%0 Journal Article
%T 术前MRI特征预测高强度聚焦超声治疗晚期胰腺癌的近期疗效<br>Preoperative Dynamic Enhanced MRI Imaging Features Predicting the Short-Term Prognosis of High Intensity Focused Ultrasound in the Treatment of Advanced Pancreatic Cancer
%A 邵长杰
%A 张靓
%A 宫川欣
%A 郭婧
%A 田雅琪
%A 马蕾媛
%A 于宁
%J Advances in Clinical Medicine
%P 8348-8354
%@ 2161-8720
%D 2022
%I Hans Publishing
%R 10.12677/ACM.2022.1291203
%X 目的：探讨术前动态增强MRI影像学特征在预测高强度聚焦超声(High-intensity focused ultrasound, HIFU)治疗晚期胰腺癌(Advanced pancreatic cancer, APC)近期疗效中的应用价值。方法：回顾性分析2019年7月至2021年5月于我院行HIFU治疗的53例APC患者的临床及影像学资料，采用Logistic回归分析探究不良预后的相关危险因素，以受试者工作特征曲线(ROC)评价其预测效能。结果：53例APC患者有效率为22.6%，局部控制率为64.2%。Logistic回归分析结果显示肿瘤大小(P = 0.008)及边缘强化(P = 0.040)是预测APC患者HIFU术后短期不良预后的独立性危险因素；ROC曲线分析显示当肿瘤大小取截断值3.45 cm时，预测效能最高。结论：术前动态增强MRI显示的肿瘤大小及边缘强化对APC患者HIFU术后的近期疗效具有较高的预测价值。<br />
Objective: To investigate the application value of preoperative dynamic enhanced MRI imaging features in predicting the short-term efficacy of High-intensity focused ultrasound (HIFU) in the treatment of advanced pancreatic cancer. Methods: The clinical and imaging data of 53 APC patients treated with HIFU in our hospital from July 2019 to May 2021 were collected. Logistic regression analysis was used to explore the related risk factors of poor prognosis, and the receiver operating characteristic curve (ROC) was used to evaluate the predictive efficacy. Results: The effective rate of 53 APC patients was 22.6%, and the local control rate was 64.2%. Logistic regression analysis showed that tumor size (P = 0.008) and edge enhancement (P = 0.040) were independent risk fac-tors for short-term poor prognosis after HIFU in APC patients. ROC curve analysis showed that when the tumor size was cut off at 3.45 cm, the predictive sensitivity was the highest. Conclusion: The tu-mor size and edge enhancement displayed by preoperative dynamic enhanced MRI have high pre-dictive value for the short-term efficacy of APC patients after HIFU.
%K 胰腺癌，高强度聚焦超声，MRI成像，影像学特征<br>Pancreatic Cancer
%K High-Intensity Focused Ultrasound
%K MRI Imaging
%K Imaging Features
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=55749