NeuroImage
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Although MRI is the gold standard for the diagnosis and monitoring of multiple sclerosis (MS), current conventional MRI techniques often fail to detect cortical alterations and provide little information about gliosis, axonal damage and myelin status of lesioned areas. Diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) provide sensitive and complementary measures of the neural tissue microstructure. Additionally, specific white matter tract integrity (WMTI) metrics modelling the diffusion in white matter were recently derived. ⋯ Interestingly, WMTI-derived metrics showed the aptitude to distinguish between the different stages of the disease. Both the intra-axonal diffusivity (Da) and the AWF were found to be decreased in the cuprizone treated group, Da specifically decreased during the acute inflammatory demyelinating phase whereas the AWF decrease was associated to the spontaneous remyelination and the recovery period. Altogether our results demonstrate that DKI is sensitive to alterations of cortical areas and provides, along with WMTI metrics, information that is complementary to DT-derived metrics for the characterization of demyelination in both white and grey matter and subsequent inflammatory processes associated with a demyelinating event.
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In this paper we describe a method for retrospective estimation and correction of eddy current (EC)-induced distortions and subject movement in diffusion imaging. In addition a susceptibility-induced field can be supplied and will be incorporated into the calculations in a way that accurately reflects that the two fields (susceptibility- and EC-induced) behave differently in the presence of subject movement. ⋯ In addition we show that the linear EC-model commonly used is insufficient for the data used in the present paper (high spatial and angular resolution data acquired with Stejskal-Tanner gradients on a 3T Siemens Verio, a 3T Siemens Connectome Skyra or a 7T Siemens Magnetome scanner) and that a higher order model performs significantly better. The method is already in extensive practical use and is used by four major projects (the WU-UMinn HCP, the MGH HCP, the UK Biobank and the Whitehall studies) to correct for distortions and subject movement.
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New MRI methods for noninvasive imaging of baseline oxygen extraction fraction (OEF) in the brain show great promise. Quantitative O2 imaging (QUO2) applies a biophysical model to measure OEF in tissue from BOLD, cerebral blood flow (CBF), and end-tidal O2 (ETO2) signals acquired during two or more gas manipulations. Alternatively, quantitative susceptibility mapping (QSM) maps baseline OEF along cerebral vessels based on the deoxyhemoblogin (dHb) susceptibility shift between veins and water. ⋯ Three-gas QUO2 values of OEF correlated with QSM values of OEF (P=0.03). However, Bland-Altman analysis revealed that QUO2 tended to measure higher baseline OEF with respect to QSM, which likely results from underestimation of the hyperoxic BOLD signal and low signal-to-noise ratio of the ASL acquisitions. Across subjects, the percent CBF change during the visual task correlated with OEF measured by 3-gas QUO2 (P<0.04); and by QSM (P=0.035), providing evidence that the new methods measure true variations in brain physiology across subjects.
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Electrophysiological recordings from subdural electrocorticography (ECoG) electrodes implanted temporarily during deep brain stimulation (DBS) surgeries offer a unique opportunity to record cortical activity for research purposes. The optimal utilization of this important research method relies on accurate and robust localization of ECoG electrodes, and intraoperative fluoroscopy is often the only imaging modality available to visualize electrode locations. However, the localization of a three-dimensional electrode position using a two-dimensional fluoroscopic image is problematic due to the lost dimension orthogonal to the fluoroscopic image, a parallax distortion implicit to fluoroscopy, and variability of visible skull contour among fluoroscopic images. ⋯ Validation of this approach demonstrated high precision with an average total Euclidian distance between three independent reviewers of 1.65±0.68mm across 8 patients and 82 electrodes. Spatial accuracy was confirmed by correspondence between recorded neural activity over sensorimotor cortex during hand movement. This semi-automated interface reliably estimates the location of temporarily implanted subdural ECoG electrodes visible on intraoperative fluoroscopy to a cortical surface.