A new study on detection of breast cancer from surgical smoke
Diathermy blade is used extensively in breast surgery. The molecules from the incised tissue evaporate to the produced surgical smoke. Surgical smoke contains fine particles that are hazardous on health. Due to occupational hazards, it is of great importance to remove the smoke from the operating theatre. The constitution of breast tumor cells and healthy breast tissue cells differ. Thus, malignant and benign breast tissue can be identified from the surgical smoke created with a diathermy blade. The article on the identification of breast tumors from diathermy smoke was published in the distinguished European Journal of Surgical Oncology in February 2019.
The new method aids both the patient and the surgeon.
“Breast cancer is treated with a conserving surgery or mastectomy,” a doctoral student Maiju Lepomäki from the Tampere University explains. “In conserving surgery the primary goal is to remove the tumor completely because an inadequate removal increases the risk of local recurrence. However, the approximation of the tumor borders visually or by palpation is not easy. Globally, every fifth patient that is treated with breast- conserving surgery require a reoperation because cancerous tissue remain in the edges of the surgical area.”
Differential ion mobility spectrometry (DMS) is a fast and economical technology and is connected to existing smoke evacuation suction device, which enables the analysis of gas mixtures.
“The technology provides a new method to assess from surgical smoke whether the analysed tissue contains malignant cells,” Lepomäki says.
Current intraoperative methods for surgical margin detection interrupt the surgeons work or are expensive and complex to use. The new method is easily applied because a diathermy blade and smoke evacuation device is currently used extensively in breast surgery.
“Surgical smoke analysis using DMS-technology enables a practical and economical method for real-time surgical margin assessment,” Lepomäki states.
In the study 106 tissue samples from 21 breast tumours and 198 samples from healthy breast tissue were analysed. The healthy tissue samples included normal mammary gland, fat tissue and vascular structures. The system used in the study to analyze surgical smoke using DMS-technology comprised of a sampling system, a gas sensor and a system which utilizes machine learning. All tissue samples were incised with a diathermy blade and the surgical smoke produced was analysed. The classification accuracy of the system was 87 %. The sensitivity and specificity of the system were 80 % and 90 %, respectively.
Doctoral student Maiju Lepomäki (nee Sutinen), Tampere University p. +35841 544 3594, maiju.sutinen [at] tuni.fi
Professor Niku Oksala, Tampere University p. +358400591911, niku.oksala [at] tuni.fi
Photo: Tissue samples were placed in a custom made well plate and incised with a diathermy blade to produce surgical smoke.