Magnetic Resonance Current Density Imaging

Eyüboğlu, B. Murat

doi:10.1002/9780471740360.ebs1329

Cited by 10 publications

(16 citation statements)

References 29 publications

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“…Magnetic resonance current density imaging (MRCDI) and MR electrical impedance tomography (MREIT) are two emerging modalities, which combine weak time-varying currents injected via surface electrodes with magnetic resonance imaging (MRI) to acquire information about the current flow and ohmic conductivity at high spatial resolution (Eyüboğlu, 2006a(Eyüboğlu, , 2006bGöksu et al, 2014;Joy, 2004;Scott et al, 1991;Seo and Woo, 2011;Woo et al, 1994). In short, the injected current flow creates a magnetic field in the head, and the component of the induced magnetic field ∆B z,c parallel to the main magnetic field of the scanner slightly changes the precession frequency of the magnetization (here, the z-axis is chosen along the static scanner field, and ∆B z,c is correspondingly the currentinduced field change).…”

Section: Introductionmentioning

confidence: 99%

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Human in-vivo brain magnetic resonance current density imaging (MRCDI)

et al. 2018

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Magnetic resonance current density imaging (MRCDI) and MR electrical impedance tomography (MREIT) are two emerging modalities, which combine weak time-varying currents injected via surface electrodes with magnetic resonance imaging (MRI) to acquire information about the current flow and ohmic conductivity distribution at high spatial resolution. The injected current flow creates a magnetic field in the head, and the component of the induced magnetic field ΔB parallel to the main scanner field causes small shifts in the precession frequency of the magnetization. The measured MRI signal is modulated by these shifts, allowing to determine ΔB for the reconstruction of the current flow and ohmic conductivity. Here, we demonstrate reliable ΔB measurements in-vivo in the human brain based on multi-echo spin echo (MESE) and steady-state free precession free induction decay (SSFP-FID) sequences. In a series of experiments, we optimize their robustness for in-vivo measurements while maintaining a good sensitivity to the current-induced fields. We validate both methods by assessing the linearity of the measured ΔB with respect to the current strength. For the more efficient SSFP-FID measurements, we demonstrate a strong influence of magnetic stray fields on the ΔB images, caused by non-ideal paths of the electrode cables, and validate a correction method. Finally, we perform measurements with two different current injection profiles in five subjects. We demonstrate reliable recordings of ΔB fields as weak as 1 nT, caused by currents of 1 mA strength. Comparison of the ΔB measurements with simulated ΔB images based on FEM calculations and individualized head models reveals significant linear correlations in all subjects, but only for the stray field-corrected data. As final step, we reconstruct current density distributions from the measured and simulated ΔB data. Reconstructions from non-corrected ΔB measurements systematically overestimate the current densities. Comparing the current densities reconstructed from corrected ΔB measurements and from simulated ΔB images reveals an average coefficient of determination R of 71%. In addition, it shows that the simulations underestimated the current strength on average by 24%. Our results open up the possibility of using MRI to systematically validate and optimize numerical field simulations that play an important role in several neuroscience applications, such as transcranial brain stimulation, and electro- and magnetoencephalography.

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Section: Introductionmentioning

confidence: 99%

“…The current-induced phase changes can thus be used to determine ∆B z,c , and to reconstruct the inner current flow and the ohmic conductivity distribution (Eyüboğlu, 2006b(Eyüboğlu, , 2006cIder and Birgül, 1998;Joy, 2004;Oh et al, 2003;Scott et al, 1991;Seo and Woo, 2011).…”

Section: Introductionmentioning

confidence: 99%

Human in-vivo brain magnetic resonance current density imaging (MRCDI)

et al. 2018

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“…Magnetic resonance current density imaging (MRCDI) and magnetic resonance electrical impedance tomography (MREIT) are two emerging imaging modalities, which combine MRI with externally applied currents (either direct current or alternating current at low frequencies combined with repeated refocusing pulses ) to reconstruct the current density distribution and ohmic conductivity variation inside body tissue . This may open up novel ways to characterize pathological tissue .…”

Section: Introductionmentioning

confidence: 99%

Sensitivity analysis of magnetic field measurements for magnetic resonance electrical impedance tomography (MREIT)

Göksu

Scheffler

Ehses

et al. 2017

Magnetic Resonance in Med

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“…Magnetic resonance current density imaging (MRCDI) and MR electrical impedance tomography (MREIT) are emerging modalities to measure the current flow of transcranial electric stimulation (TES) (1) and the ohmic tissue conductivities non-invasively in the human brain (2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12). They combine MRI with weak electrical currents of 1-2 mA baseline-to-peak, alternating at low frequencies (0-100 Hz; Fig.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity and resolution improvement for in-vivo magnetic resonance current density imaging (MRCDI) of the human brain

Göksu

Scheffler

Gregersen

et al. 2021

Preprint

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Purpose: Magnetic resonance current density imaging (MRCDI) combines MR brain imaging with the injection of time-varying weak currents (1-2 mA) to assess the current flow pattern in the brain. However, the utility of MRCDI is still hampered by low measurement sensitivity and poor image quality. Methods: We recently introduced a multi-gradient-echo-based MRCDI approach that has the hitherto best documented efficiency. We now advanced our MRCDI approach in three directions and performed phantom and in-vivo human brain experiments for validation: First, we verified the importance of enhanced spoiling and optimize it for imaging of the human brain. Second, we improved the sensitivity and spatial resolution by using acquisition weighting. Third, we added navigators as a quality control measure for tracking physiological noise. Combining these advancements, we tested our optimized MRCDI method by using 1 mA transcranial electrical stimulation (TES) currents injected via two different electrode montages in five subjects. Results: For a session duration of 4:20 min, the new MRCDI method was able to detect magnetic field changes caused by the TES current flow at a sensitivity level of 84 pT, representing in a twofold increase relative to our original method. Comparing both methods to current flow simulations based on personalized head models demonstrated a consistent increase in the coefficient of determination of ∆R2=0.12 for the current-induced magnetic fields and ∆R2=0.22 for the current flow reconstructions. Interestingly, some of the simulations still clearly deviated from the measurements despite of the strongly improved measurement quality. This suggests that MRCDI can reveal useful information for the improvement of head models used for current flow simulations. Conclusion: The advanced method strongly improves the sensitivity and robustness of MRCDI and is an important step from proof-of-concept studies towards a broader application of MRCDI in clinical and basic neuroscience research.

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Magnetic Resonance Current Density Imaging

Cited by 10 publications

References 29 publications

Human in-vivo brain magnetic resonance current density imaging (MRCDI)

Human in-vivo brain magnetic resonance current density imaging (MRCDI)

Sensitivity analysis of magnetic field measurements for magnetic resonance electrical impedance tomography (MREIT)

Sensitivity and resolution improvement for in-vivo magnetic resonance current density imaging (MRCDI) of the human brain

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