General discussion The general aim of the research work presented in this thesis was to investigate the potential gain of technological innovations in glioblastoma (GBM) diagnosis and therapy that could be implemented in the near future to improve the prognosis of patients with this disease. This work was divided into three parts: 1) decision support systems, 2) ultra-high field MRI, 3) autophagy inhibition, for which the following specific objectives had been defined: 1. Review the current and novel diagnostic imaging methods and techniques used for the prediction of treatment response and the optimization of decision support systems to improve outcome prediction in patients with a GBM (Chapter 2 and 3). 2. Investigate the technical feasibility of incorporating 7 Tesla MRI into neurosurgical navigation and radiation treatment planning systems for patients with GBM (Chapter 4 and 5). 3. Determine the recommended phase II dose for chloroquine (CQ) in combination with concurrent radiotherapy with temozolomide (TMZ) in patients with a newly diagnosed GBM (Chapter 6). This chapter presents a critical appraisal of the topics investigated. The three parts of this thesis are summarized and put into the current clinical perspective, after which future perspectives are discussed.
Decision support systems Chapter 2 provides a comprehensive overview of the currently available techniques that capture tumor heterogeneity of GBM in a non-invasive way and can be integrated into decision support systems. This chapter reviews imaging techniques such as MR imaging, nuclear imaging and liquid biopsies and novel integrated approaches such as radiogenomics and radiomics that allow to both monitor and predict the treatment response. This chapter also introduces the “Non-invasive Glioblastoma Testing” (NIGT) platform. With the diagnostic techniques integrated in the NIGT platform information on the tumor as a whole, including driver mutations and the tumor microenvironment, can be captured in a non-invasive manner. Histopathological and molecular analysis of tissue samples taken by a biopsy or resection is currently the golden standard for the diagnosis of GBM. However, GBM demonstrate a large amount of intratumoral heterogeneity that often cannot be fully captured with these types of analyses, especially when only a biopsy is taken. This intratumoral heterogeneity is one of the main challenges for GBM treatment as clones within the tumor may demonstrate a different amount of sensitivity to both radiation treatment and chemotherapy, ultimately resulting in treatment resistance. The NIGT platform will enable physicians to select the optimal treatment both at the stage of diagnosis and recurrence without the need for repeated tissue verification. - 152 -
