Multi-center studies are crucial for advancing medical and radiological research. Data exploration, collaboration discovery, and study progress monitoring are essential for maximizing their potential. However, in practice these processes often rely on manual communication and shared tables, which quickly become outdated and hinder efficient coordination in large distributed studies. This highlights the need for dedicated monitoring solutions that provide transparent and up-to-date insights into study progress. We propose a lightweight, open-source monitoring architecture for multi-center studies based on the widely used Grafana-Prometheus stack. The framework collects aggregated monitoring metrics from distributed study sites and visualizes them through configurable dashboards. As a real-world deployment example, the framework is integrated into the medical imaging platform Kaapana and evaluated within a large multi-center research network. By deploying our solution within the Germany-wide RACOON consortium, we demonstrate its ability to enable privacy-preserving data exploration and study progress monitoring across all 38 German university clinics. The monitoring framework supports transparent coordination of distributed research activities and can facilitate more efficient management of large-scale multi-center studies. The source code and Kaapana integration are publicly available at https://github.com/MIC-DKFZ/study-monitoring-kaapana.

翻译：多中心研究对于推动医学及放射学研究至关重要。数据探索、协作发现与研究进度监测是最大化其潜力的关键。然而，实践中这些过程通常依赖于手动沟通和共享表格，这些方式在大型分布式研究中会迅速过时，阻碍高效协调。这凸显了对专用监测解决方案的需求，以提供透明且实时更新的研究进展洞察。我们提出一种轻量级、开源的监测架构，基于广泛使用的Grafana-Prometheus技术栈。该框架收集来自分布式研究站点的聚合监测指标，并通过可配置仪表盘进行可视化。作为实际部署示例，该框架被集成到医学影像平台Kaapana中，并在一个大型多中心研究网络内进行了评估。通过在德国全境的RACOON联盟部署我们的解决方案，我们证明了其能够在所有38家德国大学医院实现隐私保护的数据探索与研究进度监测。该监测框架支持分布式研究活动的透明协调，并有助于促进大规模多中心研究的更高效管理。源代码及Kaapana集成方案已在https://github.com/MIC-DKFZ/study-monitoring-kaapana上公开提供。