ArticleScientific reports2022
The utility of texture analysis of kidney MRI for evaluating renal dysfunction with multiclass classification model.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Texture Analysis of Multiparametric Kidney MRI-A Non-Invasive Approach to Chronic Kidney Disease State.Biomedicines · 2026Article
- Kidney MRI Texture Analysis-A Universal Assessment of Kidney State and Function?Journal of clinical medicine · 2026Article
- Insight into Kidney Function and Microstructure Through Renal MRI-Review of the Literature.Bioengineering (Basel, Switzerland) · 2026Review
- The role of texture analysis of T1 weighted images in diagnosis of chronic kidney disease.Scientific reports · 2026Article
- Using magnetic resonance imaging-based subregional texture analysis models to classify knee osteoarthritis severity by compartment.Scientific reports · 2025Article
- Texture Analysis of T2-Weighted Images as Reliable Biomarker of Chronic Kidney Disease Microstructural State.Biomedicines · 2025Article
- Multi-parametric MRI-based machine learning model for prediction of pathological grade of renal injury in a rat kidney cold ischemia-reperfusion injury model.BMC medical imaging · 2024Article
- Three-dimensional convolutional neural network-based classification of chronic kidney disease severity using kidney MRI.Scientific reports · 2024Article
- The utility of automatic segmentation of kidney MRI in chronic kidney disease using a 3D convolutional neural network.Scientific reports · 2023Article
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Authors and funding
10 authors.
Funding
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Abstract
We evaluated a multiclass classification model to predict estimated glomerular filtration rate (eGFR) groups in chronic kidney disease (CKD) patients using magnetic resonance imaging (MRI) texture analysis (TA). We identified 166 CKD patients who underwent MRI comprising Dixon-based T1-weighted in-phase (IP)/opposed-phase (OP)/water-only (WO) images, apparent diffusion coefficient (ADC) maps, and T2* maps. The patients were divided into severe, moderate, and control groups based on eGFR borderlines of 30 and 60 mL/min/1.73 m
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