多参数美国用于识别代谢功能障碍相关的脂肪肝炎:一个前性的多中心研究
Fangyi Liu1, Mingsen Bi1, Xiang Jing1
1From the Department of Interventional Ultrasound, Fifth Medical Center, Chinese PLA General Hospital, No. 28 Fuxing Rd, Beijing 100853, China (F.L., M.B., Z.C., Z.H., J.Y., P.L.); Department of Ultrasound, Tianjin Third Central Hospital, Tianjin, China (X.J., H.Z.); Department of Ultrasound, Huashan Hospital, Fudan University, Shanghai, China (H.D.); Department of Medical Ultrasound, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China (J.Z., R.Z.); Department of Ultrasound in Medicine, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China (Y.C.); Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China (W.W.); Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China (X.X.); Department of Ultrasound, General Hospital of Ningxia Medical University, Yinchuan, China (C.M.); Department of Ultrasound Medicine, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China (M.C.); Department of Ultrasound, Harbin Medical University Cancer Hospital, Harbin, China (W.C.); Department of Ultrasound, North China University of Science and Technology Affiliated Hospital, Tangshan, China (S.Z.); Department of Pathology, First Medical Center, Chinese PLA General Hospital, Beijing, China (Z.W.); and Department of Ultrasound, The Second Affiliated Hospital of Nanchang University, Nanchang, China (C.Z.).
多参数超声波精确预测代谢功能障碍相关的脂肪肝炎 (MASH) 在患有脂肪肝疾病的患者. 使用衰减系数,ALT和INR的组合模型显示出良好的诊断性能.
科学领域:
- 肝病学 肝病学是一种肝病学.
- 医疗成像医学成像
- 诊断性超声波 超声波 超声波 超声波
背景情况:
- 与代谢功能障碍相关的脂肪肝疾病 (MAFLD) 的非侵入性评估至关重要.
- 对MAFLD评估的多参数超声波的多中心研究是有限的.
- 需要准确预测代谢功能障碍相关的脂肪肝炎 (MASH).
研究的目的:
- 评估多参数超声波,包括衰减成像 (ATI) 和2D剪切波弹性成像 (SWE).
- 评估这些技术在预测MAFLD患者MASH的能力.
- 为了确定诊断性能,无论乙型肝炎病毒感染状态如何.
主要方法:
- 对424名患有MAFLD的成年人进行前性,横截面,多中心研究.
- 进行了多参数超声波 (ATI和2D SWE) 和肝脏活检.
- 多变量逻辑回归和ROC曲线分析用于风险因素评估和诊断性能评估.
主要成果:
- 衰减系数 (AC),ALT和INR独立地与MASH相关.
- 一个组合模型 (AC,ALT,INR) 实现了MASH预测的AUC为0.85 (训练) 和0.77 (验证).
- 在糖尿病或乙型肝炎病毒感染的和没有糖尿病的子组中观察到良好的诊断性能.
结论:
- 一个结合了AC,ALT水平和INR的组合模型显示出在MAFLD患者中预测MASH的显著能力.
- 多参数超声波为MAFLD中MASH评估提供了一个有希望的非侵入性方法.
- 这项多中心研究为这种组合模型的临床实用性提供了强有力的证据.


