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

  • Computed Tomography
  • Published:
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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.

Key Points

• No previously reported study has utilised radiomics nomograms to preoperatively predict the MVI of HCC using 3D contrast-enhanced CT imaging.

• The combined radiomics clinical factor (CF) nomogram for predicting MVI achieved superior performance than either the radiomics signature or the CF nomogram alone.

• Nomograms combing PVP radiomics and CF may be useful as an imaging marker for predicting MVI of HCC preoperatively and could guide personalised treatment.

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Abbreviations

AFP:

Alpha-fetoprotein

AP:

Arterial phase

AUC:

Area under the curve

CECT:

Contrast-enhanced computed tomography

CF:

Clinical factor

CI:

Confidence interval

CT:

Computed tomography

DP:

Delay phase

HBsAg:

Hepatitis B surface antigen

HCC:

Hepatocellular carcinoma

ICC:

Intraclass correlation coefficient

LASSO:

Least absolute shrinkage and selection operator

LR:

Liver resection

MR:

Magnetic resonance

MTD:

Maximum tumour diameter

MVI:

Microvascular invasion

OR:

Odds ratio

PACS:

Picture archiving and communication system

PVP:

Portal venous phase

ROI:

Region of interest

RVI:

Radiogenomic venous invasion

SVM:

Support vector machine

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Funding

This study has received funding from the 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, 61231004) and National Key R&D Program of China (2017YFA0205200, 2017YFC1309100).

Author information

Author notes

  1. Xiaohong Ma and Jingwei Wei contributed equally to this work.

Authors and Affiliations

  1. 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

    Xiaohong Ma, Yongjian Zhu, Bing Feng, Meng Liang, Shuang Wang & Xinming Zhao

  2. Key Laboratory of Molecular Imaging, Chinese Academy of Sciences, Beijing, People’s Republic of China

    Jingwei Wei, Dongsheng Gu & Jie Tian

Authors
  1. Xiaohong Ma
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Corresponding authors

Correspondence to Xinming Zhao or Jie Tian.

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Guarantor

The scientific guarantor of this publication is Jie Tian.

Conflict of interest

The authors declare that they have no conflict of interest.

Statistics and biometry

Jingwei Wei kindly provided statistical advice for this manuscript.

One of the authors (Dongsheng Gu) has significant statistical expertise.

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was waived by the institutional review board.

Ethical approval

Institutional review board approval was obtained.

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• Retrospective

• Diagnostic or prognostic study

• Performed at one institution

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Ma, X., Wei, J., Gu, D. et al. Preoperative radiomics nomogram for microvascular invasion prediction in hepatocellular carcinoma using contrast-enhanced CT. Eur Radiol 29, 3595–3605 (2019). https://doi.org/10.1007/s00330-018-5985-y

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  • DOI: https://doi.org/10.1007/s00330-018-5985-y

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