ArticleFrontiers in neuroscience2021
Conductivity Tensor Imaging of the Human Brain Using Water Mapping Techniques.
Article in Frontiers in neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Evaluation of conductivity tensor image along the perivascular space in the brains of patients with cognitive impairments.Frontiers in aging neuroscience · 2026Article
- Human brain imaging with high-density electroencephalography: Techniques and applications.The Journal of physiology · 2026Review
- Mapping EEG Metrics to Human Affective and Cognitive Models: An Interdisciplinary Scoping Review from a Cognitive Neuroscience Perspective.Biomimetics (Basel, Switzerland) · 2025Review
- Materials and device strategies to enhance spatiotemporal resolution in bioelectronics.Nature reviews. Materials · 2025Article
- Exploring the relationship between larmor-frequency electrical conductivity, diffusivity, and tissue volume in the aging brain.Quantitative imaging in medicine and surgery · 2025Article
- Comparison of modelled diffusion-derived electrical conductivities found using magnetic resonance imaging.Frontiers in radiology · 2025Article
- Validation of conductivity tensor imaging against diffusion tensor magnetic resonance electrical impedance tomography.Scientific reports · 2024Article
- A biophysically constrained brain connectivity model based on stimulation-evoked potentials.Journal of neuroscience methods · 2024Article
- A biophysically constrained brain connectivity model based on stimulation-evoked potentials.bioRxiv : the preprint server for biology · 2023Article
- High frequency conductivity decomposition by solving physically constraint underdetermined inverse problem in human brain.Scientific reports · 2023Article
- Brainstorm-DUNEuro: An integrated and user-friendly Finite Element Method for modeling electromagnetic brain activity.NeuroImage · 2023Article
- Estimation of brain tissue response by electrical stimulation in a subject-specific model implemented by conductivity tensor imaging.Frontiers in neuroscience · 2023Article
- Measurement of extracellular volume fraction using magnetic resonance-based conductivity tensor imaging.Frontiers in physiology · 2023Article
- The Apparent Diffusion Coefficient of Diffusion-Weighted Whole-Body Magnetic Resonance Imaging Affects the Survival of Multiple Myeloma Independently.Frontiers in oncology · 2022Article
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4 authors.
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Abstract
Conductivity tensor imaging (CTI) has been recently proposed to map the conductivity tensor in 3D using magnetic resonance imaging (MRI) at the frequency range of the brain at rest, i.e., low-frequencies. Conventional CTI mapping methods process the trans-receiver phase of the MRI signal using the MR electric properties tomography (MR-EPT) technique, which in turn involves the application of the Laplace operator. This results in CTI maps with a low signal-to-noise ratio (SNR), artifacts at tissue boundaries and a limited spatial resolution. In order to improve on these aspects, a methodology independent from the MR-EPT method is proposed. This relies on the strong assumption for which electrical conductivity is univocally pre-determined by water concentration. In particular, CTI maps are calculated by combining high-frequency conductivity derived from water maps and multi b-value diffusion tensor imaging (DTI) data. Following the implementation of a pipeline to optimize the pre-processing of diffusion data and the fitting routine of a multi-compartment diffusivity model, reconstructed conductivity images were evaluated in terms of the achieved spatial resolution in five healthy subjects scanned at rest. We found that the pre-processing of diffusion data and the optimization of the fitting procedure improve the quality of conductivity maps. We achieve reproducible measurements across healthy participants and, in particular, we report conductivity values across subjects of 0.55 ± 0.01
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