Lung cancer claims over 2 million lives worldwide each year and is the most common cause of cancer death. A new artificial intelligence blood testing technology has been developed by researchers at the Johns Hopkins Kimmel Cancer Center and it was found to detect lung cancer with high accuracy in samples from about 800 individuals with and without cancer. This new test approach is called DELFI: DNA evaluation of fragments for early interception. It works by spotting unique patterns in fragmentation of DNA shed from cancer cells circulating in the blood.
With this new technology, the researchers have found that the DELFI approach was able to accurately distinguish between patients with and without lung cancer. The test combined with analysis of clinical risk factors, protein biomarker, and followed by computed tomography imaging. DELFI approach detected over 90% of lung cancer patients including those with early and advanced stages as well as with different subtypes.
With the use of AI to detect tumor cells, this blood test is much easier to administer as compared to low-dose CT scans. This allows for screening of more individuals in shorter periods of time. It requires a low coverage sequence of the genome and this makes it cost-effective in screening settings.
“It is clear that there is an urgent and unmet clinical need for the development of alternative non-invasive approaches to improve cancer screening in high-risk individuals and ultimately the general population.” The lead author, Dimitrios Machios, a postdoctoral fellow at Johns, said. “Lung cancer blood tests, or “liquid biopsies,” are easy to perform, widely accessible, and cost-effective, and we believe they are a good way to enhance our screening efforts.” The group would further like to study DELFI in other types of cancers as well.
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