Rare diseases are rarely without suffering

It can be years before a patient with Interstitial lung disease (ILD - diseases of the lung interstitium) receives a diagnosis. In over 40 percent of cases, diagnosis takes more than one year, and nearly 20 percent of patients have to wait over three years. During that period of uncertainty, they repeatedly seek out medical treatment.² Then, even once they receive their diagnosis, they learn that their prognosis remains tenuous. "There aren't yet any defined stages or instruments to predict how these diseases will progress,"³ explains Andre Wichmann, our contact at OSIC, the Open Source Imaging Consortium. 

The non-profit consortium aims to establish a foundation for improving detection, diagnosis, and treatment of ILD. Four years ago, Siemens Healthineers was one of its founding members. Initiated by the Computed Tomography Business Line, our incubation team within the Strategy Department supported with the implementation. “It was exciting to see that our company is working with this kind of multilateral approach involving different partners,” explains Wichmann. 

Our expertise in medical imaging is a major asset for the consortium. Diagnosing these diseases requires a high-resolution computed tomography image (HRCT) of the lung. Yet even with the help of such images, most medical specialists still struggle with diagnosis: For one thing, ILDs are rare, and on top of that, there are numerous different ILDs, many of which manifest ambiguous symptoms. That makes them very difficult to diagnose in most cases — even for specialists.⁴

"In the consortium, leading medtech and pharmaceutical companies, healthcare facilities, and patient representatives are laying the groundwork for rapid progress in the fight against fibrosing lung diseases," says Wichmann. He heads the consortium's subproject Data Privacy and Architecture. As the team was building the data storage platform and established the processes needed to run it, technical challenges were not their only concern; they also had to make sure that all the clinical data was being input and output correctly, that the data was fully anonymized, and that user data was secure.

"As the project manager, it's my job to gather up and weave together all the various strands of the project across departments, both within the OSIC project itself and inside our company," says Wichmann, who studied electrical engineering and quickly found his niche in the field of medical technology. "I always found it fascinating how the field unites different disciplines: technology, medicine, physics, and meanwhile also more and computer sciences." 

During his studies, Wichmann completed a six-month internship at the Marburg Particle Therapy Center (MIT), which was established around that time. The experience cemented his interest in medical technology: "Ultimately, it was a matter of finding purpose in my work, perhaps — giving something back, helping people. There is enormous demand in medicine and there is also enormous potential for new solutions." 

For the past four years, Wichmann has been part of our Strategy Department — the perfect place to manage the potential of different solutions across the entire company.

Thanks to the work of Andre Wichmann and many supporting colleagues, it is now possible to compile the anonymized data of patients with ILDs across the entire world in a single, secure database. "Soon we'll be taking another step in our development: We are shifting the database to the cloud, where we can carry out quality assurance directly and make it much easier to access the data," explains Wichmann. 

This will bring the OSIC and its members one step closer to their goal of using anonymized clinical images and data to develop algorithms through machine learning. These algorithms would ultimately help doctors recognize the signs of ILD and diagnose the disease. The solutions that we and the other members of the OSIC will be working on over the next few years have the potential to help patients worldwide. 

When combined with lung cancer screening protocols, these solutions stand to become even more significant: "A lot of CT images are acquired during screening protocols. If AI solutions process these images in advance, it may be possible to detect both cancer and the early stages of pulmonary fibrosis." That would make it possible to begin treatment early on and monitor the progression of diseases over longer periods. "The hope is that we can improve prognoses, too," says Wichmann. For patients with ILDs and their families, this would finally mean more certainty about the future.