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Analysis of Sonazoid contrast-enhanced ultrasound for predicting the risk of microvascular invasion in hepatocellular carcinoma: a prospective multicenter study

  • Ultrasound
  • Published:
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Abstract

Objectives

The aim of this study was to evaluate the potential of Sonazoid contrast-enhanced ultrasound (SNZ-CEUS) as an imaging biomarker for preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

Methods

From August 2020 to March 2021, we conducted a prospective multicenter study on the clinical application of Sonazoid in liver tumor; a MVI prediction model was developed and validated by integrating clinical and imaging variables. Multivariate logistic regression analysis was used to establish the MVI prediction model; three models were developed: a clinical model, a SNZ-CEUS model, and a combined model and conduct external validation. We conducted subgroup analysis to investigate the performance of the SNZ-CEUS model in non-invasive prediction of MVI.

Results

Overall, 211 patients were evaluated. All patients were split into derivation (n = 170) and external validation (n = 41) cohorts. Patients who had MVI accounted for 89 of 211 (42.2%) patients. Multivariate analysis revealed that tumor size (> 49.2 mm), pathology differentiation, arterial phase heterogeneous enhancement pattern, non-single nodular gross morphology, washout time (< 90 s), and gray value ratio (≤ 0.50) were significantly associated with MVI. Combining these factors, the area under the receiver operating characteristic (AUROC) of the combined model in the derivation and external validation cohorts was 0.859 (95% confidence interval (CI): 0.803–0.914) and 0.812 (95% CI: 0.691–0.915), respectively. In subgroup analysis, the AUROC of the SNZ-CEUS model in diameter  ≤ 30 mm and ˃ 30 mm cohorts were 0.819 (95% CI: 0.698–0.941) and 0.747 (95% CI: 0.670–0.824).

Conclusions

Our model predicted the risk of MVI in HCC patients with high accuracy preoperatively.

Clinical relevance statement

Sonazoid, a novel second-generation ultrasound contrast agent, can accumulate in the endothelial network and form a unique Kupffer phase in liver imaging. The preoperative non-invasive prediction model based on Sonazoid for MVI is helpful for clinicians to make individualized treatment decisions.

Key Points

• This is the first prospective multicenter study to analyze the possibility of SNZ-CEUS preoperatively predicting MVI.

• The model established by combining SNZ-CEUS image features and clinical features has high predictive performance in both derivation cohort and external validation cohort.

• The findings can help clinicians predict MVI in HCC patients before surgery and provide a basis for optimizing surgical management and monitoring strategies for HCC patients.

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Abbreviations

AP:

Arterial phase

AUROC:

Area under the receiver operating characteristic

CEUS:

Contrast-enhanced ultrasonography

CI:

Confidence interval

DP:

Delay phase

HCC:

Hepatocellular carcinoma

KP:

Kupffer phase

MVI:

Microvascular invasion

OR:

Odds ratio

PVP:

Portal venous phase

ROI:

Region of interest

SNZ-CEUS:

Sonazoid contrast-enhanced ultrasound

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Acknowledgements

We would like to acknowledge the effort of clinical data collection from Pingping Zhou (Affiliated Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology), Jinshu Pang (the First Affiliated Hospital of Guangxi Medical University), Wenhan Xu (Huashan Hospital, Fudan University), Ling Gao (West China Hospital, Sichuan University), Qiannan Huang (the Third Affiliated Hospital of Sun Yat-sen University), Rui Zhang (the First Affiliated Hospital of Sun Yat-sen University), Kun Zhao (Peking University Cancer Hospital & Institute), and Xu Wang (the Third Central Hospital of Tianjin).

Funding

This study was funded by the National Natural Science Foundation of China (Grant No. 92159305, 82227804, 82172027).

Author information

Author notes

  1. X.L.Y., P.L., and Z.Y.H. contributed equally to this work as co-corresponding authors.

Authors and Affiliations

  1. Department of Interventional Ultrasound, First Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China

    Jundong Yao, Shuo Wang, Yiqiong Zhang, Yunlin Li, Erpeng Qi & XiaoLing Yu

  2. Chinese PLA Medical School, Beijing, 100853, China

    Jundong Yao

  3. Department of Ultrasound Imaging, Affiliated Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China

    Kaiyan Li

  4. Department of Ultrasound, the First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, China

    Hong Yang

  5. Department of Hepatobiliary Surgery, First Medical Center of Chinese PLA General Hospital, Beijing, 100853, China

    Shichun Lu

  6. Department of Ultrasound, Huashan Hospital, Fudan University, Shanghai, 200040, China

    Hong Ding

  7. Department of Ultrasound, West China Hospital, Sichuan University, Chengdu, 610041, China

    Yan Luo

  8. Department of Ultrasound, the Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, China

    Kai Li

  9. Department of Ultrasound, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, China

    Xiaoyan Xie

  10. Department of Ultrasound, Peking University Cancer Hospital & Institute, Beijing, 100142, China

    Wei Wu

  11. Department of Ultrasound, the Third Central Hospital of Tianjin, Tianjin, 300170, China

    Xiang Jing

  12. Department of Interventional Ultrasound, Fifth Medical Center of Chinese PLA General Hospital, No. 28 Fuxing Road, Beijing, 100853, China

    Fangyi Liu, Jie Yu, Zhigang Cheng, Shuilian Tan, Jianping Dou, XueJuan Dong, Zhiyu Han & Ping Liang

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  1. Jundong Yao
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Corresponding authors

Correspondence to Zhiyu Han, Ping Liang or XiaoLing Yu.

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Guarantor

The scientific guarantor of this publication is XiaoLing Yu.

Conflict of interest

The authors of this manuscript declare no competing interests.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was obtained from all patients in this study.

Ethical approval

The study protocol was approved by the Institutional Review Boards of PLA General Hospital S2020-300-01.

Methodology

• prospective

• diagnostic or prognostic study

• multicenter study

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Yao, J., Li, K., Yang, H. et al. Analysis of Sonazoid contrast-enhanced ultrasound for predicting the risk of microvascular invasion in hepatocellular carcinoma: a prospective multicenter study. Eur Radiol 33, 7066–7076 (2023). https://doi.org/10.1007/s00330-023-09656-3

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