Pituitary gland height evaluated with magnetic resonance imaging in premature twins: the impact of growth and sex.

BACKGROUND: Pituitary gland height reflects secretory activity of the hypothalamo-pituitary axis. OBJECTIVE: To assess the cumulative impact of fetal growth and sex on pituitary gland height in premature twins, dissociated from prematurity. MATERIALS AND METHODS: A retrospective study was conducted, assessing the pituitary gland height in 63 pairs of preterm twins, measured from T1-weighted magnetic resonance imaging (MRI). Auxological parameters, including body weight, body length, and head circumference, at birth and at the time of MRI, were used as proxies for fetal and postnatal growth, respectively. The study population was divided into two groups, using corrected age at around term equivalent as the cutoff point. Statistical analysis was performed using mixed-effects linear regression models. RESULTS: When pituitary gland height was evaluated at around term equivalent, a greater pituitary gland height, suggesting a more immature hypothamo-pituitary axis, was associated with the twin exhibiting lower auxological data at birth. The same association was observed when body weight and length at MRI were used as covariants. In the group evaluated after term equivalent, a smaller pituitary gland height, suggesting a more mature hypothamo-pituitary axis, was associated with male sex. This difference was observed in twin pairs with higher average body weight at birth, and in babies exhibiting higher auxological data at MRI. CONCLUSION: After isolating the effect of prematurity, at around term equivalent, pituitary gland height reflects the cumulative impact of fetal growth on the hypothalamo-pituitary axis. Subsequently, pituitary gland height shows effects of sex and of fetal and postnatal growth.

Survival Outcome Prediction in Glioblastoma: Insights from MRI Radiomics.

Background: Extracting multiregional radiomic features from multiparametric MRI for predicting pretreatment survival in isocitrate dehydrogenase (IDH) wild-type glioblastoma (GBM) patients is a promising approach. Methods: MRI data from 49 IDH wild-type glioblastoma patients pre-treatment were utilized. Diffusion and perfusion maps were generated, and tumor subregions segmented. Radiomic features were extracted for each tissue type and map. Feature selection on 1862 radiomic features identified 25 significant features. The Cox proportional-hazards model with LASSO regularization was used to perform survival analysis. Internal and external validation used a 38-patient training cohort and an 11-patient validation cohort. Statistical significance was set at p < 0.05. Results: Age and six radiomic features (shape and first and second order) from T1W, diffusion, and perfusion maps contributed to the final model. Findings suggest that a small necrotic subregion, inhomogeneous vascularization in the solid non-enhancing subregion, and edema-related tissue damage in the enhancing and edema subregions are linked to poor survival. The model's C-Index was 0.66 (95% C.I. 0.54-0.80). External validation demonstrated good accuracy (AUC > 0.65) at all time points. Conclusions: Radiomics analysis, utilizing segmented perfusion and diffusion maps, provide predictive indicators of survival in IDH wild-type glioblastoma patients, revealing associations with microstructural and vascular heterogeneity in the tumor.