肝脏 ›› 2025, Vol. 30 ›› Issue (8): 1071-1075.

• 肝纤维化及肝硬化 • 上一篇    下一篇

剪切波弹性成像与门静脉血流动力学预测乙型肝炎肝硬化患者胃底静脉曲张破裂风险的临床评价

李锋, 牛娜, 吴英   

  1. 215000 江苏 苏州市中西医结合医院超声科
  • 收稿日期:2024-09-20 发布日期:2025-09-19
  • 通讯作者: 吴英,Email:59690396@qq.com
  • 基金资助:
    江苏省卫生健康委科研项目(LKM2022044)

Predicting the risk of gastric variceal rupture in patients with hepatitis B-related cirrhosis by shear wave elastography and portal venous hemodynamics

LI Feng, NIU Na, WU Ying   

  1. Department of Ultrasound,Suzhou Integrated Traditional Chinese and Western Medicine Hospital, Suzhou 215000, China
  • Received:2024-09-20 Published:2025-09-19
  • Contact: WU Ying, Email:59690396@qq.com

摘要: 目的 探讨剪切波弹性成像(SWE)技术与门静脉血流动力学参数在预测乙型肝炎相关肝硬化患者胃底静脉曲张(GV)破裂风险中的应用价值。 方法 选取2021年8月至2024年5月苏州市中西医结合医院收治的81例HBV相关肝硬化患者作为研究对象,根据日本门静脉高压症研究会的分类系统评估其GV破裂的风险,分为高风险组(n=18)和低风险组(n=63)。所有患者均进行彩色多普勒超声及SWE检查,评估Child-Pugh肝功能分级、门静脉血流参数和脾脏弹性。分析Child-Pugh肝功能分级与门静脉血流参数、脾脏弹性的相关性。通过ROC曲线评估各指标及其联合的预测效能。 结果 高风险组Child-Pugh A级为3例(16.67%),Child-Pugh B级为8例(44.44%),Child-Pugh C级为7例(38.89%);低风险组Child-Pugh A级为37例(58.73%),Child-Pugh B级为20例(31.75%),Child-Pugh C级为6例(9.52%),两组患者的Child-Pugh肝功能分级比较差异有统计学意义(χ2=13.190,P<0.05)。高风险组患者的门静脉内径(PVD)为(1.62±0.09)cm、门静脉流量(PVQ)为(1424.83±186.37)mL/min、脾脏指数(SI)为(77.29±8.12)cm2,脾脏弹性硬度值为(16.36±3.18)kPa,均高于低风险组,分别为(1.41±0.07)cm、(1320.95±171.19)mL/min、(71.58±7.03)cm2和(12.22±2.27)kPa;同时,高风险组的门静脉流速(PVV)为(10.49±1.37)cm/s,低于低风险组的(13.84±1.52)cm/s(P<0.05)。采用Spearman相关性分析发现Child-Pugh肝功能分级与PVD、PVQ、SI、脾脏弹性硬度值存在正相关(r=0.303、0.302、0.361、0.464;均P<0.05),与PVV存在负相关(r=-0.311;P<0.05)。ROC曲线表明,SWE联合门静脉血流参数在预测GV破裂方面具有较高的临床价值,AUC值为0.974,灵敏度为94.4%,特异度为98.4%。 结论 SWE与门静脉血流动力学参数能有效预测HBV相关肝硬化患者GV破裂的风险,可作为临床评估该患者群体破裂风险的重要工具。

关键词: 剪切波弹性成像, 门静脉血流动力学, 乙型肝炎, 肝硬化, 胃底静脉曲张, 风险预测

Abstract: Objective To investigate the application value of shear wave elastography (SWE) technology and portal vein hemodynamic parameters for predicting the risk of gastric varices (GV) rupture in patients with hepatitis B virus (HBV)-related cirrhosis. Methods A total of 81 patients with HBV-related cirrhosis admitted to Suzhou Hospital of Traditional Chinese and Western Medicine from August 2021 to May 2024 were selected as study subjects. Based on the classification system of the Japan Society for Portal Hypertension, patients were categorized into a high-risk group (n=18) and a low-risk group (n=63) according to their risk of GV rupture. All participants underwent color Doppler ultrasound and SWE to assess Child-Pugh classification, portal venous hemodynamics [portal vein diameter (PVD), portal venous flow volume (PVQ), splenic index (SI), portal venous velocity (PVV)], and spleen stiffness. The correlations between Child-Pugh classification and hemodynamic/spleen stiffness parameters were analyzed. Receiver operating characteristic (ROC) curves were generated to evaluate predictive performance. Results The high-risk group exhibited significantly higher proportions of Child-Pugh-B (44.44%) and Child-Pugh-C (38.89%) patients compared to that of the low-risk group (31.75% and 9.52%, respectively; χ2=13.190, P<0.05). Elevated PVD (1.62±0.09 cm vs. 1.41±0.07 cm), PVQ (1424.83±186.37 mL/min vs. 1320.95±171.19 mL/min), SI (77.29±8.12 cm2 vs. 71.58±7.03 cm2), and spleen stiffness (16.36±3.18 kPa vs. 12.22±2.27 kPa) were observed in patients of the high-risk group (all P<0.05), whereas their PVV was reduced (10.49±1.37 cm/s vs. 13.84±1.52 cm/s, P<0.05). Child-Pugh classifications were positively correlated with PVD (r=0.303), PVQ (r=0.302), SI (r=0.361), and spleen stiffness (r=0.464), but negatively correlated with PVV (r=-0.311; all P<0.05). ROC analysis demonstrated superior predictive performance of the combined SWE-hemodynamic model (AUC=0.974, sensitivity=94.4%, specificity=98.4%). Conclusion The integration of SWE and portal venous hemodynamic parameters provides an effective noninvasive approach for stratifying GV rupture risk in patients with HBV-related cirrhosis, supporting its clinical utility in the risk assessment.

Key words: Shear wave elastography, Portal vein hemodynamics, Hepatitis B, Cirrhosis, Gastric varices, Risk prediction