AI Image Analysis Module Detects Cancers at the Time of Surgery

Invenio Imaging Inc.’s (Santa Clara, CA, USA) NIO Laser Imaging System uses Stimulated Raman Histology to image unprocessed tissue specimen without sectioning or staining, enabling histologic evaluation outside the laboratory. It has been used in over 2000 brain tumor procedures across multiple institutions in the US and in Europe. SRH allows three-dimensional imaging of thick specimens using optical sectioning and relies on laser spectroscopy to interrogate the chemical composition of the sample. As such, it does not require physical sectioning, (e.g. with a microtome on frozen or paraffin-embedded tissue) or dye staining, and it allows optical imaging of fresh tissue specimens with minimal tissue preparation.

In contrast to other laser spectroscopy techniques, SRH is unique in that it performs a spectroscopic measurement at each pixel and displays the results as a pseudo-color image, instead of a point spectrum. The NIO Laser Imaging System uses a high numerical aperture objective with 25x magnification and a 0.5mm scan width. Larger areas up to 10mm x 10mm can then be acquired by stitching multiple fields of view in a fully automated process. NIO images are natively digital and can be shared with existing IT infrastructure via a vendor-neutral DICOM interface. The NIO Glioma Reveal image analysis module now adds immediate decision support to the NIO Laser Imaging System by allowing the imaging of multiple samples from the resection cavity. Invenio has received the CE Mark for the NIO Glioma Reveal image analysis module, allowing neurosurgeons in the EU to use it to inform intraoperative decisions.

"By streamlining intraoperative tissue imaging, the NIO Laser Imaging System allows the imaging of multiple samples from the resection cavity. The NIO Glioma Reveal image analysis module now adds immediate decision support", said Chris Freudiger, PhD, co-founder and CTO of Invenio Imaging.

"Glioma Reveal provides cancer detection where we really need it, dramatically improving brain tumor surgery," added Prof. Dr. Jürgen Beck, Chair of Neurosurgery at the University of Freiburg.

"Applying reliable artificial intelligence to digital pathology appears to me, as a surgeon, to be the missing piece in the puzzle of rapid intraoperative histology-based decision-making," said Asst. Prof. Dr. Volker Neuschmelting, Vice-Chair of Neurosurgery at the University of Cologne.

"The NIO Laser Imaging System can also be combined with other important imaging techniques such as 5-ALA fluorescence to further improve brain tumor detection during surgery," explained Prof. Dr. Georg Widhalm, neurosurgeon at the University of Vienna.

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