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Utility of radiomics based on contrast-enhanced CT and clinical data in the differentiation of benign and malignant gallbladder polypoid lesions

  • Hepatobiliary
  • Published:
Abdominal Radiology Aims and scope Submit manuscript

Abstract

Purpose

To develop and validate a novel method based on radiomics for the preoperative differentiation of benign and malignant gallbladder polypoid lesions (PLG).

Patients and methods

A total of 145 patients with pathological proven gallbladder polypoid lesions ≥ 1 cm were included in this retrospective study. All the patients underwent abdominal contrast-enhanced computed tomography (CT) examinations 3 weeks before cholecystectomy from January 2013 to January 2019. Seventy percent of the cases were randomly selected for the training dataset, and 30% of the cases were independently used for testing. Radiomics features extracted from portal venous-phase CT of the PLG and clinical features were analyzed, and the LASSO regression algorithm was used for data dimension reduction. Multivariable logistic regression was used to generate radiomics signatures, clinical signatures, and combination signatures. The receiver operating characteristic (ROC) curve and decision curve were plotted to assess the differentiating performance of the three signatures.

Results

The area under the ROC curve (AUC) of the radiomics signature and clinical signature was 0.924 and 0.861 in the testing dataset, respectively. For the radiomics signature, the accuracy was 88.6%, with 88.0% specificity and 89.5% sensitivity. When combined, the AUC was 0.931, the specificity was 84.0%, and the sensitivity was 89.5%. The differences between the AUC values of the two sole models and the combination model were statistically nonsignificant.

Conclusion

Radiomics based on CT images can be helpful to differentiate benign and malignant gallbladder polyps ≥ 1 cm in size.

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Data availability

All authors have reviewed the final version of the paper and would like to take public responsibility for its content. The authors declare that they had full access to all of the data in this study and the authors take complete responsibility for the integrity of the data and the accuracy of the data analysis.

Abbreviations

3D:

Three-dimensional

AUC:

Area under the curve

CI:

Confidence interval

CT:

Computed tomography

DICOM:

Digital Imaging and Communications in Medicine

PLG:

Gallbladder polypoid lesions

ROC:

Receiver operating characteristic

ROI:

Region of interests

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Authors and Affiliations

  1. Department of Radiology, The First Affiliated Hospital of China Medical University, No.155 Nanjing Road Heping Area, Shenyang, 110000, Liaoning Province, China

    Xiaodong Yang, Yi Liu, Ruimei Chai, Meng Niu & Ke Xu

  2. GE Health, Shanghai, 200000, China

    Yan Guo

Authors
  1. Xiaodong Yang
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  2. Yi Liu
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  3. Yan Guo
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  4. Ruimei Chai
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  5. Meng Niu
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  6. Ke Xu
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Contributions

Xu and Niu contributed to the study design. Yang, Liu, and Chai carried out the collection and assembly of data and drafted the manuscript. Guo did the feature extraction statistical work. All authors reviewed the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Ke Xu.

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The authors declare that they have no competing interests.

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Ethical approval was obtained for this retrospective analysis, and the informed consent requirement was waved.

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Yang, X., Liu, Y., Guo, Y. et al. Utility of radiomics based on contrast-enhanced CT and clinical data in the differentiation of benign and malignant gallbladder polypoid lesions. Abdom Radiol 45, 2449–2458 (2020). https://doi.org/10.1007/s00261-020-02461-2

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  • DOI: https://doi.org/10.1007/s00261-020-02461-2

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