A team at Tampere University, Finland has developed a technique using surgical smoke that allows neurosurgeons to ID cancerous tissue during surgery.
A new method developed by researchers at Tampere University in Finland helps analyze surgical smoke to distinguish between malignant tissue and health tissue. The researcher’s work was recently published in the Journal of Neurosurgery.
The technology is based on differential mobility spectrometry, wherein flue gas ions are fed into an electric field. The distribution of ions in the electric field is tissue-specific, and the tissue can be identified on the basis of the resulting "odor fingerprint."
The study analyzed 694 tissue samples collected from 28 brain tumors and control specimens.The system consists of a machine learning system, which analyses the flue gas with DMS technology, and an electric knife, which is used to produce the flue gas from the tissues.
The system's classification accuracy was 83% when all the samples were analyzed. The accuracy improved in more restricted settings. When comparing low malignancy tumors (gliomas) to control samples, the classification accuracy of the system was 94%, reaching to 97% sensitivity and 90% specificity.