BY THE OPTIMIST DAILY EDITORIAL TEAM

Early detection of breast cancer dramatically increases survival rates, but identifying the disease in its earliest stages remains a challenge. Now, a new artificial intelligence (AI) method, combined with a specialized blood screening technique, has the potential to catch breast cancer sooner than ever before.

A recent pilot study published in the Journal of Biophotonics tested this innovative approach and found it could detect stage 1A breast cancers with an accuracy between ninety and one hundred percent. “This study is a milestone in being able to identify subtypes of breast cancers at very early stages, with high accuracy,” says Kevin Saruni Tipatet, the study’s lead author from the University of Edinburgh. “Early cancer diagnosis saves lives—that’s why our study is important.”

However, before this method can be implemented in hospitals, researchers must validate the results in larger-scale studies. The initial trial only included twenty-four patients, and experts agree that broader clinical trials are essential to confirm its effectiveness.

How this AI method works

Traditional cancer detection relies on imaging techniques like mammograms or biopsies, which focus on spotting visible tumors. However, early-stage cancers, particularly those at stage 1A, can be as small as a few millimeters and may not appear in scans.

This new approach takes a different route by analyzing the body’s biological response to cancer rather than searching for the tumor itself. “Most technologies are focused on finding that needle in the haystack,” explains Tipatet. “But they don’t look at the whole picture around it.”

Instead of identifying cancerous tissue, the research team searched for molecular fingerprints—unique chemical markers in the blood that indicate the body is responding to cancer. These markers may come from the cancer itself or from immune system cells fighting the disease.

To capture these molecular fingerprints, scientists used Raman spectroscopy, a powerful analytical tool that measures the molecular composition of blood samples. Once the data was collected, an AI algorithm was trained to detect patterns associated with breast cancer.

AI-assisted analysis: promising but not yet ready

The AI model was then tested on blood samples from the twenty-four patients, achieving an impressive detection accuracy of up to one hundred percent depending on the cancer subtype. However, while the results are encouraging, experts caution against overhyping the findings before further validation.

“This study presents an exciting approach, but the small sample size limits the broader generalizability of these findings,” says Juergen Popp, director of the Leibniz Institute of Photonic Technology in Germany. “Larger trials are essential for validating its clinical utility and scalability.”

Tipatet acknowledges these limitations and confirms that the research team is already planning a larger trial. “We need to see if we can reproduce these findings on a larger scale,” he says.

What this could mean for the future of cancer detection

If further studies confirm its effectiveness, this AI-powered blood screening method could offer a game-changing tool for early breast cancer detection. Catching cancer at stage 1A allows for less invasive treatments and significantly improves survival rates. Smaller tumors are easier to remove or target with treatments such as surgery or radiation therapy, increasing a patient’s chances of recovery.

Beyond breast cancer, researchers are also exploring the method’s potential applications for other common cancers. “We are looking into the so-called ‘Big Four’ cancers—lung, colorectal, prostate, and breast cancer,” Tipatet explains. “These four cancers account for around fifty percent of global cancer cases. Investing in early detection could improve survival rates for millions worldwide.”

While AI is already being used to enhance cancer diagnostics—such as the UK’s National Health Service incorporating AI to analyze mammograms—this new method could add another layer of precision by identifying cancer at an even earlier stage.

The research is still in its early phases, but the potential is clear: AI-assisted blood tests could become a powerful tool in the fight against cancer, transforming how we detect and treat the disease. As larger trials move forward, the medical community will be watching closely to see if this method lives up to its promise.

Source study: National Library of Medicine—Subtype-specific detection in stage Ia breast cancer: integrating Raman spectroscopy, machine learning, and liquid biopsy for personalised diagnostics