Novel Artificial Intelligence (AI) Blood Test Can Detect Over 90% of Lung Cancers

A novel blood test identifies lung cancer using artificial intelligence (AI) to detect unique patterns in the fragmentation of DNA shed from cancer cells compared to normal profiles.

The novel AI blood testing technology developed by researchers at the Johns Hopkins Kimmel Cancer Center (Baltimore, MD, USA) was found to detect over 90% of lung cancers in samples from nearly 800 individuals with and without cancer. The test approach, called DELFI (DNA evaluation of fragments for early interception), spots unique patterns in the fragmentation of DNA shed from cancer cells circulating in the bloodstream. Applying this technology to blood samples taken from 796 individuals, the investigators found that the DELFI approach accurately distinguished between patients with and without lung cancer. Combining the test with analysis of clinical risk factors, a protein biomarker, and followed by computed tomography imaging, DELFI helped detect 94% of patients with cancer across stages and subtypes. This included 91% of patients with earlier or less invasive stage I/II cancers and 96% of patients with more advanced stage III/IV cancers.


The DELFI technology uses a blood test to indirectly measure the way DNA is packaged inside the nucleus of a cell by studying the size and amount of cell-free DNA present in the circulation from different regions across the genome. Healthy cells package DNA like a well-organized suitcase, in which different regions of the genome are placed carefully in various compartments. The nuclei of cancer cells, by contrast, are like more disorganized suitcases, with items from across the genome thrown in haphazardly. When cancer cells die, they release DNA in a chaotic manner into the bloodstream. DELFI helps identify the presence of cancer using machine learning, a type of artificial intelligence, to examine millions of cell-free DNA fragments for abnormal patterns, including the size and amount of DNA in different genomic regions. This approach provides a view of cell-free DNA referred to as the “fragmentome.” The DELFI approach only requires low-coverage sequencing of the genome, enabling this technology to be cost-effective in a screening setting, the researchers say.

“DNA fragmentation patterns provide a remarkable fingerprint for early detection of cancer that we believe could be the basis of a widely available liquid biopsy test for patients with lung cancer,” said author Rob Scharpf, Ph.D., associate professor of oncology at the Johns Hopkins Kimmel Cancer Center.

“We believe that a blood test, or ‘liquid biopsy,’ for lung cancer could be a good way to enhance screening efforts, because it would be easy to do, broadly accessible and cost-effective,” said lead author Dimitrios Mathios, a postdoctoral fellow at the Johns Hopkins Kimmel Cancer Center.

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Johns Hopkins Kimmel Cancer Center