ArticleCardiovascular and interventional radiology2025
MRI-Based Radiomics to Predict Renal Function Response to Renal Artery Stenting for Atherosclerotic Renal Artery Stenosis.
Article in Cardiovascular and interventional radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo investigate magnetic resonance imaging (MRI)-based radiomics for predicting renal function response for patients treated for atherosclerotic renal artery stenosis (ARAS) by endoluminal means. MATERIAL AND
methodsA cohort of 146 ARAS patients who underwent stenting was analyzed, with retrospective training and prospective validation groups delineated based on the treatment timing. Patients were categorized into benefit and no-benefit groups based on postoperative renal function during follow-up. Optimal radiomics labels were selected from regions of interest (ROIs) including the stenotic side and both kidneys. The nomogram combined optimal radiomics signatures with independent clinical factors using multivariable logistic regression. Shapley Additive exPlanations (SHAP), decision curve analysis (DCA), the net reclassification index (NRI), and the total integrated discrimination index (IDI) were conducted to determine the clinical usefulness of the nomogram.
resultsSplit renal function of the stenotic side and diabetes emerged as independent clinical predictors. A nomogram, incorporating these clinical factors and radiomics features from the stenotic side and both kidneys, achieved area under the curve (AUCs) of 0.927 (0.861-0.979) and 0.904 (0.819-0.972) in the training and test groups, respectively, for predicting benefits. The clinical-radiomics model significantly improved diagnostic performance (p = 0.001 and p = 0.011 for the training and test groups, respectively). DCA, NRI, and IDI analyses suggested the nomogram's superiority. SHAP analysis highlighted the radiomics feature from stenotic side kidney as the most critical predictive feature.
conclusionsBoth MRI radiomics and clinical factors may be valuable in pre-treatment counseling of ARAS patients who may benefit from endovascular treatment.
Indexed as
Identifiers
40355764What 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.