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
Sign In
Advertise with Us
PURITAN MEDICAL

Download Mobile App




AI Application in Pathology Reveals Novel Insights in Endometrial Cancer Diagnostics

By LabMedica International staff writers
Posted on 19 Dec 2022
Print article
Image: A new study has shown the power of AI applied to endometrial carcinoma microscopy images (Photo courtesy of Pexels)
Image: A new study has shown the power of AI applied to endometrial carcinoma microscopy images (Photo courtesy of Pexels)

Endometrial carcinoma is the most common cancer of the gynecologic tract. Now, researchers have shown the power of artificial intelligence (AI) can be applied to endometrial carcinoma microscopy images, offering novel insights that could improve diagnosis and treatment of uterine cancer.

In the past years, researchers at Leiden University (Leiden, the Netherlands) had played a leading role in the development of a novel tumor classification system based on molecular alterations, resulting in four endometrial cancer subtypes. This time, the team set out to investigate if it was possible to predict these molecular classes, based on microscopy-images alone. The researchers applied artificial intelligence on microscopy images of thousands of endometrial carcinoma images from patients that participated in the study.

The team developed a model that robustly predicts the four molecular classes of endometrial carcinomas based on one (hematoxylin and eosin)-stained microscopy slide image, which is the standard histological stain used in diagnostics for assessment of tumor grading and histological subtyping. This model was not “a black-box”, but through reverse-engineering the researchers were able to show which image-features were relevant for its predictions. The model provided the team with important novel insights that can be utilized in future studies to further improve diagnostics, prognostication, and management of endometrial cancer patients.

“The application of AI in pathology is emerging,” said Dr. Tjalling Bosse at Leiden University. “In this project we studied the morphology of tumors that shared the same molecular alteration to better understand the effect these changes have on the appearance of the tumor. With this work, the computer model has directed us to areas in- and outside the tumor that are important.”

“In cancer diagnostics, the number of variables (molecular, tumor morphology, patient data) has increased exponentially and has complexified patient prognosis prediction,” added Sarah Fremond. “Through training unbiased AI models, AI predictions can also teach pathologists in return by, for instance, identifying novel morphological details on microscopy slide images with prognostic value.”

Related Links:
Leiden University

Platinum Member
COVID-19 Rapid Test
OSOM COVID-19 Antigen Rapid Test
Magnetic Bead Separation Modules
MAG and HEATMAG
Anti-Cyclic Citrullinated Peptide Test
GPP-100 Anti-CCP Kit
New
Gold Member
Magnetic Bead Separation Modules
MAG and HEATMAG

Print article

Channels

Clinical Chemistry

view channel
Image: The 3D printed miniature ionizer is a key component of a mass spectrometer (Photo courtesy of MIT)

3D Printed Point-Of-Care Mass Spectrometer Outperforms State-Of-The-Art Models

Mass spectrometry is a precise technique for identifying the chemical components of a sample and has significant potential for monitoring chronic illness health states, such as measuring hormone levels... Read more

Molecular Diagnostics

view channel
Image: Liquid biopsy could detect and monitor aggressive small cell lung cancer (Photo courtesy of Shutterstock)

Blood-Based Test Detects and Monitors Aggressive Small Cell Lung Cancer

Small cell lung cancer (SCLC) is a highly aggressive type of cancer known for its ability to metastasize. The behavior of tumors is largely governed by which genes are turned on, or transcribed, irrespective... Read more

Hematology

view channel
Image: The CAPILLARYS 3 DBS devices have received U.S. FDA 510(k) clearance (Photo courtesy of Sebia)

Next Generation Instrument Screens for Hemoglobin Disorders in Newborns

Hemoglobinopathies, the most widespread inherited conditions globally, affect about 7% of the population as carriers, with 2.7% of newborns being born with these conditions. The spectrum of clinical manifestations... Read more

Immunology

view channel
Image: The groundbreaking treatment approach has shown promise in hard-to-treat cancers (Photo courtesy of 123RF)

Genetic Testing Combined With Personalized Drug Screening On Tumor Samples to Revolutionize Cancer Treatment

Cancer treatment typically adheres to a standard of care—established, statistically validated regimens that are effective for the majority of patients. However, the disease’s inherent variability means... Read more

Microbiology

view channel
Image: Microscope image showing human colorectal cancer tumor with Fusobacterium nucleatum stained in a red-purple color (Photo courtesy of Fred Hutch Cancer Center)

Mouth Bacteria Test Could Predict Colon Cancer Progression

Colon cancer, a relatively common but challenging disease to diagnose, requires confirmation through a colonoscopy or surgery. Recently, there has been a worrying increase in colon cancer rates among younger... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.