• Genetic risk assessment: A polygenic risk score is calculated from a single saliva sample – a measure that combines many small genetic variants to indicate an individual’s risk of prostate cancer.
   
• Artificial Intelligence (AI) in image analysis: AI models assist in the analysis of MRI images, whilst also taking into account laboratory and clinical values such as the PSA level.

Seven university hospitals are enrolling 443 men aged between 50 and 70 who are already scheduled to undergo a prostate MRI scan. The fact that the data comes from several regions across Germany is crucial: this is the only way to reliably validate the results and extrapolate them to the general population in Germany.

The aim is to achieve earlier detection that is more targeted and less invasive – identifying aggressive tumours at an early stage whilst sparing men unnecessary examinations. In doing so, the project responds to a call by the Council of the European Union for risk-adapted prostate cancer screening.

Full title: ‘Improving the diagnostic efficiency of the prostate cancer MRI pathway through pre-imaging polygenic risk stratification and AI-derived imaging biomarkers’ | Funding: Network University Medicine (NUM), 3rd funding phase | Duration: 02/2026 – 07/2028