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南京医科大学学报(自然科学版)                                  第43卷第4期
               ·542 ·                       Journal of Nanjing Medical University(Natural Sciences)  2023年4月


             ·临床研究·

              基于影像组学方法构建弥漫性低级别胶质瘤癫痫发生及远期

              生存预测模型



              胡定东 ,郭      震 ,王丽君     1*
                             2
                     1
               江苏省肿瘤医院(南京医科大学附属肿瘤医院)肿瘤放射治疗科,江苏省肿瘤防治研究所,影像科,江苏 南京                                     210009
              1                                                                    2


             [摘    要] 目的:构建预测弥漫性低级别胶质瘤患者癫痫发作风险的影像组学风险模型,并初步评估患者预后。方法:利用癌
              症基因组图谱(the cancer genome atlas,TCGA)数据库和癌症影像档案(the cancer imaging archive,TCIA)数据库提供的影像数
              据集及临床资料,通过影像组学方法构建癫痫风险评分模型,并结合临床指标建立列线图以预测癫痫发生概率及远期生存概
              率。用受试者工作特征(receiver operating characteristic,ROC)曲线及决策曲线分析评价模型的预测效能。结果:筛选出10个
              癫痫相关的影像特征建立风险评分模型,内部及外部验证的ROC曲线下面积分别为0.900和0.636。高风险组和低风险组的
              癫痫阳性率分别为80.6%和27.3%。高风险组和低风险组患者的5年疾病总生存率存在明显统计学差异(P=0.029),临床决策
              分析曲线显示“影像⁃临床”癫痫预测模型的净获益率优于临床预测模型。校准曲线显示3年、5年生存列线图有良好的校准和
              区分能力,列线图中高低危组5年总生存有明显统计学差异(P=0.008)。结论:本研究建立了一个基于术前MRI的影像组学模
              型,可用于无创预测弥漫性低级别胶质瘤患者癫痫发生风险及预后,为临床采取个体化治疗策略提供参考。
             [关键词] 弥漫性低级别胶质瘤;癫痫;影像组学;磁共振成像
             [中图分类号] R739.41                    [文献标志码] A                      [文章编号] 1007⁃4368(2023)04⁃542⁃08
              doi:10.7655/NYDXBNS20230414


              A predictive model of epilepsy and long⁃term survival of diffuse low⁃grade glioma based on

              radiomics
                         1
                                    2
              HU Dingdong ,GUO Zhen ,WANG Lijun 1*
               Department of Radiation Therapy,Department of Image,Jiangsu Cancer Hospital,the Affiliated Cancer Hospital of
              1                            2
              Nanjing Medical University,Jiangsu Institute of Cancer Research,Nanjing 210009,China

             [Abstract] Objective:To construct a radiomic risk model to predict the risk of epileptic seizures in patients with diffuse low⁃grade
              glioma and to preliminarily assess patient outcomes. Methods:Using the imaging datasets and clinical data provided by TCGA and TCIA
              databases,an epilepsy risk score model was constructed by radiomics methods. Further nomograms were established based on the model
              combined with clinical indicators to predict the probability of epilepsy and the long⁃term survival rate. Receiver operator characteristic
             (ROC)curve and decision curve analysis were used to evaluate the predictive effectiveness of predictive models. Results:In the current
              study,10 radiomic features were filtered out to establish the epilepsy risk scoring model. The area under ROC curve of internal
              verification and external verification were 0.900 and 0.636,respectively. The positive rate of epilepsy in high⁃risk group and low⁃risk
              group were 80.6% and 27.3%,respectively. There was significant difference in 5⁃year overall survival between the high⁃risk and low⁃risk
              groups(P=0.029). Clinical decision curve analysis showed that the net benefit rate of the image⁃clinical model was higher than that of the
              clinical prediction model. The calibration curve showed that the 3⁃year,5⁃year survival nomogram had good calibration and differentiation
              ability and the 5⁃year overall survival between the high risk group and the low risk group in the nomogram had significant difference
             (P=0.008). Conclusion:In the current study,a radiomic model based on preoperative MRI of diffuse low⁃grade glioma was established
              for non⁃invasive prediction of the associated epilepsy and prognosis,which provides a reference for the individualized treatment strategies.
             [Key words] diffuse low⁃grade gliomas;epilepsy;radiomics;magnetic resonance imaging
                                                                            [J Nanjing Med Univ,2023,43(04):542⁃549]

             [基金项目] 江苏省预防医学会课题(Y2018091);江苏省卫健委面上项目(M2021093)
              ∗
              通信作者(Corresponding author),E⁃mail:dr_wanglj@njmu.edu.cn
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