Imagine a super-fast camera that can 'see' the chemical fingerprints of cancer cells without needing any dyes or stains. It works like a high-speed scanner that identifies bad cells instantly, almost like a digital highlighter for surgeons. This helps doctors know exactly where the tumor ends and healthy tissue begins while they are still operating.
Traditional cancer diagnosis relies on slow, manual histopathologic analysis of frozen tissue, which is subjective and provides limited molecular data during surgery.
A label-free vibrational microscope combining PT-IR, FT-IR, and DHM. Key components include broadband IR laser pulses and a widefield all-optical lock-in camera.
If you are an equipment manufacturer dealing with the slow speed of current biopsy analysis — this project developed a label-free vibrational microscopy system that provides high-speed chemical selectivity. This allows for the creation of a new class of intraoperative diagnostic tools.
If you are a surgical center dealing with the risk of incomplete tumor resection — this project developed an AI-integrated microscope that identifies resistant tumor clones. This ensures more complete resection during a single intervention.
If you are a biotech company dealing with therapy resistance in cancer patients — this project developed a way to image molecular biomarkers with high spatial resolution. This helps in identifying the best tailored therapeutic approach for the patient.
Based on available project data, there is no information regarding the cost or commercial pricing of the system.
The project involves 1 industry partner and 1 SME, suggesting a path toward industrialization, though specific scaling metrics are not provided in the data.
Based on available project data, specific patent or licensing details are not mentioned; however, the project is currently in the development phase (2022-2026).
The system is designed to assist healthcare professionals during tumor biopsy diagnostics and oncosurgery to provide real-time grading and staging.
The project period runs from 2022-09-01 to 2026-12-31, indicating that the technology is still under development.
The consortium is heavily research-oriented, consisting of 4 universities and 2 research organizations, with a low industry ratio of 14% (1 industry partner and 1 SME). This suggests the project is currently focused on technical feasibility and fundamental physics rather than immediate commercial rollout.
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