Evidence map›Paper›PMID 42633028›Full record

ReviewClinical kidney journal2026

Integrating kidney imaging for risk prediction, therapeutic monitoring, and prognostication across the kidney disease spectrum: a review of emerging evidence.

Mustafa Guldan, Ibrahim Gulmaliyev, Rama AlShiab, Ermeena Shah, Lasin Ozbek, Mahmut Altindal, Bengi Gurses, Magdalena Madero, Alberto Ortiz, Adrian Covic and 1 more

Abstract readReview
In one paragraph

Review in Clinical kidney journal, 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

11 authors.

Mustafa GuldanDepartment of Medicine, Koc University School of Medicine, Istanbul, Turkiye.
Ibrahim GulmaliyevDepartment of Medicine, Koc University School of Medicine, Istanbul, Turkiye.
Rama AlShiabDepartment of Medicine, Koc University School of Medicine, Istanbul, Turkiye.
Ermeena ShahDepartment of Medicine, Koc University School of Medicine, Istanbul, Turkiye.
Lasin OzbekDepartment of Medicine, Koc University School of Medicine, Istanbul, Turkiye.
Mahmut AltindalDepartment of Internal Medicine, Division of Nephrology, Koc University School of Medicine, Istanbul, Turkiye.
Bengi GursesDepartment of Radiology, Koc University School of Medicine, Istanbul, Turkiye.
Magdalena MaderoDepartment of Nephrology, Instituto Nacional de Cardiología Ignacio Chavez, Mexico City, Mexico.
Alberto OrtizDepartment of Medicine, Universidad Autonoma de Madrid and IIS-Fundacion Jimenez Diaz, Madrid, Spain.ORCID https://orcid.org/0000-0002-9805-9523
Adrian CovicNephrology Clinic, Dialysis and Renal Transplant Center, "C.I. Parhon" University Hospital and "Grigore T. Popa" University of Medicine, Iasi, Romania.
Mehmet KanbayDepartment of Internal Medicine, Division of Nephrology, Koc University School of Medicine, Istanbul, Turkiye.ORCID https://orcid.org/0000-0002-1297-0675

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Kidney imaging advances are transforming the field of nephrology by allowing non-invasive examination of renal structure, function, and pathology. Traditional measures such as albuminuria and estimated glomerular filtration rate (eGFR) are only partially effective in identifying early or regionally variable kidney damage. As an example, imaging identifies chronic kidney disease (CKD) in autosomal dominant polycystic kidney disease (ADPKD) decades earlier than eGFR or albuminuria, addressing the "blind spot" in CKD, and providing a criterion to start early therapy. Currently, quantitative imaging techniques such as advanced ultrasound (Doppler sonography, photoacoustic imaging [PAI], contrast-enhanced ultrasound [CEUS], and ultrasound-based elastography), multiparametric MRI, and some CT methods provide insights into fibrosis, lipid infiltration, oxygenation, and microvascular integrity. Imaging biomarkers, including cortical

Indexed as

artificial intelligencechronic kidney diseasediabetic kidney diseasekidney transplantationmultiparametric MRIradiomicsrenal fibrosisrenal imagingrisk predictiontherapeutic monitoringultrasound elastography

Identifiers

PMID42633028
PMCPMC13498872

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.