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超声样本熵成像:评估肝脂肪变性和纤维化的新方法。

Ultrasound Sample Entropy Imaging: A New Approach for Evaluating Hepatic Steatosis and Fibrosis.

机构信息

Department of Medical Imaging and Radiological SciencesCollege of Medicine, Chang Gung University Taoyuan 333323 Taiwan.

Department of Biomedical EngineeringFaculty of Environment and LifeBeijing University of Technology Beijing 100124 China.

出版信息

IEEE J Transl Eng Health Med. 2021 Nov 2;9:1800612. doi: 10.1109/JTEHM.2021.3124937. eCollection 2021.

Abstract

Hepatic steatosis causes nonalcoholic fatty liver disease and may progress to fibrosis. Ultrasound is the first-line approach to examining hepatic steatosis. Fatty droplets in the liver parenchyma alter ultrasound radiofrequency (RF) signal statistical properties. This study proposes using sample entropy, a measure of irregularity in time-series data determined by the dimension [Formula: see text] and tolerance [Formula: see text], for ultrasound parametric imaging of hepatic steatosis and fibrosis. Liver donors and patients were enrolled, and their hepatic fat fraction (HFF) ([Formula: see text]), steatosis grade ([Formula: see text]), and fibrosis score ([Formula: see text]) were measured to verify the results of sample entropy imaging using sliding-window processing of ultrasound RF data. The sample entropy calculated using [Formula: see text] 4 and [Formula: see text] was highly correlated with the HFF when a small window with a side length of one pulse was used. The areas under the receiver operating characteristic curve for detecting hepatic steatosis that was [Formula: see text]mild, [Formula: see text]moderate, and [Formula: see text]severe were 0.86, 0.90, and 0.88, respectively, and the area was 0.87 for detecting liver fibrosis in individuals with significant steatosis. Ultrasound sample entropy imaging enables the identification of time-series patterns in RF signals received from the liver. The algorithmic scheme proposed in this study is compatible with general ultrasound pulse-echo systems, allowing clinical fibrosis risk evaluations of individuals with developing hepatic steatosis.

摘要

肝脂肪变性导致非酒精性脂肪性肝病,并可能进展为纤维化。超声是检查肝脂肪变性的首选方法。肝实质内的脂肪滴改变了超声射频 (RF) 信号的统计特性。本研究提出使用样本熵,一种由维度 [公式:见文本] 和公差 [公式:见文本] 确定的时间序列数据不规则性的度量,用于超声参数成像肝脂肪变性和纤维化。 招募了肝供体和患者,并测量了他们的肝脂肪分数 (HFF) ([公式:见文本])、脂肪变性程度 ([公式:见文本]) 和纤维化评分 ([公式:见文本]),以验证使用超声 RF 数据滑动窗口处理的样本熵成像结果。 使用 [公式:见文本] 4 和 [公式:见文本] 计算的样本熵与 HFF 高度相关,当使用边长为一个脉冲的小窗口时。用于检测 [公式:见文本] 轻度、[公式:见文本] 中度和 [公式:见文本] 重度肝脂肪变性的受试者工作特征曲线下面积分别为 0.86、0.90 和 0.88,用于检测有明显脂肪变性个体的肝纤维化的面积为 0.87。 超声样本熵成像能够识别从肝脏接收到的 RF 信号中的时间序列模式。本研究提出的算法方案与通用超声脉冲回波系统兼容,允许对发生肝脂肪变性的个体进行临床纤维化风险评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b4b/8580366/566267a9f098/tsui1-3124937.jpg

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