Noninvasive electrical conductivity measurement by MRI: a test of its validity and the electrical conductivity characteristics of glioma

MR‐based electrical properties tomography converts the MRI transmit/receive RF field measurements to tissue electrical property maps through dedicated reconstruction algorithms. Recent reports showed that despite limitations, electrical properties tomography holds promise for generating additional contrast for tumor detection and patient‐specific modeling of tissue–RF field interactions. This review summarizes the available tissue electrical property contrasts and compares them with the capabilities of the most commonly used electrical properties tomography reconstruction method. Future directions and prospects of clinical translation are discussed.

Section: Overviewmentioning

confidence: 94%

Electrical properties tomography: Available contrast and reconstruction capabilities

Hancu

Liu

Hua

et al. 2018

“…Tumors could pose a significant SAR risk based on literature which suggests that high grade brain tumors have higher electrical conductivity than normal brain tissue. Several studies in particular have used electrical properties tomography (EPT) to noninvasively measure conductivity in brain tumors in vivo . EPT is a technique that uses MR imaging to compute dielectric properties of human tissue by analyzing the complex B1 fields .…”

Section: Theorymentioning

confidence: 99%

Local specific absorption rate in brain tumors at 7 tesla

Restivo

Berg

Lier

et al. 2015

“…In Appendix (available online), the use of G′ and G in phase‐based EPT is derived from the governing equations of phase‐based EPT . In this study, phase‐based EPT was employed for the reconstruction of experimental data because it is a widely useable approach in experimental and/or clinical settings . Also, it is known that conductivity reconstruction depends largely on phase of the

B_{1}^{+}

…”

Section: Theorymentioning

confidence: 99%

Redesign of the Laplacian kernel for improvements in conductivity imaging using MRI

Shin

Kim

2018

Purpose To develop an electrical property tomography reconstruction method that achieves improvements over standard method by redesigning the Laplacian kernel. Theory and Methods A decomposition property of the governing PET equation shows the possibility of redesigning the Laplacian kernel for conductivity reconstruction. Hence, the discrete Laplacian operator used for electrical property tomography reconstruction is redesigned to have a Gaussian‐like envelope, which enables manipulation of the spatial and spectral response. The characteristics of the proposed kernel are investigated through numerical simulations and in vivo brain experiments. Results The proposed method reduces textured noise, which hampers observing features of the conductivity image. Furthermore, the proposed scheme can mitigate the propagation of local phase error such as flow‐induced phase. By doing so, the proposed method can recover feature information in conductivity (or resistivity) images. Lastly, the proposed kernel can be extended to other electrical property tomography reconstructions, improving the quality of images. Conclusion An alternative design of the Laplacian kernel for conductivity imaging has been developed to mitigate the textured noise and the propagation of local phase artifact.