Light-based technique shows 90% accuracy in early prostate cancer detection
Researchers at Aston University developed a light-based technique for early prostate cancer detection, achieving 90% accuracy by analyzing dried blood samples, potentially revolutionizing cancer diagnosis and monitoring.
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A novel light-based technique developed by researchers at Aston University demonstrates a 90% accuracy rate in the early detection of prostate cancer. Led by Professor Igor Meglinski, the team utilized a polarization-based imaging method to analyze the microstructure of dried blood samples. This approach focuses on changes in the proteins' tertiary and quaternary structures, which occur during the early stages of cancer. The study involved 108 blood film samples from healthy individuals and those diagnosed with prostate cancer, including cases with aggressive cell characteristics. The findings indicate that this non-invasive method could significantly improve cancer diagnosis and monitoring, offering a less traumatic alternative to traditional tissue biopsies. The technique's precision and reliance on blood samples mark a substantial advancement in liquid biopsy technology, potentially enhancing patient care and treatment outcomes. The research also highlights the collaboration with Ukrainian colleagues amidst ongoing conflict, underscoring the resilience of the scientific community.
- The new technique shows 90% accuracy in early prostate cancer detection.
- It utilizes a non-invasive method based on analyzing dried blood samples.
- The research involved 108 samples from healthy individuals and prostate cancer patients.
- This advancement could revolutionize cancer diagnosis and monitoring.
- The study reflects collaboration with Ukrainian researchers during challenging circumstances.
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7 commentsWe’re slowly getting there:
https://www.fusfoundation.org/diseases-and-conditions/prosta...
Or does it mean, "of all the patients who developed cancer, it detected 90% of them"?
Where the later is referring to the entire population, and the former is only about those detected.
Pretty amazing if it pans out.
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