MISTAI: Medical Intelligence & Skills Training in AI

Wed, 01 Jul 2026 00:00:00 +0000

The war in Ukraine has severely disrupted medical research and teaching. Digital pathology and AI offer a way to keep both going without depending on physical infrastructure. MISTAI is a bilateral cooperation between the University Hospital Bonn and Dnipro State Medical University (DSMU), funded by the Ministry of Culture and Science of North Rhine-Westphalia (MKW NRW).

Goals

Shared data infrastructure: digitise and validate at least 100 H&E and IHC whole-slide images from a DSMU cohort of muscle-invasive bladder cancer (MIBC), on a joint secure platform.
AI diagnostic pipeline: fine-tune state-of-the-art pathology foundation models on the combined Bonn–Dnipro data, including spatial analysis of tumour-infiltrating lymphocytes from routine H&E slides, inspired by the UC-TIL approach.
Clinical tool: a QuPath plugin that lets pathologists run the trained model directly in their existing workflow.
Capacity building: weekly remote collaboration, a one-week exchange visit to Bonn, and a Computational Pathology teaching module for the DSMU curriculum.
Follow-on work: a joint DFG/BMBF proposal outline and a MICCAI challenge concept.

Partners

Bonn contributes high-resolution slide scanners, AI infrastructure and expertise in computational medical imaging (Prof. Shadi Albarqouni) and translational lung and tumour pathology (Prof. Verena Tischler). DSMU contributes a clinically distinct bladder-cancer cohort and long-standing pathology expertise (Assoc. Prof. Nina Bondarenko, Department of Pathological Anatomy).

Bladder Cancer |

MISTAI: Medical Intelligence & Skills Training in AI

Goals

Partners