ArticleFrontiers in oncology2023
Multiparametric magnetic resonance imaging-based radiomics nomogram for predicting tumor grade in endometrial cancer.
Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.
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13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 16 citations in OpenAlex.
- Evaluating the quality of radiomics-based studies for endometrial cancer using RQS and METRICS tools.European radiology · 2025Pooled it
- Application of magnetic resonance imaging radiomics in endometrial cancer: a systematic review and meta-analysis.La Radiologia medica · 2024Pooled it
- A 3T Magnetic Resonance Fractional Order Calculus Model for the Diagnosis and Grading of Endometrial Cancer.Current medical imaging · 2026Article
- MRI-Based Habitat Radiomics for Differentiating Early-Stage Endometrial Carcinoma from Submucous Leiomyoma: A Multicenter Validation Study.Journal of Cancer · 2026Article
- Integrative intratumoral and peritumoral radiomic model for predicting endometrial cancer grade.Oncology letters · 2025Article
- Artificial Intelligence in Obstetric and Gynecological MR Imaging.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025Review
- The value of nomogram analysis in predicting pulmonary metastasis in hepatic alveolar echinococcosis.Scientific reports · 2025Article
- Nomogram prediction of molecular characteristics in WHO grade 3-4 diffuse gliomas based on fractal analysis and VASARI features.Scientific reports · 2025Article
- Contrast-enhanced MRI and CT in evaluating treatment response for recurrent endometrial cancer: a retrospective case-control study.American journal of cancer research · 2025Article
- Multiparametric MRI-based radiomics and deep learning for differentiating uterine serous carcinoma from endometrioid carcinoma: a multicenter retrospective study.Frontiers in oncology · 2025Article
- Preoperative prediction of aggressive endometrial cancer using multiparametric MRI-based deep transfer learning models.Frontiers in oncology · 2025Article
- Intratumoral and peritumoral multiparametric MRI-based radiomics nomogram for preoperative risk stratification in patients with endometrial cancer.Frontiers in oncology · 2025Article
- An ultrasound-based radiomics model for survival prediction in patients with endometrial cancer.Journal of medical ultrasonics (2001) · 2023Article
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7 authors at 1 institution in 1 country.
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Abstract
Background: Tumor grade is associated with the treatment and prognosis of endometrial cancer (EC). The accurate preoperative prediction of the tumor grade is essential for EC risk stratification. Herein, we aimed to assess the performance of a multiparametric magnetic resonance imaging (MRI)-based radiomics nomogram for predicting high-grade EC. Methods: One hundred and forty-three patients with EC who had undergone preoperative pelvic MRI were retrospectively enrolled and divided into a training set ( Results: In total, 35/143 patients had high-grade EC and 108 had low-grade EC. The areas under the ROC curves of the clinical model, rad-score, and radiomics nomogram were 0.837 (95% confidence interval [CI]: 0.754-0.920), 0.875 (95% CI: 0.797-0.952), and 0.923 (95% CI: 0.869-0.977) for the training set; 0.857 (95% CI: 0.741-0.973), 0.785 (95% CI: 0.592-0.979), and 0.914 (95% CI: 0.827-0.996) for the validation set, respectively. The radiomics nomogram showed a good net benefit according to the DCA. NRIs were 0.637 (0.214-1.061) and 0.657 (0.079-1.394), and IDIs were 0.115 (0.077-0.306) and 0.053 (0.027-0.357) in the training set and validation set, respectively. Conclusion: The radiomics nomogram based on multiparametric MRI can predict the tumor grade of EC before surgery and yield a higher performance than that of dilation and curettage.
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