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Background: High-and low-risk endometrial cancer (EC) differ in whether lymphadenectomy is performed. Assessment of high-risk EC is essential for planning surgery appropriately. Purpose: To develop a radiomics nomogram for high-risk EC prediction preoperatively. Study Type: Retrospective. Population: In all, 717 histopathologically confirmed EC patients (mean age, 56 years AE 9) divided into a primary group (394 patients from Center A), validation groups 1 and 2 (146 patients from Center B and 177 patients from Centers C-E). Field Strength/Sequence: 1.5/3T scanners; T 2-weighted imaging, diffusion-weighted imaging, apparent diffusion coefficient, and contrast enhancement sequences. Assessment: A radiomics nomogram was generated by combining the selected radiomics features and clinical parameters (metabolic syndrome, cancer antigen 125, age, tumor grade following curettage, and tumor size). The area under the curve (AUC) of the receiver operator characteristic was used to evaluate the predictive performance of the radiomics nomogram for high-risk EC. The surgical procedure suggested by the nomogram was compared with the actual procedure performed for the patients. Net benefit of the radiomics nomogram was evaluated by a clinical decision curve (CDC), net reclassification index (NRI), and integrated discrimination improvement (IDI). Statistical Tests: Binary least absolute shrinkage and selection operator (LASSO) logistic regression, linear regression, and multivariate binary logistic regression were used to select radiomics features and clinical parameters. Results: The AUC for prediction of high-risk EC for the radiomics nomogram in the primary group, validation groups 1 and 2 were 0.896 (95% confidence interval [CI]: 0.866-0.926), 0.877 (95% CI: 0.825-0.930), and 0.919 (95% CI: 0.879-0.960), respectively. The nomogram achieved good net benefit by CDC analysis for high-risk EC. NRIs were 1.17, 1.28, and 1.51, and IDIs were 0.41, 0.60, and 0.61 in the primary group, validation groups 1 and 2, respectively. Data Conclusion: The radiomics nomogram exhibited good performance in the individual prediction of high-risk EC, and might be used for surgical management of EC. Level of Evidence: 4 Technical Efficacy Stage: 2

BackgroundA solitary necrotic nodule (SNN) of the liver is an uncommon lesion, which is different from primary and metastatic liver cancers.ObjectivesTo analyze the classification, CT and MR manifestation, and the pathological basis of solitary necrotic nodule of the liver (SNN) in order to evaluate CT and MRI as a diagnosing tool.Patients and MethodsThis study included 29 patients with liver SNNs, out of which 14 had no clinical symptoms and were discovered by routine ultrasound examinations, six were found by computed tomography (CT) due to abdominal illness, four had ovarian tumors, and five had gastrointestinal cancer surgeries, previously. Histologically, these SNNs can be divided into three subtypes, i.e., type I, pure coagulation necrosis (14 cases); type II, coagulation necrosis mixed with liquefaction necrosis (five cases); and type III, multi-nodular fusion (10 cases). CT and magnetic resonance imaging (MRI) patterns were shown to be associated with SNN histology. All patients were treated surgically with good prognosis.ResultsCT and MRI appearance and correlation with pathology types: three subtypes of lesions were hypo-density on both pre contrast and post contrast CT, 12 lesions were found the enhanced capsule and 1 lesion of multi- nodular fusion type showed septa enhancement. The lesions were hypo-intensity on T2WI and the lesions of type II showed as mixed hyperintensity on T2WI. The capsule showed delayed enhancement in all cases, and all lesions of multi- nodular fusion type showed delayed septa enhancement on MR images. 15 cases on CT were misdiagnosed and Four cases on MRI were misdiagnosed and the accuracy of CT and MRI were 48.3% and 86.2% respectively.ConclusionsIn conclusion, CT and MRI are useful tools for SNN diagnosis.