Relationship between the volume of ventricles, brain parenchyma and neurocognition in children after hydrocephalus treatment

The treatment of hydrocephalus aims to facilitate optimal brain development and improve the overall condition of patients. To further evaluate the postoperative recovery process in individuals undergoing hydrocephalus treatment, we investigated the interplay between brain parenchymal and ventricular volumes, alongside neurocognitive parameters.

In this study, 52 children under the age of 10 undergoing hydrocephalus treatment were included. All participants underwent T1w MR images and Gesell developmental schedule assessments. Initially, we investigated the correlation between patients’ brain development and motor assessment scores. This analysis explored the association between cognition and both brain parenchymal and ventricular sizes. Furthermore, we investigated these relationships in the contexts of communicating and obstructive hydrocephalus. Finally, to quantitatively evaluate patients’ brain development using more detailed texture information from imaging, we employed three different classification models for prediction. To compare their performances, we assessed these classification frameworks using a fourfold cross-validation method.

Leveraging the deep learning framework, both pre- and postoperative T1w MR images have demonstrated a significant predictive value in estimating patients’ brain development, with the accuracy of 0.808 for postoperative images. In the statistical analysis, we identified a correlation between developmental assessments in children with communicating hydrocephalus and postoperative brain parenchymal volume.

The findings indicate that postoperative evaluation of brain development is more closely associated with brain parenchymal and ventricular volumes than the Evans index. Additionally, deep learning frameworks exhibit promising potential as effective tools for accurately predicting patients’ postoperative recovery.