Electric field distribution study in inhomogeneous biological tissues. (20th November 2019)

• Record Type: Journal Article
• Authors: Sieni, Elisabetta; Sgarbossa, Paolo; Mognaschi, Maria Evelina; Forzan, Michele; Parupudi, Tejasvi; Mittal, Lakshya; Camarillo, Ignacio G.; Sundararajan, Raji
• Other Names: Wang Chao‐Fu guestEditor.
• Is Part Of: International journal of numerical modelling. Volume 33:Number 2(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-11-20
• Subjects: electric field -- electrical conductivity -- Finite Element Analysis -- inhomogeneous tumor -- vegetal tissue -- tissue mimic material; Electric networks -- Mathematical models -- Periodicals; Electronics -- Mathematical models -- Periodicals; 621.3011
• DOI: 10.1002/jnm.2699
• Languages: English
• ISSNs: 0894-3370

Abstract

Abstract: Most solid tumors are inhomogeneous, because of the different types of cells present, different tissues and fat, etc, along with irregular vascularization, pH variation, and heterogeneous oxygen concentration. It is of interest to study the electric field distribution when electrochemotherapy is administered. The variations in the physical and hence the electrical properties, such as the resistance (or conductance), will vary, and parts of the tumor might not get the same electric field and hence will not have the required or the desired efficacy. In this study, the effect of tissue inhomogeneity is explored using potato and apple tissue samples. For this purpose, agar gel and other tissue mimic materials are used to create the inhomogeneity and pulsed to study the effect of electrical pulses. In addition, the electric field distribution is studied using a numerical model to evaluate the effect of tissue inhomogeneity in terms of electric field distribution when electroporation is applied to permeabilize cells, for enhanced drug uptake. The electric field is evaluated by means of finite element analysis and is compared with the distribution found in a phantom model. Good correlation is obtained between the experimental and simulation results. This research has the potential to study the real tumor inhomogeneity conditions.