EU 11 - Computational tools for the establishment and use of diagnostic reference levels (DRLs)

1. To understand why DRLs should be seen as a dynamic tool that follows the development of clinical practice and technology advances.
2. To appreciate the potential role of AI in establishing DRLs.
3. To learn how AI can assist in dose estimation and optimisation.

1. To understand the importance of dose management systems (DMS) in establishing and using dose reference levels (DRLs) for radiation dose management in radiology practices.
2. To learn about the different types of DMS available and their respective advantages and limitations in implementing DRLs for different radiological procedures.
3. To gain insights into the best practices for integrating DMS with DRLs to optimise the quality of radiological examinations.

1. To understand the importance of big data in establishing DRLs for medical imaging.
2. To identify potential challenges associated with using big data for DRLs, including anonymisation, security, privacy, verification, data quality, data interoperability, bias, ethical considerations, and cost.
3. To learn about potential solutions to overcome these challenges, such as automated quality control tools, data validation processes, peer review, collaboration, data sharing, and random sampling.