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Maximize the utility of
imaging biomarkers
to the benefit of
patients with arthritis.
Learn more about the project  

AutoPiX is a major international project focused on improving healthcare for people with rheumatic and musculoskeletal diseases (RMDs).

The AutoPiX project brings together pharmaceutical and medical technology partners with leading academic institutions to enhance the use of imaging biomarkers for patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA), and axial spondyloarthritis (axSpA), collectively known as systemic arthritides.

It aims to develop advanced imaging tools and artificial intelligence (AI) models to better diagnose, monitor, and treat these conditions. These tools will make use of imaging biomarkers—like X-rays, ultrasounds, and MRIs—to provide more precise and personalised care.

AutoPiX is a major international project focused on improving healthcare for people with rheumatic and musculoskeletal diseases (RMDs).

The AutoPiX project brings together pharmaceutical and medical technology partners with leading academic institutions to enhance the use of imaging biomarkers for patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA), and axial spondyloarthritis (axSpA), collectively known as systemic arthritides.

It aims to develop advanced imaging tools and artificial intelligence (AI) models to better diagnose, monitor, and treat these conditions. These tools will make use of imaging biomarkers—like X-rays, ultrasounds, and MRIs—to provide more precise and personalised care.

Learn more about the project  

MUW – Medical University of Vienna

The Medical University of Vienna is one of Europe‘s oldest international top universities for medicine and a research centre for driving innovation in biomedical sciences. The institutes, clinics, and departments work together in an integrated manner to facilitate education, research, and patient care. The university provides access to cutting-edge technologies and highly skilled personnel. By focusing on translational research and technological innovation, the MUW aims to bring significant benefits to its patients. Through the distinctive integration of basic research and clinical applications, patients can directly reap the rewards of clinical study outcomes. MUW has identified IMIDs as a field of currently unmet medical need with the potential for novel therapeutic approaches.

The Division of Rheumatology in the Department of Medicine 3 sees itself as a leading European competence center for the diagnosis, therapy and research of rheumatic diseases. In close cooperation with numerous other departments of the university, more than 10,000 patients are treated annually as outpatients, day patients and inpatients according to the highest standards. Continuous training, not only of students but also of staff, ensures consistent quality. Our focus is on the diagnosis and therapy of inflammatory rheumatic diseases. This is done in close interdisciplinary cooperation with other medical specialties. Improving the quality of life and maintaining the independence of people with rheumatic diseases are the focus of diagnostics and therapy. Research into the development and causes of rheumatological disease patterns and the development of new therapeutic options is the central goal of our scientific activities. We pass on our experience and knowledge to students, physicians in training and with completed specialization as well as to interested patients. We continuously strive to be a national and international leader in research, teaching, diagnosis and therapy in the field of rheumatology.

The Computational Imaging Research Lab (CIR) is a division of the Department of Biomedical Imaging and Image-guided Therapy at the Medical University of Vienna, curious about how machine learning has to evolve to make an impact in healthcare. CIR is an interdisciplinary research lab bringing together scientists in machine learning, imaging, medicine, and biology, developing novel methods to understand disease and to improve precision care. CIR is home to an international group of researchers and PIs leading their research groups in different areas of machine learning, medical imaging and precision medicine. It is closely linked to many clinical disciplines including radiology, oncology, surgery, paediatrics, pathology and neuroscience. CIR develops methods to predict disease course and treatment response in breast- and lung cancer, identify novel treatment targets, and model the reorganization of the brain during disease, working with all kinds of imaging incuding radiology, nuclear medicine, pathology, ultrasound, or microscopy data. Spin-off companies of CIR members are developing software for clinical radiology and accurate large-scale clinical annotation campaigns.

What is the role of MUW in Autopix

The MUW, represented by the Division of Rheumatology and CIR is the coordinator of the AutoPiX project and is leading 3 work packages including management (WP1), machine learning development in peripheral arthritis (WP4) and the development of visual foundation models and the research platform (WP7).

Q&A

In what part of the patient journey will your institution most likely contribute?

As coordinator, MUW will provide oversight and lead WPs 1, 4 and 7 and contribute to all WPs and the majority of tasks within the project, specifically to the development of machine-learning algorithms for conventional radiography, magnetic resonance imaging and ultrasound in peripheral arthritis, the development of the visual foundation models and the research platform. In addition, we will coordinate 3 of the 7 clinical trials in WPs 3 and 6, focusing on the validation of the robotic ultrasound system, and innovative imaging with PET/CT and automated high-content imaging.

What long-term impacts do you envision of your contribution?

Ideally, this could mean that doctors and possibly also patients, who are not experts in reading medical images themselves, acquire access to machine learning algorithms in routine clinical practice that can monitor typical radiological changes in common forms of inflammatory arthritis or predict the course of the disease or, in combination with other parameters, the response to therapy.

Why is it so important?

Automatization of in-clinic, point-of-care examinations such as thermography, can offer solutions to staff shortages in outpatient care. innovative imaging techniques such as positron emission tomography (PET) with novel nuclear radionuclide tracers or immunoscintigraphy may gain relevance as potential replacements for invasive tissue diagnostics and would represent less invasive alternatives for patients.

Team picture of Medical University of Vienna

Contact

Daniel Aletaha
Head of Division of Rheumatology
Peter Mandl
Director of Clinical and Epidemiological Research and senior consultant at Division of Rheumatology
Georg Langs
Head of Computational Imaging Research Lab
Daniela Sieghart
Senior project manager at Division of Rheumatology