Neuroradiology最新文献

Purpose: The choroid plexus (CP) plays an interactive role in diverse pathophysiological mechanisms of cerebral small vessel disease (CSVD). We aimed to explore whether the CP has specific imaging or clinical consequences in CSVD by itself.

Methods: A total of 90 patients with CSVD and 31 healthy controls (HCs) who underwent multiparameter MRI and neuropsychological tests, were retrospectively evaluated. The CP of the lateral ventricles was automatically segmented and manually corrected. The normalized CP volume, susceptibility and perfusion information of CP, and the diffusion tensor image analysis along the perivascular space (DTI-ALPS) index relating to glymphatic efflux were obtained. Partial correlation and multiple linear regression analyses were used to assess the relationship between CP and disease severity and CSVD-related cognitive decline.

Results: Patients with CSVD had greater CP volume, lower susceptibility, reduced perfusion, and smaller DTI-ALPS indices (all p < 0.05). CP volume was correlated with white matter hyperintensities, lacunes, and CSVD burden (r = 0.237, p = 0.028; r= 0.228, p = 0.034; r = 0.320, p= 0.003). CP volume and perfusion showed correlations with specific cognitive domains (all p < 0.05), including memory, attention, and visuospatial functions. Interestingly, the susceptibility and arterial transit time of CP were related to DTI-ALPS in HC group (β = 0.542,p= 0.047; β=-0.605,p = 0.015), while the correlation vanished in CSVD group.

Conclusion: The CP showed structural and functional abnormalities, which was related to CSVD disease severity and cognitive status, highlighting CP-targeted interventions as a potential therapeutic strategy. The uncoupling between CP and DTI-ALPS in CSVD patients suggests disrupted fluid homeostasis, warranting further validation via direct glymphatic imaging.

Purpose: Medulloblastoma (MB) and pilocytic astrocytoma (PA) are common in pediatric brain tumors and difficult to distinguish. To establish and evaluate a radiomics model based on multimodal MRI to distinguish medulloblastoma from pilocytic astrocytoma.

Methods: Retrospective collection of magnetic resonance images from 113 patients with MB and 74 patients with PA. Radiomics analysis was performed on Dynamic Contrast-Enhanced T1 weighted imaging (DCE-T1WI), T2 weighted imaging (T2WI), and Apparent diffusion coefficient (ADC) images, respectively. A multimodal MRI combined radiomics model incorporating DCE-T1WI, T2WI, and ADC sequence features was developed by extraction of valuable features, and the radiomics nomogram was generated to evaluate its diagnostic capability. The DeLong test was used to compare the diagnostic performance of DCE-T1WI, T2WI, ADC single sequence model, and multimodal MRI radiomics model.

Results: The combined model showed the highest performance among all models, with an area under the curve (AUC) of 0.999 on the primary cohort and maintained an AUC of 0.994 during the validation cohort. For the single-sequence model, the ADC sequence model performs better in the primary cohort, with an AUC of 0.996; the T2WI sequence model slightly outperforms in validation cohort, with an AUC of 0.985. The DCE-T1WI sequence model performed slightly worse than ADC and T2WI in the validation cohort, with an AUC of 0.951. Overall, the combined model performed best in the differential diagnosis of MB and PA.

Conclusion: Multimodal MRI-based radiomics analysis is effective in differentiating MB from PA and radiomics imaging may have important clinical significance in the preoperative detection of posterior fossa brain tumors in children.