4.6 Article

Computational Modelling for Electrical Impedance Spectroscopy-Based Diagnosis of Oral Potential Malignant Disorders (OPMD)

Journal

SENSORS
Volume 22, Issue 15, Pages -

Publisher

MDPI
DOI: 10.3390/s22155913

Keywords

impedance spectroscopy; oral cancer; oral potential malignant disorder; finite element modelling; histology

Funding

  1. SBRI Healthcare

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This study applied a multiscale modelling approach to simulate the electrical properties of oral tissue for the electrical impedance-based diagnosis of oral potential malignant disorder (OPMD). Finite element models of different cell types and a tissue scale model informed by histological analysis were used to distinguish different degrees of dysplasia and healthy tissue. However, significant keratinisation could cause OPMD tissue to exhibit larger than expected impedance values, potentially leading to misidentification as healthy tissue.
A multiscale modelling approach has been applied to the simulation of the electrical properties of oral tissue, for the purpose of informing an electrical impedance-based method of oral potential malignant disorder (OPMD) diagnosis. Finite element models of individual cell types, with geometry informed by histological analysis of human oral tissue (normal, hyperplastic and dysplastic), were generated and simulated to obtain electrical parameters. These were then used in a histology-informed tissue scale model, including the electrode geometry of the ZedScan tetrapolar impedance-measurement device. The simulations offer insight into the feasibility of distinguishing moderate dysplasia from severe dysplasia or healthy tissue. For some oral sites, simulated spectra agreed with real measurements previously collected using ZedScan. However, similarities between simulated spectra for dysplastic, keratinised and non-dysplastic but hyperkeratinised tissue suggest that significant keratinisation could cause some OPMD tissues to exhibit larger than expected impedance values. This could lead to misidentification of OPMD spectra as healthy. Sources of uncertainty within the models were identified and potential remedies proposed.

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