[1]于 翔,谢 坪,李金泽,等.预测DEB-TACE治疗肝细胞肝癌术后生存率的放射组学列线图[J].介入放射学杂志,2022,31(01):39-44.
 YU Xiang,XIE Ping,LI Jinze,et al.Application of CT radiomics nomogram model in predicting the survival time of patients with hepatocellular carcinoma after receiving drug- eluting beads transarterial chemoembolization[J].journal interventional radiology,2022,31(01):39-44.
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预测DEB-TACE治疗肝细胞肝癌术后生存率的放射组学列线图()

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《介入放射学杂志》[ISSN:1008-794X/CN:31-1796/R]

卷:
31
期数:
2022年01
页码:
39-44
栏目:
肿瘤介入
出版日期:
2022-01-25

文章信息/Info

Title:
Application of CT radiomics nomogram model in predicting the survival time of patients with hepatocellular carcinoma after receiving drug- eluting beads transarterial chemoembolization
作者:
于 翔 谢 坪 李金泽 曹 磊 顾 露 尚 兰
Author(s):
YU Xiang XIE Ping LI Jinze CAO Lei GU Lu SHANG Lan.
Department of Radiology, Sichuan Provincial People’s Hospital, Sichuan Provincial Academy of Medical Sciences, Chengdu, Sichuan Province 610041, China
关键词:
【关键词】 肝癌 药物洗脱微球 化疗栓塞 影像组学评分 列线图
文献标志码:
A
摘要:
【摘要】 目的 探讨CT放射组学列线图模型预测CalliSpheres药物洗脱微球- 经导管动脉栓塞术(DEB- TACE)治疗肝细胞癌(HCC)生存期的价值。方法 回顾性分析2016年1月至2018年12月经穿刺病理或临床诊断为HCC,且巴塞罗那临床肝癌B期(BCLC- B)行DEB- TACE的100例患者(训练组60例,测试组40例)。利用A.K.软件进行术前CT影像组学特征提取,并将选定的特征与相应的非零系数相乘的线性组合来计算每个患者的放射组学评分(Rad- score)。Cox回归分析与术后生存相关的独立危险因素。根据独立危险因素,共建立5个预测模型,并进行模型间AUC比较,选出最佳预测模型。以最佳预测模型生成影像组学列线图,并用校准图形法直观表示其预测符合度。结果 100例患者中,存活52例,死亡48例。肿瘤数目、GGT、Rad-score值是影响DEB- TACE治疗HCC术后生存期的独立危险因素,临床- 静脉期影像组学联合模型在训练组和验证组中的AUC及准确率最高(训练组AUC=0.921,准确率84.4%;验证组AUC=0.904,准确率81.5%),为最佳模型。该模型在训练组和验证组中都显示出良好的校正能力。结论 术前CT影像组学列线图模型对预测DEB- TACE治疗BCLC- B期HCC生存期具有价值。

参考文献/References:

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备注/Memo

备注/Memo:
(收稿日期:2021- 02- 18)
(本文编辑:俞瑞纲)
更新日期/Last Update: 2022-01-12