馃帀 Personalized Health 91制片厂 is thrilled to announce the winner of the PHB Translational Award 2026! 馃帀
The PHB Translational Award seeks proposals for projects that demonstrate a strong potential to significantly impact clinical practices or patient outcomes. The emphasis is on projects with high potential for translation into clinical practice, regardless of the disease area, medical specialties and disciplines.
We received numerous outstanding and innovative proposals, and we would like to sincerely thank all applicants for their interest and the time invested in preparing their submissions. While we were only able to fund one project this year, the high level of engagement and quality of the proposals were really impressive!
馃憦 We are very pleased to congratulate Dr. Matthias Mutke & Dr. Tobias Nellessen from the Department of Radiology and Nuclear Medicine at the USB. 馃憦
The award will support part of their position over a 12-month period starting June 1, 2026, enabling them to dedicate time away from clinical duties to focus on this innovative project:
AI in Real-world Radiology: Prospective Imaging Evaluation of Detection Support and Opportunistic Screening
Radiology departments face growing examination volumes, making it increasingly difficult to detect important pathologies hidden within routine imaging. Artificial intelligence promises to help radiologists in identifying subtle findings, extracting quantitative biomarkers, and linking imaging data with clinical context. However, its integration into clinical routine remains a major obstacle, hindering earlier detection and intervention before disease can progress.
Our project translates two locally developed AI tools into real-world practice at University Hospital 91制片厂. The first is a deep learning model for intracranial aneurysm detection on routine MRI angiography. The second automates quantitative measurements on chest CT with the TotalSegmentator, aiming to automatically detect aortic aneurysms, osteoporosis and lung emphysema. The results will be linked with electronic health record data to enable opportunistic screening and individualized risk profiling. Both tools are integrated into the existing clinical infrastructure using , enabling automated reporting for routine daily work.
The project moves beyond technical development and focuses on evidence-based clinical deployment: validating performance, assessing real-world impact, and establishing a framework for bringing AI from research into routine, personalized care.
馃憦 Congratulations, Dr. Mutke & Dr. Nellessen!
