Prediction of pathological response to neo‐adjuvant chemoradiotherapy for oesophageal cancer using vibrational spectroscopy
|Title:||Prediction of pathological response to neo‐adjuvant chemoradiotherapy for oesophageal cancer using vibrational spectroscopy||Authors:||Nguyen, Thi N. Q.; Maguire, Adrian; Mooney, Catherine; et al.||Permanent link:||http://hdl.handle.net/10197/12181||Date:||Mar-2021||Online since:||2021-05-19T16:43:17Z||Abstract:||In oesophageal cancer (OC) neo‐adjuvant chemoradiotherapy (neoCRT) is used to debulk tumour size prior to surgery, with a complete pathological response (pCR) observed in approximately ∼30% of patients. Presently no predictive quantitative methodology exists which can predict response, in particular a pCR or major response (MR), in patients prior to therapy. Raman and Fourier transform infrared imaging were performed on OC tissue specimens acquired from 50 patients prior to therapy, to develop a computational model linking spectral data to treatment outcome. Modelling sensitivities and specificities above 85% were achieved using this approach. Parallel in‐vitro studies using an isogenic model of radioresistant OC supplied further insight into OC cell spectral response to ionising radiation where a potential spectral biomarker of radioresistance was observed at 977 cm−1. This work demonstrates that chemical imaging may provide an option for triage of patients prior to neoCRT treatment allowing more precise prescription of treatment.||Funding Details:||Health Research Board
Science Foundation Ireland
|Type of material:||Journal Article||Publisher:||Wiley||Journal:||Translational Biophotonics||Volume:||3||Issue:||1||Copyright (published version):||2020 the Authors||Keywords:||Complete pathological response; FTIR spectroscopy; Machine learning; Neo-adjuvant chemoradiotherapy; Raman spectroscopy||DOI:||10.1002/tbio.202000014||Language:||en||Status of Item:||Peer reviewed||ISSN:||2627-1850||This item is made available under a Creative Commons License:||https://creativecommons.org/licenses/by/3.0/ie/|
|Appears in Collections:||Computer Science Research Collection|
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