Artificial intelligence (AI) is being applied in the medical field to improve healthcare, but it also poses challenges, particularly in terms of ethics and societal implications. It raises complex questions surrounding informed consent, biases leading to inequality, data privacy and protection risks, as well as responsibility and liability concerns. To address these issues, several guiding principles and recommendations have been formulated based on key ethical values. However, these principles need to be adapted and applied specifically to each field of application – in the case of EuCanImage AI systems in radiology and oncology. This deliverable presents the results of an analysis conducted on the ethical and societal implications of AI in oncologic imaging. The analysis utilizes empirical data gathered in WP1 of EuCanImage and focusses on trustworthy AI as a key concept. Aligned with the FUTURE-AI initiative, this deliverable provides guidelines and tools for AI systems design, including considerations of potential biases (especially regarding sex and gender dimensions), an interdisciplinary and embedded ethics approach, the importance of considering situated practices, stakeholder engagement, as well as environmental aspects.