Correction of FLASH-based MT saturation in human brain for residual bias of B1-inhomogeneity at 3T

Background: Magnetization transfer (MT) saturation reflects the additional saturation of the MRI signal imposed by an MT pulse and is largely driven by the saturation of the bound pool. This reduction of the bound polarization by the MT pulse is less efficient than predicted by the differential B1-square law of absorption. Thus, B1 inhomogeneities lead to a residual bias in the MT saturation maps. We derive a heuristic correction to reduce this bias for a widely used multi-parameter mapping protocol at 3T. Methods: The amplitude of the MT pulse was varied via the nominal flip angle to mimic variations in B1. The MT saturation's dependence on the actual flip angle features a linear correction term, which was determined separately for gray and white matter. Results: The deviation of MT saturation from differential B1-square law is well described by a linear decrease with the actual flip angle of the MT pulse. This decrease showed no significant differences between gray and white matter. Thus, the post hoc correction does not need to take different tissue types into account. Bias-corrected MT saturation maps appeared more symmetric and highlighted highly myelinated tracts. Discussion:Our correction involves a calibration that is specific for the MT pulse. While it can also be used to rescale nominal flip angles, different MT pulses and/or protocols will require individual calibration. Conclusion: The suggested B1 correction of the MT maps can be applied post hoc using an independently acquired flip angle map

Asymmetric representation of aversive prediction errors in Pavlovian threat conditioning

Learning to predict threat is important for survival. Such learning may be driven by differences between expected and encountered outcomes, termed prediction errors (PEs). While PEs are crucial for reward learning, the role of putative PE signals in aversive learning is less clear. Here, we used functional magnetic resonance imaging in humans to investigate neural PE signals. Four cues, each with a different probability of being followed by an aversive outcome, were presented multiple times. We found that neural activity only at omission - but not at occurrence - of predicted threat related to PEs in the medial prefrontal cortex. More expected omission was associated with higher neural activity. In no brain region did neural activity fulfill necessary computational criteria for full signed PE representation. Our result suggests that, different from reward learning, aversive learning may not be primarily driven by PE signals in one single brain region

Mapping the human cortical surface by combining quantitative T(1) with retinotopy

We combined quantitative relaxation rate (R1= 1/T1) mapping-to measure local myelination-with fMRI-based retinotopy. Gray-white and pial surfaces were reconstructed and used to sample R1 at different cortical depths. Like myelination, R1 decreased from deeper to superficial layers. R1 decreased passing from V1 and MT, to immediately surrounding areas, then to the angular gyrus. High R1 was correlated across the cortex with convex local curvature so the data was first "de-curved". By overlaying R1 and retinotopic maps, we found that many visual area borders were associated with significant R1 increases including V1, V3A, MT, V6, V6A, V8/VO1, FST, and VIP. Surprisingly, retinotopic MT occupied only the posterior portion of an oval-shaped lateral occipital R1 maximum. R1 maps were reproducible within individuals and comparable between subjects without intensity normalization, enabling multi-center studies of development, aging, and disease progression, and structure/function mapping in other modalities

Quantitative Magnetization Transfer in In Vivo Healthy Human Skeletal Muscle at 3 T

The value of quantitative MR methods as potential biomarkers in neuromuscular disease is being increasingly recognized. Previous studies of the magnetization transfer ratio have demonstrated sensitivity to muscle disease. The aim of this work was to investigate quantitative magnetization transfer imaging of skeletal muscle in healthy subjects at 3 T to evaluate its potential use in pathological muscle. The lower limb of 10 subjects was imaged using a 3D fast low-angle shot acquisition with variable magnetization transfer saturation pulse frequencies and amplitudes. The data were analyzed with an established quantitative two-pool model of magnetization transfer. T1 and B1 amplitude of excitation radiofrequency field maps were acquired and used as inputs to the quantitative magnetization transfer model, allowing properties of the free and restricted proton pools in muscle to be evaluated in seven different muscles in a region of interest analysis. The average restricted pool T2 relaxation time was found to be 5.9 ± 0.2μs in the soleus muscle and the restricted proton pool fraction was 8 ± 1%. Quantitative magnetization transfer imaging of muscle offers potential new biomarkers in muscle disease within a clinically feasible scan time. Magn Reson Med, 2010. © 2010 Wiley-Liss, Inc

Estimating the apparent transverse relaxation time (R2*) from images with different contrasts (ESTATICS) reduces motion artifacts

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

Dopaminergic modulation of cortical motor network lateralization

Introduction Unilateral movements are primarily processed in contralateral cortical and subcortical areas and additionally in ipsilateral cerebellum, leading to an asymmetric pattern of neural activation. Decrease of lateralization is characteristic of aging (Naccarato et al., 2006; Wu et al., 2005), and disease, for example, in unilateral brain lesions or stroke (Carr et al., 1993; Rehme et al., 2011) and Parkinson's disease (PD; Wu et al., 2015). The explanation for imbalanced lateralization in drug-naive PD is an adaptive compensation, compatible with the finding that PD-associated deficient input from cortico-subcortical circuits is compensated by reduced cortical inhibition and increased cortical facilitation (Blesa et al., 2017). Here, we investigated the effect of dopamine depletion and substitution on cortical motor lateralization, with the hypothesis that lateralization decreases in advanced PD and that administration of levodopa, at least to a certain extent, reinstates lateralization. Methods We used fMRI to study motor activation in advanced PD patients and in healthy controls (HC) during unilateral upper and lower limb movements. Ten right-handed, left side symptom-dominant PD patients were tested in pseudo-randomized order after intake of their usual dopaminergic medication – 'ON' state – and after withdrawal of medication – 'OFF' state. Eighteen right-handed age-matched HC participated in a single session. We quantified activation lateralization using the average laterality index (AveLI; Matsuo et al., 2012) in three cortical motor regions of interest (ROIs): primary motor cortex (M1), supplementary motor area (SMA) and premotor cortex (PMC), during the four movement conditions. We compared AveLI between group pairs (PD OFF vs. HC, PD ON vs. HC, PD OFF vs. PD ON) within each ROI and movement condition. We estimated the effective connectivity between ROIs using bilinear dynamic causal modeling (DCM; Friston et al., 2003) and developed a measure to quantify the lateralization of the resulting connectivity networks to compare between groups. By constructing a group level parametric empirical Bayes (PEB) model (Friston et al., 2016) over all the subjects and conducting a search over nested models, we compared DCM parameter estimates between groups, thus providing the potential link between changes in motor lateralization and connectivity. Results In line with our predictions, motor activation lateralization as estimated with the AveLI showed a trend towards decrease in the PD OFF group compared to HC, in all three ROIs during left hand movement and in M1 during left foot movement (Fig. 1). Between-group differences were observed solely in conditions corresponding to movement of the more affected body side. Contrary to our hypothesis, dopamine substitution did not reinstate lateralization – in fact, AveLI in the PD ON group closely resembled that of the PD OFF group. Connectivity lateralization of input-specific modulation (DCM.B) networks was significantly lower in all conditions in the PD group as compared to HC. While on the body side more affected by PD, differences were found for both PD OFF and PD ON, input-specific modulation related to the less affected side was more altered in PD ON. PEB analysis revealed qualitatively more between-group differences in input-specific modulation on the more affected PD side and included many interhemispheric connections (Fig. 2). Conclusions Decreased lateralization is not only present in drug-naïve PD patients (Wu et al., 2015) but also in dopa-treated patients. Acute dopamine modulation does not alter lateralization. Decreased lateralization is evident in both fMRI activation amplitudes (as estimated with AveLI) and effective connectivity (as demonstrated through the DCM analysis)

hMRI - A toolbox for quantitative MRI in neuroscience and clinical research

Neuroscience and clinical researchers are increasingly interested in quantitative magnetic resonance imaging (qMRI) due to its sensitivity to micro-structural properties of brain tissue such as axon, myelin, iron and water concentration. We introduce the hMRI-toolbox, an open-source, easy-to-use tool available on GitHub, for qMRI data handling and processing, presented together with a tutorial and example dataset. This toolbox allows the estimation of high-quality multi-parameter qMRI maps (longitudinal and effective transverse relaxation rates and , proton density and magnetisation transfer saturation) that can be used for quantitative parameter analysis and accurate delineation of subcortical brain structures. The qMRI maps generated by the toolbox are key input parameters for biophysical models designed to estimate tissue microstructure properties such as the MR g-ratio and to derive standard and novel MRI biomarkers. Thus, the current version of the toolbox is a first step towards in vivo histology using MRI (hMRI) and is being extended further in this direction. Embedded in the Statistical Parametric Mapping (SPM) framework, it benefits from the extensive range of established SPM tools for high-accuracy spatial registration and statistical inferences and can be readily combined with existing SPM toolboxes for estimating diffusion MRI parameter maps. From a user's perspective, the hMRI-toolbox is an efficient, robust and simple framework for investigating qMRI data in neuroscience and clinical research

Restoring statistical validity in group analyses of motion-corrupted MRI data

Motion during the acquisition of magnetic resonance imaging (MRI) data degrades image quality, hindering our capacity to characterise disease in patient populations. Quality control procedures allow the exclusion of the most affected images from analysis. However, the criterion for exclusion is difficult to determine objectively and exclusion can lead to a suboptimal compromise between image quality and sample size. We provide an alternative, data-driven solution that assigns weights to each image, computed from an index of image quality using restricted maximum likelihood. We illustrate this method through the analysis of quantitative MRI data. The proposed method restores the validity of statistical tests, and performs near optimally in all brain regions, despite local effects of head motion. This method is amenable to the analysis of a broad type of MRI data and can accommodate any measure of image quality

Quantitative MRI provides markers of intra-, inter-regional, and age-related differences in young adult cortical microstructure

Measuring the structural composition of the cortex is critical to understanding typical development, yet few investigations in humans have charted markers in vivo that are sensitive to tissue microstructural attributes. Here, we used a well-validated quantitative MR protocol to measure four parameters (R1, MT, R2*, PD*) that differ in their sensitivity to facets of the tissue microstructural environment (R1, MT: myelin, macromolecular content; R2*: myelin, paramagnetic ions, i.e., iron; PD*: free water content). Mapping these parameters across cortical regions in a young adult cohort (18–39 years, N = 93) revealed expected patterns of increased macromolecular content as well as reduced tissue water content in primary and primary adjacent cortical regions. Mapping across cortical depth within regions showed decreased expression of myelin and related processes – but increased tissue water content – when progressing from the grey/white to the grey/pial boundary, in all regions. Charting developmental change in cortical microstructure cross-sectionally, we found that parameters with sensitivity to tissue myelin (R1 & MT) showed linear increases with age across frontal and parietal cortex (change 0.5–1.0% per year). Overlap of robust age effects for both parameters emerged in left inferior frontal, right parietal and bilateral pre-central regions. Our findings afford an improved understanding of ontogeny in early adulthood and offer normative quantitative MR data for inter- and intra-cortical composition, which may be used as benchmarks in further studies