Alberto de Luca

UMC Utrecht

In short, Alberto de Luca's research entails the following:

Fast and accurate intraoperative reconstruction of brain tracts with AI to optimize efficacy of pediatric posterior fossa tumor surgery

Tumors of the posterior fossa account for nearly half of pediatric brain cancers. While less common, they also occur in adults. These tumors are associated with devastating outcomes, contributing to a 25% mortality rate among affected children. Brain surgery is the primary treatment for posterior fossa tumors, regardless of their aggressiveness. However, even when surgery successfully removes the tumor, it can lead to short-term adverse effects in approximately one-third of cases. One particularly impactful complication is cerebellar mutism syndrome (CMS), a condition where children lose the ability to speak for weeks to months, placing a significant emotional and practical burden on both patients and their families. 

CMS is believed to result from damage to specific brain connections. Intra-operative diffusion-MRI holds the potential to visualize these critical connections and guide surgeons in minimizing harm during the procedure. However, this application remains limited by the lack of fast and reliable methodologies compatible with the stringent time constraints of surgery and the suboptimal imaging quality of intra-operative MRI systems.

This project aims to address these challenges by developing innovative methods, including artificial intelligence techniques, to enable high-quality reconstructions of brain connections using intra-operative diffusion-MRI. We will evaluate the potential of these methods to support surgeries for children with posterior fossa tumors.