基于瘤周1cm内ADC值构建的列线图模型预测胶质瘤术后进展的临床价值  

Clinical value of a nomogram model based on ADC values within 1cm around the tumor for predicting the postoperative progression of glioma

作　　者：程梦雨 杨哲 范嘉玮 李文菲 王文希 王占秋 CHENG Mengyu;YANG Zhe;FAN Jiawei;LI Wenfei;WANG Wenxi;WANG Zhanqiu(Department of Radiation Medicine,Hebei Medical University,Shijiazhuang 050000,China;Hebei North University,Zhangjiakou 075000,China;Department of Radiology,Qinhuangdao First Hospital Affiliated to Hebei Medical University,Qinhuangdao 066000,China)

机构地区：[1]河北医科大学放射医学教研室,石家庄050000 [2]河北北方学院,张家口075000 [3]河北医科大学附属秦皇岛市第一医院放射科,秦皇岛066000

出　　处：《磁共振成像》2023年第1期136-142,150,共8页Chinese Journal of Magnetic Resonance Imaging

基　　金：秦皇岛市科技计划项目(编号:201805A078)。

摘　　要：目的构建基于瘤周1 cm内表观扩散系数(apparent diffusion coefficient,ADC)值的列线图模型对预测胶质瘤术后进展的临床价值。材料与方法回顾性分析2016年1月至2020年12月间于秦皇岛市第一医院就诊的脑胶质瘤切除术患者的临床及影像资料,通过影像储存和传输系统(Picture Archiving and Communication Systems,PACS)收集并测量平均ADC(mean apparent diffusion coefficient,mADC)值。通过X-tile选取最优mADC阈值后进行Kaplan-Meier生存曲线分析。采用Cox回归分析筛选独立危险因素并构建列线图预测模型,进而预测胶质瘤患者术后进展。绘制受试者工作特征(receiver operating characteristic,ROC)曲线评价模型的准确性,决策曲线(decision curve analysis,DCA)评价模型的临床价值。结果单因素及多因素Cox回归分析显示,瘤周mADC值、瘤周强化程度、年龄及肿瘤切除程度是预测胶质瘤术后进展的独立危险因素(P均<0.05)。列线图模型预测胶质瘤患者术后1、2年病情进展的ROC曲线下面积(area under the curve,AUC)分别为0.79、0.76。校正曲线显示模型中观察值与预测值之间有良好的一致性。DCA显示列线图模型有较好的临床应用价值。结论基于瘤周1 cm内mADC值首次建立的列线图模型可直观全面地预测胶质瘤患者术后病情进展情况,为临床个性化评估患者生存预后及制订治疗方案提供有力工具。Objective:To investigate the clinical value of nomogram model based on the apparent diffusion coefficient(ADC)within 1cm around the tumor for predicting the postoperative progression of glioma.Materials and Methods:Clinical data of glioma patients underwent surgery retrospectively retrieved from First Hospital of Qinhuangdao were obtained.Mean apparent diffusion coefficient(mADC)was collected and measured by Picture Archiving and Communication Systems(PACS).Kaplan-Meier survival curve was performed with optimal mADC threshold determined by X-tile.Cox regression analysis was used to screen independent risk factors,then a nomogram was developed to predict the progression of postoperative glioma patients.The receiver operating characteristic(ROC)curve was drawn to evaluate the prediction accuracy of the model,and the decision curve analysis(DCA)was carried out to assess the clinical value of the nomogram.Results:Univariate and multivariate Cox regression analysis showed that the peritumoral mADC values,the degree of peritumoral enhancement,age and the degree of tumor resection were independent risk factors for predicting the postoperative progression of glioma(all P<0.05).The ROC curve of the nomogram predicting 1 and 2 years postoperative progression was 0.79 and 0.76.The calibration curve showed that there was a good consistency between the observed values and the predicted values in the model.The curve showed that the nomogram model had good clinical application value.Conclusions:The nomogram model established for the first time based on mADC value within 1 cm around the tumor can predict the postoperative condition of glioma patients intuitively and comprehensively.It can provide a relatively accurate prediction tool for neurosurgeons to individualized evaluation of survival and prognosis and formulated treatment plans for patients.

关 键 词：胶质瘤 瘤周水肿 瘤周强化 术后进展 磁共振成像 扩散加权成像 表观扩散系数 列线图 

分 类 号：R445.2[医药卫生—影像医学与核医学] R730.264[医药卫生—诊断学]