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
Sekisui Diagnostics

Download Mobile App




AI Detects Early Prostate Cancer Missed by Pathologists

By LabMedica International staff writers
Posted on 26 Aug 2025

Men who are assessed as healthy after a pathologist examines their prostate tissue may still harbor an early form of cancer. More...

The difficulty lies in the fact that subtle tissue changes often remain invisible to the human eye, leading to cancers being missed until they become more aggressive. Researchers have now demonstrated that a new artificial intelligence (AI) tool can identify these hidden signs well before traditional pathology reveals them.

The AI tool developed by researchers at Uppsala University (Uppsala, Sweden), in collaboration with Umeå University (Umeå, Sweden; www.umu.se), is trained to analyze prostate tissue images, pixel by pixel, to identify abnormal patterns present in men who later develop cancer. Unlike earlier studies that focused on single mutations or obvious tissue changes, this system can detect minute, complex changes in the tissue architecture.

In the study, nicknamed the ‘missed study’, as the goal of finding the cancer was ‘missed’ by the pathologists, the researchers examined biopsy samples from 232 men whose tissues had initially been assessed as healthy by pathologists. Within two and a half years, half of these men developed aggressive prostate cancer, while the rest remained cancer-free eight years later. The AI was trained on these samples and then tested on an independent set of images to validate its accuracy.

The findings, published in Scientific Reports, show that the AI detected early signs of prostate cancer that were missed by pathologists in more than 80% of samples from men who later developed the disease. When reviewing the patterns ranked most informative by the AI, the researchers found subtle changes in the tissue surrounding prostate glands, consistent with results from other studies. This confirmed that the AI can pick up clinically significant signals invisible to human observers.

Such an approach could transform how men diagnosed as healthy are monitored in the future. The system may help determine how soon follow-up tests should occur, reducing the risk of late detection of aggressive cancers. Importantly, the imaging data and methods used in this study are openly available, enabling other researchers to further refine the model and apply it to broader clinical practice.

“We have now shown that with the help of AI, it is possible to find signs of prostate cancer that were not observed by pathologists in more than 80 per cent of samples from men who later developed cancer,” said Carolina Wählby, who led the AI development in the study.

Related Links:
Uppsala University
Umeå University


Platinum Member
Automated Coagulation Analyzer
Hemolumi H6
βeta-Hydroxybutyrate Reagent
β-Hydroxybutyrate LiquiColor®
CMV CLIA Diagnostic
CLIA CMV IgA Screen Group
Gold Member
Clinical Chemistry Assay
Sorbitol Dehydrogenase (SDH)
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

Molecular Diagnostics

view channel
Image: The test combines RNA signals from the tumor-immune microenvironment to predict treatment response, rather than relying on a single marker such as PD-L1 expression.(Image Credit: Adobe Stock)

RNA-Based Test Predicts Immunotherapy Response in Non-Small Cell Lung Cancer

Non-small cell lung cancer (NSCLC) represents the largest U.S. patient population eligible for immune checkpoint inhibitor therapy. Treatment selection often relies on PD-L1 expression, but a single protein... Read more

Immunology

view channel
Image Credit: Adobe Stock

Immune Profiling Identifies Early Maternal Autoantibodies Linked to Preterm Birth Risk

A typical pregnancy lasts about 40 weeks, but labor begins prematurely in roughly one in 10 pregnancies. Preterm birth is the leading cause of newborn death worldwide, yet its underlying causes and which... Read more

Technology

view channel
Image: The laser-based photoacoustic spectroscopy setup consists of a Mid-IR laser equipped with three QCL modules covering wavelengths from 5.6 μm to 12.9 μm, two silver coated mirrors (SCM), a dichroic mirror (DM) with a transmittance of 90%, a thermal power sensor head (PM) to monitor the output laser power, a mechanical chopper (MC) for frequency modulation and a CEPAS-detector with a self-designed swab holder (SH). (Credit: Graunke, T., Scholz, T., Pieniak, M. et al. Scientific Reports (2026). https://doi.org/10.1038/s41598-026-68298-9)

Laser-Based Swab Analysis Shows Promise for Detecting Disease-Linked Odor Patterns

Disease-related changes in volatile organic compounds can alter body odor, producing measurable patterns in exhaled breath and bodily fluids. Current analytical methods can be complex, time-consuming,... Read more

Industry

view channel
Image Credit: iStock

Global TB Summit Connects Diagnostic Testing With Prevention and Clinical Care

Tuberculosis remains a major global infectious disease challenge despite declining deaths. In 2024, an estimated 10.7 million people worldwide developed the disease and nearly 1.2 million died from it.... Read more
Copyright © 2000-2026 Globetech Media. All rights reserved.