ArticleCancers2022
MRI- and Histologic-Molecular-Based Radio-Genomics Nomogram for Preoperative Assessment of Risk Classes in Endometrial Cancer.
Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 3 of them syntheses that pooled it.
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Who cites it
22 citing papers in PubMed, 3 syntheses or guidelines pooled it, 33 citations in OpenAlex.
- 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
- Preoperative magnetic resonance imaging-radiomics in cervical cancer: a systematic review and meta-analysis.Frontiers in oncology · 2024Pooled it
- Molecular and AI enabled prognostication in endometrial cancer a 2015 to 2024 bibliometric Atlas and critical review.Discover oncology · 2026Article
- AI-driven radiogenomics in gynecologic oncology: from radiological digital biopsy to a new paradigm in precision therapy.Frontiers in oncology · 2026Review
- Evaluate lymphovascular space invasion in endometrial cancer using diffusion-weighted imaging-based habitat imaging.Scientific reports · 2025Article
- Ultrasound based radiomics nomogram combined with clinical parameters to predict lymphovascular space invasion in endometrioid adenocarcinoma.Scientific reports · 2025Article
- A Nomogram for Preoperative Prediction of Tumor Aggressiveness and Lymphovascular Space Involvement in Patients with Endometrial Cancer.Journal of clinical medicine · 2025Article
- Development and validation of clinical-radiomics deep learning model based on MRI for endometrial cancer molecular subtypes classification.Insights into imaging · 2025Article
- Comparing survival outcomes between surgical and non-surgical treatments in patients with early-onset endometrial cancer and developing a nomogram to predict survival: a study based on Eastern and Western data sets.World journal of surgical oncology · 2025Article
- Exploratory Analysis of Radiomics and Pathomics in Uterine Corpus Endometrial Carcinoma.Scientific reports · 2024Article
- Both intra- and peri-tumoral radiomics signatures can be used to predict lymphatic vascular space invasion and lymphatic metastasis positive status from endometrial cancer MR imaging.Abdominal radiology (New York) · 2024Article
- Multimodal MRI-based radiomics models for the preoperative prediction of lymphovascular space invasion of endometrial carcinoma.BMC medical imaging · 2024Article
- Magnetic resonance imaging-based radiomics model for preoperative assessment of risk stratification in endometrial cancer.World journal of clinical cases · 2024Article
- Evaluation of multi-parameter MRI in preoperative staging of endometrial carcinoma.European journal of radiology open · 2024Article
- Segmentation method of magnetic resonance imaging brain tumor images based on improved UNet network.Translational cancer research · 2024Article
- Predictive Value of Magnetic Resonance Imaging in Risk Stratification and Molecular Classification of Endometrial Cancer.Cancers · 2024Article
- Artificial Intelligence and Radiomics for Endometrial Cancer MRI: Exploring the Whats, Whys and Hows.Journal of clinical medicine · 2023Review
- Impact of COVID-19 Pandemic on the Diagnostic and Therapeutic Management of Endometrial Cancer: A Monocentric Retrospective Comparative Study.Journal of clinical medicine · 2023Article
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Corrections and comments
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Authors and funding
24 authors at 6 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High- and low-risk endometrial carcinoma (EC) differ in whether or not a lymphadenectomy is performed. We aimed to develop MRI-based radio-genomic models able to preoperatively assess lymph-vascular space invasion (LVSI) and discriminate between low- and high-risk EC according to the ESMO-ESGO-ESTRO 2020 guidelines, which include molecular risk classification proposed by "ProMisE". This is a retrospective, multicentric study that included 64 women with EC who underwent 3T-MRI before a hysterectomy. Radiomics features were extracted from T2WI images and apparent diffusion coefficient maps (ADC) after manual segmentation of the gross tumor volume. We constructed a multiple logistic regression approach from the most relevant radiomic features to distinguish between low- and high-risk classes under the ESMO-ESGO-ESTRO 2020 guidelines. A similar approach was taken to assess LVSI. Model diagnostic performance was assessed via ROC curves, accuracy, sensitivity and specificity on training and test sets. The LVSI predictive model used a single feature from ADC as a predictor; the risk class model used two features as predictors from both ADC and T2WI. The low-risk predictive model showed an AUC of 0.74 with an accuracy, sensitivity, and specificity of 0.74, 0.76, 0.94; the LVSI model showed an AUC of 0.59 with an accuracy, sensitivity, and specificity of 0.60, 0.50, 0.61. MRI-based radio-genomic models are useful for preoperative EC risk stratification and may facilitate therapeutic management.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.