多参数磁共振影像组学列线图在术前可有效预测直肠癌淋巴血管浸润  

Multi-parametric magnetic resonance imaging radiomics nomogram can effectively predict lymphovascular invasion in rectal cancer before surgery

作　　者：王月燕 赵以惠 陈艾琪 杜小萌 钱宝鑫 潘成武[4] 马宜传[1] WANG Yueyan;ZHAO Yihui;CHEN Aiqi;DU Xiaomeng;QIAN Baoxin;PAN Chengwu;MA Yichuan(Department of Radiology,The First Affiliated Hospital of Bengbu Medical College,Bengbu 233000,China;Graduate School of Bengbu Medical College,Bengbu 233000,China;Huiyi Huiying Medical Technology Co.,Ltd.,Beijing 100000,China;Department of Tumor Surgery,The First Affiliated Hospital of Bengbu Medical College,Bengbu 233000,China)

机构地区：[1]蚌埠医学院第一附属医院放射科,安徽蚌埠233000 [2]蚌埠医学院研究生院,安徽蚌埠233000 [3]汇医慧影医疗科技有限公司,北京100000 [4]蚌埠医学院第一附属医院肿瘤外科,安徽蚌埠233000

出　　处：《分子影像学杂志》2024年第1期36-41,共6页Journal of Molecular Imaging

基　　金：蚌埠医学院自然科学重点项目(BYKY2019025ZD)。

摘　　要：目的 探讨基于多参数磁共振影像组学结合临床危险因素构建的列线图模型在术前预测直肠癌淋巴血管浸润的价值。方法 回顾性分析蚌埠医学院第一附属医院术前行多参数MRI检查且术后病理证实为直肠腺癌的患者112例,收集患者的临床和盆腔影像资料,以7:3的比例随机分为训练集和验证集。通过单-多因素Logistic回归分析筛选与直肠癌淋巴血管浸润相关的临床独立危险因素;分别于T2WI、扩散加权成像和T1WI增强序列手动勾画感兴趣区并提取影像组学特征,经特征降维筛选最优影像组学特征构建影像组学模型;结合临床预测因子与影像组学评分标签构建列线图模型。采用ROC曲线下面积、校准曲线、决策曲线分析评价模型的预测效能。结果 列线图模型的预测效能最佳,其曲线下面积在训练集和验证集分别为0.876(95%CI:0.799~0.952)、0.769(95%CI:0.600~0.938),显著高于单独影像组学模型(0.818、0.741)和临床模型(0.714、0.548)。结论 本研究构建的列线图模型在预测直肠癌淋巴血管浸润方面具有较高的诊断性能,可以术前为临床决策提供重要指导。Objective To explore the value of a nomogram model based on multi-parametric MRI radiomics combined with clinical risk factors in preoperative prediction of lymphovascular invasion of rectal cancer.Methods A total of 112 patients who underwent preoperative multi-parametric MRI examination and were confirmed as rectal adenocarcinomas by postoperative pathology in the First Affiliated Hospital of Bengbu Medical College were retrospectively analyzed.The clinical and pelvic imaging data of the patients were collected,and they were randomly divided into training set and validation set at a ratio of 7:3.Clinical independent risk factors related to lymphovascular invasion in rectal cancer were selected through single-multiple Logistic regression analysis.Regions of interest were manually delineated on T2WI,diffusion weighted imaging and T1WI enhanced sequences,and radiomics characteristics were extracted.The optimal radiomics characteristics were selected through characteristics dimension reduction,and a radiomics model was constructed.A nomogram model was built by combining clinical predictive factors with radiomics score labels.The predictive efficiency of the model was evaluated adopting area under the ROC curve,calibration curve and decision curve analysis.Results The nomogram model showed excellent predictive efficiency,with an area under the curve of 0.876(95%CI:0.799-0.952)and 0.769(95%CI:0.600-0.938)for the training set and validation set respectively,which was significantly higher than the radiomics model(0.818,0.741)and clinical model(0.714,0.548).Conclusion The nomogram model exhibited excellent predictive efficiency in predicting lymphovascular invasion of rectal cancer,which can provide important guidance for clinical decision-making preoperatively.

关 键 词：直肠癌 淋巴血管浸润 影像组学 磁共振成像 列线图模型 

分 类 号：R735.37[医药卫生—肿瘤] R445.2[医药卫生—临床医学]