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Gd-EOB-DTPA-enhanced MRI radiomics to predict vessels encapsulating tumor clusters (VETC) and patient prognosis in hepatocellular carcinoma

  • Hepatobiliary-Pancreas
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

The study was to develop a Gd-EOB-DTPA-enhanced MRI radiomics model for preoperative prediction of VETC and patient prognosis in hepatocellular cancer (HCC).

Methods

The study included 182 (training cohort: 128; validation cohort: 54) HCC patients who underwent preoperative Gd-EOB-DTPA-enhanced MRI. Volumes of interest including intratumoral and peritumoral regions were manually delineated in the hepatobiliary phase images, from which 1316 radiomics features were extracted. The least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression were used to select the useful features. Clinical, intratumoral, peritumoral, combined radiomics, and clinical radiomics models were established using machine learning algorithms. The Kaplan–Meier survival analysis was used to assess early recurrence and progression-free survival (PFS) in the VETC + and VETC- patients.

Results

In the validation cohort, the area under the curves (AUCs) of radiomics models were higher than that of the clinical model using random forest (all p < 0.05). The peritumoral radiomics model (AUC = 0.972;95% confidence interval [CI]:0.887–0.998) had significantly higher AUC than intratumoral model (AUC = 0.919; 95% CI: 0.811–0.976) (p = 0.044). There were no significant differences in AUC between intratumoral or peritumoral radiomics model (PR) and combined radiomics model (p > 0.05). Early recurrence and PFS were significantly different between the PR-predicted VETC + and VETC- HCC patients (p < 0.05). PR-predicted VETC was independent predictor of early recurrence (hazard ratio [HR]: 2.08[1.31–3.28]; p = 0.002) and PFS (HR: 1.95[1.20–3.17]; p = 0.007).

Conclusions

The intratumoral or peritumoral radiomics model may be useful in predicting VETC and patient prognosis preoperatively. The peritumoral radiomics model may yield an incremental value over intratumoral model.

Key Points

• Radiomics models are useful for predicting vessels encapsulating tumor clusters (VETC) and patient prognosis preoperatively.

• Peritumoral radiomics model may yield an incremental value over intratumoral model in prediction of VETC.

• Peritumoral radiomics-model-predicted VETC was an independent predictor of early recurrence and progression-free survival.

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Abbreviations

3D VIBE:

Three-dimensional volume interpolated breath-hold examination

AFP:

Alpha-fetoprotein

ALT:

Alanine aminotransferase

AST:

Aspartate aminotransferase

AUC:

Area under the receiver operating characteristic curve

CI:

Confidence interval

Gd-EOB-DTPA:

Gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid

Glcm:

Gray level co-occurrence matrix

Gldm:

Gray level dependence matrix

Glrlm:

Gray level run length matrix

Glszm:

Gray level size zone matrix

HCC:

Hepatocellular carcinoma

HR:

Hazard ratio

ICC:

Intra-class correlation coefficient

IQR:

Interquartile range

LASSO:

Least absolute shrinkage and selection operator

LoG:

Laplacian of gaussian

MVI:

Microvascular invasion

Ngtdm:

Neighboring gray tone difference matrix

PFS:

Progression-free survival

PR:

Peritumoral radiomics model

SVM:

Support vector machine

VETC:

Vessels encapsulating tumor clusters

VOI:

Volume of interest

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (81801692) and Suzhou Municipal Science and Technology Bureauand (SYS2020125, SS2019057, SS201808).

Funding

This study has received funding from the National Natural Science Foundation of China (81801692) and Suzhou Municipal Science and Technology Bureauand (SYS2020125, SS2019057, SS201808).

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Author notes

  1. Yixing Yu and Yanfen Fan contributed equally to this work.

Authors and Affiliations

  1. Department of Radiology, the First Affiliated Hospital of Soochow University, No.188, Shi Zi Street, Suzhou, 215006, Jiangsu, China

    Yixing Yu, Yanfen Fan, Ximing Wang, Mo Zhu, Mengjie Hu, Cen Shi & Chunhong Hu

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  1. Yixing Yu
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  2. Yanfen Fan
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  3. Ximing Wang
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  4. Mo Zhu
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  7. Chunhong Hu
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Corresponding author

Correspondence to Chunhong Hu.

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Guarantor

The scientific guarantor of this publication is Chunhong Hu.

Conflict of interest

The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

Ximing Wang kindly provided statistical advice for this manuscript.

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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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Yu, Y., Fan, Y., Wang, X. et al. Gd-EOB-DTPA-enhanced MRI radiomics to predict vessels encapsulating tumor clusters (VETC) and patient prognosis in hepatocellular carcinoma. Eur Radiol 32, 959–970 (2022). https://doi.org/10.1007/s00330-021-08250-9

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  • DOI: https://doi.org/10.1007/s00330-021-08250-9

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