Prediction of malignant transformation in oral epithelial dysplasia using infrared absorbance spectra

Ellis, Barnaby, Risk, Janet ORCID: https://orcid.org/0000-0002-8770-7783, Weightman, Peter ORCID: https://orcid.org/0000-0002-0907-3930, Shaw, Richard ORCID: https://orcid.org/0000-0002-5157-4042, Barrett, Steve ORCID: https://orcid.org/0000-0003-2960-3334 and Triantafyllou, Asterios ORCID: https://orcid.org/0000-0001-8752-5595 (2022) Prediction of malignant transformation in oral epithelial dysplasia using infrared absorbance spectra. [Data Collection]

Data Catalogue DOI: 10.17638/datacat.liverpool.ac.uk/1622

Original publication URL: https://doi.org/10.1371/journal.pone.0266043

Description

Oral epithelial dysplasia (OED) is a histopathologically-defined, potentially premalignant condition of the oral cavity. The rate of transformation to frank carcinoma is relatively low (12% within 2 years) and prediction based on histopathological grade is unreliable, leading to both over- and under-treatment. Alternative approaches include infrared (IR) spectroscopy, which is able to classify cancerous and non-cancerous tissue in a number of cancers, including oral. The aim of this study was to explore the capability of FTIR (Fourier-transform IR) microscopy and machine learning as a means of predicting malignant transformation of OED. Supervised, retrospective analysis of longitudinally-collected OED biopsy samples from 17 patients with high risk OED lesions: 10 lesions transformed and 7 did not over a follow-up period of more than 3 years. FTIR spectra were collected from routine, unstained histopathological sections and machine learning used to predict malignant transformation, irrespective of OED classification. PCA-LDA (principal component analysis followed by linear discriminant analysis) provided evidence that the subsequent transforming status of these 17 lesions could be predicted from FTIR data with a sensitivity of 79 ± 5% and a specificity of 76 ± 5%. Six key wavenumbers were identified as most important in this classification. Although this pilot study used a small cohort, the strict inclusion criteria and classification based on known outcome, rather than OED grade, make this a novel study in the field of FTIR in oral cancer and support the clinical potential of this technology in the surveillance of OED.

Keywords:

infrared, OED, oral dysplasia, FTIR, pre-cancer, malignant transformation

Divisions:

Faculty of Health and Life Sciences > Institute of Systems, Molecular and Integrative Biology > Molecular and Clinical Cancer Medicine

Depositing User:

Janet Risk

Date Deposited:

28 Feb 2022 14:27

Last Modified:

31 Mar 2023 13:12

DOI:

10.17638/datacat.liverpool.ac.uk/1622

URI:

https://datacat.liverpool.ac.uk/id/eprint/1622

Additional details

Creators:	Ellis, Barnaby Risk, Janet Weightman, Peter Shaw, Richard Barrett, Steve Triantafyllou, Asterios
Research funder:	Grant Number Name of the Funder The Funder's ID 150161 Cancer Research UK C7738/A26196
Date:	4 February 2022
Statement on legal, ethical and access issues :	Open Access All patient identifiers have been removed and replaced with research IDs
Resource language:	English
Project Details:	Project ID The title of the Project Project Funding ID Project Start Date Project End Date 150161 Infrared spectral early detection of oral cancer C7738/A2619 1 July 2018 30 June 2022
Publisher:	University of Liverpool
Contact email address:	sc35@liverpool.ac.uk
Last Modified:	31 Mar 2023 13:12