New blood test uses infrared light, AI to detect signs of brain cancer

Researchers have developed a new blood test that could lead to improved brain cancer diagnoses, according to new findings published in Nature Communications.

The study’s authors noted that providing a “timely” brain cancer diagnosis can be challenging for healthcare providers.

“Diagnosing brain tumors is difficult, leading to delays and frustration for lots of patients,” co-author Paul M. Brennan, University of Edinburgh in the UK, said in a prepared statement. “The problem is that symptoms of brain tumor are quite non-specific, such as headache, or memory problems. It can be difficult for doctors to tell which people are most likely to have a brain tumor.”

The test involves attenuated total reflection Fourier transform infrared (ATF-FTIR) spectroscopy and machine learning technologies. The researchers found that the test achieved a specificity of 87%, a sign that it “would deliver significant cost savings to the health services.”

The test’s sensitivity, meanwhile, was 83.3%.

“From a patient perspective, higher sensitivity has the greatest impact on quality of life due to the opportunity to identify and treat cancers early,” the authors wrote in the study. “From an economic perspective, a test with high specificity is desirable as the number of unnecessary brain scans can be reduced.”

The Brain Tumour Charity, a U.K.-based charity, is helping fund this team’s research. Hayley Smith, an ambassador of the charity, spoke about the impact such a blood test could make on patient care.

“Scotland now has research teams from all over the world and all are experts in their fields,” Smith said in the prepared statement. “It's so promising to know that we have the best of the best looking into quicker diagnosis and new treatments. This kind of test will be vital to patients, helping people to get the correct diagnosis quicker which ultimately will help people to get the urgent medical care that they need.”

Michael Walter
Michael Walter, Managing Editor

Michael has more than 16 years of experience as a professional writer and editor. He has written at length about cardiology, radiology, artificial intelligence and other key healthcare topics.

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