Reconstruction of Electrical Conductivity of Tissues by Means of Magnetic Resonance Techniques (2019-2022)

Reconstruction of Electrical Conductivity of Tissues by Means of Magnetic Resonance Techniques (2019-2022)
Head: Assist. Prof. Matej Kranjc, University of Ljubljana, Faculty of Electrical Engineering
Partner: /
Funding: Slovenian Research Agency (ARRS), Slovenia
Code: J2-1733


The project is funded by the Slovenian Research Agency (ARRS).

Member of University of Ljubljana

University of Ljubljana, Faculty of Electrical Engineering

Reconstruction of Electrical Conductivity of Tissues by Means of Magnetic Resonance Techniques
01.07.2019 - 30.06.2022
Amount of financing
1.3 FTE

Assist. Prof. Matej Kranjc

Research activity
Tehnika - Sistemi in kibernetika
Research Organisation

Electrical properties of biological tissues have been of interest for over a century as they determine the pathways of current flow through the body and are therefore important in the analysis of a wide range of biomedical applications. A particular application of electromagnetic fields that gained its attention in recent years is electroporation. It involves exposing biological cells to pulsed electric fields, which results in increased permeability of cell membrane. One of the most important conditions for successful electroporation is the exposure of cells to sufficiently high electric field, which is determined within the tissue mainly by its electrical properties. In order to obtain most appropriate distribution of electric field in the treated tissue, treatment planning is used. Treatment planning already proved to have a great potential in clinical use in medical application of electroporation. However, its applicability is currently limited due to uncertain conductivity values of the treated areas, especially in tumor tissue. Therefore, new techniques for determining maps of electrical conductivity are needed. Even though different attempts to obtain maps of conductivity distribution of tissues were already reported in the literature, each of them has its own disadvantages; poor spatial resolution in the case of electrical impedance tomography, requirement of current injections in the case of magnetic resonance electrical impedance tomography and limitation to high-frequency conductivity values in the case of Electrical Properties Tomography (EPT). Thus, obtaining quantitative maps of electrical conductivity at sufficient spatial resolution without current injection remains a challenge – a challenge that is addressed by the Conductivity Tensor Imaging (CTI).

The purpose of this project is to implement and validate CTI for measurement of low-frequency electrical conductivity distribution using MRI techniques. It was recently demonstrated that CTI enables reconstruction of low-frequency conductivity tensor images using an MRI scanner without current injections. This new technique could be used to provide patient-specific electrical conductivities for numerical models used in treatment planning of applications of electroporation and also in other medical applications employing electromagnetic fields. Improved treatment plans with patient-specific electrical conductivities will enable better prediction of the treatment outcome, hence safer and more efficient treatments. Still, before CTI implementation in the treatment plan workflow, the method needs to be additionally evaluated. Therefore, in the scope of Work Packages (WP) 1-4 described in the proposed research project, we will evaluate CTI by careful examination of each its components through different imaging experiments on phantoms, ex vivo and in vivo biological tissues using different MRI scanners.


Link to SICRIS.

The phases of the project and their realization

The aim of the project is to evaluate Conductivity Tensor Imaging (CTI) by examining of each components technique, i.e., Electrical Properties Tomography (EPT) in Work Package (WP) 1 and diffusion-weighted imaging (DW-MRI) in WP 2 by performing imaging experiments on phantoms and biological tissues. After successful validation of both components, we will implement CTI and demonstrate its ability to reconstruct low-frequency electrical conductivity distribution on mouse tumors and on human tissues imaged by a clinical MRI scanner (WP 3). Since the CTI technique is still not well known, we will take special care to disseminate results of the project to the scientific community through different communication channels (WP 4).

In Work Package 1 (WP 1), we will focus on implementation and measurement of electrical conductivity at the Larmor frequency in phantoms using Electrical Properties Tomography (EPT). First, we will implement appropriate imaging sequence for EPT on two MRI systems, each with different Larmor frequency, which will enable us to obtain conductivity distribution at two different frequencies (100 and 400 MHz). Using raw data image data from the MRI systems, we will reconstruct electrical conductivity of imaged phantoms at the Larmor frequency using appropriate numerical algorithms. In the second part of WP 1, we will evaluate EPT on two different phantoms, simple agar phantoms and cell-like phantoms, and compare measurement results to expected values of conductivity.

MR diffusion-weighted magnetic resonance imaging (DW-MRI) uses the signal loss associated with the random thermal motion of water molecules in the presence of magnetic field gradients to derive a number of parameters that reflect the translational mobility of the water molecules in tissues. In highly organized but asymmetric structures, mobility of the water molecules may be affected by the obstacles present in a direction-dependent way. Important examples of this are white brain matter and the stem of certain plants, such as asparagus, that contains fibrous components where diffusion of water molecules across fibers is much more restricted than along the fibers. In Work Package 2 (WP 2), we will first implement DW-MRI on both MRI scanners, then evaluate its performance on asparagus plant and mouse brains ex vivo. We will also validate DW-MRI on phantoms with controllable and defined anisotropy.

In Work Package 3 (WP 3), we will establish Conductivity Tensor Imaging (CTI) technique for reconstruction of low-frequency electrical conductivity distribution in tissues. CTI utilizes B1 mapping imaging sequence (developed in WP 1) to recover high-frequency isotropic conductivity image, which is determined by contents in both extracellular and intracellular spaces of tissue, and multi-b diffusion weighted imaging (developed in WP 2) to extract effects of the extracellular space and incorporate its directional properties. We will first develop the CTI algorithm and then evaluate and validate it on cell-like phantoms consisted of giant unilamellar vesicles. After successful validation, we will start with in vivo imaging. First, we will perform imaging of conductivity distribution of a mouse skeletal muscle and then of mouse tumors in order to demonstrate CTI ability to image heterogeneity of tumors at different time points. In the final part of WP 3, we will evaluate CTI algorithm on images obtained by a clinical MRI scanner.

In Work Package 4 (WP 4), we will disseminate achieved results of the project to interested scientific community. Since the method conductivity imaging by means of CTI is still not well known, we will take special care to use various communication channels, such as scientific journals and conferences. In order to share knowledge and expertise related to CTI, we will prepare a training course in the scope of the international scientific workshop and postgraduate course Electroporation based Technologies and Treatment.

Citations for bibliographic records

Link to SICRIS will be published once the project is available on SICRIS.