Department of Diagnostic and Interventional Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Zu Berlin, Berlin Institute of Health, Augustenburger Platz 1, 13353, Berlin, Germany.
Berlin Institute of Health (BIH), Anna-Louisa-Karsch-Straße 2, 10178, Berlin, Germany.
Sci Rep. 2021 May 24;11(1):10778. doi: 10.1038/s41598-021-90257-9.
The implementation of radiomics in radiology is gaining interest due to its wide range of applications. To develop a radiomics-based model for classifying the etiology of liver cirrhosis using gadoxetic acid-enhanced MRI, 248 patients with a known etiology of liver cirrhosis who underwent 306 gadoxetic acid-enhanced MRI examinations were included in the analysis. MRI examinations were classified into 6 groups according to the etiology of liver cirrhosis: alcoholic cirrhosis, viral hepatitis, cholestatic liver disease, nonalcoholic steatohepatitis (NASH), autoimmune hepatitis, and other. MRI examinations were randomized into training and testing subsets. Radiomics features were extracted from regions of interest segmented in the hepatobiliary phase images. The fivefold cross-validated models (2-dimensional-(2D) and 3-dimensional-(3D) based) differentiating cholestatic cirrhosis from noncholestatic etiologies had the best accuracy (87.5%, 85.6%), sensitivity (97.6%, 95.6%), predictive value (0.883, 0.877), and area under curve (AUC) (0.960, 0.910). The AUC was larger in the 2D-model for viral hepatitis, cholestatic cirrhosis, and NASH-associated cirrhosis (P-value of 0.05, 0.05, 0.87, respectively). In alcoholic cirrhosis, the AUC for the 3D model was larger (P = 0.01). The overall intra-class correlation coefficient (ICC) estimates and their 95% confident intervals (CI) for all features combined was 0.68 (CI 0.56-0.87) for 2D and 0.71 (CI 0.61-0.93) for 3D measurements suggesting moderate reliability. Radiomics-based analysis of hepatobiliary phase images of gadoxetic acid-enhanced MRI may be a promising noninvasive method for identifying the etiology of liver cirrhosis with better performance of the 2D- compared with the 3D-generated models.
基于钆塞酸增强 MRI 的放射组学模型对肝硬化病因学的分类：多中心研究。放射组学在放射学中的应用越来越受到关注，因为它的应用范围很广。为了开发一种基于放射组学的模型，用于使用钆塞酸增强 MRI 对肝硬化的病因进行分类，我们对 248 例已知肝硬化病因的患者进行了 306 次钆塞酸增强 MRI 检查，对这些患者进行了分析。根据肝硬化的病因，将 MRI 检查分为 6 组：酒精性肝硬化、病毒性肝炎、胆汁淤积性肝病、非酒精性脂肪性肝炎（NASH）、自身免疫性肝炎和其他。MRI 检查被随机分为训练和测试子集。从肝胆期图像的感兴趣区域中提取放射组学特征。五重交叉验证模型（基于 2 维和 3 维）在区分胆汁淤积性肝硬化与非胆汁淤积性病因方面具有最佳的准确性（87.5%，85.6%）、敏感性（97.6%，95.6%）、预测值（0.883，0.877）和曲线下面积（AUC）（0.960，0.910）。在病毒性肝炎、胆汁淤积性肝硬化和 NASH 相关性肝硬化中，2D 模型的 AUC 更大（P 值分别为 0.05、0.05、0.87）。在酒精性肝硬化中，3D 模型的 AUC 更大（P=0.01）。所有特征联合的总体组内相关系数（ICC）估计值及其 95%置信区间（CI）为 2D 为 0.68（CI 0.56-0.87），3D 为 0.71（CI 0.61-0.93），表明具有中度可靠性。基于钆塞酸增强 MRI 肝胆期图像的放射组学分析可能是一种很有前途的非侵入性方法，可用于识别肝硬化的病因，与 3D 生成的模型相比，2D 模型的性能更好。
