DOI: 10.21227/6y85-5k37
title: Thyroid and Parathyroid computational model relating to electrical impedance spectroscopy - global sensitivity results

description: This dataset comprises the global sensitivity results that relate to the paper: The Use of Virtual Tissue Constructs that Include Morphological Variability to Assess the Potential of Electrical Impedance Spectroscopy to Differentiate Between Thyroid and Parathyroid Tissues during SurgeryAbstract: Electrical impedance spectroscopy (EIS) has been proposed as a promising noninvasivemethod to differentiate healthy thyroid from parathyroid tissues during thyroidectomy. However,previously reported similarities in the in vivo measured spectra of these tissues during a pilot studysuggest that this separation may not be straightforward. We utilise computational modelling as amethod to elucidate the distinguishing characteristics in the EIS signal and explore the features of thetissue that contribute to the observed electrical behaviour. Firstly, multiscale finite element models(or ‘virtual tissue constructs’) of thyroid and parathyroid tissues were developed and verified againstin vivo tissue measurements. A global sensitivity analysis was performed to investigate the impactof physiological micro-, meso- and macroscale tissue morphological features of both tissue typeson the computed macroscale EIS spectra and explore the separability of the two tissue types. Ourresults suggest that the presence of a surface fascia layer could obstruct tissue differentiation, butan analysis of the separability of simulated spectra without the surface fascia layer suggests thatdifferentiation of the two tissue types should be possible if this layer is completely removed by thesurgeon. Comprehensive in vivo measurements are required to fully determine the potential for EISas a method in distinguishing between thyroid and parathyroid tissues impedance spectroscopy (EIS) has been proposed as a promising noninvasivemethod to differentiate healthy thyroid from parathyroid tissues during thyroidectomy. However,previously reported similarities in the in vivo measured spectra of these tissues during a pilot studysuggest that this separation may not be straightforward. We utilise computational modelling as amethod to elucidate the distinguishing characteristics in the EIS signal and explore the features of thetissue that contribute to the observed electrical behaviour. Firstly, multiscale finite element models(or ‘virtual tissue constructs’) of thyroid and parathyroid tissues were developed and verified againstin vivo tissue measurements. A global sensitivity analysis was performed to investigate the impactof physiological micro-, meso- and macroscale tissue morphological features of both tissue typeson the computed macroscale EIS spectra and explore the separability of the two tissue types. Ourresults suggest that the presence of a surface fascia layer could obstruct tissue differentiation, butan analysis of the separability of simulated spectra without the surface fascia layer suggests thatdifferentiation of the two tissue types should be possible if this layer is completely removed by thesurgeon. Comprehensive in vivo measurements are required to fully determine the potential for EISas a method in distinguishing between thyroid and parathyroid tissues