Markus Karjalainen, our hardware engineer, just defended his PhD dissertation with success! Congratulations Markus! The work consisted of four original publications with two main focuses. First, the structure and potential hazards of surgical smoke, and second the possibility of utilizing this smoke in surgical margin assessment. Factors affecting the technical performance of such detection equipment was also considered.
Study I aimed to characterize surgical smoke from various tissues, and considered the implications for occupational safety in the operating room. Tissues were able to be divided into three groups based on the particulate matter (PM) production. Smoke evacuation and filtration masks were recommended to be used especially when employing electrosurgery on the high- and medium-PM tissues.
Publication II aimed for identification of brain tumors with DMS from diathermy smoke. The sampling was performed with an automated tissue sampler. Brain tumor samples from 28 patients resulted in a total of over 600 smaller sample pieces, which were evaporated with the diathermy-based sampler. The study demonstrated that surgical smoke from various brain tumors produce distinct DMS profiles.
In study III, the effect of different tube materials and dimensions was studied in context of system recovery from smoke samples. The effect of temperature was also studied. Uncoated steel was found to have the best performance in increased temperature. Plastics performed well in lower temperatures, when adsorption exceeded absorption.
In study IV, the Olfactomics IonVision was used! The study focused on the signal kinetics of a DMS device in the surgical tissue classification context. Delay indicators for the system were studied by producing surgical smoke samples with a diathermy knife. The system was found to have low latency but long retention times, best described by the Lévy distribution.
You can find the full work on Tampere Univeristy’s Trepo site here! The work is in English.