Department of Radiology, National Clinical Research Center for Infectious Disease, Shenzhen Third People's Hospital, The Second Affiliated Hospital, School of Medicine Southern University of Science and Technology, 29 Bulan Road, Longgang District, Shenzhen, 518000, Guangdong, People's Republic of China.
Department of Pathology, National Clinical Research Center for Infectious Disease, Shenzhen Third People's Hospital, The Second Affiliated Hospital, School of Medicine Southern University of Science and Technology, 29 Bulan Road, Longgang District, Shenzhen, 518000, Guangdong, People's Republic of China.
Eur Radiol. 2023 Mar;33(3):1653-1667. doi: 10.1007/s00330-022-09137-z. Epub 2022 Sep 23.
To investigate the value of R2* mapping-based radiomics nomograms in staging liver fibrosis in patients with chronic hepatitis B.
Between January 2020 and December 2020, 151 patients with chronic hepatitis B were randomly divided into training (n = 103) and validation (n = 48) cohorts. From January to February 2021, 58 patients were included in a test cohort. Radiomics features were selected using the interclass correlation coefficient and least absolute shrinkage and selection operator method. Three radiomics nomograms, combining the radiomics score (Radscore) derived from R2* mapping and clinical variables, were used for staging significant and advanced fibrosis, and cirrhosis. Performance of the model was evaluated using the AUC. The utility and clinical benefits were evaluated using the continuous net reclassification index (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA).
The Radscore calculated by 12 radiomics features and independent factors (laminin and platelet) of advanced fibrosis were used to construct the radiomics nomograms. In the test cohort, the AUCs of the radiomics nomograms for staging significant fibrosis, advanced fibrosis, and cirrhosis were 0.738 (95% confidence interval [CI]: 0.604-0.872), 0.879 (95% CI: 0.779-0.98), and 0.952 (95% CI: 0.878-1), respectively. NRI, IDI, and DCA confirmed that radiomics nomograms demonstrated varying degrees of clinical benefit and improvement for advanced fibrosis and cirrhosis, but not for significant fibrosis.
Radiomics nomograms combined with R2* mapping-based Radscore, laminin, and platelet have value in staging advanced fibrosis and cirrhosis but limited value for staging significant fibrosis.
• Laminin and platelets were independent predictors of advanced fibrosis. • Radiomics analysis based on R2* mapping was beneficial for evaluating advanced fibrosis and cirrhosis. • It was difficult to distinguish significant fibrosis using a radiomics nomogram, which is possibly due to the complex pathological microenvironment of chronic liver diseases.
探讨 R2* 映射基放射组学列线图在慢性乙型肝炎患者肝纤维化分期中的价值。
2020 年 1 月至 12 月,将 151 例慢性乙型肝炎患者随机分为训练队列(n=103)和验证队列(n=48)。2021 年 1 月至 2 月,58 例患者纳入测试队列。采用组内相关系数和最小绝对值收缩和选择算子法选择放射组学特征。使用 R2* 映射衍生的放射组学评分(Radscore)和临床变量,构建三种放射组学列线图,用于分期显著和进展性纤维化以及肝硬化。采用 AUC 评估模型性能。采用连续净重新分类指数(NRI)、综合判别改善(IDI)和决策曲线分析(DCA)评估效用和临床获益。
基于 12 个放射组学特征和进展性纤维化的独立因素(层粘连蛋白和血小板)计算 Radscore,构建放射组学列线图。在测试队列中,放射组学列线图分期显著纤维化、进展性纤维化和肝硬化的 AUC 分别为 0.738(95%置信区间:0.604-0.872)、0.879(95%置信区间:0.779-0.98)和 0.952(95%置信区间:0.878-1)。NRI、IDI 和 DCA 证实,放射组学列线图在分期进展性纤维化和肝硬化方面具有不同程度的临床获益和改善,但在分期显著纤维化方面效果有限。
基于 R2* 映射的 Radscore、层粘连蛋白和血小板的放射组学列线图在分期进展性纤维化和肝硬化方面具有一定价值,但在分期显著纤维化方面价值有限。