Numerical Simulations of MREIT Conductivity Imaging for Brain Tumor Detection

Meng, Zijun; Sajib, Saurav Z. K.; Chauhan, Munish; Sadleir, Rosalind; Kim, Hyung Joong; Kwon, Ohin; Woo, Eung Je

doi:10.1155/2013/704829

Cited by 11 publications

(16 citation statements)

References 34 publications

(41 reference statements)

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“…Because only a minority of the blood vessels included in our model was within the white matter compartment, we expect no major insights for the questions addressed in the present study from modeling white matter anisotropy. Recent advances in electrical impedance tomography (EIT) and more specifically in magnetic resonance EIT (Zhang et al, 2008; Woo and Seo, 2008; Meng et al, 2013; Degirmenci and Eyuboglu, 2013; Kim et al, 2008) suggest that using individualized anisotropic and inhomogeneous conductivities for head modeling may be possible in the future, opening up exciting new possibilities in volume conductor head modeling.…”

Section: Discussionmentioning

confidence: 99%

The role of blood vessels in high-resolution volume conductor head modeling of EEG

et al. 2016

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Reconstruction of the electrical sources of human EEG activity at high spatiotemporal accuracy is an important aim in neuroscience and neurological diagnostics. Over the last decades, numerous studies have demonstrated that realistic modeling of head anatomy improves the accuracy of source reconstruction of EEG signals. For example, including a cerebrospinal fluid compartment and the anisotropy of white matter electrical conductivity were both shown to significantly reduce modeling errors. Here, we for the first time quantify the role of detailed reconstructions of the cerebral blood vessels in volume conductor head modeling for EEG. To study the role of the highly arborized cerebral blood vessels, we created a submillimeter head model based on ultra-high-field-strength (7 T) structural MRI datasets. Blood vessels (arteries and emissary/intraosseous veins) were segmented using Frangi multi-scale vesselness filtering. The final head model consisted of a geometry-adapted cubic mesh with over 17 × 106 nodes. We solved the forward model using a finite-element-method (FEM) transfer matrix approach, which allowed reducing computation times substantially and quantified the importance of the blood vessel compartment by computing forward and inverse errors resulting from ignoring the blood vessels. Our results show that ignoring emissary veins piercing the skull leads to focal localization errors of approx. 5 to 15 mm. Large errors (>2 cm) were observed due to the carotid arteries and the dense arterial vasculature in areas such as in the insula or in the medial temporal lobe. Thus, in such predisposed areas, errors caused by neglecting blood vessels can reach similar magnitudes as those previously reported for neglecting white matter anisotropy, the CSF or the dura — structures which are generally considered important components of realistic EEG head models. Our findings thus imply that including a realistic blood vessel compartment in EEG head models will be helpful to improve the accuracy of EEG source analyses particularly when high accuracies in brain areas with dense vasculature are required.

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Section: Discussionmentioning

confidence: 99%

The role of blood vessels in high-resolution volume conductor head modeling of EEG

et al. 2016

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“…1(c), Table I). 17 Since the MREIT used imaging current with a low frequency, 18 we selected the values with a frequency range at 100 Hz. The segmented brain data set was then exported to the three-dimensional image processing and meshing software package (Simpleware Ltd, Exeter, UK).…”

Section: A Three-dimensional Head Modelmentioning

confidence: 99%

Evaluation of three-dimensional anisotropic head model for mapping realistic electromagnetic fields of brain tissues

Jeong

Sajib

et al. 2015

AIP Advances

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Electromagnetic fields provide fundamental data for the imaging of electrical tissue properties, such as conductivity and permittivity, in recent magnetic resonance (MR)-based tissue property mapping. The induced voltage, current density, and magnetic flux density caused by externally injected current are critical factors for determining the image quality of electrical tissue conductivity. As a useful tool to identify bio-electromagnetic phenomena, precise approaches are required to understand the exact responses inside the human body subject to an injected currents. In this study, we provide the numerical simulation results of electromagnetic field mapping of brain tissues using a MR-based conductivity imaging method. First, we implemented a realistic three-dimensional human anisotropic head model using high-resolution anatomical and diffusion tensor MR images. The voltage, current density, and magnetic flux density of brain tissues were imaged by injecting 1 mA of current through pairs of electrodes on the surface of our head model. The current density map of anisotropic brain tissues was calculated from the measured magnetic flux density based on the linear relationship between the water diffusion tensor and the electrical conductivity tensor. Comparing the current density to the previous isotropic model, the anisotropic model clearly showed the differences between the brain tissues. This originates from the enhanced signals by the inherent conductivity contrast as well as the actual tissue condition resulting from the injected currents.

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“…Hence CT, PET, SPECT procedures have some disadvantages. Recently, EIT, magnetic resonance electrical impedance tomography (MREIT) [116,126,127,151,167,183,214], magnetic resonance electrical property tomography (MREPT) [222,223,224], Quantitative Susceptibility Mapping (QSM) [141,145,211,212] have been studied for brain imaging.…”

Section: Present Scenario and The Future Trendsmentioning

confidence: 99%

“…MREIT is a new tomographic imaging modality which provides the image the electrical properties of human body tissue using MRI phase information along with an external current injection [151]. MREIT is based on the Magnetic Resonance Current Density Imaging (MRCDI) [120] technique which requires current injection into the body within an MRI scanner [223].…”

Section: Present Scenario and The Future Trendsmentioning

confidence: 99%

“…MREIT is based on the Magnetic Resonance Current Density Imaging (MRCDI) [120] technique which requires current injection into the body within an MRI scanner [223]. Recent in vivo MREIT studies conducted on animal and human have demonstrated that the different physiological and pathological conditions of tissues or organs can be visualized with some unique conductivity contrasts [151].…”

Section: Present Scenario and The Future Trendsmentioning

confidence: 99%

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