We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
LGC Clinical Diagnostics

Download Mobile App




AI Image Analysis Module Detects Cancers at the Time of Surgery

By LabMedica International staff writers
Posted on 26 May 2022
Print article
Image: NIO Laser Imaging System (Photo courtesy of Invenio Imaging)
Image: NIO Laser Imaging System (Photo courtesy of Invenio Imaging)

A new image analysis module based on deep learning allows neurosurgeons to identify areas of cancer infiltration in patients undergoing primary treatment of a diffuse glioma, providing cancer detection where they really need it and dramatically improving brain tumor 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.

Related Links:
Invenio Imaging Inc.

Gold Member
Flocked Fiber Swabs
Puritan® Patented HydraFlock®
Verification Panels for Assay Development & QC
Seroconversion Panels
New
Benchtop Cooler
PCR-Cooler & PCR-Rack
New
Blood Gas and Chemistry Analysis System
Edan i500

Print article

Channels

Clinical Chemistry

view channel
Image: QIP-MS could predict and detect myeloma relapse earlier compared to currently used techniques (Photo courtesy of Adobe Stock)

Mass Spectrometry-Based Monitoring Technique to Predict and Identify Early Myeloma Relapse

Myeloma, a type of cancer that affects the bone marrow, is currently incurable, though many patients can live for over 10 years after diagnosis. However, around 1 in 5 individuals with myeloma have a high-risk... Read more

Immunology

view channel
Image: The cancer stem cell test can accurately choose more effective treatments (Photo courtesy of University of Cincinnati)

Stem Cell Test Predicts Treatment Outcome for Patients with Platinum-Resistant Ovarian Cancer

Epithelial ovarian cancer frequently responds to chemotherapy initially, but eventually, the tumor develops resistance to the therapy, leading to regrowth. This resistance is partially due to the activation... Read more

Technology

view channel
Image: Ziyang Wang and Shengxi Huang have developed a tool that enables precise insights into viral proteins and brain disease markers (Photo courtesy of Jeff Fitlow/Rice University)

Light Signature Algorithm to Enable Faster and More Precise Medical Diagnoses

Every material or molecule interacts with light in a unique way, creating a distinct pattern, much like a fingerprint. Optical spectroscopy, which involves shining a laser on a material and observing how... Read more

Industry

view channel
Image: The collaboration aims to leverage Oxford Nanopore\'s sequencing platform and Cepheid\'s GeneXpert system to advance the field of sequencing for infectious diseases (Photo courtesy of Cepheid)

Cepheid and Oxford Nanopore Technologies Partner on Advancing Automated Sequencing-Based Solutions

Cepheid (Sunnyvale, CA, USA), a leading molecular diagnostics company, and Oxford Nanopore Technologies (Oxford, UK), the company behind a new generation of sequencing-based molecular analysis technologies,... Read more
Copyright © 2000-2025 Globetech Media. All rights reserved.