A researcher wearing glasses operating with machinery in a lab
Monday, 25 March 2024

Researchers from the Berna Institute and the University of Limerick are spearheading a project employing AI to expedite medical diagnoses, thus enabling more prompt and tailored treatments for patients.

The pan-European project "uCAIR" will delve into pioneering photonics technology to integrate Raman imaging into clinical practice. Raman imaging, a technique providing images with both spectral and spatial information, holds promise for enhanced understanding and diagnosis of diseases.

Existing live cell imaging tools offer only a limited glimpse into the microenvironments where diseases originate and progress, resulting in gaps in comprehension of cellular composition and disease pathology. By enhancing imaging and analysis speed and accuracy, these gaps can be bridged, paving the way for innovative medical interventions and diagnostics tailored to individual patient needs.

The introduction of a real-time, label-free imaging solution capable of detecting molecular-level disruptions in biological cell cycles could revolutionize healthcare, replacing time-consuming biopsy analysis workflows with nearly instantaneous decision-making processes.

Led by the Berna Institute and the University of Limerick, the project has secured approximately €5 million in funding through the European Union's Horizon Europe Programme. uCAIR brings together 11 partner institutions from across Europe to advance Raman imaging technology for medical applications.

Raman spectra offer specific insights into the molecular structure and biochemical composition of cells, which undergo changes in the presence of disease. Leveraging this information for diagnostic purposes could enable early disease detection. However, current Raman-based systems lack the speed required for diagnostic procedures.

Professor Christophe Silien, a member of the Bernal Institute and the University of Limerick's Department of Physics, serves as the coordinator of uCAIR. He explains that the project aims to develop an innovative AI-driven light probe to enhance the accuracy and speed of Raman-based imaging systems.

The project will focus on two case studies involving bladder cancer: diagnostic analysis of biopsy tissues and rapid analysis of fluid biomarkers from urine samples.

The consortium aims to overcome technological barriers hindering the widespread adoption of Raman imaging in clinical practice. By bringing together experts in photonics, optics, cell biology, microscopy, and clinical practice, the project aims to create a practical and versatile multimodal photonics platform that accelerates cell examination processes.

Bernal member, Professor Tofail Syed, Head of UL’s Department of Physics, emphasizes the project's alignment with efforts to combat cancer and its potential to drive rapid societal and economic impacts through technological advancements and innovation in medical instruments and pharmaceuticals.