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Background: Gamma Knife radiosurgery (GKS) was recommended for treating patients with breast cancer brain metastasis (BCBM), but predictions of the existing prognostic models for therapeutic responsiveness vary substantially. Purpose: To investigate the prognostic value of pretreatment clinical, MRI radiologic, and texture features in patients with BCBM undergoing GKS. Material and Methods: The data of 81 BCBMs in 44 patients were retrospectively reviewed. Progressive disease was defined as an increase of at least 20% in the longest diameter of the target lesion or the presence of new intracranial lesions on contrast-enhanced T1-weighted (CE-T1W) imaging. Radiomic features were extracted from pretreatment CE-T1W images, T2-weighted (T2W) images, and ADC maps. Cox proportional hazard analyses were performed to identify independent predictors associated with BCBM-specific progression-free survival (PFS). A nomogram was constructed and its calibration ability was assessed. Results: The cumulative BCBM-specific PFS was 52.27% at six months and 11.36% at one year, respectively. Age (hazard ratio [HR] 1.04; 95% confidence interval [CI] 1.01–1.06; P = 0.004) and CE-T1W-based kurtosis (HR 0.72; 95% CI 0.57–0.92; P = 0.008) were the independent predictors. The combination of CE-T1W-based kurtosis and age displayed a higher C-index (C-index 0.70; 95% CI 0.63–0.77) than did CE-T1W-based kurtosis (C-index 0.65; 95% CI 0.57–0.73) or age (C-index 0.63; 95% CI 0.56–0.70) alone. The nomogram based on the combinative model provided a better performance over age (P < 0.05). The calibration curves elucidated good agreement between prediction and observation for the probability of 7- and 12-month BCBM-specific PFS. Conclusion: Pretreatment CE-T1W-based kurtosis combined with age could improve prognostic ability in patients with BCBM undergoing GKS. [ABSTRACT FROM AUTHOR]

The approach of graph-based diffusion tensor imaging (DTI) networks has been used to explore the complicated structural connectivity of brain aging. In this study, the changes of DTI networks of brain aging were quantitatively and qualitatively investigated by comparing the characteristics of brain network. A cohort of 60 volunteers was enrolled and equally divided into young adults (YA) and older adults (OA) groups. The network characteristics of critical nodes, path length (Lp), clustering coefficient (Cp), global efficiency (Eglobal), local efficiency (Elocal), strength (Sp), and small world attribute (σ) were employed to evaluate the DTI networks at the levels of whole brain, bilateral hemispheres and critical brain regions. The correlations between each network characteristic and age were predicted, respectively. Our findings suggested that the DTI networks produced significant changes in network configurations at the critical nodes and node edges for the YA and OA groups. The analysis of whole brains network revealed that Lp, Cp increased (p < 0.05, positive correlation), Eglobal, Elocal, Sp decreased (p < 0.05, negative correlation), and σ unchanged (p ≥ 0.05, non-correlation) between the YA and OA groups. The analyses of bilateral hemispheres and brain regions showed similar results as that of the whole-brain analysis. Therefore the proposed scheme of DTI networks could be used to evaluate the WM changes of brain aging, and the network characteristics of critical nodes exhibited valuable indications for WM degeneration.