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




New Technique Paints Tissue Samples with Light

By LabMedica International staff writers
Posted on 15 Apr 2015
One infrared scan can give pathologists a window into the structures and molecules inside tissues and cells, enabling fast and broad diagnostic assessments, due to a newly developed imaging technique.

Doctors and scientist use stains or dyes that stick to the particular structure or molecule they are looking for when studying tissue samples. More...
Staining can be a long and exacting process, and the added chemicals can damage cells. Histologists also have to choose which things to test for, because it is not always possible to obtain multiple samples for multiple stains from one biopsy. Dyes such as hematoxylin and eosin (H&E) and immunohistochemical stains have been increasingly used to visualize tissue composition in clinical practice.

Scientists at the University of Illinois Cancer Center (Urbana, IL, USA) and their colleagues have developed a technique using a combination of advanced microscope imaging and computer analysis. The new, advanced infrared imaging technique uses no chemical stains, instead scanning the sample with infrared light to directly measure the chemical composition of the cells. The computer then translates spectral information from the microscope into chemical stain patterns, without the bother of applying dyes to the cells.

The Fourier transform infrared (FT-IR) spectroscopic imaging and computation and stainless computed histopathology can enable a rapid, digital, quantitative and non-perturbing visualization of morphology and multiple molecular epitopes simultaneously in a variety of clinical pathology applications. The investigators reproduced a wide array of molecular stains by computationally isolating the spectra of specific molecules. This allows the user to simply tune to a required stain, for as many different stains as are necessary, all without damaging the original tissue sample, which can then be used for other tests.

David Mayerich, PhD, the lead author of the study, said, “We are relying on the chemistry to generate the ground truth and act as the 'supervisor' for a supervised learning algorithm. One of the bottlenecks in automated pathology is the extensive processing that must be applied to stained images to correct for staining artifacts and inconsistencies. The ability to apply stains uniformly across multiple samples could make these initial image processing steps significantly easier and more robust.” The study was published on March 20, 2015, in the journal Technology.

Related Links:

University of Illinois Cancer Center 



Gold Member
Fully Automated Cell Density/Viability Analyzer
BioProfile FAST CDV
Verification Panels for Assay Development & QC
Seroconversion Panels
New
Benchtop Cooler
PCR-Cooler & PCR-Rack
New
Unstirred Waterbath
HumAqua 5
Read the full article by registering today, it's FREE! It's Free!
Register now for FREE to LabMedica.com and get access to news and events that shape the world of Clinical Laboratory Medicine.
  • Free digital version edition of LabMedica International sent by email on regular basis
  • Free print version of LabMedica International magazine (available only outside USA and Canada).
  • Free and unlimited access to back issues of LabMedica International in digital format
  • Free LabMedica International Newsletter sent every week containing the latest news
  • Free breaking news sent via email
  • Free access to Events Calendar
  • Free access to LinkXpress new product services
  • REGISTRATION IS FREE AND EASY!
Click here to Register








Channels

Clinical Chemistry

view channel
Image: The GlycoLocate platform uses multi-omics and advanced computational biology algorithms to diagnose early-stage cancers (Photo courtesy of AOA Dx)

AI-Powered Blood Test Accurately Detects Ovarian Cancer

Ovarian cancer ranks as the fifth leading cause of cancer-related deaths in women, largely due to late-stage diagnoses. Although over 90% of women exhibit symptoms in Stage I, only 20% are diagnosed in... 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: The new algorithms can help predict which patients have undiagnosed cancer (Photo courtesy of Adobe Stock)

Advanced Predictive Algorithms Identify Patients Having Undiagnosed Cancer

Two newly developed advanced predictive algorithms leverage a person’s health conditions and basic blood test results to accurately predict the likelihood of having an undiagnosed cancer, including ch... Read more
Copyright © 2000-2025 Globetech Media. All rights reserved.