SpectraBrest

Breast-conserving surgery is the preferred treatment for early-stage breast cancer, yet up to 20% of patients still require a second intervention because residual tumor tissue is detected only after postoperative histopathological analysis.

Current intraoperative margin assessment methods are often slow, subjective, and difficult to implement routinely, creating significant clinical, emotional, and economic burdens for both patients and healthcare systems.

Spectra-BREAST addresses this challenge through the development of an advanced multimodal intraoperative platform that combines hyperspectral imaging, fiber-optic Raman spectroscopy, robotics, and artificial intelligence to provide surgeons with rapid and highly accurate assessment of tumor resection margins directly during surgery.

The system first identifies suspicious regions across the excised tissue using hyperspectral imaging and then performs targeted Raman analysis guided by AI algorithms, enabling real-time detection of cancerous tissue with a target accuracy above 95% and response times under five minutes.

By supporting more precise resections in a single procedure, Spectra-BREAST aims to drastically reduce reoperation rates, improve patient outcomes and quality of life, and lower healthcare costs while paving the way for broader applications in image-guided oncologic surgery.