ArticleQuantitative imaging in medicine and surgery2021
Texture analysis based on quantitative magnetic resonance imaging to assess kidney function: a preliminary study.
Article in Quantitative imaging in medicine and surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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
12 citing papers in PubMed, 16 citations in OpenAlex.
- 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
- Associations between CT radiomics analyses and kidney biopsy in patients with kidney disease.BMC nephrology · 2026Article
- Insight into Kidney Function and Microstructure Through Renal MRI-Review of the Literature.Bioengineering (Basel, Switzerland) · 2026Review
- Dual-center validation of a multi-sequence MRI radiomics nomogram for noninvasive assessment of renal fibrosis in chronic kidney disease.BMC medical imaging · 2026Article
- Article
- The role of texture analysis of T1 weighted images in diagnosis of chronic kidney disease.Scientific reports · 2026Article
- Histopathological correlations of CT-based radiomics imaging biomarkers in native kidney biopsy.BMC medical imaging · 2024Article
- AI-based segmentation of renal enhanced CT images for quantitative evaluate of chronic kidney disease.Scientific reports · 2024Article
- Three-dimensional convolutional neural network-based classification of chronic kidney disease severity using kidney MRI.Scientific reports · 2024Article
- Clinical study on the use of advanced magnetic resonance imaging in lupus nephritis.BMC medical imaging · 2022Article
- The utility of texture analysis of kidney MRI for evaluating renal dysfunction with multiclass classification model.Scientific reports · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMagnetic resonance imaging (MRI) has demonstrated its potential in the evaluation of renal function. Texture analysis (TA) is a novel technique to quantify tissue heterogeneity. We aim to investigate the feasibility of using TA based on the apparent diffusion coefficient (ADC), as well as T1 and T2 maps to evaluate renal function.
methodsPatients with impaired renal function and subjects with a normal renal function who underwent renal diffusion weighted imaging (DWI), as well as T1 and T2 mapping at 3T, were prospectively enrolled. The participants were classified into four groups according to the estimated glomerular filtration rate (eGFR, mL/min/1.73 m
resultsIn total, 116 candidates were included (94 patients and 22 healthy volunteers, mean age 37.9±14.9 years). There were 46 participants in the normal renal function group, 14 in the mildly impaired renal function group, 27 in the moderately impaired renal function group, and 29 in the severely impaired renal function group. Texture features from the ADC and T1 maps exhibited a good correlation to eGFR. The AUC, sensitivity, specificity, PPV, and NPV to differentiate between the normal and impaired renal function groups were 0.835, 0.792, 0.867, 0.905, and 0.722, respectively; to differentiate between the mildly impaired and moderately impaired groups were 0.937, 0.889, 0.857, 0.923, and 0.800, respectively; and to differentiate between the moderately impaired and severely impaired groups was 0.940, 0.759, 0.889, 0.880, and 0.774, respectively.
conclusionsTA based on ADC and T1 maps is feasible for evaluating renal function with relatively good accuracy.
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.