Connecting Glioma Experts in Research and Teaching

Gliomas are a group of brain tumors that come in many types, each needing its own specific treatment. Doctors mostly use Magnetic Resonance Imaging (MRI) to detect and monitor these tumors. But even with MRI, its hard to tell where the tumor ends, how much swelling is around it, or whether changes appearing in the medical images are from reoccurring tumor or from treatment side effects. Positron Emission Tomography (PET) examinations can help, but they often give unclear results. Artificial Intelligence (AI) has the potential to make diagnosis and treatment planning more accurate. However, progress in development of specific AI tools is slow because there isnt enough high-quality data, some of the biological background is not fully understood behind what is see in medical images and the cooperation between experts from different fields necessary to understand Gliomas as a whole is often challenging in practice. The project CONGLIOMERATE, is set up to tackle these current challenges. CONGLIOMERATE brings together experts from medicine, science, and technology to improve how gliomas are understood and treated. This will be achieved by a close collaboration of the experts with a specific focus on combining clinical and biological knowledge with advanced AI based technologies. Furthermore, CONGLIOMERATE trains the next generation of scientists who can work across these different fields to improve inter disciplinary cooperation. The CONGLIOMERATE faculty has designed five main projects to improve different aspects of current glioma diagnosis: (1) the first project aims on using AI to link what is see in medical images (how the tumor looks) with the tumors genetic makeup. This can help doctors predict how risky a tumor is for each individual patient. (2) in the second project a new method to analyze PET scans is developed which tries to link the PET signal to underlying biological and anatomical conditions. (3) Project three will study how different treatments affect tumors at a biological level, using lab-based models, to better understand how and why tumors change and how these changes look in PET and MRI scans. (4) Project four aims on developing an AI system that can tell whether a tumor is actually getting worse or just looks like it is due to treatment effects, by combining data from multiple scan types. (5) And finally project five will investigate new strategies to train AI systems to work well even when theres limited information because brain tumors are rare and data is usually sparse. In summary, CONGLIOMERATE will create a lasting platform for better brain tumor research in Vienna. It will lead to smarter, more accurate diagnosis methods and help train new scientists who can think across disciplines. It will also build stronger connections between clinicians and researchers.