Department of Radiology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Department of Nuclear Medicine, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Int J Med Sci. 2021 Sep 7;18(16):3624-3630. doi: 10.7150/ijms.64458. eCollection 2021.
Since non-invasive tests for prediction of liver fibrosis have a poor diagnostic performance for detecting low levels of fibrosis, it is important to explore the diagnostic capabilities of other non-invasive tests to diagnose low levels of fibrosis. We aimed to evaluate the performance of radiomics based on F-fluorodeoxyglucose (F-FDG) positron emission tomography (PET) in predicting any liver fibrosis in individuals with biopsy-proven metabolic dysfunction-associated fatty liver disease (MAFLD). A total of 22 adults with biopsy-confirmed MAFLD, who underwent F-FDG PET/CT, were enrolled in this study. Sixty radiomics features were extracted from whole liver region of interest in F-FDG PET images. Subsequently, the minimum redundancy maximum relevance (mRMR) method was performed and a subset of two features mostly related to the output classes and low redundancy between them were selected according to an event per variable of 5. Logistic regression, Support Vector Machine, Naive Bayes, 5-Nearest Neighbor and linear discriminant analysis models were built based on selected features. The predictive performances were assessed by the receiver operator characteristic (ROC) curve analysis. The mean (SD) age of the subjects was 38.5 (10.4) years and 17 subjects were men. 12 subjects had histological evidence of any liver fibrosis. The coarseness of neighborhood grey-level difference matrix (NGLDM) and long-run emphasis (LRE) of grey-level run length matrix (GLRLM) were selected to predict fibrosis. The logistic regression model performed best with an AUROC of 0.817 [95% confidence intervals, 0.595-0.947] for prediction of liver fibrosis. These preliminary data suggest that F-FDG PET radiomics may have clinical utility in assessing early liver fibrosis in MAFLD.
由于非侵入性的肝纤维化预测检测对于低水平纤维化的诊断性能不佳，因此探索其他非侵入性检测方法对于诊断低水平纤维化的诊断能力非常重要。我们旨在评估基于 F-氟脱氧葡萄糖（F-FDG）正电子发射断层扫描（PET）的放射组学在预测经活检证实的代谢相关脂肪性肝病（MAFLD）患者任何程度肝纤维化中的表现。
本研究共纳入 22 例经活检证实的 MAFLD 患者，他们均接受了 F-FDG PET/CT 检查。从 F-FDG PET 图像的全肝感兴趣区提取了 60 个放射组学特征。随后，采用最小冗余最大相关性（mRMR）方法，根据每个变量 5 个事件的原则，选择与输出类别最相关且冗余度低的两个特征子集。基于选定的特征构建了逻辑回归、支持向量机、朴素贝叶斯、5-最近邻和线性判别分析模型。采用受试者工作特征（ROC）曲线分析评估预测性能。
受试者的平均（标准差）年龄为 38.5（10.4）岁，其中 17 例为男性。12 例患者的组织学检查存在任何程度的肝纤维化。选择灰度共生矩阵（GLCM）的角二阶矩（ASM）和灰度游程长度矩阵（GLRLM）的长行程强调（LRE）来预测纤维化。逻辑回归模型的 AUROC 为 0.817[95%置信区间，0.595-0.947]，在预测肝纤维化方面表现最佳。
这些初步数据表明，F-FDG PET 放射组学可能在评估 MAFLD 患者早期肝纤维化方面具有临床应用价值。
