OGC P28 Raman Needle Probe Lymph Node Assessment for Oesophageal Cancer: The DOLOMITE Study

Abstract

Background Oesophageal cancer (OC) accounts for 3% of all new cancer diagnosis in the UK. Presentation is often late, reflected in a poor 5-year survival rate of 12%. The importance of identifying lymph node (LN) metastases has been demonstrated as the single biggest prognostic factor. The current ‘gold standard’ diagnosis of LN metastases is from histopathological assessment of the tissue after surgical resection of the primary tumour and surrounding tissue. The use of imaging techniques to try and gain this information preoperatively is standard practice but far from perfect. Raman spectroscopy (RS) has been investigated as a diagnostic tool to detect cancer and pre-cancerous change in the oesophagus, and preliminary work demonstrating the application of vibrational spectroscopy (Raman and FTIR) to LN analysis has been undertaken. The development of Raman needle probes (RNP) with potential for use in-vivo furthers the clinical impact. The DOLOMITE study started recruitment in the summer of 2022 to investigate the ability of RNP to identify the presence of malignant deposits in resected lymph nodes. Methods Patients identified by the clinical team as needing oesophagectomy to treat their OC were invited to participate in the study. After the specimen has been resected, prior to formalin fixation, three lymph nodes are dissected representing gastric, para-oesophageal and sub-carinal nodes. These are bisected longitudinally with half remaining with the specimen. The half for research is snap frozen in liquid nitrogen until needed for analysis. Adjacent sections are cut from the nodes to create slides for Raman mapping and conventional H&E staining. The bulk node left is used for Raman probe analysis. Spectral data is then analysed using MATlab. Results At this early stage, our initial measurements have provided information used for calibration in advance of completing recruitment. The Raman mapping has been assessed for correlation with the pathology identified in the H&E slides taken from the lymph node block. This data in turn has provided the background for developing interpretation of the Raman probe data, with further samples we will use this to create a classification model. Conclusions With ongoing recruitment the study will be able to fully report by September 2023. References 1. Stone N, Kendall C, Shepherd N, Crow P, Barr H Near-infrared Raman spectroscopy for the classification of epithelial pre-cancers and cancers 2002 33(7):564–573 2. Kong K, Kendall C, Stone N, Notingher I. Raman spectroscopy for medical diagnostics--From in-vitro biofluid assays to in-vivo cancer detection. Adv Drug Deliv Rev. 2015;89:121–34.