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Radiomics using CT images for preoperative prediction of futile resection in intrahepatic cholangiocarcinoma

  • Computed Tomography
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

To investigate and compare radiomics and clinical information for preoperative prediction of futile resection in intrahepatic cholangiocarcinoma (ICC).

Methods

A total of 203 ICC patients from two centers were included and randomly allocated with a ratio of 7:3 into the training cohort and the validation cohort. Clinical characteristics and radiomics features were selected using random forest algorithm and logistic models to construct a clinical model and a radiomics model, respectively. A combined logistic model that incorporated the developed radiomics signature and clinical risk factors was then built. The performance of these models was evaluated and compared by plotting the receiver operating characteristic (ROC) curve and calculating the area under the curve (AUC).

Results

The radiomics model showed a higher AUC than the clinical model in the validation cohort (AUC: 0.804 (95% CI: 0.697, 0.912) vs. 0.590 (95% CI: 0.415, 0.765), p = 0.043) for predicting futile resection in ICC. The radiomics model reached a sensitivity of 0.846 (95% CI: 0.546, 0.981) and a specificity of 0.771 (95% CI: 0.627, 0.880) in the validation cohort. Moreover, the radiomics model had comparable AUCs with the combined model in training and validation cohorts.

Conclusions

We presented an internally validated radiomics model for the prediction of futile resection in ICC patients. Compared with clinical information, radiomics using CT images had greater potential for predicting futile resection accurately before surgery.

Key Points

• Radiomics model using CT images could predict futile resection in intrahepatic cholangiocarcinoma preoperatively.

• Radiomics model using CT images was superior to clinical information for predicting futile resection accurately before surgery.

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Abbreviations

AFP:

Alpha-fetoprotein

ALB:

Albumin

ALT:

Alanine transaminase

AST:

Aspartate aminotransferase

AUC:

Area under the curve

BTC:

Biliary tract cancer

CA19-9:

Carbohydrate antigen CA19-9

CEA:

Carcinoembryonic antigen

CT:

Computerized tomography

DBIL:

Direct bilirubin

Hb:

Hemoglobin

HBsAg:

Hepatitis B surface antigen

ICC:

Intrahepatic cholangiocarcinoma

NLR:

Neutrophil to lymphocyte ratio

NPV:

Negative predictive value

OS:

Overall survival

PLT:

Platelet count

PPV:

Positive predictive value

PT:

Prothrombin time

ROC:

Receiver operating characteristic curve

ROI:

Regions of interest

TB:

Total bilirubin

WBC:

White blood cell count

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Acknowledgments

This study was funded by the Science and Technology Program of Guangzhou, China (No. 201704020215). Ming Kuang, working in the First Affiliated Hospital of Sun Yat-sen University, was the guarantor of this study.

Funding

This study has received funding from the Science and Technology Program of Guangzhou, China (No. 201704020215).

Author information

Author notes

  1. Hongpeng Chu and Zelong Liu contributed equally to this work.

Authors and Affiliations

  1. Department of Liver Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China

    Hongpeng Chu, Ying Zhang, Kai Lei & Ming Kuang

  2. Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, 58 Zhong Shan Road 2, Guangzhou, 510080, China

    Zelong Liu, Shuling Chen & Ming Kuang

  3. Department of Radiology, The Zhu Jiang Hospital of Southern Medical University, Guangzhou, China

    Wen Liang

  4. Clinical Trial Unit, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China

    Qian Zhou, Yiheng Cao & Sui Peng

  5. Department of Radiology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China

    Mimi Tang

  6. Department of Gastroenterology and Hepatology, The First Affiliated Hospital of Sun Yat-sen University, 58 Zhong Shan Road 2, Guangzhou, 510080, China

    Sui Peng

Authors
  1. Hongpeng Chu
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  2. Zelong Liu
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  3. Wen Liang
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  4. Qian Zhou
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  5. Ying Zhang
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  6. Kai Lei
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  7. Mimi Tang
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  8. Yiheng Cao
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  9. Shuling Chen
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  10. Sui Peng
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  11. Ming Kuang
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Corresponding authors

Correspondence to Sui Peng or Ming Kuang.

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Guarantor

The scientific guarantor of this publication is Ming Kuang.

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

Qian Zhou, one of the authors has significant statistical expertise.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• retrospective

• observational

• multicenter study

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Chu, H., Liu, Z., Liang, W. et al. Radiomics using CT images for preoperative prediction of futile resection in intrahepatic cholangiocarcinoma. Eur Radiol 31, 2368–2376 (2021). https://doi.org/10.1007/s00330-020-07250-5

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  • DOI: https://doi.org/10.1007/s00330-020-07250-5

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