![]() LGG data were retrieved from TCGA and categorized into training and internal validation datasets. Immune features were explored using MRI radiomics features to prediction the overall survival (OS) of lower-grade glioma (LGG) patients and their response to immune checkpoints. This study aimed to identify a series of prognostically relevant immune features by immunophenoscore. In multivariate Cox analysis, pathological types, ADC and radscore were independent risk factors for recurrence.Ĭonclusions: ADC value and radscore were independent predictors of recurrence of EC, which can supplement prognostic information in addition to clinicopathological information and provide basis for individualized treatment and follow-up plan. In univariate analyses, FIGO stage, pathological types, myometrial invasion, lymphovascular space invasion (LVSI), ADC value and radscore were associated with recurrence. ![]() Results: ADC values showed inverse correlation with recurrence, while radscore was positively associated with recurrence. Kaplan–Meier analysis was performed and a Cox regression model was used to evaluate the correlation between clinicopathological features, ADC values and radiology with recurrence. Radiomic parameters were extracted on T2 weighted imaging and screened by logistic regression, and then a radiomics signature was developed to calculate the radiomic score (radscore). Baseline clinicopathological features and ADC values were analyzed. Methods: One hundred and seventy-four EC patients who were treated with operation and followed up in our institution were retrospectively reviewed. ![]() Background: To identify predictive value of apparent diffusion coefficient (ADC) values and magnetic resonance imaging (MRI)-based radiomics for all recurrences in patients with endometrial carcinoma (EC). ![]()
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