摘要
目的探讨原发性肝癌患者的MRI影像学特征及与预后之间的关系。方法回顾性分析2014年7月至2016年8月本院100例原发性肝癌患者术前MRI资料,记录肿瘤大小、数目、形态、以及包膜、肿瘤边缘、环形强化、内部坏死状况,探讨MRI征象与患者预后的相关性,分析影响原发性肝癌患者预后的危险因素。结果100例患者3年随访期间内生存41例,死亡59例,3年总生存率为41.00%;原发性肝癌生存组与死亡组性别、年龄、肿瘤数目、肿瘤形态、包膜状况比较差异无统计学意义(P>0.05);生存组肿瘤直径大于死亡组,毛刺或不规则边缘、环形强化、内部坏死比例低于死亡组,差异有统计学意义(P<0.05);Logisitic回归分析显示,肿瘤大小、肿块边缘、环形强化、内部坏死征象是原发性肝癌患者3年生存率的影响因素。结论MRI征象中肿瘤大小、肿块边缘、环形强化、内部坏死与原发性肝癌患者预后具有相关性。
Objective To explore the relationship between MRI features and prognosis in patients with primary liver cancer.Methods A retrospective analysis was performed on preoperative MRI scan imaging data of 100 patients with primary liver cancer in the hospital from July 2014 to August 2016.The tumor size,number,morphology,and capsule,tumor margin,annular enhancement and internal necrosis condition were recorded.The relationship between MRI signs and prognosis was explored.The risk factors affecting prognosis of patients with primary liver cancer were analyzed.Results Of the 100 patients,there were 41 cases survived during the 3-year follow-up period,and 59 cases died.The 3-year overall survival rate was 41.00%.There was no significant difference in gender,age,tumor number,tumor morphology,or capsule status between survival group and death group(P>0.05).The tumor diameter in survival group was larger than that in death group,while promotion of burr or irregular edge,annular enhancement and internal necrosis was lower than that in death group(P<0.05).Logisitic regression analysis showed that tumor size,mass edge,annular enhancement and internal necrosis were influencing factors of 3-year survival rate in patients with primary liver cancer.Conclusion The size,margin,ring enhancement and internal necrosis of the tumor in MRI signs are correlated with the prognosis of patients with primary liver cancer.
作者
陈兵阳
CHEN Bing-yang(Department of Critical Care Medicine,Chengdu Seventh People's Hospital,Chengdu 610021,Sichuan Province,China)
出处
《中国CT和MRI杂志》
2020年第12期80-83,共4页
Chinese Journal of CT and MRI
关键词
原发性肝癌
磁共振成像
影像学特征
预后
Primary Liver Cancer
Magnetic Resonance Imaging
Imaging Feature
Prognosis