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Ultrasound-based radiomics score: a potential biomarker for the prediction of microvascular invasion in hepatocellular carcinoma

  • Ultrasound
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Abstract

Purpose

To develop an ultrasound (US)-based radiomics score for preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

Methods

Between January 1, 2012, and October 31, 2017, a total of 482 HCC patients who underwent contrast-enhanced ultrasound (CEUS) were retrospectively reviewed. The study population was divided into a training cohort (n = 341) and a validation cohort (n = 141) based on a cutoff time of January 1, 2016. Radiomics features were extracted from the grayscale US images of HCC. After features selection, a radiomics score was developed from the training cohort. The incremental value of the radiomics score to the clinic-pathological factors for MVI prediction was assessed in the validation cohort with respect to discrimination, calibration, and clinical usefulness.

Results

The US-based radiomics score consisted of six selected features. Multivariate logistic regression analysis showed that the radiomics score, alpha-fetoprotein (AFP), and tumor size were independent predictors of MVI. The radiomics nomogram (based on the three factors) showed better performance for MVI detection (area under the curve [AUC] 0.731[0.647, 0.815] than the clinical nomogram (based on AFP and tumor size) (0.634 [0.543, 0.724]) (p = 0.015). Both nomograms showed good calibration. Decision curve analysis demonstrated that in terms of clinical usefulness, the radiomics nomogram outperformed the clinical nomogram.

Conclusion

The US-based radiomics score was an independent predictor of MVI in HCC. Combining the radiomics score with clinical factors improved the prediction efficacy.

Key points

• Radiomics can be applied in US images.

• US-based radiomics score was an independent predictor of MVI.

• Radiomics nomogram incorporated with the radiomics score showed good performance for MVI prediction.

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Abbreviations

AFP:

Alpha-fetoprotein

ALB:

Albumin

ALT:

Alanine aminotransferase

AST:

Aspartate aminotransferase

AUC:

Area under the curve

CEUS:

Contrast-enhanced ultrasound

CT:

Computed tomography

DCA:

Decision curve analysis

HBsAg:

Hepatitis B virus surface antigen

HBV-DNA:

Hepatitis B virus DNA load

HCC:

Hepatocellular carcinoma

ICC:

Interclass correlation coefficient

LASSO:

Least absolute shrinkage and selection operator

MRI:

Magnetic resonance imaging

MVI:

Microvascular invasion

PLT:

Platelet

PT:

Prothrombin time

ROC:

Receiver operating curve

ROI:

Region of interest

US:

Ultrasound

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Acknowledgements

We acknowledge the following two pathologists for reviewing the specimen slices: Bing Liao and Li-li Chen (Department of Pathology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China).

Funding

This study was supported by “National Nature Science Foundation of China” (No: 81701701), “Guangdong Natural Science Foundation” (No: 2017A030313661), “Training Project for Young Teacher of Sun Yat-sen University” (No: 16YKPY37), and “Guangdong Science and Technology Foundation” (No: 2017A020215195).

Author information

Author notes

  1. Hang-tong Hu and Zhu Wang contributed equally to this work.

Authors and Affiliations

  1. Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, No. 58 Zhongshan Road 2, Guangzhou, People’s Republic of China

    Hang-tong Hu, Zhu Wang, Shu-ling Chen, Xin Zheng, Si-min Ruan, Xiao-yan Xie & Wei Wang

  2. Department of Ultrasonography, Zhongshan Hospital of Traditional Chinese Medicine, Affiliated to Guangzhou University of Chinese Medicine, Zhongshan, People’s Republic of China

    Xiao-wen Huang

  3. Division of Interventional Ultrasound and Department of Liver Surgery, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, People’s Republic of China

    Ming-de Lu & Ming Kuang

  4. Department of interventional Ultrasound, Chinese PLA General Hospital, Beijing, 100853, People’s Republic of China

    Jie Yu & Ping Liang

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

    Jie Tian

  6. Department of Hepatobiliary Surgery, The First Affiliated Hospital of Sun Yat-sen University, No. 58 Zhongshan Road 2, Guangzhou, 510080, Guangdong, People’s Republic of China

    Ming Kuang

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  1. Hang-tong Hu
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  2. Zhu Wang
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  12. Wei Wang
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Corresponding authors

Correspondence to Wei Wang or Ming Kuang.

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The scientific guarantor of this publication is Wei Wang.

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The authors declare that they have no conflict of interest.

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Written informed consent was waived by the Institutional Review Board.

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Institutional Review Board approval was obtained.

Methodology

• retrospective

• diagnostic or prognostic study

• performed at one institution

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Hu, Ht., Wang, Z., Huang, Xw. et al. Ultrasound-based radiomics score: a potential biomarker for the prediction of microvascular invasion in hepatocellular carcinoma. Eur Radiol 29, 2890–2901 (2019). https://doi.org/10.1007/s00330-018-5797-0

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