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https://www.selleckchem.com/products/ly333531.html To determine the capabilities of MRI-based traditional radiomics and computer-vision (CV) nomogram for predicting lymphovascular space invasion (LVSI) in patients with endometrial carcinoma (EC). A total of 184 women (mean age, 52.9±9.0 [SD] years; range, 28-82 years) with EC were retrospectively included. Traditional radiomics features and CV features were extracted from preoperative T2-weighted and dynamic contrast-enhanced MR images. Two models (Model 1, the radiomics model; Model 2, adding CV radiomics signature into the Model 1) were built. The performance of the models was evaluated by the area under the curve (AUC) of the receiver operator characteristic (ROC) in the training and test cohorts. A nomogram based on clinicopathological metrics and radiomics signatures was developed. The predictive performance of the nomogram was assessed by AUC of the ROC in the training and test cohorts. For predicting LVSI, the AUC values of Model 1 in the training and test cohorts were 0.79 (95% confidence intervtter clinical decision-making. MRI-based traditional radiomics and computer-vision nomogram are useful for preoperative risk stratification in patients with EC and may facilitate better clinical decision-making. Metastatic Leydig cell tumors (LCT) are rare, difficult-to-treat malignancies without known underlying molecular-genetic events. An index case of metastatic LCT showed an LDLR-TERT gene fusion upon routine genetic profiling for detection of therapeutic targets, which was then followed by an investigation into a cohort of additional LCTs. Twenty-nine LCT (27 male and 2 female patients) were profiled using next-generation sequencing and immunohistochemistry. TERT gene fusions were detected only in testicular metastatic LCTs, in 3 of 7 successfully analyzed cases (RMSTTERT, LDLRTERT, and B4GALT5TERT). TOP1 and CCND3 amplifications were identified in the case with a B4GALT5TERT fusion. A TP53 mutation was detected

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