KURE – AI-Supported Intraoperative Raman Analysis for Urological Cancer Detection

Project Duration

November 2025 – October 2028

Project Description

In cancer surgery, reliable pathological diagnoses are often available only hours or even days after tissue sampling. The collaborative research project KURE aims to develop a novel approach that enables the rapid and accurate differentiation between benign and malignant tumors directly during surgery.

To achieve this, Raman spectroscopy is combined with artificial intelligence (AI). Laser light generates a molecular “fingerprint” of the tissue, which is analyzed in real time by AI models. The results are provided via a cloud-based platform to support surgeons and pathologists in intraoperative decision-making. The approach aims to reduce diagnostic turnaround times, improve surgical decision-making, and complement conventional frozen section diagnostics. Initially, the project focuses on tumors of the kidney, testis, and prostate, with the long-term goal of extending the technology to additional tumor entities.

Role of Dresden University Medicine

At Dresden University Medicine, the project brings together the Institute of Pathology and the Department of Urology at the University Hospital Carl Gustav Carus (UKD), as well as the Usability & Technology Acceptance Research Group at the Institute for Medical Informatics and Biometry (IMB) and the Center for Medical Informatics (ZMI). Together, the partners contribute clinical, pathological, and medical informatics expertise to the development and evaluation of the AI-supported system.

The responsibilities of the Usability & Technology Acceptance Research Group (IMB & ZMI) include:

Analyzing clinical workflows, usage contexts, and decision-making processes in urology and pathology as the basis for the user-centered design of the AI-supported system.
Eliciting, structuring, and prioritizing user requirements for the user interface, AI functionalities, and the presentation of diagnostic analysis and classification results.
Designing and evaluating interaction and visualization concepts that promote transparent, understandable, and trustworthy human-AI interaction.
Planning, conducting, and analyzing qualitative and quantitative usability studies as well as clinical evaluations to investigate usability, user acceptance, and trust in the AI-supported system.

Contact

Group leader

Ms PD Dr. rer. biol. hum. habil. Brita Sedlmayr

Send email

work Tel.
fax Fax: +49 351 458-5738

Funding

The project is funded by the German Federal Ministry for Research, Technology and Space (BMFTR) as part of the National Decade Against Cancer.