Novel device that accurately identifies cancer in seconds

Novel device that accurately identifies cancer in seconds
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Highlights

Scientists have developed a pen-like device that accurately identifies cancerous tissue during surgery in 10 seconds, that improve treatments and reduce the chances of cancer recurrence. The MasSpec Pen, developed by researchers from University of Texas, Austin in the US, is a handheld instrument that gives surgeons precise diagnostic information about what tissue to cut or preserve during surgery

Houston : Scientists have developed a pen-like device that accurately identifies cancerous tissue during surgery in 10 seconds, that improve treatments and reduce the chances of cancer recurrence. The MasSpec Pen, developed by researchers from University of Texas, Austin in the US, is a handheld instrument that gives surgeons precise diagnostic information about what tissue to cut or preserve during surgery.

The current methods for diagnosing cancers and determining the boundary between cancer and normal tissue during surgery, is slow and sometimes inaccurate. Each sample takes 30 minutes or more to prepare and interpret by a pathologist, which increases the risk of infection in patients. However, in tests on tissues removed from 253 human cancer patients, the MasSpec Pen took about 10 seconds to provide a diagnosis and was more than 96 per cent accurate.

The technology was also able to detect cancer in marginal regions between normal and cancer tissues that presented mixed cellular composition. Living cells, whether they are healthy or cancerous, produce small molecules called metabolites. These molecules are involved in all the important processes of life - such as generating energy, growing and reproducing - as well as other useful functions such as removing toxins, researchers said. Each type of cancer produces a unique set of metabolites and other bio markers that act as fingerprints.

The molecular fingerprint obtained by the MasSpec Pen from an uncharacterised tissue sample is instantaneously evaluated by software, trained on a database of molecular fingerprints that was gathered from 253 human tissue samples. The samples included both normal and cancerous tissues of the breast, lung, thyroid and ovary.

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