Currently, it takes surgeons about half an hour to determine if samples of tissue are cancerous or not, and it’s still somewhat of a guessing game because either too little or too much tissue is removed during surgery. Sometimes cancer patients may even be required to come in for a second or third round of tissue removal surgery before they are cleared of cancer.
Dr. Zoltan Takats of Imperial College London developed the iKnife, a system that combines an electrosurgical knife and a smoke analyzer to instantly determine whether tissue being severed is cancerous or not. Electrosurgical knives are used to quickly heat and cut through tissue while minimizing blood loss. When the tissue is cut, it vaporizes, resulting in smoke being outputted and sucked away via an extraction tube. Takats realized that this smoke is full of tons of biological information because of the thousands of metabolites contained in it.
The smoke is then run through a mass spectrometer which analyzes the metabolites to determine which type of cells produce them, and based on a library of information, they can determine whether the tissue is cancerous or not.
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 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.
You can read the full study in the latest journal of Science Translational Medicine.