London scientists develop ‘iKnife’, can tell if tissue is cancerous
In what can be considered a surgical breakthrough, scientists at the Imperial College London have developed an “intelligent knife” that can tell surgeons immediately whether the tissue they are cutting is cancerous or not.
iKnife
Image/Video Screen Shot
The research, Intraoperative Tissue Identification Using Rapid Evaporative Ionization Mass Spectrometry, is published in the journal Science Translational Medicine.
In the study, the “iKnife” diagnosed tissue samples from 91 patients with 100 per cent accuracy, instantly providing information that normally takes up to half an hour to reveal using laboratory tests, according to a College press release Wednesday.
Surgery is generally the best treatment for cancers involving solid tumors. However, it is often impossible to tell by sight which tissue is cancerous.
The iKnife is based on the decades old technology, electrosurgery. Electrosurgical knives use an electrical current to rapidly heat tissue, cutting through it while minimising blood loss. In doing so, they vaporise the tissue, creating smoke that is normally sucked away by extraction systems.
According to the release, Dr Zoltan Takats of Imperial College London and the iKnife inventor, realised 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 analyse 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 tumours 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 theatre 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.
