Department of Interventional Ultrasound, Fifth Medical Center of Chinese PLA General Hospital, Beijing, China.
Department of Ultrasound, Huashan Hospital, Fudan University, Shanghai, China.
Hepatology. 2024 Feb 1;79(2):438-450. doi: 10.1097/HEP.0000000000000566. Epub 2023 Aug 22.
To evaluate the diagnostic performance of dual elastography (dual-elasto) in continuous differentiation of liver fibrosis and inflammation in a large prospective cohort of patients with chronic HBV.
Adults with positive HBsAg for at least 6 months were recruited from 12 medical centers. Participants underwent dual-elasto evaluations. Biopsy was performed 3 days after dual-elasto examination. Four logistic regression models were trained and strung together into series models. Decision trees based on the series models were performed to achieve continuous differentiation of liver fibrosis and inflammation. The influence of inflammation on the fibrosis stage was also evaluated. A total of 560 patients were included in the training set and 240 in the validation set. Areas under the receiver operating characteristic curve of the series model were 0.82, 0.86, 0.93, and 0.96 to predict ≥F1, ≥F2, ≥F3, and F4 in the validation set, which were significantly higher than those of serum markers and shear wave elastography (all p < 0.05), except for the ≥ F1 levels ( p = 0.09). The AUCs of the series model were 0.93, 0.86, 0.95, and 0.84 to predict inflammation stages ≥G1, ≥G2, ≥G3, and G4, respectively. Decision trees realized 5 continuous classifications of fibrosis and inflammation. Inflammation could enhance the mild fibrosis stage classification while showing limited influences on severe fibrosis or cirrhosis diagnosis.
Dual-elasto demonstrated high performance in the continuous discrimination of fibrosis and inflammation in patients with HBV and could be used to diagnose mild fibrosis without the influence of inflammation.
评估双弹性成像(dual-elasto)在慢性乙型肝炎患者的大型前瞻性队列中连续区分肝纤维化和炎症的诊断性能。
从 12 个医疗中心招募了 HBsAg 阳性至少 6 个月的成年人。参与者接受了双弹性评估。双弹性检查后 3 天进行活检。建立了 4 个逻辑回归模型,并串联成系列模型。基于系列模型的决策树用于实现肝纤维化和炎症的连续区分。还评估了炎症对纤维化分期的影响。共有 560 名患者纳入训练集,240 名患者纳入验证集。系列模型在验证集中预测≥F1、≥F2、≥F3 和 F4 的受试者工作特征曲线下面积分别为 0.82、0.86、0.93 和 0.96,显著高于血清标志物和剪切波弹性成像(均 p<0.05),除≥F1 水平(p=0.09)外。系列模型预测炎症≥G1、≥G2、≥G3 和 G4 的 AUC 分别为 0.93、0.86、0.95 和 0.84。决策树实现了纤维化和炎症的 5 个连续分类。炎症可以增强轻度纤维化分期的分类,而对严重纤维化或肝硬化的诊断影响有限。
dual-elasto 在乙型肝炎患者中连续区分纤维化和炎症具有较高的性能,可用于诊断无炎症影响的轻度纤维化。