Exploring the potential of rapid evaporative ionization mass spectrometry (Intelligent Knife) for point-of-care testing in aortic surgery. (11th April 2021) - Davies, Hannah A.; Caamano-Gutierrez, Eva; Sarsby, Joscelyn; Nawaytou, Omar; Harky, Amer; Akhtar, Riaz; Field, Mark; Madine, Jillian
Abstract:  : OBJECTIVES: Many intraoperative decisions regarding the extent of thoracic aortic surgery are subjective and are based on the appearance of the aorta, perceived surgical risks and likelihood of early recurrent disease. Our objective in this work was to carry out a cross-sectional study to demonstrate that rapid evaporative ionization mass spectrometry (REIMS) of electrosurgical aerosol is able to empirically discriminate ex vivo aneurysmal human thoracic aorta from normal aorta, thus providing supportive evidence for the development of the technique as a point-of-care test guiding intraoperative surgical decision-making. METHODS: Human aortic tissue was obtained from patients undergoing surgery for thoracic aortic aneurysms ( n  = 44). Normal aorta was obtained from a mixture of post-mortem and punch biopsies from patients undergoing coronary surgery ( n  = 13). Monopolar electrocautery was applied to samples and surgical aerosol aspirated and analysed by REIMS to produce mass spectral data. RESULTS: Models generated from REIMS data can discriminate aneurysmal from normal aorta with accuracy and precision of 88.7% and 85.1%, respectively. In addition, further analysis investigating aneurysmal tissue from patients with bicuspid and tricuspid aortic valves was discriminated from normal tissue and each other with accuracies and precision of 93.5% and 91.4% for control, 83.8% and 76.7% for bicuspid aortic valve and 89.3% and 86.0% for tricuspid aortic valve, respectively. CONCLUSIONS: Analysis of electrosurgical aerosol from ex vivo aortic tissue using REIMS allowed us to discriminate aneurysmal from normal aorta, supporting its development as a point-of-care test (Intelligent Knife) for guiding surgical intraoperative decision-making.