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Intra- and peritumoral radiomics for predicting early recurrence in patients with high-grade serous ovarian cancer

  • Special Section: Ovarian Cancer
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Abstract

Purpose

To explore values of intra- and peritumoral CT-based radiomics for predicting recurrence in high-grade serous ovarian cancer (HGSOC) patients.

Methods

This study enrolled 110 HGSOC patients from our hospital between Aug 2017 and Apr 2021. All patients underwent contrast-enhanced CT scans before treatment. The least absolute shrinkage and selection operator (LASSO) regression was used to select radiomics features from intra- and peritumoral areas. Radiomics signatures were built based on selected features from Intra-RS, Peri-RS, and in Com-RS. A nomogram was constructed by combining radiomics signatures and clinical parameters with predictive potential. Receiver operating characteristics (ROC), calibration, and decision curve analyses (DCA) curves were used to evaluate performance of the nomogram.

Results

The intra- and peritumoral combined Com-RS showed effective ability in predicting recurrent HGSOC in the training (AUCs, Intra-RS vs. Peri-RS vs. Com-RS, 0.861 vs. 0.836 vs. 899) and validation (AUCs, Intra-RS vs. Peri-RS vs. Com-RS, 0.788 vs. 0.762 vs. 815) cohort. The Federation of International of FIGO stage, menstruation, and location were found to be strongly associated with tumor recurrence. The nomogram has the best predictive ability in the training (AUCs, Com-RS vs. clinical model vs. nomogram, 0.899 vs. 0.648 vs. 0.901) and validation (AUCs, Com-RS vs. clinical model vs. nomogram, 0.815 vs. 0.666 vs. 0.818) cohort.

Conclusion

Our findings suggested values of intra- and peritumoral-based radiomics for predicting recurrent HGSOC. The constructed nomogram may be of importance in clinical application.

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Funding

This work was supported by the Natural Science Foundation of Liaoning Province (2021-MS-205), the China National Natural Science Foundation (31770147), Soft Science Research Program of Liaoning Province (2021JH4/10100037), and the Beijing Health Alliance Charitable Foundation (BJHA-CRP-018).

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Author notes

  1. Yujiao Wu and Wenyan Jiang have contributed equally to this work.

Authors and Affiliations

  1. Department of Biomedical Engineering, School of Intelligent Medicine, China Medical University, Shenyang, 110122, People’s Republic of China

    Yujiao Wu, Langyuan Fu, Meihong Ren & Hua Ai

  2. Department of Scientific Research and Academic, Liaoning Cancer Hospital and Institute, Cancer Hospital of China Medical University, Shenyang, 110042, People’s Republic of China

    Wenyan Jiang

  3. Department of Gynecology, Liaoning Cancer Hospital and Institute, Cancer Hospital of China Medical University, Shenyang, 110042, People’s Republic of China

    Xingling Wang

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  1. Yujiao Wu
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Contributions

YW and XW contributed to study design, WJ, LF, MR, HA, and YW contributed to data collection. YW and WJ contributed to data analysis and interpretation. YW and XW contributed to manuscript writing. XW and HA contributed to funding acquisition. All authors contributed to the article and approved the submitted version.

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Correspondence to Xingling Wang.

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Wu, Y., Jiang, W., Fu, L. et al. Intra- and peritumoral radiomics for predicting early recurrence in patients with high-grade serous ovarian cancer. Abdom Radiol 48, 733–743 (2023). https://doi.org/10.1007/s00261-022-03717-9

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