EP1131 the Iknife and Its Application for the Treatment of Cervical Abnormalities

Introduction/Background Surgical management of presumed early stage cervical cancer presents challenges as clearance of surgical margins avoids adjuvant chemoradiotherapy that can substantially increase morbidity and may allow fertility preservation in young women. Improved intra-operative diagnostic tools have the potential to improve outcomes. In this study, we explore whether the Rapid Evaporative Ionization Mass Spectrometry (REIMS), also known as the iKnife (intelligent Knife), can accurately discriminate between healthy, pre-invasive and invasive cervical tissue ex vivo. Methodology We prospectively collected fresh frozen cervical tissue samples in normal controls and women with Human Papilloma Virus (HPV) ± cervical intraepithelial neoplasia (CIN) and cervical cancer (Cancer) between 2006 and 2018. A handheld diathermy device was used to burn the biopsies; the surgical aerosol produced was subsequently transferred into a mass-spectrometer. The tissue was then stained for histopathological validation. We used principal component and linear discriminant analysis to calculate the accuracy of the iKnife in discriminating between the 3 groups. Cancerous and normal tissues were then processed with REIMS tandem MS (REI-MS/MS) to further delineate the most significant peaks allowing separation of the two classes and identify their lipid profile. Results The iKnife had an overall 97.8% accuracy in discriminating accurately normal (100%) vs HPV±CIN (100%) versus cancer (83.3%) when compared to histology as the gold standard. REI-MS/MS and LipidMAPS revealed twelve significant MS peaks in the cancer to normal separation. Conclusion This study shows that REIMS iKnife has the potential to accurately discriminate healthy, from precancerous and invasive lesions on the cervix. The overexperessed lipids in cancer may be used as markers of disease. If these finding are replicated in larger cohorts, the iKnife may allow real-time intra-operative diagnosis of the presence of disease in surgical margins and lymph nodes. Disclosure Nothing to disclose