People all around the world have surgeries each day to remove cancerous tissue from their bodies in an attempt to defeat the disease. The challenge for surgeons and medical personnel is to tell which tissue is cancerous and which is healthy so they know how much to remove. A team of scientists and engineers from the University of Texas at Austin has invented a new tool that will make it much easier for a surgeon to tell what tissue is cancerous and what is healthy during a surgery.
The team behind the MasSpec Pen says that it can accurately identify cancerous tissue during a surgery in about ten seconds. That is 150 times faster than existing technology. MasSpec Pen is a handheld tool and the designers say that it will help reduce the chance of a cancer returning due to not removing all the cancerous tissue during procedures. The current process for determining what is cancer and what is normal tissue during surgery is called Frozen Section Analysis and the process is slow and sometime inaccurate.
The samples can take up to 30 minutes to prepare and interpret by a pathologist. Scientists note that the process can be difficult to do with some types of cancers and could give unreliable results in 10-20% of cases. The MasSpec Pen was tested using tissue removed from 253 human cancer patients and in those tests it took about ten seconds to provide a diagnosis and was over 96% accurate.
The tech detected cancer in marginal regions between the normal tissue and cancerous tissue that have mixed cellular composition. The UT team expects that the MasSpec Pen will be used in oncological surgeries starting in 2018. The device works by detecting metabolites produced by each type of cancer that are said to be akin to fingerprints.
The MasSpec Pen takes a molecular fingerprint for the tissue being tested and that fingerprint is evaluated by software called a statistical classifier. The software compares the sample’s molecular fingerprint to a database of similar data to determine if the tissue is cancerous. The results are clearly identified using words on a screen as “Normal” or “Cancer.” The team has filed for a patent on the device.