MSACL 2019 EU Abstract

Rapid Evaporative Ionisation Mass Spectrometry (REIMS): A Diagnostic Tool for Omental Metastases in Patients with Primary Ovarian Cancer

Eftychios Manoli (1), Jacey Ip (1), Julia Balog (2), Steven Pringle (3), Hiromi Kudo (1), Robert Goldin (1), Ara Darzi (1), James Kinross (1), Zoltan Takats (1)
(1) Imperial College London, UK, (2) Waters Research Centre, Budapest, Hungary (3) Waters Corporation, Wilmslow, UK

Warning: Undefined variable $headshot in /var/www/html/view_abstract/view_abstract_in_program.php on line 704

Eftychios Manoli (Presenter) Imperial College London

Presenter Bio: Graduated from the University of Leicester with a BSc in Chemistry and worked as a Mass Spectrometry Analyst at the National Mass Spectrometry Facility in Swansea University and at the Mass Spectrometry Facility at Kings College London. Currently doing a Ph.D. in the Department of Surgery and Cancer at Imperial College London, on developing intraoperative instrumentation in minimal invasive surgery using mass spectrometry.

Relevant Financial Disclosures (within past 24 months) Grant/Research Support NIHR BRC, Waters Corp. Conflict mitigation NOT REQUIRED.

Introduction
In the new era of precision surgery, novel tools for real-time tissue diagnosis during surgical procedures are required that will enable surgeons to personalise intraoperative decisions improving patients’ outcomes. Currently, surgical strategy is based on pre-operative imaging and visual assessment of anatomy intra-operatively, with postoperative histology guiding the necessity for any future intervention.This approach is often subjective, time-consuming, and costly. In patients with advance ovarian cancer, the metastatic lesions found at staging laparoscopy undergo subjective visual assessment by the surgeon and does not yield to any biochemical information about the cancer.Rapid Evaporative Ionisation Mass Spectrometry(REIMS) performs real-time chemical analysis of biological tissues utilising electrosurgery-generated aerosols. Here, we integrated REIMS with the Harmonic scalpel, an advanced laparoscopic surgical instrument, assessing its efficacy in diagnosing omental metastasis.
Methods
Patients undergoing surgical resection for ovarian cancer with omental metastasis were recruited at Hammersmith Hospital, UK, as part of a prospective cohort study. Fresh frozen normal and tumour-infiltrated omentum samples were analysed ex-vivo using a Harmonic ACE® +7 fitted with a tapered-tip blade (Ethicon). Sampling was performed at 5W, with aerosols aspirated into a Xevo G2-XS QToF mass spectrometer (Waters). The relative abundance of cellular metabolites was subjected to multivariate statistical analyses including principle components analysis and orthogonal partial least squares discriminant analysis in SIMCA (Umetrics). The ability of REIMS to predict the presence of tumour infiltration was assessed using leave-one-spectrum-out cross-validation. Univariate statistical analysis was performed in R Studio.
Results
2 patients with ovarian primary cancer were included (median age 57). 22 normal and 23 tumour-infiltrated omentum samples were analysed resulting in 45 spectra. REIMS was able to accurately distinguish normal from tumour-infiltrated omentum tissue in the range of 100-1000Da, demonstrating an overall diagnostic accuracy of 100% (sensitivity 100%, specificity 100%). The relative abundance of metabolites in the mass-to-charge range of 100-550 and 600-1000 were responsible for differentiating the normal and tumour groups; corresponding to a variety of cellular lipid species. Significant characteristic species (p<0.05) associated with the separation were predominately Triglycerides, Phospholipids (600-1000Da) and Fatty Acids (100-550Da). Putative identification was done using Metlin and Lipid maps.
Conclusions
REIMS can be coupled to the Harmonic surgical device to accurately distinguish tumour-infiltrated and normal omentum in patients with ovarian cancer. This can provide the surgeon with real time tissue feedback of indeterminant lesions, allowing intra-operative decision making to improve clinical outcomes.