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Performance of CT radiomics in predicting the overall survival of patients with stage III clear cell renal carcinoma after radical nephrectomy

  • Abdominal Radiology
  • Published:
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Abstract

Purpose

To investigate the performance of CT radiomics in predicting the overall survival (OS) of patients with stage III clear cell renal carcinoma (ccRCC) after radical nephrectomy.

Materials and methods

The 132 patients with stage III ccRCC undergoing radical nephrectomy were collected, and the patients were divided into training set (n = 79) and validation set (n = 53). The ccRCC was segmented and 396 radiomics features were extracted. After dimensionality reduction, radiomics score (RS) was obtained. COX regression was used to construct Model 1 (clinical variables + CT findings) and Model 2 (clinical variables + CT findings + RS) in the training set to predict the OS of patients, and then, the performance of the two models in the two data sets was compared.

Results

In the training set, Akaike information criterion, C-index, and corrected C-index were 295.51, 0.744, and 0.728 for Model 1, and 271.78, 0.805, and 0.799 for Model 2, respectively. In the validation set, the corresponding values were 185.68, 0.701, and 0.699 for Model 1, and 175.99, 0.768, and 0.768 for Model 2. The calibration curves showed that both models had good calibration degrees in the validation set. Compared with Model 1, the continuous net reclassification index and integrated discrimination improvement index of Model 2 in the two data sets were positively improved.

Conclusion

The two prediction models showed high performance in the evaluation of OS of stage III ccRCC patients after radical nephrectomy, among which Model 2 based on ISUP grade and RS was more concise and efficient.

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Abbreviations

RCC:

Renal cell carcinoma

ccRCC:

Clear cell RCC

OS:

Overall survival

ISUP:

International society of urological pathology

LASSO:

Least absolute shrinkage and selection operator

RS:

Radiomics score

AIC:

Akaike information criterion

NRI:

Net reclassification index

IDI:

Integrated discrimination improvement index

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Acknowledgements

We would like to thank Dr. Jian Ying Li of GE Healthcare, China, for his technique support and editing the article.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

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Authors and Affiliations

  1. Department of Medical Image, The First Affiliated Hospital of Xi’an Jiaotong University, No. 277 West Yanta Road, Xi’an, 710061, Shaanxi, China

    Dong Han & Xiaoyi Duan

  2. Department of Radiology, Affiliated Hospital of Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, China

    Dong Han, Nan Yu, Yong Yu & Taiping He

Authors
  1. Dong Han
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  2. Nan Yu
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  3. Yong Yu
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  4. Taiping He
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  5. Xiaoyi Duan
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Contributions

All authors contributed to the study conception and design. Dong Han and Xiaoyi Duan involved in conceptualization; Nan Yu and Yong Yu involved in methodology and software; Dong Han and Nan Yu involved in writing original draft; Taiping He and Xiaoyi Duan contributed to resources; Dong Han, Nan Yu, Yong Yu, Taiping He and Xiaoyi Duan involved in review and editing.

Corresponding author

Correspondence to Xiaoyi Duan.

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Conflict of Interests

The authors have no relevant financial or non-financial interests to disclose.

Ethics approval

This retrospective study was approved by the Affiliated Hospital of Shaanxi University of Chinese Medicine Institutional Ethics Committee (the approval document no.: SZFYIEC-PF-2019 no. [13]), and the consents from patients were waived.

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Han, D., Yu, N., Yu, Y. et al. Performance of CT radiomics in predicting the overall survival of patients with stage III clear cell renal carcinoma after radical nephrectomy. Radiol med 127, 837–847 (2022). https://doi.org/10.1007/s11547-022-01526-0

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  • DOI: https://doi.org/10.1007/s11547-022-01526-0

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