Electrical Impedance Measurements in the Gastrointestinal Tract

Abstract

Objective: This work focuses on the feasibility of using Electrical Impedance Spectroscopy (EIS) to differentiate between cancerous and healthy tissues in real-time alongside the GI tract. This is to see whether it is possible to support surgeons when taking biopsies, or to see if it is possible to make biopsies obsolete with EIS. Methods: The study is limited to three tissue types representing the GI tract. These tissues are the esophagus, ileum, and colon tissue. Impedance measurements are taken with a 4-electrode probe on a Hewlett Packard 4192A LF HP Impedance Analyzer. All measurements are taken over a frequency range of 1 kHz to 7 MHz in 300 steps. Seven patients are included: three esophagus, two
leum, and two colon. Forty-eight ex vivo measurements are taken; 32 are on healthy tissue and 16 on cancerous tissue. Almost all measurements are verified by histological assessment (golden standard). In this work, a combination of parameterization with a classification method is made to create a classification strategy. These can be listed as the Cole impedance model, the two-pole Cole impedance model, the two-pole Cole impedance model in combination with a
Constant Phase Element (CPE), and PCA. The Cole impedance models are combined with thresholding, and the PCA is combined with a SVM. Results: The thresholding algorithm is created in combination with the α2 parameter (P < 0.05) from the two-pole Cole impedance model in combination with a CPE. The thresholding value is determined in a LOOCV approach via ROC curves created to search for the threshold that gives the most significant summation of sensitivity and specificity. In the combination of PCA and SVM, the PCA uses three principal components (containing 96.37% of the total variance), and the SVM applies an Radial Basis Function (RBF) kernel. For the 2-pole Cole impedance model with CPE
in combination with thresholding, we find an accuracy 0.5208, sensitivity 0.4375, specificity 0.5625, Positive Predictive Value (PPV) 0.3333, Negative Predictive Value (NPV) 0.6666, and Mathews Correlation Coefficient (MCC) 0.0000. For the PCA in combination with the SVM, we find an accuracy of 0.4167, a sensitivity of 0.0000, specificity of 0.6250, PPV of 0.0000, NPV of 0.5556, and MCC -0.4082. Conclusion: It is concluded that we cannot create an algorithm that either supports surgeons or replaces a biopsy in the GI tract with the current setup. This is highly likely due to the extremely low amount of data that is included to train
the algorithm.