Invenio Imaging provides the NIO Laser Imaging System utilizing Stimulated Raman Histology for rapid tissue evaluation. This system delivers high-quality, unstained histology images in under three minutes directly in the operating room. The native digital images support immediate intraoperative decision-making and allow for subsequent downstream analysis of the retrieved tissue sample.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional histology requires extensive sample preparation, including fixation, sectioning, and staining, which delays intraoperative decision-making and can compromise tissue viability for subsequent analysis. This process limits the ability of surgical teams to obtain rapid, real-time tissue feedback during procedures.
Solution
Invenio Imaging's NIO Laser Imaging System utilizes Stimulated Raman Histology (SRH) to provide rapid, on-site tissue evaluation without the need for staining or sectioning. The system enables intraoperative imaging of fresh tissue specimens in under three minutes, delivering digital, shareable images directly to surgical teams. This streamlined workflow facilitates immediate assessment of tissue margins and cellular architecture, supporting informed intraoperative decisions. Furthermore, the SRH process preserves specimen integrity, allowing for retrieval and downstream analysis after imaging.
Target Audience
The primary target audience includes surgeons and pathologists requiring intraoperative tissue assessment, as well as hospital systems and research institutions seeking to enhance surgical workflow efficiency and diagnostic capabilities.
Features
- Stimulated Raman Histology (SRH) for label-free, molecularly specific imaging of fresh tissue.
- NIO Laser Imaging System capable of acquiring high-resolution histology images in under three minutes.
- Integrated sample preparation workflow that eliminates the need for traditional fixation, sectioning, and staining.
- Digital image output compatible with existing IT infrastructure via a vendor-neutral DICOM interface.
- Preservation of tissue specimens post-imaging, enabling subsequent molecular or genomic analysis.
- AI-powered image analysis algorithms (e.g., NIO Glioma Reveal) for automated detection of cancerous infiltration (currently for research use in the US).
- Application across multiple surgical subspecialties including neurosurgery, pulmonology, urology, and oncology.