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Preoperative radiomics nomogramfor microvascular invasion prediction in hepatocellular carcinoma using contrast-enhanced CT
Ma Xiaohong1; Wei Jingwei2; Gu Dongsheng2; Zhu Yongjian1; Feng Bing1; Liang Meng1; Wang Shuang1; Zhao Xinming1; Tian Jie2
Source PublicationEuropean Raidology
2018-12
Issue1Pages:11
Abstract

Objectives

To develop and validate a radiomics nomogram for preoperative prediction of microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC).

Methods

The 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.

Results

Five 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.

Conclusions

The above-described radiomics nomogram can preoperatively predict MVI in patients with HCC and may constitute a usefully clinical tool to guide subsequent personalised treatment.

KeywordHepatocellular Carcinoma Microvessel Forecasting Imaging Three-dimensional Tomography
DOI10.1007/s00330-018-5985-y
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Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/23678
Collection学术期刊
中国科学院分子影像重点实验室
Corresponding AuthorZhao Xinming; Tian Jie
Affiliation1.Department of Diagnostic Radiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17, Panjiayuan Nanli, Chaoyang District, Beijing 100021, People’s Republic of China
2.Key Laboratory of Molecular Imaging, Chinese Academy of Sciences, Beijing, People’s Republic of China
Recommended Citation
GB/T 7714
Ma Xiaohong,Wei Jingwei,Gu Dongsheng,et al. Preoperative radiomics nomogramfor microvascular invasion prediction in hepatocellular carcinoma using contrast-enhanced CT[J]. European Raidology,2018(1):11.
APA Ma Xiaohong.,Wei Jingwei.,Gu Dongsheng.,Zhu Yongjian.,Feng Bing.,...&Tian Jie.(2018).Preoperative radiomics nomogramfor microvascular invasion prediction in hepatocellular carcinoma using contrast-enhanced CT.European Raidology(1),11.
MLA Ma Xiaohong,et al."Preoperative radiomics nomogramfor microvascular invasion prediction in hepatocellular carcinoma using contrast-enhanced CT".European Raidology .1(2018):11.
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