AI‑driven blood tests redefine early breast cancer detection
The use of artificial intelligence (AI) in detecting breast cancer is reaching new levels thanks to an innovative diagnostic method that allows for identifying the disease, even when it is difficult to recognize through traditional tests. This approach could significantly change patient outcomes.
AI-based algorithms are becoming increasingly effective in detecting cancer based on radiological data, confirming their superiority over traditional methods. Some solutions have already been implemented, with the UK National Health Service (NHS) currently using artificial intelligence to analyze mammograms. This helps detect cancer cases that doctors may have missed. Now, new AI possibilities have been discovered.
AI will detect cancer by analyzing blood samples
Scientists have developed a new method for diagnosing breast cancer at a very early stage, utilizing AI. The study published in the "Journal of Biophotonics" showed that combining blood sample analysis with Raman spectroscopy and AI algorithms allows for detecting early-stage breast cancer with an accuracy of 90 to 100 percent. This applies to stages labeled as 1A when the tumor reaches a size of about 2.5 cm or less and does not extend to the lymph nodes.
Traditional breast cancer diagnostic methods, such as X-ray mammography and biopsies, focus on directly detecting cancer cells and often miss early-stage cancers. Prof. Tipatet emphasizes that current technologies focus on a small, single element instead of observing a broader picture, which can lead to delays in diagnosis.
Molecular fingerprints could be a breakthrough
The new approach focuses on analyzing patients' blood using Raman spectroscopy, a chemical technique that measures molecular patterns in blood samples. This allows for the identification of molecular fingerprints, which signal the early stages of the body's response to cancer. AI algorithms process these data, identifying characteristic patterns indicating the presence of breast cancer.
This promising technique used in clinical diagnostics may become a key element of modern medicine. Professor Juergen Popp from the Leibniz Institute of Photonic Technology in Jena noted that Raman spectroscopy is "beginning to show great potential for clinical diagnoses [of many diseases]."
Integrating AI with the current system could be costly
Despite promising results, Professor Tipatet admitted that the study was conducted on a small group of 24 patients. He emphasized the need for further studies on a larger scale to confirm the method's effectiveness and reliability before its implementation in clinical practice. Additionally, integrating this technology with existing healthcare systems may face challenges related to costs, personnel training, and the standardization of diagnostic procedures.
Introducing AI into breast cancer diagnostics could significantly increase early disease detection rates, which is crucial for effective treatment and improving patient survival. However, the study authors believe that to fully realize the potential of this technology, further work and investments in medical infrastructure are necessary to enable its widespread use in clinical practice.
