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We spoke with Professor Peter van Ooijen, president of the European Society of Medical Imaging Informatics (EuSoMII), about his plans for the society and the growing role AI plays inside the hospital and the radiology department in particular.

As EuSoMII President, what are your goals?

My predecessors have done a great job and achieved so much. I will continue with their strategy and further expand our partnership with other professional societies, such as the European Society of Radiology, the Society for Imaging Informatics in Medicine, the European Federation of Organizations for Medical Physics, and the European Federation of Radiographer Societies.

Of course, I am also particularly interested in partnering with our industrial partners. Without their support, we could hardly carry out our scientific work.

Professor Peter van Ooijen, president of the European Society of Medical Imaging Informatics (EuSoMII)

EuSoMII is a unique professional society because we do not focus on a specific disease or modality. Medical imaging is a broad topic and involves many clinical disciplines, whom we can share our expertise with.

Another item that is very close to my heart is to expand our annual meeting. This year, the program will unfold over two full days and we will have a workshop for our young members right before the meeting starts.

Do you also want to expand beyond radiology then?

Yes, imaging informatics also plays a role in, for example, nuclear medicine and radiotherapy. To reach our potential members, I am interested in clearly communicating our goals to show where our strengths lie. This also involves improving our presence in journals, through statements, papers and guidelines. A perfect example is our Radiomics auditing group, which has already published several papers.

We want to show that we are not only about artificial intelligence (AI). Everyone is talking about AI in radiology, but our topics of interest go far beyond that. 

Our topics are interdisciplinary and range from network infrastructure and imaging modalities, to AI-based decision support and workflow systems.

This means that new members could come from different disciplines. Who are your members today?

You’re right about new members potentially coming from a wide range of specialties. But please remember that, we are a subspecialty society of the European Society of Radiology (ESR), so traditionally we have been very radiology-oriented.

10 percent of our members are radiographers and about 60 percent are radiologists. About 20 percent are technicians – e.g. clinical physicists, data scientists or computer scientists – and the final 10 percent are from the industry.

Since we have renamed our society from EuroPACS to EuSoMII and set medical imaging and informatics as our scope, our membership has become much more diverse.

Again, medical imaging does not only include radiology but also for example nuclear medicine and radiotherapy, the latter of which is my focus. 

We are particularly proud of the fast-growing number of radiographers, as we only started to officially collaborate with the European Federation of Radiographer Societies (EFRS) last year. Radiographers play a unique and important role in the clinical introduction of AI algorithms.

Is the rapidly increasing proportion of members from partner disciplines already reflected within the organization of the EuSoMII?

Yes, and to our delight, we have already been able to appoint EFRS members to our board.

Our membership is also increasingly young. Members aged between 25 and 35 represent around 20 percent of our members and the age group 35-45 represents another 25 percent. 

Young members play a key role in EuSoMII because they still have much time ahead in their careers. This is why we have created the Young Club, which has successfully been led by Merel Huisman, and has two of its members on the EuSoMII board. This way, we want to enable young people to actively participate and take on responsibility within our society.

AI has yet to be included everywhere in the medical education curriculum. The curricula are not uniform across Europe. Some countries are very advanced and others still need to catch up to incorporate AI into their medical training.

Almost everywhere we see positive trends because there’s no escaping it. AI has to be part of the medical training in the future. For example, we see a massive trend among practitioners who participate in continuing education including about AI related topics, to expand their knowledge and expertise. 

In its European Training Curriculum, in which the EuSoMII provides the Medical Imaging Informatics part, the ESR recommends to address AI and other imaging informatics topics early on in radiology training.

We cooperate as much as possible with the ESR and the European School of Radiology in this regard. We also organize seminars and have already published three volumes in a Medical Imaging Informatics series. 

We also started the ESR Masterclass in AI this year. My predecessor Professor Elmar Kotter heads the faculty, which is therefore also very closely connected to our society. 

In your opinion, are AI platforms the best way to integrate algorithms?

I think platforms will be one of the many ways to integrate algorithms into the workflow in the future. A lot will depend on the implementation of standards. The integration profiles of IHE and DICOM are constantly being developed to better integrate AI into the workflow. This could benefit the direct integration of algorithms, as standardization helps to connect different IT systems.

How do you think AI use will develop in the future?

AI will not be limited to radiology but also permeate every hospital department

AI will soon take interdisciplinary cooperation to a whole new level. Only with the deep integration of patient information from different disciplines will we be able to analyze the immense amounts of data that are now available. With AI-based evaluation of the electronic patient record, including medical history, laboratory findings, and the entire range of diagnostic procedures, we can take a significant step toward more precise diagnostics and personalized therapies.