Electrosurgical resection, a common neurosurgery technique done with an electric knife or diathermy blade, produces surgical smoke, called diathermy smoke, from the burning of tissue during the procedure. Researchers in Finland have developed a device that can identify cancerous brain tissue based on properties of the diathermy smoke. This device could enable a surgeon to more quickly and accurately identify malignant tissue during brain cancer surgery in order to ensure that all parts of a tumor are excised.
"In current clinical practice, frozen section analysis is the gold standard for intraoperative tumor identification. In that method, a small sample of the tumor is given to a pathologist during surgery. Our new method offers both a promising way to identify malignant tissue in real time and the ability to study several samples from different points of the tumor," explained Ilkka Haapala of the Unit of Neurosurgery, Tampere University Hospital, Finland, and lead author of the study, which has now been published in the Journal of Neurosurgery.
The researchers' device uses a differential mobility spectrometry (DMS) connected to a special smoke sampling system. "The specific advantage of the equipment is that it can be connected to the instrumentation already present in neurosurgical operating theaters," explained Haapala.
The researchers tested the DMS device on brain tissue samples from 28 patients who had undergone neurosurgical resection. The tissue samples, which were cut into a total of 694 smaller specimens, included meningiomas (WHO grade I), grade I pilocytic astrocytomas, other grade II gliomas, grade IV glioblastomas, central nervous system metastases, and, for control samples, hemorrhagic or traumatically damaged brain tissue.
In a classification system that consisted of seven different categories, the DMS device achieved an overall classification accuracy of 50%, compared with 14% by chance. This accuracy rate improved substantially, by up to 83%, when the investigators excluded from analysis samples that had originally been preserved in Tissue-Tek® conservation medium. When fewer categories were used, the classification accuracy improved further. The DMS device achieved the highest classification accuracy—94%—in grade II glioma, for which it reached 97% sensitivity and 90% specificity.
The results "show that surgical smoke from various brain tumors has distinct DMS profiles," conclude Haapala and colleagues in their publication. "The DMS analyzer connected to a special sampling system can differentiate between tumorous and nontumorous tissue and also between different tumor types ex vivo."
For More Information
Haapala I, Karjalainen M, Kontunen A, et al (2019). Identifying brain tumors by differential mobility spectrometry analysis of diathermy smoke. J Neurosurg. [Epub ahead of print] DOI:10.3171/2019.3.JNS19274Image credit: Antti Roine