, eGFR, proteinuria) did not improve the HR [from 4.62 (95% CI 1.56-13.67) to 4.36 (95% CI 1.46-13.02)] and marginally increased Harrell's C-index (0.77 to 0.79). Adjusting the regression model for ΔT2 yielded no enhancement in predictive power. Conclusions: Cortical T1 is strongly associated with poor renal outcome but did not enhance prognostic power of the DW-MRI-based model.

Indexed as

chronic kidney diseasemagnetic resonance imagingpredictionrenal fibrosisrenal function decline

Identifiers

PMID40123968
PMCPMC11926595

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