Abstract
Purpose
To develop and validate a model that incorporates radiomics based on MRI scans and clinical characteristics to predict lymphovascular invasion (LVSI) in endometrial cancer (EC) patients.
Methods
There were 332 patients with EC enrolled retrospectively in this multicenter study. Radiomics score (Radscore) were computed using the valuable radiomics features. The independent predictors of LVSI were identified by univariate logistic analysis. Multivariate logistic regression was used to develop a clinical–radiomics predictive model. Based on the model, a nomogram was developed and validated internally and externally. The nomogram was evaluated with discrimination, calibration, decision curve analysis (DCA), and clinical impact curves (CIC).
Results
Three predictive models were constructed based on clinicopathological features, radiomic factors and a combination of them, and that the clinic-radiomic model performed best among the three models. Four independent factors comprised the clinical–radiomics model: dynamic contrast enhancement rate of late arterial phase (DCE2), deep myometrium invasion (DMI), lymph node metastasis (LNM), and Radscore. Clinical–radiomics model performance was 0.901 (95% CI 0.84–0.96) in the training cohort, 0.80 (95% CI 0.68–0.92) in the internal validation cohort, and 0.81 (95% CI 0.73–0.9) in the external validation cohort for identifying patients with LVSI, respectively. The model is used to develop a nomogram for clinical use.
Conclusions
The MRI-based radiomics nomogram could serve as a noninvasive tool to predict LVSI in EC patients.
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Data availability
The data that support the findings of this study are available on request from the corresponding author.
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Acknowledgements
The authors greatly appreciate all the patients and their families for participating in this trial. We also express our gratitude to the staffs from our Hospital for their selfless dedication. The authors would like to thank the clinicians in the Department of Radiology, The Affiliated Hospital of Nanjing University of Chinese Medicine for their professional clinical advice.
Funding
This work is funded by National Natural Science Foundation of China, Grant/Award Number: 82171925; Developing Program for High-level Academic Talent in Jiangsu Hospital of TCM, Grant/Award Number: y2021rc03.
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We are so glad to submit our paper to “Journal of Cancer Research and Clinical Oncology”. In this research, XW, HL and LS contributed significantly to analysis and manuscript preparation; JC, XW, WZ and YT performed the data analyses and wrote the manuscript; ZW helped perform the analysis with constructive discussions. All the authors reviewed the manuscript, provided feedback, and approved the manuscript in its final form.
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432_2023_5044_MOESM1_ESM.tif
Supplementary file1 Figure S1 The calibration curves of the clinical-radiomics nomogram in the training, internal validation and external validation cohorts. (TIF 3067 KB)
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Chen, J., Wang, X., Lv, H. et al. Development and external validation of a clinical–radiomics nomogram for preoperative prediction of LVSI status in patients with endometrial carcinoma. J Cancer Res Clin Oncol 149, 13943–13953 (2023). https://doi.org/10.1007/s00432-023-05044-y
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DOI: https://doi.org/10.1007/s00432-023-05044-y