ArticleQuantitative imaging in medicine and surgery2024
Quantitative assessment of renal steatosis in patients with type 2 diabetes mellitus using the iterative decomposition of water and fat with echo asymmetry and least squares estimation quantification sequence imaging: repeatability and clinical implications.
Article in Quantitative imaging in medicine and surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Multimodal Magnetic Resonance Imaging in Diabetic Kidney Disease: From Pathophysiological Insights to Clinical Applications.Diagnostics (Basel, Switzerland) · 2026Review
- A comparison study to assess U-Net driven volumetric versus single-slice analysis and MRI sequences with different volume coverage to detect renal sinus fat in people with and without diabetes.Scientific reports · 2026Article
- Comparative effects of sevoflurane and desflurane on postoperative renal function in patients with type 2 Diabetes mellitus.Renal failure · 2025Article
- MASLD: Lipotoxicity and Imaging Parallels from Liver Steatosis to Kidney Injury.Life (Basel, Switzerland) · 2025Review
- Magnetic resonance imaging for noninvasive assessment of renal fat deposition and hypoxia in diabetic kidney disease.BMC medical imaging · 2025Article
- Renal ectopic fat deposition and hemodynamics in type 2 diabetes mellitus assessment with magnetic resonance imaging.Insights into imaging · 2025Article
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Abstract
Background: Fatty kidney disease is linked to renal function damage, but there is no noninvasive tool for monitoring renal fat accumulation. This study aimed to explore the repeatability of the iterative decomposition of water and fat with echo asymmetry and least squares estimation quantification (IDEAL-IQ) sequence imaging in quantifying renal fat deposition and to assess the differences observed in patients with type 2 diabetes mellitus (T2DM). Methods: A total of 26 healthy participants underwent two IDEAL-IQ scans without repositioning, and the repeatability of the imaging technique was assessed with Bland-Altman analysis. Additionally, 96 patients with T2DM underwent a single IDEAL-IQ scan for the examination of renal fat deposition. The patients with T2DM were classified into three groups based on their estimated glomerular filtration rate (eGFR). One-way analysis of variance was used to analyze the differences of renal fat depositions between the groups. Receiver operating characteristic curve analysis was used to assess the diagnostic performance of IDEAL-IQ. Results: Bland-Altman analyses showed narrower limits of agreement and a significant correlation (r=0.81; P<0.05) between the two IDEAL-IQ scans. Statistically significant differences between the healthy volunteers and patients with T2DM, diabetic kidney disease (DKD) I-II, and or DKD III-IV were found in renal parenchymal proton-density fat fraction (PDFF) values (P<0.001). Renal parenchymal PDFF was negatively correlated with eGFR (r=-0.437; P<0.001) and positive correlated with serum creatinine level (µmol/L) (r=0.421; P<0.001). The area under the curve of IDEAL-IQ in discriminating between the healthy volunteers and patients with T2DM was 0.857. For discriminating T2DM from DKD I-II and DKD III-IV, the IDEAL-IQ had an area under the curve of 0.689 and 0.823, respectively. Conclusions: IDEAL-IQ is a promising and reproducible technique for the assessment of renal fat deposition and identification of risk of DKD in patients with T2DM. Moreover, IDEAL-IQ imaging is expected to improve the sensitivity and specificity of early renal function damage and staging assessment of patients with T2DM.
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