ArticleFrontiers in oncology2021
Combination Analysis of a Radiomics-Based Predictive Model With Clinical Indicators for the Preoperative Assessment of Histological Grade in Endometrial Carcinoma.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 3 of them syntheses that pooled it.
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18 citing papers in PubMed, 3 syntheses or guidelines pooled it, 26 citations in OpenAlex.
- Preoperative risk assessment of invasive endometrial cancer using MRI-based radiomics: a systematic review and meta-analysis.Abdominal radiology (New York) · 2025Pooled it
- Application of magnetic resonance imaging radiomics in endometrial cancer: a systematic review and meta-analysis.La Radiologia medica · 2024Pooled it
- Accuracy of radiomics in the diagnosis and preoperative high-risk assessment of endometrial cancer: a systematic review and meta-analysis.Frontiers in oncology · 2024Pooled it
- 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
- Multi-sequence MRI-based clinical-radiomics models for the preoperative prediction of microsatellite instability-high status in endometrial cancer.Precision radiation oncology · 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
- Exploratory Analysis of Radiomics and Pathomics in Uterine Corpus Endometrial Carcinoma.Scientific reports · 2024Article
- MRI Radiomics Data Analysis for Differentiation between Malignant Mixed Müllerian Tumors and Endometrial Carcinoma.Cancers · 2024Article
- Predicting Risk Stratification in Early-Stage Endometrial Carcinoma: Significance of Multiparametric MRI Radiomics Model.Journal of imaging informatics in medicine · 2024Article
- Radiomics model based on multi-sequence MRI for preoperative prediction of ki-67 expression levels in early endometrial cancer.Scientific reports · 2023Article
- Radiomics-guided prognostic assessment of early-stage hepatocellular carcinoma recurrence post-radical resection.Journal of cancer research and clinical oncology · 2023Article
- Radiomics-based fertility-sparing treatment in endometrial carcinoma: a review.Insights into imaging · 2023Review
- Multiparametric magnetic resonance imaging-based radiomics nomogram for predicting tumor grade in endometrial cancer.Frontiers in oncology · 2023Article
- Different multiparametric MRI-based radiomics models for differentiating stage IA endometrial cancer from benign endometrial lesions: A multicenter study.Frontiers in oncology · 2022Article
- External validation study of endometrial cancer preoperative risk stratification model (ENDORISK).Frontiers in oncology · 2022Article
- MRI-based radiomics and ADC values are related to recurrence of endometrial carcinoma: a preliminary analysis.BMC cancer · 2021Article
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHistological grade is one of the most important prognostic factors of endometrial carcinoma (EC) and when selecting preoperative treatment methods, conducting accurate preoperative grading is of great significance. PURPOSE: To develop a magnetic resonance imaging (MRI) radiomics-based nomogram for discriminating histological grades 1 and 2 (G1 and G2) from grade 3 (G3) EC.
methodsThis was a retrospective study included 358 patients with histologically graded EC, stratified as 250 patients in a training cohort and 108 patients in a test cohort. T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI) and a dynamic contrast-enhanced three-dimensional volumetric interpolated breath-hold examination (3D-VIBE) were performed
resultsAll three models showed some amount of predictive ability. Using ADC alone to predict the histological risk of EC was limited in both the cohort [area under the curve (AUC), 0.715; 95% confidence interval (CI), 0.6509-0.7792] and test cohorts (AUC, 0.621; 95% CI, 0.515-0.726). In comparison with Model
conclusionThe described radiomics-based nomogram can be used to predict EC histological classification preoperatively.
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