中华放射学杂志2024,Vol.58Issue(1) :57-63.DOI:10.3760/cma.j.cn112149-20230814-00089

原发灶及癌旁胃壁外脂肪组织CT影像组学评估胃癌T分期的价值

The value of CT radiomics of the primary gastric cancer and the adipose tissue outside the gastric wall beside cancer in evaluating T staging of gastric cancer

王芷旋 王霄霄 卢超 陆思远 丁奕 潘冬刚 周月圆 姚俊 张久楼 蒋鹏程 单秀红
中华放射学杂志2024,Vol.58Issue(1) :57-63.DOI:10.3760/cma.j.cn112149-20230814-00089

原发灶及癌旁胃壁外脂肪组织CT影像组学评估胃癌T分期的价值

The value of CT radiomics of the primary gastric cancer and the adipose tissue outside the gastric wall beside cancer in evaluating T staging of gastric cancer

王芷旋 1王霄霄 1卢超 1陆思远 1丁奕 1潘冬刚 1周月圆 1姚俊 2张久楼 3蒋鹏程 4单秀红1
扫码查看

作者信息

  • 1. 镇江市第一人民医院江苏大学附属人民医院影像科,镇江 212002
  • 2. 镇江市第一人民医院江苏大学附属人民医院消化内科,镇江 212002
  • 3. 南京医科大学影像学院人工智能影像实验室,南京 210029
  • 4. 镇江市第一人民医院江苏大学附属人民医院普外科,镇江 212002
  • 折叠

摘要

目的 探讨基于胃癌原发灶及癌旁胃壁外脂肪组织的CT影像组学模型鉴别T1~2与T3~4期胃癌的价值.方法 本研究为病例对照研究,回顾性收集2011年12月到2019年12月江苏大学附属人民医院465例胃癌患者,根据术后病理将其分为T1~2期(150例)及T3~4期(315例).采用分层抽样方法按7:3的比例分为训练集(326例)和测试集(139例),训练集中T1~2期104例、T3~4期222例,测试集中T1~2期46例、T3~4期93例.选择术前1周内静脉期增强CT图像勾画胃癌原发灶及癌旁胃壁外脂肪组织为感兴趣区(ROI),采用Pyradiomics软件提取ROI的影像组学特征,用最小绝对收缩和选择算子回归筛选与T分期相关的特征,建立胃癌原发灶和胃壁外脂肪组织影像组学模型.采用独立样本 t 检验或x2检验比较训练集中T1~2与T3~4期患者临床特征的差异,将差异有统计学意义的特征建立临床模型.联合2个影像组学模型及临床模型构建临床-影像组学联合模型,并生成列线图.用受试者操作特征曲线下面积(AUC)评价各模型鉴别胃癌T1~2与T3~4期的效能,用校准曲线评价列线图预测胃癌的T分期与实际T分期的一致性,决策曲线评价采用列线图和临床模型指导治疗的临床净收益.结果 训练集中T1~2和T3~4期患者间CT-T分期、CT-N分期差异有统计学意义(x2=10.59、15.92,P=0.014、0.001),联合建立临床模型.经筛选和降维,胃癌原发灶ROI得到5个特征,胃壁外脂肪组织ROI得到6个特征,分别建立影像组学模型.在训练集和测试集中,原发灶影像组学模型鉴别胃癌 T1~2 与 T3~4 期的 AUC 为 0.864(95%CI 0.820~0.908)、0.836(95%CI 0.762~0.910),癌旁胃壁外脂肪组织的影像组学模型为0.782(95%CI0.731~0.833)、0.784(95%CI 0.702~0.866),临床模型为 0.761(95%CI 0.705~0.817)、0.758(95%C1 0.671~0.845),列线图为 0.876(95%CI 0.835~0.917)、0.851(95%CI0.781~0.921).校准曲线反映列线图在训练集中预测胃癌的T分期与实际的T分期具有较高的一致性(x2=1.70,P=0.989),决策曲线显示风险阈值在0.01~0.74时,采用列线图指导治疗可获得更高的临床净获益率.结论 原发灶及癌旁胃壁外脂肪组织的CT影像组学模型能较好地区分T1~2与T3~4期胃癌,联合临床特征能进一步提升预测效能.

Abstract

Objective To investigate the value of CT radiomic model based on analysis of primary gastric cancer and the adipose tissue outside the gastric wall beside cancer in differentiating stage T1-2 from stage T3-4 gastric cancer.Methods This study was a case-control study.Totally 465 patients with gastric cancer treated in Affiliated People's Hospital of Jiangsu University from December 2011 to December 2019 were retrospectively collected.According to postoperative pathology,they were divided into 2 groups,one with 150 cases of T1-2 tumors and another with 315 cases of T3-4 tumors.The cases were divided into a training set(326 cases)and a test set(139 cases)by stratified sampling method at 7:3.There were 104 cases of T1-2 stage and 222 cases of T3-4 stage in the training set,46 cases of T1-2 stage and 93 cases of T3-4 stage in the test set.The axial CT images in the venous phase during one week before surgery were selected to delineate the region of interest(ROI)at the primary lesion and the extramural gastric adipose tissue adjacent to the cancer areas.The radiomic features of the ROIs were extracted by Pyradiomics software.The least absolute shrinkage and selection operator was used to screen features related to T stage to establish the radiomic models of primary gastric cancer and the adipose tissue outside the gastric wall beside cancer.Independent sample t test or x2 test were used to compare the differences in clinical features between T1-2 and T3-4 patients in the training set,and the features with statistical significance were combined to establish a clinical model.Two radiomic signatures and clinical features were combined to construct a clinical-radiomics model and generate a nomogram.The area under the receiver operating characteristic curve(AUC)was used to evaluate the efficacy of each model in differentiating stage T1-2 from stage T3-4 gastric cancer.The calibration curve was used to evaluate the consistency between the T stage predicted by the nomogram and the actual T stage of gastric cancer.And the decision curve analysis was used to evaluate the clinical net benefit of treatment guided by the nomogram and by the clinical model.Results There were significant differences in CT-T stage and CT-N stage between T1-2 and T3-4 patients in the training set(x2=10.59,15.92,P=0.014,0.001)and the clinical model was established.After screening and dimensionality reduction,the 5 features from primary gastric cancer and the 6 features from the adipose tissue outside the gastric wall beside cancer established the radiomic models respectively.In the training set and the test set,the AUC values of the primary gastric cancer radiomic model were 0.864(95%CI 0.820-0.908)and 0.836(95%CI 0.762-0.910),and the adipose tissue outside the gastric wall beside cancer radiomic model were 0.782(95%CI 0.731-0.833)and 0.784(95%CI 0.702-0.866).The AUC values of the clinical model were 0.761(95%CI 0.705-0.817)and 0.758(95%CI 0.671-0.845),and the nomogram were 0.876(95%CI 0.835-0.917)and 0.851(95%CI 0.781-0.921).The calibration curve reflected that there was a high consistency between the T stage predicted by the nomogram and the actual T stage in the training set(x2=1.70,P=0.989).And the decision curve showed that at the risk threshold 0.01-0.74,a higher clinical net benefit could be obtained by using a nomogram to guide treatment.Conclusions The CT radiomics features of primary gastric cancer lesions and the adipose tissue outside the gastric wall beside cancer can effectively distinguish T1-2 from T3-4 gastric cancer,and the combination of CT radiomic features and clinical features can further improve the prediction accuracy.

关键词

胃肿瘤/体层摄影术,X线计算机/脂肪组织/T分期/影像组学

Key words

Stomach neoplasms/Tomography,X-ray computed/Adipose tissue/T staging/Radiomics

引用本文复制引用

基金项目

镇江市科技创新基金(SH2020049)

镇江市科技创新基金(SH2022040)

镇江市第一人民医院科研基金(Y2021011-S)

出版年

2024
中华放射学杂志
中华医学会

中华放射学杂志

CSTPCD北大核心
影响因子:1.756
ISSN:1005-1201
参考文献量18
段落导航相关论文