PhD defence F. (Fatih) Incekara

This thesis contributes to our knowledge on the value of imaging and resection of glioma, in particular glioblastoma. We presented promising results on molecular predictions based on preoperative MRI scans using artificial intelligence. We showed in a randomized controlled trial that intraoperative ultrasound enables complete tumor resection more often than standard glioblastoma surgery, without harming patients. We recommend intraoperative ultrasound guided surgery, rather than standard surgery, to achieve complete safe tumor resection. We found that augmented reality was potentially useful to visualize and locate glioblastoma for neurosurgical planning on the operating room.

Complete glioblastoma resection was already associated with improved patient survival. We confirmed this association in molecularly defined IDHwt glioblastoma. We externally validated these results in a multi-center glioblastoma cohort and predicted survival of patients with a glioblastoma with nomograms. In addition, we found that resection of non-contrast enhanced tumor beyond contrast enhancement or supratotal resection showed potential survival benefit for patients with glioblastoma. We encourage further research on the safety of maximizing glioblastoma resection, especially beyond the borders of contrast enhancement.

Finally, we shared future perspectives, in which we expect that new imaging technologies and artificial intelligence will improve how we understand, diagnose and surgically treat patients with brain tumors. We hope that this thesis will be of benefit for future brain tumor research, clinical care and for patients with a brain tumor.

Due to corona, the PhD defences do not take place publicly in the usual way in the Senate Hall or in the Professor Andries Querido Room. The candidates will defend their dissertation either in a small group or online.