Development of a parametric model to distinguish between specific tissue types

Abstract

In the Netherlands, 362.000 people suffered from atrial fibrillation in 2019. During a catheter intervention, the tissue that causes atrial fibrillation is destroyed by heat generated by an alternating current exerted from an ablation catheter. Two problems of this treatment are over-ablation of the heart tissue and the non-contingent surrounding of scar tissue around the pulmonary veins. Better surgical outcomes can be obtained if an extra imaging technique is added to prevent these problems from occurring. Impedance spectroscopy has potential, it is already widely used for measurements and food characterization and it enables the measurement of the distinct dielectric properties and impedance of different tissue types. Based on the dielectric properties and impedance, different tissue types can be distinguished from each other and the surgeon can adapt his procedure according to this information.

The goal of this Master Thesis is to distinguish different tissue types in the radiofrequency range with impedance spectroscopy during a cardiac ablation procedure. Impedance data for this Master Thesis are gathered via impedance measurements on three porcine hearts with two-needle electrodes over a frequency range from 100 Hz to 1 MHz. Ablated lesions are created with an electrosurgical knife in fulguration and pure cut mode. To distinguish between different tissue types with impedance spectroscopy there is a need for a parametric model that can parameterize the impedance spectra. This enables the comparison of different tissue types based on a couple of parameters instead of a complete spectrum. A parametric model is fitted to the measured impedance spectra and the resulting best-fit parameters are evaluated. The parametric model that is used is a series combination of a CPE model and a two-pole Cole impedance model. The CPE model models the electrode polarization contribution to the impedance spectrum. This way no a-priory knowledge regarding the electrode polarization is needed. The two-pole Cole impedance model models the tissue contribution to the impedance spectrum.

In the measurements that are performed in this Master Thesis, an increase in impedance is seen after ablation. The differences between the healthy and ablated measurements are mostly described by (significant) differences in the parameters of the CPE model (K and m) and the second Cole term R2, t2 and a2). The mean values of R2 and a2 increased after ablation, while the values of t2, K and m decreased after ablation for most measurements. Classification of healthy and ablated tissue is performed based on a formula consisting of a combination of these model parameters. The sensitivity and specificity are both around the 80%. This classification serves as a first impression, with the results indicating that discrimination of healthy from ablated tissue is possible with parametric modeling.