The iKnife: real time Intra-operative tissue diagnostics using rapid evaporative ionisation mass spectrometry

Background: This thesis describes the development of a novel technique for intra-operative tissue diagnostics, which aims to provide the operating surgeon with molecular diagnostic information in vivo and in near real time by the application of mass spectrometry analysis to tissue specific ions contained within the metabolite rich electrosurgery smoke plume. The system is known as Rapid Evaporative Ionisation Mass Spectrometry (REIMS) or the ‘iKnife’ and it utilises recent developments in systems biology and spectroscopic technology to provide accurate, real time metabolic information in the clinical and operating theatre environment. In addition to tissue diagnostics, REIMS is a potential tool for investigation of the biological processes underpinning the detected lipid changes, contributing to a greater understanding of tumour biology and lipid profiling and identification of novel prognostic or therapeutic targets. Methodology: This body of work developed the instrumentation and tested and validated the analytical methodology for REIMS. Prospective observational studies of breast (N= 45) and colorectal cancer (N=40) were performed at Imperial College NHS trust, for the identification of histologically discrete specific lipidomic profiles. Finally, an endoscopic application was created for the translational application of this technology in the diagnosis and treatment of colorectal cancer. Results: Optimal machine set up was obtained using a Waters Xevo G2-S QTof i-Knife mass spectrometer with a modified atmospheric interface. Multivariate analysis lead to the identification of colorectal adenocarcinoma and invasive breast cancer models through the quantitative analysis of lipid profiles. Significant lipid species responsible for the distinction of healthy tissue and cancer were identified and, based on these profiles, colorectal and breast cancer were identified with a diagnostic accuracy of 93.6% and 88.5% respectively. In addition, tumour characteristics including grade, stage, presence of genetic mutations and hormone receptor status influenced spectral profiles and allowed further discrimination of tumour samples. An endoscopic tool for near real time analysis of colorectal tissue accurately identified the anatomical layers of the colonic wall and discriminated colorectal adenocarcinoma from normal mucosa, ex vivo, with a diagnostic accuracy of 88% and 89.5% respectively. This work lead to the development of fully functioning iKnife and iendoscope instrumental platforms Conclusions: The REIMS platform developed in this thesis is a fundamental first step in facilitating future in vivo REIMS experimentation to determine its potential value as a clinical tool. This analysis has optimized, standardized and validated a methodology for breast and colorectal tissue sampling, and it has identified candidate lipid biomarkers of translational use.Open Acces