Temporospatial changes of TSPO expression in glioblastoma in response to therapy and during disease progression – a multimodal TSPO PET, amino acid PET, and MRI study

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Our previous work and that of others has shown that TSPO PET and FET PET demonstrate diverging uptake patterns in malignant glioma and provide complementary information to contrast enhanced MRI. Increased TSPO PET signal correlates with tumor grade and poor prognosis and, especially in the relative absence of FET enhancement, may reflect therapy induced changes in the tumor and its inflammatory microenvironment. However, longitudinal assessment of TSPO signaling in response to therapy and during disease progression and its impact on the clinical outcome and individual prognosis of glioblastoma patients has not been assessed so far. Therefore, this project aims to visualize temporal and spatial changes of TSPO expression by means of a single arm observational study using longitudinal multimodal TSPO / FET PET and ceMRI for patients with glioblastoma, and to correlate imaging findings with changes on the cellular and molecular level as well with the clinical outcome. In work package 1 patients with newly diagnosed brain tumors suspicious for glioblastoma (n=58) will be recruited and prospectively enrolled. Recruitment phase of the study will be 18 months with follow-up of another 18 months. All data retrieved from clinical workup, clinical-follow-up, imaging and neuropathological analysis will be put into an electronic database. Tumor specimen collected during tumor resection and serial stereotactic biopsies will be performed using an image guided neuronavigation system. Localizations of tissue samples will be assigned to PET and MRI data, which enables a precise spatial correlation of PET information with histopathological findings and pathway analyses for project A2/3. This collaboration with project A2/A3 allows in-depth analyses of changes of the tumor microenvironment, cellular contributions to the TSPO signal (myeloid cells vs. tumor cells) and molecular alterations in a unique longitudinal study cohort with tissue samples obtained with TSPO PET image guidance at primary diagnosis and at relapse. Work package 2 focusses on advanced image analysis of the multimodal imaging data and its correlation with clinical and neuropathological data obtained in work package 1. The analyses include pharmacokinetic modelling, machine learning and deep learning approaches to perform non-invasive tissue classification, distinguish therapy responders from non-responders at an early time point and to predict the time and localization of tumor recurrence and ultimately, to link imaging features with overall survival.