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双能CT影像组学模型评估进展期胃癌新辅助化疗后浆膜侵犯的临床价值研究

王凌云 张阳 陈勇 葛颖倩 许芷菡 谭晶文 王兰 杜联军 潘自来 潘召城

王凌云, 张阳, 陈勇, 葛颖倩, 许芷菡, 谭晶文, 王兰, 杜联军, 潘自来, 潘召城. 双能CT影像组学模型评估进展期胃癌新辅助化疗后浆膜侵犯的临床价值研究[J]. CT理论与应用研究, 2021, 30(5): 591-602. doi: 10.15953/j.1004-4140.2021.30.05.07
引用本文: 王凌云, 张阳, 陈勇, 葛颖倩, 许芷菡, 谭晶文, 王兰, 杜联军, 潘自来, 潘召城. 双能CT影像组学模型评估进展期胃癌新辅助化疗后浆膜侵犯的临床价值研究[J]. CT理论与应用研究, 2021, 30(5): 591-602. doi: 10.15953/j.1004-4140.2021.30.05.07
WANG Lingyun, ZHANG Yang, CHEN Yong, GE Yingqian, XU Zhihan, TAN Jingwen, WANG Lan, DU Lianjun, PAN Zilai, PAN Zhaocheng. Clinical Value of Applying Dual-energy CT Radio-mics Model to Evaluate Serosal Invasion of Advanced Gastric Cancer after Neoadjuvant Chemotherapy Treatment[J]. CT Theory and Applications, 2021, 30(5): 591-602. doi: 10.15953/j.1004-4140.2021.30.05.07
Citation: WANG Lingyun, ZHANG Yang, CHEN Yong, GE Yingqian, XU Zhihan, TAN Jingwen, WANG Lan, DU Lianjun, PAN Zilai, PAN Zhaocheng. Clinical Value of Applying Dual-energy CT Radio-mics Model to Evaluate Serosal Invasion of Advanced Gastric Cancer after Neoadjuvant Chemotherapy Treatment[J]. CT Theory and Applications, 2021, 30(5): 591-602. doi: 10.15953/j.1004-4140.2021.30.05.07

双能CT影像组学模型评估进展期胃癌新辅助化疗后浆膜侵犯的临床价值研究

doi: 10.15953/j.1004-4140.2021.30.05.07
基金项目: 

上海市科委科技创新行动临床创新领域(基于多模态影像人工智能对胃癌术前分期辅助诊断系统的研究(18411953000));国家自然基金(多模态影像学研究CIP2A调控Akt/NF-κB通路介导的胃癌腹膜转移发生发展的分子机制(81771789))。

详细信息
    作者简介:

    王凌云,男,医学硕士,上海交通大学医学院附属瑞金医院放射科住院医师,主要从事影像诊断工作,擅长胃肠道肿瘤的诊断,E-mail:945078311@qq.com;潘召城*,男,医学博士,上海交通大学医学院附属瑞金医院放射科主治医师,主要从事影像诊断工作,擅长心血管疾病的影像诊断,E-mail:pzc11947@rjh.com.cn。

  • 中图分类号: R814.42

Clinical Value of Applying Dual-energy CT Radio-mics Model to Evaluate Serosal Invasion of Advanced Gastric Cancer after Neoadjuvant Chemotherapy Treatment

  • 摘要: 目的:探讨基于碘图(IM)的双能CT影像组学模型在新辅助化疗(NAC)后局部进展期胃癌(LAGC)浆膜浸润的术前再分期中的诊断效能。方法:对155例(训练组110例,测试组45例)术前经过标准NAC治疗的LAGC患者进行回顾性研究。所有CT图像由两名放射科医生分析,并进行人工分类。半自动勾画感兴趣区体积(VOI),在IM和120kVp图像上分别从每个病变中提取了1226个影像组学特征。采用Spearman相关分析和最小绝对收缩选择算子(LASSO)惩罚Logistic回归过滤不稳定及冗余特征,从而筛选出重要特征。通过多因素Logistic回归分析,分别得到了基于120kVp选择的特征和120kVp结合IM选择的特征建立的两个预测模型(120kVp和IM-120kVp)。结果:两种影像组学模型(IM-120kVp AUC:训练组,0.953,测试组,0.879;120kVp AUC:训练组,0.940,测试组,0.831)在训练和测试组中均显示出较高的预测准确度和效能。所有模型在测试组的诊断准确率(IM-120kVp:84.4%,120kVp:80.0%)均高于人工分类(68.9%)。IM-120kVp模型在训练(P<0.001)和测试组中的诊断效能(P=0.034)均优于人工分类。结论:基于双能CT的影像组学模型在NAC治疗后LAGC术前再分期鉴别浆膜侵犯方面表现出令人信服的诊断效能。

     

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  • 收稿日期:  2020-12-13
  • 网络出版日期:  2021-09-23

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