Raphael Patcas

Prof. Raphael Patcas is a Swiss board-certified orthodontist who has been jointly responsible for the clinical and theoretical teaching of orthodontics at the University of Zurich since 2011. He has been presented the university’s Teacher of the Year award numerous times and is an internationally sought-after lecturer. Dr. Patcas opened a small private orthodontic clinic in the heart of Zurich in 2020 while maintaining his affiliation to the University and commitment to academics.

Prof. Patcas holds a Dr. med. dent. from the University of Zurich and a PhD from the University of Tampere, and is one of only four orthodontists to have completed their habilitation at the University of Zurich in the last 50 years, thus receiving the highest academic credentials.

His scientific work comprises more than 80 publications and he has co-authored several book chapters with renowned publishers. Dr. Patcas has supervised over a dozen doctoral and master’s theses. His scientific achievements in research and teaching were recognized with appointments as honorary associate professor at the University of Hong Kong in the past, and presently as titular professor at the University of Zurich.

Course Details

This lecture will take listeners on a journey spanning the very first achievements of radiology in orthodontics to current cutting-edge innovations. We will review the major achievements that built the foundation of orthodontic radiology, and will examine the challenges and pitfalls faced in daily practice and research, with special emphasis on the application of AI in diagnostic imaging. We will explore the direction CBCT and other 3D imaging methods are heading towards, including model integration, and identify how these innovations are already redefining clinic practice and research.

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Learning outcomes

After attending this lecture, listeners will be able to:

1. Dream about future opportunities that are based on emerging innovations.
2. Appreciate the strengths and limitations of CBCT.
3. Recognise the potential and risks of AI in orthodontic imaging.
4. Integrate strategies on how to appraise new technology.