Publications by authors named "R J Sadleir"

Background And Purpose: The 3-dimensional cranial nerve imaging (CRANI) sequence may assist visualization of anatomical details of extraforaminal cranial nerves and aid in clinical diagnosis and preoperative planning. In this study, we investigated the feasibility of using a combined CRANI and magnetization-prepared rapid-acquisition gradient-echo (MPRAGE) imaging protocol to comprehensively identify trigeminal nerve projections.

Method: We evaluated the detection of distal regions of three branches of the ophthalmic nerve (V1), three branches of the maxillary nerve (V2), and five branches of the mandibular nerve (V3) in seven healthy adult subjects, with and without contrast injection.

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Diffusion tensor magnetic resonance electrical impedance tomography (DT-MREIT) and electrodeless conductivity tensor imaging (CTI) are two emerging modalities that can quantify low-frequency tissue anisotropic conductivity properties by assuming similar properties underlie ionic mobility and water diffusion. While both methods have potential applications to estimating neuro-modulation fields or formulating forward models used for electrical source imaging, a direct comparison of the two modalities has not yet been performed in-vitro or in-vivo. Therefore, the aim of this study was to test the equivalence of these two modalities.

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. This focus collection aims at presenting recent advances in electrical impedance tomography (EIT), including algorithms, hardware, and clinical applications..

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Objective: The aim of this study was to compare stimulation thresholds and current densities in the brain for transcranial motor evoked potentials (tcMEPs) from the hands and feet with linked quadripolar (LQP), M3-M4 and C1-C2 electrode montages.

Methods: Twenty-five patients underwent cerebral vascular surgery with tcMEP monitoring. tcMEP voltage thresholds were compared between LQP (C1, M3, C2, M4), C1-C2, and M3-M4 montages.

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Computational modeling of neuroactivity plays a central role in our effort to understand brain dynamics in the advancements of neural engineering such as deep brain stimulation, neuroprosthetics, and magnetic resonance electrical impedance tomography. However, analytic solutions do not capture the fundamental nonlinear behavior of an action potential. What is needed is a method that is not constrained to only linearized models of neural tissue.

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