Nikolaus Weiskopf

Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Saxony, Germany

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Publications (155)733.9 Total impact

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    ABSTRACT: Despite the constant improvement of algorithms for automated brain tissue classification, the accurate delineation of subcortical structures using magnetic resonance images (MRI) data remains challenging. The main difficulties arise from the low grey-white matter contrast of iron rich areas in T1-weighted (T1w) MRI data and from the lack of adequate priors for basal ganglia and thalamus. The most recent attempts to obtain such priors were based on cohorts with limited size that included subjects in a narrow age range, failing to account for age-related grey-white matter contrast changes. Aiming to improve the anatomical plausibility of automated brain tissue classification from T1w data, we have created new tissue probability maps for subcortical grey matter regions. Supported by atlas-derived spatial information, raters manually labelled subcortical structures in a cohort of healthy subjects using magnetization transfer saturation and R2* MRI maps, which feature optimal grey-white matter contrast in these areas. After assessment of inter-rater variability, the new tissue priors were tested on T1w data within the framework of voxel-based morphometry. The automated detection of grey matter in subcortical areas with our new probability maps was more anatomically plausible compared to the one derived with currently available priors. We provide evidence that the improved delineation compensates age-related bias in the segmentation of iron rich subcortical regions. The new tissue priors, allowing robust detection of basal ganglia and thalamus, have the potential to enhance the sensitivity of voxel-based morphometry in both healthy and diseased brains.
    No preview · Article · Feb 2016 · NeuroImage
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    ABSTRACT: The g-ratio, quantifying the ratio between the inner and outer diameters of a fiber, is an important microstructural characteristic of fiber pathways and is functionally related to conduction velocity. We introduce a novel method for estimating the MR g-ratio non-invasively across the whole brain using high-fidelity magnetization transfer (MT) imaging and single-shell diffusion MRI. These methods enabled us to map the MR g-ratio in vivo across the brain's prominent fiber pathways in a group of 37 healthy volunteers and to estimate the inter-subject variability. Effective correction of susceptibility-related distortion artifacts was essential before combining the MT and diffusion data, in order to reduce partial volume and edge artifacts. The MR g-ratio is in good qualitative agreement with histological findings despite the different resolution and spatial coverage of MRI and histology. The MR g-ratio holds promise as an important non-invasive biomarker due to its microstructural and functional relevance in neurodegeneration.
    Full-text · Article · Dec 2015 · Frontiers in Neuroscience
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    ABSTRACT: Purpose: Inter-scan motion causes differential receive field modulation between scans, leading to errors when they are combined to quantify MRI parameters. We present a robust and efficient method that accounts for inter-scan motion by removing this modulation before parameter quantification. Theory and methods: Five participants moved between two high-resolution structural scans acquired with different flip angles. Before each high-resolution scan, the effective relative sensitivity of the receive head coil was estimated by combining two rapid low-resolution scans acquired receiving on each of the body and head coils. All data were co-registered and sensitivity variations were removed from the high-resolution scans by division with the effective relative sensitivity. R1 maps with and without this correction were calculated and compared against reference maps unaffected by inter-scan motion. Results: Even after coregistration, inter-scan motion significantly biased the R1 maps, leading to spurious variation in R1 in brain tissue and deviations with respect to a no-motion reference. The proposed correction scheme reduced the error to within the typical scan-rescan error observed in datasets unaffected by motion. Conclusion: Inter-scan motion negatively impacts the accuracy and precision of R1 mapping. We present a validated correction method that accounts for position-specific receive field modulation. Magn Reson Med, 2015. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
    No preview · Article · Nov 2015 · Magnetic Resonance in Medicine
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    ABSTRACT: We compared the sensitivity of standard single-shot 2D echo planar imaging (EPI) to three advanced EPI sequences, i.e., 2D multi-echo EPI, 3D high resolution EPI and 3D dual-echo fast EPI in fixed effects and random effects group level fMRI analyses at 3 Tesla. The study focused on how well the variance reduction in fixed effects analyses achieved by advanced EPI sequences translates into increased sensitivity in the random effects group level analysis. The sensitivity was estimated in a functional MRI experiment of an emotional learning and a reward based learning tasks in a group of 24 volunteers. Each experiment was acquired with the four different sequences. The task-related response amplitude, contrast level and respective t-value were proxies for the functional sensitivity across the brain. All three advanced EPI methods increased the sensitivity in the fixed effects analyses, but standard single-shot 2D EPI provided a comparable performance in random effects group analysis when whole brain coverage and moderate resolution are required. In this experiment inter-subject variability determined the sensitivity of the random effects analysis for most brain regions, making the impact of EPI pulse sequence improvements less relevant or even negligible for random effects analyses. An exception concerns the optimization of EPI reducing susceptibility-related signal loss that translates into an enhanced sensitivity e.g. in the orbitofrontal cortex for multi-echo EPI. Thus, future optimization strategies may best aim at reducing inter-subject variability for higher sensitivity in standard fMRI group studies at moderate spatial resolution.
    No preview · Article · Oct 2015 · NeuroImage
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    ABSTRACT: Obesity-related structural brain alterations point to a consistent reduction in gray matter with increasing body mass index (BMI) but changes in white matter have proven to be more complex and less conclusive. Hence, more recently diffusion tensor imaging (DTI) has been employed to investigate microstructural changes in white matter structure. Altogether, these studies have mostly shown a loss of white matter integrity with obesity-related factors in several brain regions. However, the variety of these obesity-related factors, including inflammation and dyslipidemia, resulted in competing influences on the DTI indices. To increase the specificity of DTI results, we explored specific brain tissue properties by combining DTI with quantitative multi-parameter mapping in lean, overweight and obese young adults. By means of multi-parameter mapping, white matter structures showed differences in MRI parameters consistent with reduced myelin, increased water and altered iron content with increasing BMI in the superior longitudinal fasciculus, anterior thalamic radiation, internal capsule and corpus callosum. BMI-related changes in DTI parameters revealed mainly alterations in mean and axial diffusivity with increasing BMI in the corticospinal tract, anterior thalamic radiation and superior longitudinal fasciculus. These alterations, including mainly fiber tracts linking limbic structures with prefrontal regions, could potentially promote accelerated aging in obese individuals leading to an increased risk for cognitive decline.
    Full-text · Article · Oct 2015 · NeuroImage
  • Patrick Freund · Siawoosh Mohammadi · Nikolaus Weiskopf · Armin Curt

    No preview · Chapter · Oct 2015
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    ABSTRACT: The blood oxygenation level dependent (BOLD) signal is widely used for functional magnetic resonance imaging (fMRI) of brain function in health and disease. The statistical power of fMRI group studies is significantly hampered by high inter-subject variance due to differences in baseline vascular physiology. Several methods have been proposed to account for physiological vascularization differences between subjects and hence improve the sensitivity in group studies. However, these methods require the acquisition of additional reference scans (such as a full resting-state fMRI session or ASL based calibrated BOLD). We present a vascular autorescaling (VasA) method, which does not require any additional reference scans. VasA is based on the observation that slow oscillations (<0.1 Hz) in arterial blood CO2 levels occur naturally due to changes in respiration patterns. These oscillations yield fMRI signal changes whose amplitudes reflect the blood oxygenation levels and underlying local vascularization and vascular responsivity. VasA estimates proxies of the amplitude of these CO2-driven oscillations directly from the residuals of task-related fMRI data without the need for reference scans. The estimates are used to scale the amplitude of task-related fMRI responses, to account for vascular differences. The VasA maps compared well to cerebrovascular reactivity (CVR) maps and cerebral blood volume maps based on VAscular Space Occupancy (VASO) measurements in four volunteers, speaking to the physiological vascular basis of VasA. VasA was validated in a wide variety of tasks in 138 volunteers. VasA increased t-scores by up to 30% in specific brain areas such as the visual cortex. The number of activated voxels was increased by up to 200% in brain areas such as the orbital frontal cortex while still controlling the nominal false positive rate. VasA fMRI outperformed previously proposed rescaling approaches based on resting-state fMRI data and can be readily applied to any task-related fMRI dataset, even retrospectively.
    Full-text · Article · Sep 2015 · NeuroImage
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    ABSTRACT: Functional magnetic resonance imaging (fMRI) studies that require high resolution whole brain coverage have long scan times that are primarily driven by the large number of thin slices acquired. 2D multiband echo-planar imaging (EPI) sequences accelerate the data acquisition along the slice direction and therefore represent an attractive approach to such studies by improving the temporal resolution without sacrificing spatial resolution. In this work, a 2D multiband EPI sequence was optimized for 1.5 mm isotropic whole brain acquisitions at 3T with 10 healthy volunteers imaged while performing simultaneous visual and motor tasks. The performance of the sequence was evaluated in terms of BOLD sensitivity and false positive activation at multiband (MB) factors of 1, 2, 4, and 6, combined with in-plane GRAPPA acceleration of 2x (GRAPPA 2), and the two reconstruction approaches of Slice-GRAPPA and Split Slice-GRAPPA. Sensitivity results demonstrate significant gains in temporal signal-to-noise ratio (tSNR) and t-score statistics for MB 2, 4, and 6 compared to MB 1. The MB factor for optimal sensitivity varied depending on anatomical location and reconstruction method. When using Slice-GRAPPA reconstruction, evidence of false positive activation due to signal leakage between simultaneously excited slices was seen in one instance, 35 instances, and 70 instances over the ten volunteers for the respective accelerations of MB 2 x GRAPPA 2, MB 4 x GRAPPA 2, and MB 6 x GRAPPA 2. The use of Split Slice-GRAPPA reconstruction supressed the prevalence of false positives significantly, to one instance, 5 instances, and 5 instances for the same respective acceleration factors. Imaging protocols using an acceleration factor of MB 2 x GRAPPA 2 can be confidently used for high resolution whole brain imaging to improve BOLD sensitivity with very low probability for false positive activation due to slice leakage. Imaging protocols using higher acceleration factors (MB 3 or MB 4 x GRAPPA 2) can likely provide even greater gains in sensitivity but should be carefully optimized to minimize the possibility of false activations. Copyright © 2015. Published by Elsevier Inc.
    Preview · Article · Sep 2015 · NeuroImage
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    ABSTRACT: In patients with sub-acute spinal cord injury (SCI), the motor system undergoes progressive structural changes rostral to the lesion, which is predictive of motor outcome. The extent to which the sensory system is affected and how this relates to sensory outcome is uncertain. Changes in the sensory system were prospectively followed by applying a comprehensive MRI protocol to fourteen patients with sub-acute traumatic SCI at baseline, two months, six months, and twelve months, combined with a full neurological examination and comprehensive pain assessment. Eighteen controls underwent the same MRI protocol. T1-weighted volumes and myelin-sensitive magnetisation transfer saturation (MT) and longitudinal relaxation rate (R1) mapping provided data on spinal cord and brain morphometry and microstructure. Regression analysis assessed the relationship between MRI readouts and sensory outcomes. At twelve months from baseline, sensory scores were unchanged and below-level neuropathic pain became prominent. Compared with controls, patients showed progressive degenerative changes in cervical cord and brain morphometry across the sensory system. At twelve months, MT and R1 were reduced in areas of structural decline. Sensory scores at twelve months correlated with rate of change in cord area and brain volume and decreased MT in the spinal cord at twelve months. This study has demonstrated progressive atrophic and microstructural changes across the sensory system with a close relation to sensory outcome. Structural MRI protocols remote from the site of lesion provide new insights into neuronal degeneration underpinning sensory disturbance and have the potential as responsive biomarkers of rehabilitation and treatment interventions. This article is protected by copyright. All rights reserved. © 2015 American Neurological Association.
    Full-text · Article · Aug 2015 · Annals of Neurology
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    ABSTRACT: Current computational neuroanatomy based on MRI focuses on morphological measures of the brain. We present recent methodological developments in quantitative MRI (qMRI) that provide standardized measures of the brain, which go beyond morphology. We show how biophysical modelling of qMRI data can provide quantitative histological measures of brain tissue, leading to the emerging field of in-vivo histology using MRI (hMRI). qMRI has greatly improved the sensitivity and specificity of computational neuroanatomy studies. qMRI metrics can also be used as direct indicators of the mechanisms driving observed morphological findings. For hMRI, biophysical models of the MRI signal are being developed to directly access histological information such as cortical myelination, axonal diameters or axonal g-ratio in white matter. Emerging results indicate promising prospects for the combined study of brain microstructure and function. Non-invasive brain tissue characterization using qMRI or hMRI has significant implications for both research and clinics. Both approaches improve comparability across sites and time points, facilitating multicentre/longitudinal studies and standardized diagnostics. hMRI is expected to shed new light on the relationship between brain microstructure, function and behaviour, both in health and disease, and become an indispensable addition to computational neuroanatomy.
    No preview · Article · Aug 2015 · Current opinion in neurology
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    Frank Scharnowski · Nikolaus Weiskopf
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    ABSTRACT: Neuroscience has demonstrated that individual differences in cognitive task performance are closely linked to differences in brain activity. Neurofeedback training based on real-time functional magnetic resonance imaging (fMRI) can effectively change specific localized brain activity. Various studies in healthy volunteers and patients have shown that self-regulation of specific brain activity can be learned with fMRI neurofeedback, and leads to specific corresponding behavioral changes. Initial evidence for cognitive enhancement due to fMRI neurofeedback include the domains of perception, motor performance, and memory. Although further conceptual and technical advances are needed to overcome current limitations of this novel method, its non-invasiveness and compatibility with other behavioral or pharmacological approaches promise that it will become a powerful tool for cognitive enhancement.
    Preview · Article · May 2015
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    ABSTRACT: Functional MRI (fMRI) used for neurosurgical planning delineates functionally eloquent brain areas by time-series analysis of task-induced BOLD signal changes. Commonly used frequentist statistics protect against false positive results based on a p-value threshold. In surgical planning, false negative results are equally if not more harmful, potentially masking true brain activity leading to erroneous resection of eloquent regions. Bayesian statistics provides an alternative framework, categorizing areas as activated, deactivated, non-activated or with low statistical confidence. This approach has not yet found wide clinical application partly due to the lack of a method to objectively define an effect size threshold. We implemented a Bayesian analysis framework for neurosurgical planning fMRI. It entails an automated effect-size threshold selection method for posterior probability maps accounting for inter-individual BOLD response differences, which was calibrated based on the frequentist results maps thresholded by two clinical experts. We compared Bayesian and frequentist analysis of passive-motor fMRI data from 10 healthy volunteers measured on a pre-operative 3T and an intra-operative 1.5T MRI scanner. As a clinical case study, we tested passive motor task activation in a brain tumor patient at 3T under clinical conditions. With our novel effect size threshold method, the Bayesian analysis revealed regions of all four categories in the 3T data. Activated region foci and extent were consistent with the frequentist analysis results. In the lower signal-to-noise ratio 1.5T intra-operative scanner data, Bayesian analysis provided improved brain-activation detection sensitivity compared with the frequentist analysis, albeit the spatial extents of the activations were smaller than at 3T. Bayesian analysis of fMRI data using operator-independent effect size threshold selection may improve the sensitivity and certainty of information available to guide neurosurgery.
    Full-text · Article · May 2015 · Frontiers in Neuroscience
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    ABSTRACT: PurposeDiffusion MRI has recently been used with detailed models to probe tissue microstructure. Much of this work has been performed ex vivo with powerful scanner hardware, to gain sensitivity to parameters such as axon radius. By contrast, performing microstructure imaging on clinical scanners is extremely challenging.Methods We use an optimized dual spin-echo diffusion protocol, and a Bayesian fitting approach, to obtain reproducible contrast (histogram overlap of up to 92%) in estimated maps of axon radius index in healthy adults at a modest, widely-available gradient strength (35 mT m ). A key innovation is the use of influential priors.ResultsWe demonstrate that our priors can improve precision in axon radius estimates—a 7-fold reduction in voxelwise coefficient of variation in vivo—without significant bias. Our results may reflect true axon radius differences between white matter regions, but this interpretation should be treated with caution due to the complexity of the tissue relative to our model.Conclusions Some sensitivity to relatively large axons (3–15 μm) may be available at clinical field and gradient strengths. Future applications at higher gradient strength will benefit from the favorable eddy current properties of the dual spin-echo sequence, and greater precision available with suitable priors. Magn Reson Med, 2015. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
    Full-text · Article · May 2015 · Magnetic Resonance in Medicine
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    ABSTRACT: Quantitative imaging aims to provide in vivo neuroimaging biomarkers with high research and diagnostic value that are sensitive to underlying tissue microstructure. In order to use these data to examine intra-cortical differences or to define boundaries between different myelo-architectural areas, high resolution data are required. The quality of such measurements is degraded in the presence of motion hindering insight into brain microstructure. Correction schemes are therefore vital for high resolution, whole brain coverage approaches that have long acquisition times and greater sensitivity to motion. Here we evaluate the use of prospective motion correction (PMC) via an optical tracking system to counter intra-scan motion in a high resolution (800 μm isotropic) multi-parameter mapping (MPM) protocol. Data were acquired on six volunteers using a 2 × 2 factorial design permuting the following conditions: PMC on/off and motion/no motion. In the presence of head motion, PMC-based motion correction considerably improved the quality of the maps as reflected by fewer visible artifacts and improved consistency. The precision of the maps, parameterized through the coefficient of variation in cortical sub-regions, showed improvements of 11-25% in the presence of deliberate head motion. Importantly, in the absence of motion the PMC system did not introduce extraneous artifacts into the quantitative maps. The PMC system based on optical tracking offers a robust approach to minimizing motion artifacts in quantitative anatomical imaging without extending scan times. Such a robust motion correction scheme is crucial in order to achieve the ultra-high resolution required of quantitative imaging for cutting edge in vivo histology applications.
    Preview · Article · Mar 2015 · Frontiers in Neuroscience
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    ABSTRACT: Task performance depends on ongoing brain activity which can be influenced by attention, arousal, or motivation. However, such modulating factors of cognitive efficiency are unspecific, can be difficult to control, and are not suitable to facilitate neural processing in a regionally specific manner. Here, we non-pharmacologically manipulated regionally specific brain activity using technically sophisticated real-time fMRI neurofeedback. This was accomplished by training participants to simultaneously control ongoing brain activity in circumscribed motor and memory-related brain areas, namely the supplementary motor area and the parahippocampal cortex. We found that learned voluntary control over these functionally distinct brain areas caused functionally specific behavioral effects, i.e. shortening of motor reaction times and specific interference with memory encoding. The neurofeedback approach goes beyond improving cognitive efficiency by unspecific psychological factors such as attention, arousal, or motivation. It allows for directly manipulating sustained activity of task-relevant brain regions in order to yield specific behavioral or cognitive effects. Copyright © 2015. Published by Elsevier B.V.
    Full-text · Article · Mar 2015 · Biological psychology
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    ABSTRACT: We evaluated the performance of an optical camera based prospective motion correction (PMC) system in improving the quality of 3D echo-planar imaging functional MRI data. An optical camera and external marker were used to dynamically track the head movement of subjects during fMRI scanning. PMC was performed by using the motion information to dynamically update the sequence's RF excitation and gradient waveforms such that the field-of-view was realigned to match the subject's head movement. Task-free fMRI experiments on five healthy volunteers followed a 2×2×3 factorial design with the following factors: PMC on or off; 3.0mm or 1.5mm isotropic resolution; and no, slow, or fast head movements. Visual and motor fMRI experiments were additionally performed on one of the volunteers at 1.5mm resolution comparing PMC on vs PMC off for no and slow head movements. Metrics were developed to quantify the amount of motion as it occurred relative to k-space data acquisition. The motion quantification metric collapsed the very rich camera tracking data into one scalar value for each image volume that was strongly predictive of motion-induced artifacts. The PMC system did not introduce extraneous artifacts for the no motion conditions and improved the time series temporal signal-to-noise by 30% to 40% for all combinations of low/high resolution and slow/fast head movement relative to the standard acquisition with no prospective correction. The numbers of activated voxels (p<0.001, uncorrected) in both task-based experiments were comparable for the no motion cases and increased by 78% and 330%, respectively, for PMC on versus PMC off in the slow motion cases. The PMC system is a robust solution to decrease the motion sensitivity of multi-shot 3D EPI sequences and thereby overcoming one of the main roadblocks to their widespread use in fMRI studies. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
    Preview · Article · Mar 2015 · NeuroImage

  • No preview · Article · Mar 2015 · Brain Stimulation
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    ABSTRACT: The human midbrain and pons contain nuclei of major neurotransmitter systems that send long-range projections to regulate brain activity in cortical and subcortical structures. Despite being small structures, these nuclei are critically implicated in a very wide range of cognitive and bodily functions, and their dysfunction plays an important role in a number of neurological and neuropsychiatric conditions. Hence, there is a considerable interest to develop functional MRI approaches that allow to image their activity in health and disease.
    No preview · Chapter · Jan 2015
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    ABSTRACT: We present an approach for combining high resolution MRI-based myelin mapping with functional information from electroencephalography (EEG) or magnetoencephalography (MEG). The main contribution to the primary currents detectable with EEG and MEG comes from ionic currents in the apical dendrites of cortical pyramidal cells, aligned perpendicular to the local cortical surface. We provide evidence from an in-vivo experiment that the known microstructural variation in myelinated pyramidal cell density across the cortex predicts the variation of the current density over individuals and thus is of functional relevance. Current dipole moments of pitch onset evoked response fields (ERFs) were source localised by means of a variational Bayesian equivalent current dipole algorithm. The myeloarchitecture was estimated indirectly from individual high resolution quantitative multi-parameter maps (MPMs) acquired at 800μm isotropic resolution. Myelin estimates across cortical areas correlated positively with dipole magnitude. This correlation was spatially specific: regions of interest in auditory cortex provided significantly better models than those covering whole hemispheres. Based on the MPM data we identified the auditory cortical area TE1.2 as the most likely origin of the pitch ERFs measured by MEG. We can now proceed to exploit the higher spatial resolution of quantitative MPMs to identify the cortical origin of M/EEG signals, inform M/EEG source reconstruction and explore structure-function relationships at the fine structural level in the living human brain. Copyright © 2014. Published by Elsevier Inc.
    Full-text · Article · Dec 2014 · NeuroImage
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    ABSTRACT: Diffusion Kurtosis Imaging (DKI) is more sensitive to microstructural differences and can be related to more specific micro-scale metrics (e.g. intra-axonal volume fraction) than diffusion tensor imaging (DTI), offering exceptional potential for clinical diagnosis and research into the white and gray matter. Currently DKI is acquired only at low spatial resolution (2-3 mm isotropic), because of the lower signal-to-noise ratio (SNR) and higher artifact level associated with the technically more demanding DKI. Higher spatial resolution of about 1mm is required for the characterization of fine white matter pathways or cortical microstructure. We used restricted-field-of-view imaging in combination with advanced post-processing methods to enable unprecedented high-quality, high-resolution DKI (1.2 mm isotropic) on a clinical 3T scanner. Post-processing was advanced by developing a novel method for Retrospective Eddy current and Motion ArtifacT Correction in High-resolution, multi-shell diffusion data (REMATCH). Furthermore, we applied a powerful edge preserving denoising method, denoted as multi-shell orientation-position-adaptive smoothing (msPOAS). We demonstrated the feasibility of high-quality, high-resolution DKI and its potential for delineating highly myelinated fiber pathways in the motor cortex. REMATCH performs robustly even at the low SNR level of high-resolution DKI, where standard EC and motion correction failed (i.e. produced incorrectly aligned images) and thus biased the diffusion model fit. We showed that the combination of REMATCH and msPOAS increased the contrast between gray and white matter in mean kurtosis (MK) maps by about 35% and at the same time preserves the original distribution of MK values, whereas standard Gaussian smoothing strongly biases the distribution.
    Full-text · Article · Dec 2014 · Frontiers in Neuroscience

Publication Stats

6k Citations
733.90 Total Impact Points

Institutions

  • 2015
    • Max Planck Institute for Human Cognitive and Brain Sciences
      • Department of Neurophysics
      Leipzig, Saxony, Germany
  • 2006-2015
    • University College London
      • • Wellcome Trust Centre for Neuroimaging
      • • Institute of Neurology
      • • Wellcome Department of Imaging Neuroscience
      Londinium, England, United Kingdom
  • 2014
    • Wellcome Trust
      Londinium, England, United Kingdom
  • 2010-2014
    • UCL Eastman Dental Institute
      Londinium, England, United Kingdom
  • 2013
    • Queen Mary, University of London
      Londinium, England, United Kingdom
  • 2002-2009
    • University of Tuebingen
      • • Institute of Medical Psychology and Behavioral Neurobiology
      • • Department of Neurology
      Tübingen, Baden-Württemberg, Germany