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.

LabMedica

Download Mobile App
Recent News Expo Medica 2025 Clinical Chem. Molecular Diagnostics Hematology Immunology Microbiology Pathology Technology Industry Focus

Novel Technology Tracks Hidden Cancer Cells Faster

By LabMedica International staff writers
Posted on 04 Dec 2025

Targeting and treating disease often hinges on the ability to locate specific cells inside the body—a challenge made difficult because harmful or therapeutic cells move through tissues and are not easily detected. Now, a new technology designed to track these cells with single-cell precision could lead to more effective therapies.

Researchers at Case Western Reserve University (Cleveland, OH, USA) are advancing their technology that enhances the ability to locate therapeutic cells or diseased cells like cancer. Their platform, based on the CryoViz cryo-imaging system, generates high-resolution 3D images using robotics, microscopy, and advanced software. By integrating artificial intelligence (AI) and machine-learning tools, the CryoViz cryo-imaging device can automatically identify healthy and diseased tissues, detect fluorescently labeled cells, and enable “virtual staining” to examine samples at a single-cell level.


Image: The CryoViz cryo-imaging device (Photo courtesy of BioInVision)
Image: The CryoViz cryo-imaging device (Photo courtesy of BioInVision)

By drastically reducing the time and complexity of whole-body imaging—mapping an entire mouse in hours instead of using millions of tissue sections—the approach aims to transform how researchers track metastatic cancer cells, evaluate T-cell behavior during immunotherapy, and assess drug delivery or imaging agents. The team will also use an AI-based “virtual staining” approach to evaluate the body’s tissue at a single-cell level, allowing them to track individual cells such as migrating or metastatic cancer cells and T-cells. This capability will help assess cell-based treatments treatments like immunotherapy.

“The computer can decide when it has detected some “glowing” fluorescent cells, like metastatic tumor cells in the lung,” said CWRU researcher Susann Brady-Kalnay. “It will automatically save tissue sections in that region so I can go back and study the tissue in detail at the cellular and molecular level.”

Related Links
Case Western Reserve University


Gold Member
Quality Control Material
iPLEX Pro Exome QC Panel
POC Helicobacter Pylori Test Kit
Hepy Urease Test
ESR Analyzer
TEST1 2.0
Sample Transportation System
Tempus1800 Necto

Latest Pathology News

Diagnostic Technology Performs Rapid Biofluid Analysis Using Single Droplet
04 Dec 2025  |   Pathology

AI Tool Improves Breast Cancer Detection
04 Dec 2025  |   Pathology

AI Tool Predicts Treatment Success in Rectal Cancer Patients
04 Dec 2025  |   Pathology



GLOBE SCIENTIFIC, LLC