MR-Based Electrical Conductivity Imaging Using Second-Order Total Generalized Variation Regularization

Xiangdong Sun,Yingjie Mei,Xiaoyun Liu,Li Qi,Lijun Lu,Wufan Chen

doi:10.3390/app10217910

Abstract

Electrical properties provide essential information for cancer detection and specific absorption rate (SAR) estimation. Magnetic resonance electrical properties tomography (MREPT) is an approach to retrieve the distribution of electrical properties. The conventional method suffers from the locally homogeneous assumption and amplification of noise. In this study, a novel approach was introduced to improve the accuracy and the noise robustness of conductivity imaging. The proposed approach reformulated the central equation of the gradient-based method to avoid the calculation of the Laplacian operator. The equation was regularized using the second-order total generalized variation, which formulates an objective function. The optimization problem was solved by the alternating direction method of multipliers (ADMM) method. The proposed method was validated by the simulation data of the cylindrical phantom and Ella head model, and the performance was compared with existing methods. The results demonstrated that the proposed method reconstructed an accurate conductivity image and alleviated the noise effects. Furthermore, phantom and healthy volunteer experiments were implemented at a 3 Tesla (T) magnetic resonance imaging (MRI) scanner. The results suggested that the developed method can provide solutions for improved conductivity reconstruction and show potential for clinical application.

Highlights

The electrical properties (EPs) of biological tissues, which include electrical conductivity σ and permittivity ε, are fundamental properties that quantify the ability to transfer electrical current inside the medium and characterize the effect of electric polarization
The distinct difference between these methods depends on the boundary artifacts in the transition region between different contrast components
On the basis of the gradient-based method, the proposed method reformulates the central equation through divergence properties and leverages the finite difference method to construct an inverse problem

Summary

Introduction

The electrical properties (EPs) of biological tissues, which include electrical conductivity σ and permittivity ε, are fundamental properties that quantify the ability to transfer electrical current inside the medium and characterize the effect of electric polarization. EPs rely on the frequency of the applied electromagnetic field and are related to multiple tissue characteristics, which involve ion concentration, volume fraction, cellular membrane permeability, and pathological condition [1,2,3]. Mapping EPs has the potential for cancer detection and diagnosis. Tissue EPs are critical for the application of transcranial magnetic stimulation and transcranial direct current stimulation, which provides potential therapeutic applications for a wide variety of disorders, Appl.

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Results

Conclusion