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Development and validation of a CT-based nomogram for preoperative prediction of clear cell renal cell carcinoma grades

European Radiology volume 31, pages 6078–6086 (2021)Cite this article

Abstract

Objectives

Nuclear grades are proved to be one of the most significant prognostic factors for clear cell renal cell carcinoma (ccRCC). Radiomics nomogram is a widely used noninvasive tool that could predict tumor phenotypes. In this study, we performed radiomics analysis to develop and validate a CT-based nomogram for the preoperative prediction of nuclear grades in ccRCC.

Method

CT images and clinical data of 258 ccRCC patients were retrieved from the Cancer Imaging Archive (TCIA). Radiomics features were extracted from arterial-phase CT images using 3D Slicer software. LASSO regression model was performed to develop a radiomics signature in the training set (n = 143). A radiomics nomogram was constructed combining radiomics signature and selected clinical predictors. Receiver operating characteristic (ROC) curve and calibration curve were used to determine the performance of the radiomics nomogram in the training and validation set (n = 115). Decision curve analysis was used to assess the clinical usefulness of the CT-based nomogram.

Results

One thousand three hundred sixteen radiomics features were extracted from arterial-phase CT images. A radiomics signature, consisting of 20 features, was developed and showed a favorable performance in discriminating nuclear grades with an area under the curve (AUC) of 0.914 and 0.846 in the training and validation set, respectively. The CT-based nomogram, including the radiomics signature and the CT-determined T stage, achieved good calibration and discrimination in the training set (AUC, 0.929; 95% CI, 0.886–0.972) and validation set (AUC, 0.876; 95% CI, 0.812–0.939). Decision curve analysis demonstrated the clinical usefulness of the CT-based nomogram.

Conclusion

The noninvasive CT-based nomogram, including radiomics signature and CT-determined T stage, could improve the accuracy of preoperative grading of ccRCC and provide individualized treatment for ccRCC patients.

Key Points

• Contrast-enhanced CT may help in preoperative grading of ccRCC.

• The CT-based nomogram incorporated a radiomics signature and CT-determined T stage could preoperatively predict ccRCC grades.

• The CT-based nomogram has the potential to improve individualized treatment and assist clinical decision making of ccRCC patients.

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Abbreviations

AUC:

Area under the curve

ccRCC:

Clear cell renal cell carcinoma

CI:

Confidence interval

CT:

Computed tomography

LASSO:

The least absolute shrinkage and selection operator

MRI:

Magnetic resonance imaging

PET-CT:

Positron emission tomography-computed tomography

RCC:

Renal cell carcinoma

ROC:

Receiver operating characteristic

ROI:

Region of interest

TCIA:

The Cancer Imaging Archive

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Acknowledgments

We thank The Cancer Imaging Archive (TCIA) and The Cancer Genome Atlas (TCGA) for the computed tomography data sets.

Funding

This study was supported by the National Natural Science Foundation of China (No. 81672534).

Author information

Affiliations

  1. Department of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China

    Zaosong Zheng, Zhiliang Chen, Yingwei Xie, Qiyu Zhong & Wenlian Xie

  2. Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China

    Zaosong Zheng, Zhiliang Chen, Yingwei Xie & Qiyu Zhong

Authors
  1. Zaosong Zheng
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  2. Zhiliang Chen
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  3. Yingwei Xie
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  5. Wenlian Xie
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Corresponding author

Correspondence to Wenlian Xie.

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Guarantor

The scientific guarantor of this publication is Wenlian Xie.

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

No complex statistical methods were necessary for this paper.

Informed consent

Informed consent was not required since TCIA data contained no personal identifying information.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• Retrospective

• Diagnostic or prognostic study

• Performed at one institution

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Zheng, Z., Chen, Z., Xie, Y. et al. Development and validation of a CT-based nomogram for preoperative prediction of clear cell renal cell carcinoma grades. Eur Radiol 31, 6078–6086 (2021). https://doi.org/10.1007/s00330-020-07667-y

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  • DOI: https://doi.org/10.1007/s00330-020-07667-y

Keywords

  • Tomography
  • Nomograms
  • Renal cell carcinoma
  • Neoplasm grading