ArticleCureus2024
An Evaluation of Renal Sinus Fat Accumulation Using the Anteroposterior Diameter of the Renal Sinus on a Computed Tomography Axial Image.
Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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.
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Who cites it
3 citing papers in PubMed.
- Integrating kidney imaging for risk prediction, therapeutic monitoring, and prognostication across the kidney disease spectrum: a review of emerging evidence.Clinical kidney journal · 2026Review
- CT-based renal and body-composition radiomics model to improve the detection ability of diabetic kidney disease in patients with type 2 diabetes mellitus.Frontiers in endocrinology · 2026Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Backgrounds and objectives Renal sinus fat (RSF) is an indicator of obesity-related complications. However, the measurement and imaging process are complicated. For a simple measurement of RSF, we focused on the kidney's shape change caused by RSF accumulation. Thus, this study aimed to investigate whether the anteroposterior diameter of the renal sinus (APDRS) on a computed tomography (CT) axial image is useful for evaluating RSF accumulation. Materials and methods The correlation between APDRS and RSF was investigated in 98 outpatients who underwent abdominal CT. In addition, the correlation between APDRS or RSF and obesity indicators (estimated glomerular filtration rate from serum creatinine levels (eGFRcreat), body mass index (BMI), and visceral adipose tissue (VAT)) was also investigated. We classified patients based on the presence or absence of at least one underlying disease (chronic kidney disease (CKD), cardiovascular diseases (CVD), hypertension, and type 2 diabetes (T2D)) and investigated significant differences between the two groups at APDRS and RSF. The intraclass correlation coefficient (ICC) was also calculated for APDRS. Results There was a strong positive correlation between RSF and APDRS (r = 0.802, P < 0.01). The obesity indicators (eGFRcreat, BMI, and VAT) were correlated with RSF and APDRS (P < 0.01). Out of 98 outpatients, 48 had at least one underlying disease. There were statistically significant differences in APDRS and RSF between the patients with and without at least one of the underlying diseases caused by obesity (P < 0.01). The inter-reader ICC for the measurement of the APDRS was 0.98. Conclusions APDRS on a CT axial image may be useful for the evaluation of RSF accumulation.
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