Primary brain tumors are neoplasms of the nervous system and the meninges and represent severe diseases due to the limited intracranial space. Therapies, prognosis and survival strongly depend on the tumor entity. For example, glioblastoma multiforme (GBM) is the most malignant type of brain tumor and affected patients have median overall survival times of less than two years despite therapy. GBMs represent ~50% of all primary brain tumors. To provide optimal therapy, accurate diagnosis is required as early as possible in the clinical workflow.

Pathological analysis requires some days to provide an integrated diagnosis that allows further clinical decision-making. If the suspicious tissue turns out to be an aggressive brain tumor, the adequate therapy (surgical removal, chemotherapy, radiotherapy) is, therefore, delayed (by days to weeks) with negative impact on the patient’s prognosis, especially in case of rapidly growing tumors. The development of strategies for direct tumor diagnosis bypassing tissue removal and lengthy pathological evaluation would allow the immediate therapy of affected patients.

We aim to develop and test a prototype of a novel tiny endoscope that probes autofluorescence of brain tissue and allows optical biopsies in situ. In the project, we will research the spectral characteristics of brain tumor fluorescence and miniaturize an endoscopic system while preserving high optical properties. This is achieved by implementation of recent advances in computational optics and programmable light. The development of tissue classification and strategies for integration of AI-supported diagnosis into the clinical workflow will allow successful translation. Moreover, the research may pave the way for future automated brain tumor diagnosis and tumor removal by laser ablation.