Imaging procedures often lead to so-called incidental findings – unexpected results that can arise in both clinical diagnostics and research projects. How these findings are handled raises important ethical questions, in particular whether, and if so which, of these findings should be disclosed to participants, and what risks or benefits are associated with this. This issue is particularly relevant in translational lung research, as it brings together different types of studies and participant groups, and research is often closely linked to clinical care. New developments, such as in lung cancer screening, have further intensified the debate on how to handle incidental findings. Our project analyses key ethical arguments and provides guidance on the responsible handling of incidental findings in translational lung research.

Project leaders: Martin Jungkunz, Julie Schweer, Hans-Ulrich Kauczor

AI-supported radiological screening programmes can make a significant contribution to the early detection of diseases, but are associated with various forms of uncertainty. Whilst the use of AI may help to overcome existing uncertainties, it also introduces new (algorithmic) uncertainties. 

The aim of the project “Adressing Uncertainty in RAdiological AI-based Screening-Programs (AURA-AI)” is to apply for funding for an interdisciplinary collaborative project that brings together ethical, radiological, legal and sociological perspectives. The project will investigate the requirements that must be met in order to address uncertainties in AI-supported radiological screening programmes in a responsible, transparent and communicative manner. 

Project leaders: Martin Jungkunz, Bettina Niederhauser, Hans-Ulrich Kauczor, Fruzsina Molnár-Gábor

• Schweer J, Jungkunz M: Cornerstones for the ethical management of incidental findings in translational lung research (Poster), DZL Annual Meeting, 1 July 2025, Heidelberg