Conventional and artificial intelligence-based computed tomography and magnetic resonance imaging quantitative techniques for non-invasive liver fibrosis staging

被引：5

作者：

Zheng, Shuang ^{[1
]}

He, Kan ^{[1
]}

Zhang, Lei ^{[1
]}

Li, Mingyang ^{[1
]}

Zhang, Huimao ^{[1
]}

Gao, Pujun ^{[2
]}

机构：

[1] First Hosp Jilin Univ, Dept Radiol, 71 Xinmin St, Changchun, Jilin, Peoples R China

[2] First Hosp Jilin Univ, Dept Hepatol, 71 Xinmin St, Changchun, Jilin, Peoples R China

来源：

EUROPEAN JOURNAL OF RADIOLOGY | 2023年 / 165卷

关键词：

Artificial intelligence; Chronic liver disease; Liver fibrosis staging; CT; MRI; SURFACE NODULARITY QUANTIFICATION; HEPATIC PERFUSION PARAMETERS; CONTRAST-ENHANCED CT; MR ELASTOGRAPHY; VIRTUAL ELASTOGRAPHY; DIFFUSION; DIAGNOSIS; CIRRHOSIS; BIOMARKER; SEVERITY;

D O I：

10.1016/j.ejrad.2023.110912

中图分类号：

R8 [特种医学]; R445 [影像诊断学];

学科分类号：

1002 ; 100207 ; 1009 ;

摘要：

Chronic liver disease (CLD) ultimately develops into liver fibrosis and cirrhosis and is a major public health problem globally. The assessment of liver fibrosis is important for patients with CLD for prognostication, treatment decisions, and surveillance. Liver biopsies are traditionally performed to determine the stage of liver fibrosis. However, the risks of complications and technical limitations restrict their application to screening and sequential monitoring in clinical practice. CT and MRI are essential for evaluating cirrhosis-associated complications in patients with CLD, and several non-invasive methods based on them have been proposed. Artificial intelligence (AI) techniques have also been applied to stage liver fibrosis. This review aimed to explore the values of conventional and AI-based CT and MRI quantitative techniques for non-invasive liver fibrosis staging and summarized their diagnostic performance, advantages, and limitations.

引用

页数：11

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