利用回声不对称和最小二乘估计量化序列成像迭代分解水和脂肪,定量评估 2 型糖尿病患者的肾脏脂肪变性:可重复性和临床意义。

IF 2.9 2区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Quantitative Imaging in Medicine and Surgery Pub Date : 2024-10-01 Epub Date: 2024-09-23 DOI:10.21037/qims-24-330
Jian Liu, Yu Wu, Chong Tian, Xunlan Zhang, Zhijie Su, Lisha Nie, Rongpin Wang, Xianchun Zeng
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引用次数: 0

摘要

背景:脂肪性肾病与肾功能损害有关,但目前还没有监测肾脏脂肪堆积的无创工具。本研究旨在探索水和脂肪迭代分解与回波不对称和最小二乘估计量化(IDEAL-IQ)序列成像在量化肾脏脂肪沉积方面的可重复性,并评估在 2 型糖尿病(T2DM)患者中观察到的差异:共有 26 名健康参与者接受了两次 IDEAL-IQ 扫描,扫描过程中未进行重新定位,并通过 Bland-Altman 分析评估了成像技术的可重复性。此外,96 名 T2DM 患者接受了一次 IDEAL-IQ 扫描,以检查肾脏脂肪沉积情况。根据估计肾小球滤过率(eGFR)将 T2DM 患者分为三组。采用单因素方差分析来分析组间肾脏脂肪沉积的差异。采用接收者操作特征曲线分析评估 IDEAL-IQ 的诊断性能:结果:布兰-阿尔特曼分析表明一致性范围较窄,相关性显著(r=0.81;PC结论:IDEAL-IQ是一种很有前途的诊断方法:IDEAL-IQ 是评估 T2DM 患者肾脏脂肪沉积和识别 DKD 风险的一种有前途且可重复的技术。此外,IDEAL-IQ 成像有望提高 T2DM 患者早期肾功能损伤和分期评估的灵敏度和特异性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.

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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来源期刊
Quantitative Imaging in Medicine and Surgery
Quantitative Imaging in Medicine and Surgery Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
4.20
自引率
17.90%
发文量
252
期刊介绍: Information not localized
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