Bioimpedance real-time charazterization of neointimal tissue inside stents

It is hereby presented a new approach to monitor restenosis in arteries fitted with a stent during an angioplasty. The growth of neointimal tissue is followed up by measuring its bioimpedance with Electrical Impedance Spectroscopy (EIS). Besides, a mathematical model is derived to analytically describe the neointima’s histological composition from its bioimpedance. The model is validated by finite-element analysis (FEA) with COMSOL Multiphysics®. Satisfactory correlation between the analytical model and the FEA simulation is achieved for most of the characterization range, detecting some deviations introduced by the thin "double layer" that separates the neointima and the blood. It is shown how to apply conformal transformations to obtain bioimpedance models for stack-layered tissues over coplanar electrodes. Particularly, this is applied to characterize the neointima in real-time. This technique is either suitable as a main mechanism of restenosis follow-up or it can be combined with proposed blood-pressure-measuring intelligent stents to auto-calibrate the sensibility loss caused by the adherence of the tissue on the micro-electro-mechanical sensors (MEMS).Ministerio de Economía, Industria y Competitividad (Spain): projects TEC2013-46242-C3-1-PMinisterio de Economía, Industria y Competitividad (Spain): projects TEC2013-46242-C3-2-

An Empirical-Mathematical Approach for Calibration and Fitting Cell-Electrode Electrical Models in Bioimpedance Tests

This paper proposes a new yet efficient method allowing a significant improvement in the on-line analysis of biological cell growing and evolution. The procedure is based on an empirical-mathematical approach for calibration and fitting of any cell-electrode electrical model. It is valid and can be extrapolated for any type of cellular line used in electrical cell-substrate impedance spectroscopy (ECIS) tests. Parameters of the bioimpedance model, acquired from ECIS experiments, vary for each cell line, which makes obtaining results difficult and—to some extent-renders them inaccurate. We propose a fitting method based on the cell line initial characterization,and carry out subsequent experiments with the same line to approach the percentage of well filling and the cell density (or cell number in the well). To perform our calibration technique, the so-called oscillation-based test (OBT) approach is employed for each cell density. Calibration results are validated by performing other experiments with different concentrations on the same cell line with the same measurement technique. Accordingly, a bioimpedance electrical model of each cell line is determined, which is valid for any further experiment and leading to a more precise electrical model of the electrode-cell system. Furthermore, the model parameters calculated can be also used by any other measurement techniques. Promising experimental outcomes for three different cell-lines have been achieved, supporting the usefulness of this technique

Remote Cell Growth Sensing Using Self-Sustained Bio-Oscillations

A smart sensor system for cell culture real-time supervision is proposed, allowing for a significant reduction in human effort applied to this type of assay. The approach converts the cell culture under test into a suitable “biological” oscillator. The system enables the remote acquisition and management of the “biological” oscillation signals through a secure web interface. The indirectly observed biological properties are cell growth and cell number, which are straightforwardly related to the measured bio-oscillation signal parameters, i.e., frequency and amplitude. The sensor extracts the information without complex circuitry for acquisition and measurement, taking advantage of the microcontroller features. A discrete prototype for sensing and remote monitoring is presented along with the experimental results obtained from the performed measurements, achieving the expected performance and outcomes