[Show abstract][Hide abstract] 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.
[Show abstract][Hide abstract] ABSTRACT: Purpose
To overcome current limitations in combined transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI) studies by employing a dedicated coil array design for 3 Tesla.
The state-of-the-art setup for concurrent TMS/fMRI is to use a large birdcage head coil, with the TMS between the subject's head and the MR coil. This setup has drawbacks in sensitivity, positioning, and available imaging techniques. In this study, an ultraslim 7-channel receive-only coil array for 3 T, which can be placed between the subject's head and the TMS, is presented. Interactions between the devices are investigated and the performance of the new setup is evaluated in comparison to the state-of-the-art setup.
MR sensitivity obtained at the depth of the TMS stimulation is increased by a factor of five. Parallel imaging with an acceleration factor of two is feasible with low g-factors. Possible interactions between TMS and the novel hardware were investigated and were found negligible.
The novel coil array is safe, strongly improves signal-to-noise ratio in concurrent TMS/fMRI experiments, enables parallel imaging, and allows for flexible positioning of the TMS on the head while ensuring efficient TMS stimulation due to its ultraslim design.
Magnetic Resonance in Medicine 11/2014; · 3.40 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Evidence from magnetic resonance imaging (MRI) studies shows that healthy aging is associated with profound changes in cortical and subcortical brain structures. The reliable delineation of cortex and basal ganglia using automated computational anatomy methods based on T1-weighted images remains challenging, which results in controversies in the literature. In this study we use quantitative MRI (qMRI) to gain an insight into the microstructural mechanisms underlying tissue ageing and look for potential interactions between ageing and brain tissue properties to assess their impact on automated tissue classification. To this end we acquired maps of longitudinal relaxation rate R1, effective transverse relaxation rate R2* and magnetization transfer - MT, from healthy subjects (n=96, aged 21 - 88years) using a well-established multi-parameter mapping qMRI protocol. Within the framework of voxel-based quantification we find higher grey matter volume in basal ganglia, cerebellar dentate and prefrontal cortex when tissue classification is based on MT maps compared with T1 maps. These discrepancies between grey matter volume estimates can be attributed to R2* - a surrogate marker of iron concentration, and further modulation by an interaction between R2* and age, both in cortical and subcortical areas. We interpret our findings as direct evidence for the impact of ageing-related brain tissue property changes on automated tissue classification of brain structures using SPM12. Computational anatomy studies of ageing and neurodegeneration should acknowledge these effects, particularly when inferring about underlying pathophysiology from regional cortex and basal ganglia volume changes.
[Show abstract][Hide abstract] ABSTRACT: Relaxation rates provide important information about tissue microstructure. Multi-parameter mapping (MPM) estimates multiple relaxation parameters from multi-echo FLASH acquisitions with different basic contrasts, i.e., proton density (PD), T1 or magnetization transfer (MT) weighting. Motion can particularly affect maps of the apparent transverse relaxation rate R2(*), which are derived from the signal of PD-weighted images acquired at different echo times. To address the motion artifacts, we introduce ESTATICS, which robustly estimates R2(*) from images even when acquired with different basic contrasts. ESTATICS extends the fitted signal model to account for inherent contrast differences in the PDw, T1w and MTw images. The fit was implemented as a conventional ordinary least squares optimization and as a robust fit with a small or large confidence interval. These three different implementations of ESTATICS were tested on data affected by severe motion artifacts and data with no prominent motion artifacts as determined by visual assessment or fast optical motion tracking. ESTATICS improved the quality of the R2(*) maps and reduced the coefficient of variation for both types of data-with average reductions of 30% when severe motion artifacts were present. ESTATICS can be applied to any protocol comprised of multiple 2D/3D multi-echo FLASH acquisitions as used in the general research and clinical setting.
[Show abstract][Hide abstract] ABSTRACT: The lateral habenula (LHb) has been shown to respond to cues that predict aversive stimuli in non-human primates (Matsumoto & Hikosaka, 2009, Nat Neurosci, 12 (1), 77-84) and has been implicated in reinforcement processing and the pathophysiology of major depression (MDD) (Roiser et al, Biol Psychiatry, 66 (5), 441-450), possibly via reciprocal connections with monoaminergic nuclei. We report the first high-resolution fMRI investigation of haemodynamic responses during appetitive and aversive conditioning in the LHb in unipolar MDD. Additionally, we report the first assessment of tonic habenula function using quantitative Arterial Spin Labelling (ASL) in MDD.
[Show abstract][Hide abstract] ABSTRACT: Learning what to approach, and what to avoid, involves assigning value to environmental cues that predict positive and negative events. Studies in animals indicate that the lateral habenula encodes the previously learned negative motivational value of stimuli. However, involvement of the habenula in dynamic trial-by-trial aversive learning has not been assessed, and the functional role of this structure in humans remains poorly characterized, in part, due to its small size. Using high-resolution functional neuroimaging and computational modeling of reinforcement learning, we demonstrate positive habenula responses to the dynamically changing values of cues signaling painful electric shocks, which predict behavioral suppression of responses to those cues across individuals. By contrast, negative habenula responses to monetary reward cue values predict behavioral invigoration. Our findings show that the habenula plays a key role in an online aversive learning system and in generating associated motivated behavior in humans.
Proceedings of the National Academy of Sciences 07/2014; · 9.81 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: We present a novel multi-shell position orientation adaptive smoothing (msPOAS) method for diffusion-weighted magnetic resonance data. Smoothing in voxel and diffusion gradient space is embedded in an iterative adaptive multiscale approach. The adaptive character avoids blurring of the inherent structures and preserves discontinuities. The simultaneous treatment of all q-shells improves the stability compared to single shell approaches such as the original POAS method. The msPOAS implementation simplifies and speeds up calculations, compared to POAS, facilitating its practical application. Simulations and heuristics support the face validity of the technique and its rigorousness. The characteristics of msPOAS were evaluated on single and multi-shell diffusion data of the human brain. Significant reduction in noise while preserving the fine structure was demonstrated for diffusion weighted images, standard DTI analysis and advanced diffusion models such as NODDI. MsPOAS effectively improves the poor signal-to-noise ratio in highly diffusion weighted multi-shell diffusion data, which is required by recent advanced diffusion micro-structure models. We demonstrate the superiority of the new method compared to other advanced denoising methods.
[Show abstract][Hide abstract] ABSTRACT: Background / Purpose:
Functional and diffusion-weighted MRI are usually performed using echo-planar imaging (EPI). A major problem with EPI are geometric distortions caused by magnetic field inhomogeneities, especially at high field strength. To determine the best way to deal with these, we compared three methods for EPI distortion correction.
Overall, the methods based on opposite phase encoding directions consistently outperform the fieldmap-based method.
20th Annual Meeting of the Organization for Human Brain Mapping (OHBM) 2014; 07/2014
[Show abstract][Hide abstract] ABSTRACT: We present an implementation of a recently developed noise reduction algorithm for dMRI data, called multi-shell position orientation adaptive smoothing (msPOAS), as a toolbox for SPM. The method intrinsically adapts to the structures of different size and shape in dMRI and hence avoids blurring typically observed in non-adaptive smoothing. We give examples for the usage of the toolbox and explain the determination of experiment-dependent parameters for an optimal performance of msPOAS.
[Show abstract][Hide abstract] ABSTRACT: Diffusion magnetic resonance imaging (dMRI) has become increasingly relevant in clinical research and neuroscience. It is commonly carried out using the ultra-fast MRI acquisition technique Echo-Planar Imaging (EPI). While offering crucial reduction of acquisition times, two limitations of EPI are distortions due to varying magnetic susceptibilities of the object being imaged and its limited spatial resolution. In the recent years progress has been made both for susceptibility artefact correction and increasing of spatial resolution using image processing and reconstruction methods. However, so far, the interplay between both problems has not been studied and super-resolution techniques could only be applied along one axis, the slice-select direction, limiting the potential gain in spatial resolution. In this work we describe a new method for joint susceptibility artefact correction and super-resolution in EPI-MRI that can be used to increase resolution in all three spatial dimensions and in particular increase in-plane resolutions. The key idea is to reconstruct a distortion-free, high-resolution image from a number of low-resolution EPI data that are deformed in different directions. Numerical results on dMRI data of a human brain indicate that this technique has the potential to provide for the first time in-vivo dMRI at mesoscopic spatial resolution (i.e. 500μm); a spatial resolution that could bridge the gap between white-matter information from ex-vivo histology (≈1μm) and in-vivo dMRI (≈2000μm).
[Show abstract][Hide abstract] ABSTRACT: Neurofeedback based on real-time functional magnetic resonance imaging (fMRI) is a new approach that allows training of voluntary control over regionally specific brain activity. However, the neural basis of successful neurofeedback learning remains poorly understood. Here, we assessed changes in effective brain connectivity associated with neurofeedback training of visual cortex activity. Using dynamic causal modeling (DCM), we found that training participants to increase visual cortex activity was associated with increased effective connectivity between the visual cortex and the superior parietal lobe. Specifically, participants who learned to control activity in their visual cortex showed increased top-down control of the superior parietal lobe over the visual cortex, and at the same time reduced bottom-up processing. These results are consistent with efficient employment of top-down visual attention and imagery, which were the cognitive strategies used by participants to increase their visual cortex activity.
PLoS ONE 03/2014; 9(3):e91090. · 3.53 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: A pressing need exists to disentangle age-related changes from pathologic neurodegeneration. This study aims to characterize the spatial pattern and age-related differences of biologically relevant measures in vivo over the course of normal aging. Quantitative multiparameter maps that provide neuroimaging biomarkers for myelination and iron levels, parameters sensitive to aging, were acquired from 138 healthy volunteers (age range: 19-75 years). Whole-brain voxel-wise analysis revealed a global pattern of age-related degeneration. Significant demyelination occurred principally in the white matter. The observed age-related differences in myelination were anatomically specific. In line with invasive histologic reports, higher age-related differences were seen in the genu of the corpus callosum than the splenium. Iron levels were significantly increased in the basal ganglia, red nucleus, and extensive cortical regions but decreased along the superior occipitofrontal fascicle and optic radiation. This whole-brain pattern of age-associated microstructural differences in the asymptomatic population provides insight into the neurobiology of aging. The results help build a quantitative baseline from which to examine and draw a dividing line between healthy aging and pathologic neurodegeneration.
Neurobiology of aging 02/2014; · 5.94 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: In Parkinson's disease the degree of motor impairment can be classified with respect to tremor dominant and akinetic rigid features. While tremor dominance and akinetic rigidity might represent two ends of a continuum rather than discrete entities, it would be important to have non-invasive markers of any biological differences between them in vivo, to assess disease trajectories and response to treatment, as well as providing insights into the underlying mechanisms contributing to heterogeneity within the Parkinson's disease population.
Here, we used magnetic resonance imaging to examine whether Parkinson's disease patients exhibit structural changes within the basal ganglia that might relate to motor phenotype. Specifically, we examined volumes of basal ganglia regions, as well as transverse relaxation rate (a putative marker of iron load) and magnetization transfer saturation (considered to index structural integrity) within these regions in 40 individuals.
We found decreased volume and reduced magnetization transfer within the substantia nigra in Parkinson's disease patients compared to healthy controls. Importantly, there was a positive correlation between tremulous motor phenotype and transverse relaxation rate (reflecting iron load) within the putamen, caudate and thalamus.
Our findings suggest that akinetic rigid and tremor dominant symptoms of Parkinson's disease might be differentiated on the basis of the transverse relaxation rate within specific basal ganglia structures. Moreover, they suggest that iron load within the basal ganglia makes an important contribution to motor phenotype, a key prognostic indicator of disease progression in Parkinson's disease.
Parkinsonism & Related Disorders 08/2013; · 4.13 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: In patients with chronic spinal cord injury, imaging of the spinal cord and brain above the level of the lesion provides evidence of neural degeneration; however, the spatial and temporal patterns of progression and their relation to clinical outcomes are uncertain. New interventions targeting acute spinal cord injury have entered clinical trials but neuroimaging outcomes as responsive markers of treatment have yet to be established. We aimed to use MRI to assess neuronal degeneration above the level of the lesion after acute spinal cord injury.
In our prospective longitudinal study, we enrolled patients with acute traumatic spinal cord injury and healthy controls. We assessed patients clinically and by MRI at baseline, 2 months, 6 months, and 12 months, and controls by MRI at the same timepoints. We assessed atrophy in white matter in the cranial corticospinal tracts and grey matter in sensorimotor cortices by tensor-based analyses of T1-weighted MRI data. We used cross-sectional spinal cord area measurements to assess atrophy at cervical level C2/C3. We used myelin-sensitive magnetisation transfer (MT) and longitudinal relaxation rate (R1) maps to assess microstructural changes associated with myelin. We also assessed associations between MRI parameters and clinical improvement. All analyses of brain scans done with statistical parametric mapping were corrected for family-wise error.
Between Sept 17, 2010, and Dec 31, 2012, we recruited 13 patients and 18 controls. In the 12 months from baseline, patients recovered by a mean of 5·27 points per log month (95% CI 1·91-8·63) on the international standards for the neurological classification of spinal cord injury (ISNCSCI) motor score (p=0·002) and by 10·93 points per log month (6·20-15·66) on the spinal cord independence measure (SCIM) score (p<0·0001). Compared with controls, patients showed a rapid decline in cross-sectional spinal cord area (patients declined by 0·46 mm per month compared with a stable cord area in controls; p<0·0001). Patients had faster rates than controls of volume decline of white matter in the cranial corticospinal tracts at the level of the internal capsule (right Z score 5·21, p=0·0081; left Z score 4·12, p=0·0004) and right cerebral peduncle (Z score 3·89, p=0·0302) and of grey matter in the left primary motor cortex (Z score 4·23, p=0·041). Volume changes were paralleled by significant reductions of MT and R1 in the same areas and beyond. Improvements in SCIM scores at 12 months were associated with a reduced loss in cross-sectional spinal cord area over 12 months (Pearson's correlation 0·77, p=0·004) and reduced white matter volume of the corticospinal tracts at the level of the right internal capsule (Z score 4·30, p=0·0021), the left internal capsule (Z score 4·27, p=0·0278), and left cerebral peduncle (Z score 4·05, p=0·0316). Improvements in ISNCSCI motor scores were associated with less white matter volume change encompassing the corticospinal tract at the level of the right internal capsule (Z score 4·01, p<0·0001).
Extensive upstream atrophic and microstructural changes of corticospinal axons and sensorimotor cortical areas occur in the first months after spinal cord injury, with faster degenerative changes relating to poorer recovery. Structural volumetric and microstructural MRI protocols remote from the site of spinal cord injury could serve as neuroimaging biomarkers in acute spinal cord injury.
SRH Holding, Swiss National Science Foundation, Clinical Research Priority Program "NeuroRehab" University of Zurich, Wellcome Trust.
The Lancet Neurology 07/2013; · 21.82 Impact Factor