Researchers at Imperial College London, say that they have developed an "intelligent knife" that can alert surgeons immediately whether the tissue they are cutting is cancerous or not. The “iKnife” diagnosed tissue samples from 91 patients with 100 percent accuracy, instantly providing information that normally takes up to half an hour to reveal using laboratory tests.

In cancers involving solid tumors, removal of the tumor, along with a margin of healthy tissue, is generally the best hope for treatment. Often, though it is impossible to tell by sight which tissue is cancerous. In cases of uncertainty, the removed tissue is sent for examination while the patient remains under general anesthetic.

The iKnife is based on electrosurgery, using an electrical current to rapidly heat tissue, cutting through it while minimizing blood loss. In doing so, it vaporizes the tissue, creating smoke that is normally sucked away by extraction systems.

The inventor of the iKnife, Dr. Zoltan Takats of Imperial College London, realized that this smoke would be a rich source of biological information. To create the iKnife, he connected an electrosurgical knife to a mass spectrometer, an analytical instrument used to identify what chemicals are present in a sample. Different types of cell produce thousands of metabolites in different concentrations, so the profile of chemicals in a biological sample can reveal information about the state of that tissue.

In the new study, the researchers first used the iKnife to analyze tissue samples collected from 302 surgery patients, recording the characteristics of thousands of cancerous and non-cancerous tissues, including brain, lung, breast, stomach, colon, and liver tumors to create a reference library. The iKnife works by matching its readings during surgery to the reference library to determine what type of tissue is being cut, giving a result in less than three seconds.

The technology was then transferred to the operating theater to perform real-time analysis during surgery. In all 91 tests, the tissue type identified by the iKnife matched the post-operative diagnosis based on traditional methods.

While the iKnife was being tested, surgeons were unable to see the results of its readings. The researchers hope to carry out a clinical trial to see whether giving surgeons access to the iKnife's analysis can improve patients' outcomes.

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