CASIA OpenIR
Preoperative radiomics nomogram for microvascular invasion prediction in hepatocellular carcinoma using contrast-enhanced CT
Ma, Xiaohong1,2; Wei, Jingwei3; Gu, Dongsheng3; Zhu, Yongjian1,2; Feng, Bing1,2; Liang, Meng1,2; Wang, Shuang1,2; Zhao, Xinming1,2; Tian, Jie3
Source PublicationEUROPEAN RADIOLOGY
ISSN0938-7994
2019-07-01
Volume29Issue:7Pages:3595-3605
Corresponding AuthorZhao, Xinming(xinmingzh@sina.com) ; Tian, Jie(jie.tian@ia.ac.cn)
AbstractObjectivesTo 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.
KeywordHepatocellular carcinoma Microvessel Forecasting Imaging Three-dimensional tomography
DOI10.1007/s00330-018-5985-y
WOS KeywordPOTENTIAL BIOMARKER ; ALPHA-FETOPROTEIN ; TEXTURE ANALYSIS ; SURVIVAL ; LIVER ; RADIOGENOMICS ; RECURRENCE ; HETEROGENEITY ; PHENOTYPES ; SIGNATURE
Indexed BySCI
Language英语
Funding ProjectCAMS 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]
Funding OrganizationCAMS 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 Research AreaRadiology, Nuclear Medicine & Medical Imaging
WOS SubjectRadiology, Nuclear Medicine & Medical Imaging
WOS IDWOS:000470679400029
PublisherSPRINGER
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/24407
Collection中国科学院自动化研究所
Corresponding AuthorZhao, Xinming; Tian, Jie
Affiliation1.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
Recommended Citation
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.
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