Preoperative radiomics nomogram for microvascular invasion prediction in hepatocellular carcinoma using contrast-enhanced CT

doi:10.1007/s00330-018-5985-y

	Preoperative radiomics nomogram for microvascular invasion prediction in hepatocellular carcinoma using contrast-enhanced CT
	Ma, Xiaohong 1,2; Wei, Jingwei3 ; Gu, Dongsheng3 ; Zhu, Yongjian 1,2; Feng, Bing 1,2; Liang, Meng 1,2; Wang, Shuang 1,2; Zhao, Xinming 1,2; Tian, Jie 3
发表期刊	EUROPEAN RADIOLOGY
ISSN	0938-7994
	2019-07-01
卷号	29 期号:7 页码:3595-3605
通讯作者	Zhao, Xinming(xinmingzh@sina.com) ; Tian, Jie(jie.tian@ia.ac.cn)
摘要	ObjectivesTo develop and validate a radiomics nomogram for preoperative prediction of microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC).MethodsThe study included 157 patients with histologically confirmed HCC with or without MVI, and 110 patients were allocated to the training dataset and 47 to the validation dataset. Baseline clinical factor (CF) data were collected from our medical records, and radiomics features were extracted from the artery phase (AP), portal venous phase (PVP) and delay phase (DP) of preoperatively acquired CT in all patients. Radiomics analysis included tumour segmentation, feature extraction, model construction and model evaluation. A final nomogram for predicting MVI of HCC was established. Nomogram performance was assessed via both calibration and discrimination statistics.ResultsFive AP features, seven PVP features and nine DP features were effective for MVI prediction in HCC radiomics signatures. PVP radiomics signatures exhibited better performance than AP and DP radiomics signatures in the validation datasets, with the AUC 0.793. In the clinical model, age, maximum tumour diameter, alpha-fetoprotein and hepatitis B antigen were effective predictors. The final nomogram integrated the PVP radiomics signature and four CFs. Good calibration was achieved for the nomogram in both the training and validated datasets, with respective C-indexes of 0.827 and 0.820. Decision curve analysis suggested that the proposed nomogram was clinically useful, with a corresponding net benefit of 0.357.ConclusionsThe above-described radiomics nomogram can preoperatively predict MVI in patients with HCC and may constitute a usefully clinical tool to guide subsequent personalised treatment.Key Points center dot No previously reported study has utilised radiomics nomograms to preoperatively predict the MVI of HCC using 3D contrast-enhanced CT imaging.center dot The combined radiomics clinical factor (CF) nomogram for predicting MVI achieved superior performance than either the radiomics signature or the CF nomogram alone.center dot Nomograms combing PVP radiomics and CF may be useful as an imaging marker for predicting MVI of HCC preoperatively and could guide personalised treatment.
关键词	Hepatocellular carcinoma Microvessel Forecasting Imaging Three-dimensional tomography
DOI	10.1007/s00330-018-5985-y
关键词[WOS]	POTENTIAL BIOMARKER ; ALPHA-FETOPROTEIN ; TEXTURE ANALYSIS ; SURVIVAL ; LIVER ; RADIOGENOMICS ; RECURRENCE ; HETEROGENEITY ; PHENOTYPES ; SIGNATURE
收录类别	SCI
语种	英语
资助项目	CAMS Innovation Fund for Medical Sciences (CIFMS)[2016-I2M-1-001] ; PUMC Youth Fund[2017320010] ; Chinese Academy of Medical Sciences (CAMS) Research Fund[ZZ2016B01] ; National Natural Science Foundation of China[81227901] ; National Natural Science Foundation of China[61231004] ; National Key R&D Program of China[2017YFA0205200] ; National Key R&D Program of China[2017YFC1309100] ; CAMS Innovation Fund for Medical Sciences (CIFMS)[2016-I2M-1-001] ; PUMC Youth Fund[2017320010] ; Chinese Academy of Medical Sciences (CAMS) Research Fund[ZZ2016B01] ; National Natural Science Foundation of China[81227901] ; National Natural Science Foundation of China[61231004] ; National Key R&D Program of China[2017YFA0205200] ; National Key R&D Program of China[2017YFC1309100] ; CAMS Innovation Fund for Medical Sciences (CIFMS)[2016-I2M-1-001] ; PUMC Youth Fund[2017320010] ; Chinese Academy of Medical Sciences (CAMS) Research Fund[ZZ2016B01] ; National Natural Science Foundation of China[81227901] ; National Natural Science Foundation of China[61231004] ; National Key R&D Program of China[2017YFA0205200] ; National Key R&D Program of China[2017YFC1309100]
项目资助者	CAMS Innovation Fund for Medical Sciences (CIFMS) ; PUMC Youth Fund ; Chinese Academy of Medical Sciences (CAMS) Research Fund ; National Natural Science Foundation of China ; National Key R&D Program of China
WOS研究方向	Radiology, Nuclear Medicine & Medical Imaging
WOS类目	Radiology, Nuclear Medicine & Medical Imaging
WOS记录号	WOS:000470679400029
出版者	SPRINGER
引用统计	被引频次：138[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/24407
专题	中国科学院分子影像重点实验室
通讯作者	Zhao, Xinming; Tian, Jie
作者单位	1.Chinese Acad Med Sci, Natl Canc Ctr, Canc Hosp, Dept Diagnost Radiol, 17 Panjiayuan Nanli, Beijing 100021, Peoples R China 2.Peking Union Med Coll, 17 Panjiayuan Nanli, Beijing 100021, Peoples R China 3.Chinese Acad Sci, Key Lab Mol Imaging, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Ma, Xiaohong,Wei, Jingwei,Gu, Dongsheng,et al. Preoperative radiomics nomogram for microvascular invasion prediction in hepatocellular carcinoma using contrast-enhanced CT[J]. EUROPEAN RADIOLOGY,2019,29(7):3595-3605.
APA	Ma, Xiaohong.,Wei, Jingwei.,Gu, Dongsheng.,Zhu, Yongjian.,Feng, Bing.,...&Tian, Jie.(2019).Preoperative radiomics nomogram for microvascular invasion prediction in hepatocellular carcinoma using contrast-enhanced CT.EUROPEAN RADIOLOGY,29(7),3595-3605.
MLA	Ma, Xiaohong,et al."Preoperative radiomics nomogram for microvascular invasion prediction in hepatocellular carcinoma using contrast-enhanced CT".EUROPEAN RADIOLOGY 29.7(2019):3595-3605.