New AI-Powered Blood Test Spots Early Signs of Breast Cancer

Researchers from the University of Edinburgh have developed a first-of-its-kind, non-invasive screening method to detect the earliest stages of breast cancer. 

This method combines laser analysis with a type of AI that detects subtle changes in the bloodstream that occur during the initial phases of the disease, known as stage 1a, which are not detectable with existing tests, the team says.

Dr Andy Downes, of the University of Edinburgh’s School of Engineering, who led the study, said: “Most deaths from cancer occur following a late-stage diagnosis after symptoms become apparent, so a future screening test for multiple cancer types could find these at a stage where they can be far more easily treated. Early diagnosis is key to long-term survival, and we finally have the technology required. We just need to apply it to other cancer types and build up a database, before this can be used as a multi-cancer test.”

The new method could improve early detection and monitoring of the disease and pave the way for a screening test for multiple forms of cancer.

Using this method, researchers were able to spot breast cancer at the earliest stage by optimizing a laser analysis technique known as Raman spectroscopy. This was combined with a form of AI machine learning.

The technique works by shining a laser beam into blood plasma taken from patients. The team analyzed the properties of the light after it interacted with the blood, using a device called a spectrometer to reveal tiny changes in the chemical makeup of cells and tissues.

A machine learning algorithm then interpreted the results, identifying similar features and helping to classify samples.

In the pilot study involving 12 samples from breast cancer patients and 12 healthy controls, the technique was 98% effective at identifying breast cancer at stage 1a.

The test could distinguish between the four main subtypes of breast cancer with 90% accuracy, which could enable patients to receive more effective, personalized treatment.

Study results were published in the Journal of Biophotonics. Blood samples used in the study were provided by the Northern Ireland Biobank and Breast Cancer Now Tissue Bank. 

Researchers from the University of Aberdeen, the Rhine-Waal University of Applied Sciences, and the Graduate School for Applied Research in North Rhine-Westphalia also participated in the study. 

The team aims to expand the work to involve more participants and include tests for early forms of other cancer types.