BMI2

Over the course of 2025, significant progress was made in several key areas—from developing clinically applicable AI tools and standardizing metadata to expanding secure research infrastructure.

Clinical Applications

To support radiologists in interpreting chest X-rays, more than 700,000 labeled image-text pairs were compiled from public data sources. On this basis, an AI model was developed that can analyze image content and answer questions about it in a conversational format.

For treatment planning and follow-up in patients with a limited number of metastases (e.g., in melanoma or non-small cell lung cancer), an extensive PET/CT dataset was built. It covers around 1,000 patients with more than 8,000 scans, many of them longitudinal. Part of the data has already been clinically curated and annotated. This subset served as the basis for developing initial automated methods to detect and delineate tumors and organs in imaging data.

In pediatric neuro-oncology, MRI data from children with brain tumors were anonymized and made available on the clinical analysis platform Leonhard Med. In addition, an automated analysis was developed that detects and labels various brain structures and tumor regions. This method was successfully tested and validated.

Metadata Standardization

As part of BMI2, unified concepts for metadata in medical imaging were developed. These were officially incorporated into the SPHN (Swiss Personalized Health Network) Schema 2025.2. The new standards have already been introduced at the Zurich partner institutions—University Hospital Zurich, Balgrist University Hospital, and University Children’s Hospital Zurich—and are to be rolled out at other SPHN institutions across Switzerland in the future.

In addition, the SCALE-QMR project is working on AI-based methods that automatically check and improve metadata. The goal is to make data acquisition and quality control more efficient and reliable in the future.

Infrastructure Expansion

Data pipelines for DICOM imaging data were set up or expanded at all three BMI2 sites. The connection to the secure computing platform Leonhard Med was extended. In addition, the technical integration into The LOOP BMIP was prepared through a shared data architecture. At the same time, the infrastructure for digital pathology (SDPI) was further developed in a targeted manner.

Governance and Regulatory Affairs

Together with the Clinical Trials Center (CTC) of the USZ, a dedicated governance and data protection concept for imaging data has largely been completed. Final alignment will take place in line with the overarching LOOP BMIP governance framework. At the same time, the ethical and legal groundwork was laid at the University Children’s Hospital Zurich to responsibly use and jointly analyze pediatric MRI data collected over many years.

The BMI2 platform project strengthens image-based precision medicine within The LOOP Zurich’s infrastructure and fosters the connection between clinical practice and data-driven research. Through standardized, interoperable technologies, BMI2 is laying a sustainable foundation for innovative applications in diagnostics, therapy, and biomedical research in Zurich.