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Background: Prognostic evaluation is important for personalized treatment in children with medulloblastoma (MB). Limited data are available for risk stratification using a radiomics‐based model. Purpose: To evaluate the incremental value of an MRI radiomics signature in stratifying the risk of pediatric MB in terms of overall survival (OS). Study type: Retrospective. Subjects: A total of 111 children (mean age 5.82 years) with pathologically confirmed MB divided into training and validation cohorts (77 and 34 children, respectively). Field Strength/Sequence: A 3 T, contrast‐enhanced T1‐weighted imaging with inversion recovery. Assessment: The study endpoint was OS defined as the time between the preoperative MRI study and death or last follow‐up. The radiomics signature model and a clinical‐MRI model were developed for personalized OS prediction. An integrative model, which combined the radiomics signature and clinical‐MRI features, was also built using multivariable Cox regression model. The performance of the three models was evaluated with the C‐index. The performance of integrative model was assessed by calibration curve and decision curve analysis (DCA). Statistical Tests: Independent T‐test, Mann–Whitney U test, Fisher's exact tests or chi‐square test, logistic regression analysis, Kaplan–Meier survival analysis, C‐index, intraclass correlation coefficients (ICC). P < 0.05 was considered statistically significant. Results: The media OS was 2.83 years (3.87 ± 1.85 years). Two clinical and one conventional MR imaging features (remnant, adjuvant treatment, and peritumoral edema) were selected for clinical‐MRI model building. The integrative model evaluated OS (C‐index 0.823) better than either the radiomics signature (C‐index 0.702) or the clinical‐MRI model (C‐index 0.771). And it also showed good performance in the validation cohort (C‐indices: 0.786, 0.756, 0.721), which was validated by the good calibration (P > 0.05) and more benefit. Data Conclusions: This study demonstrated that the integrative model, which combined radiomics signature, clinical, and conventional MRI features, showed best performance in OS evaluation for children with MB. The radiomics signature may confer incremental value over clinical‐MRI features. Evidence Level: 3. Technical Efficacy: Stage 2. [ABSTRACT FROM AUTHOR]

Background: T1, T2, and T1ρ might be potential biomarkers for assessing liver fibrosis. However, few studies reported the value of them in different animal models. Purpose To investigate and compare the performances of T1, T2, and T1ρ for noninvasively staging liver fibrosis in bile duct ligation (BDL) or carbon tetrachloride (CCl4) model. Study Type: Prospective animal model. Subjects: Liver fibrosis was induced by BDL or injection of CCl4 in 120 rats. Field Strength/Sequence: 11.7 T, T1 mapping with 10 repetition times, T2 mapping with 32 echo times, and T1ρ with 10 spin‐lock times. Assessment T1, T2, and T1ρ were measured and correlated with liver fibrosis stages, as well as the degree of inflammation, steatosis, iron deposition, and the expression of cytokeratin 19. The discriminative performance of T1, T2, and T1ρ for staging liver fibrosis was compared. Statistical Tests: One‐way analysis of variance (ANOVA), Spearman's correlation analysis, factorial design ANOVA, and receiver operating characteristic curves (P < 0.05 was considered statistically significant). Results: T1, T2, and T1ρ (BDL: rho = 0.73, 0.85, 0.68; CCl4: rho = 0.80, 0.29, 0.61) were significantly correlated with liver fibrosis stages, while there was no significant difference in T2 among stage F0–F4 in the CCl4 model (P = 0.204). The area under the curves (AUCs) range of T1, T2, and T1ρ for predicting ≥F1, ≥F2, ≥F3, and F4 were 0.76–0.95, 0.89–0.98, and 0.80–0.94 in the CCl4 model. For the CCl4 model, the AUCs range of T1, T2, and T1ρ for predicting ≥F1, ≥F2, ≥F3, and F4 were 0.83–0.95, 0.61–0.74, and 0.73–0.89, respectively. T2 had significantly higher AUC in the BDL model than CCl4 model for diagnosing liver fibrosis. Data Conclusion: The most sensitive and accurate method for staging liver fibrosis appeared to be T1 in our animal models followed by T1ρ. T2 may not be suitable for evaluating liver fibrosis. Level of Evidence: 1 Technical Efficacy Stage: 2 [ABSTRACT FROM AUTHOR]