Multi-parametric quantification of white matter microstructure in the human brain

To date the majority of MRI studies of white matter (WM) microstructure have used diffusion tensor MRI (DT-MRI), comparing groups on a voxel-by-voxel basis. There are limitations to this approach. Firstly, the analysis approach treats each voxel independently, ignoring the fact that adjacent voxels may come from the same tract (or may come from completely separate tracts). Secondly, DT-MRI is sensitive to both interesting properties of WM (e.g., myelination, axon density), and less interesting properties (e.g., intra-voxel orientational dispersion). In contrast, other imaging approaches, based on different contrast mechanisms, can provide increased specificity and therefore sensitivity to differences in one particular attribute of tissue microstructure (e.g., myelin content or axonal density). Both quantitative magnetization transfer (qMT) imaging and multicomponent relaxometry provide proxy estimates of myelin content while the combined hindered and restricted model of diffusion (CHARMED) provides a proxy estimate of axon density. We present a novel imaging method called tractometry, which permits simultaneous quantitative assessment of these different microstructural attributes along specific pathways.Crucially, the metrics were only weakly correlated, suggesting that tractometry provides complementary WM microstructural information to DT-MRI. In developing the tractometry pipeline, we also performed a detailed examination of the qMT pipeline, identifying and reducing sources of variance to provide optimized results. We also identify a number of issues with the current state-of-the art, including the stability of tract based spatial statistics (TBSS). We show that conducting a structure-function correlation TBSS study may lead to vastly different conclusions, based simply on the participants recruited into the study. We also address microstructural asymmetry, including the degree of partial-volume effects (PVEs) from free water, which impact on WM metrics. The observed spatial heterogeneity of PVEs can potentially confound interpretation in studies where contralateral hemispheres are used as internal controls, and could either exacerbate or possibly negate tissue difference

Improving the reliability of network metrics in structural brain networks by integrating different network weighting strategies into a single graph

Structural brain networks estimated from diffusion MRI (dMRI) via tractography have been widely studied in healthy controls and in patients with neurological and psychiatric diseases. However, few studies have addressed the reliability of derived network metrics both node-specific and network-wide. Different network weighting strategies (NWS) can be adopted to weight the strength of connection between two nodes yielding structural brain networks that are almost full-weighted. Here, we scanned 5 healthy participants 5 times each, using a diffusion-weighted MRI protocol and computed edges between 90 regions of interest (ROIs) from the AAL template. The edges were weighted according to nine different methods.We propose a linear combination of these nine NWS into a single graph using an appropriate diffusion distance metric. We refer to the resulting weighted graph as an integrated weighted structural brain network (ISWBN). Additionally, we consider a topological filtering scheme that maximizes the information flow in the brain network under the constraint of the overall cost of the surviving connections. We compared each of the nine NWS and the ISWBN based on the improvement of : a) intra-class correlation coefficient (ICC) of well-known network metrics, both node-wise and per network level; and b) the recognition accuracy of each subject over the rest of the cohort, as an attempt to access the uniqueness of the structural brain network for each subject; after first applying our proposed topological filtering scheme. Based on a threshold that the network-level ICC should be > 0.90, our findings revealed six out of nine NWS lead to unreliable results at the network-level, while all nine NWS were unreliable at the node-level. In comparison, our proposed ISWBN performed as well as the best-performing individual NWS at the network-level, and the ICC was higher compared to all individual NWS at the node-level. Importantly, both network- and node-wise ICCs of network metrics derived from the topologically filtered ISBWN(ISWBNTF), were further improved compared to non-filtered ISWBN. Finally, in the recognition accuracy tests, we assigned each single ISWBNTF to the correct subject. Overall, these findings suggest that the proposed methodology results in improved characterisation of genuine between-subject differences in connectivit

Why diffusion tensor MRI does well only some of the time: Variance and covariance of white matter tissue microstructure attributes in the living human brain

Fundamental to increasing our understanding of the role of white matter microstructure in normal/abnormal function in the living human is the development of MR-based metrics that provide increased specificity to distinct attributes of the white matter (e.g., local fibre architecture, axon morphology, and myelin content). In recent years, different approaches have been developed to enhance this specificity, and the Tractometry framework was introduced to combine the resulting multi-parametric data for a comprehensive assessment of white matter properties. The present work exploits that framework to characterise the statistical properties, specifically the variance and covariance, of these advanced microstructural indices across the major white matter pathways, with the aim of giving clear indications on the preferred metric(s) given the specific research question. A cohort of healthy subjects was scanned with a protocol that combined multi-component relaxometry with conventional and advanced diffusion MRI acquisitions to build the first comprehensive MRI atlas of white matter microstructure. The mean and standard deviation of the different metrics were analysed in order to understand how they vary across different brain regions/individuals and the correlation between them. Characterising the fibre architectural complexity (in terms of number of fibre populations in a voxel) provides clear insights into correlation/lack of correlation between the different metrics and explains why DT-MRI is a good model for white matter only some of the time. The study also identifies the metrics that account for the largest inter-subject variability and reports the minimal sample size required to detect differences in means, showing that, on the other hand, conventional DT-MRI indices might still be the safest choice in many contexts

Myelination of the right parahippocampal cingulum is associated with physical activity in young healthy adults

Recent evidence suggests that individual differences in physical activity (PA) may be associated with individual differences in white matter microstructure and with grey matter volume of the hippocampus. Therefore, this study investigated the association between PA and white matter microstructure of pathways connecting to the hippocampus. A total of 33 young, healthy adults underwent magnetic resonance imaging (MRI). High angular resolution diffusion-weighted imaging and multi-component relaxometry MRI scans (multi-component driven equilibrium pulse observation of T1 and T2) were acquired for each participant. Activity levels (AL) of participants were calculated from 72-h actigraphy recordings. Tractography using the damped Richardson Lucy algorithm was used to reconstruct the fornix and bilateral parahippocampal cinguli (PHC). The mean fractional anisotropy (FA) and the myelin water fraction (MWF), a putative marker of myelination, were determined for each pathway. A positive correlation between both AL and FA and between AL and MWF were hypothesized for the three pathways. There was a selective positive correlation between AL and MWF in the right PHC (r = 0.482, p = 0.007). Thus, our results provide initial in vivo evidence for an association between myelination of the right PHC and PA in young healthy adults. Our results suggest that MWF may not only be more specific, but also more sensitive than FA to detect white matter microstructural alterations. If PA was to induce structural plasticity of the right PHC this may contribute to reverse structural alterations of the right PHC in neuropsychiatric disorder with hippocampal pathologies

Drumming motor sequence training induces apparent myelin remodelling in Huntington’s disease: a longitudinal diffusion MRI and quantitative magnetization transfer study

Background:Impaired myelination may contribute to Huntington’s disease (HD) pathogenesis. Objective:This study assessed differences in white matter (WM) microstructure between HD patients and controls, and tested whether drumming training stimulates WM remodelling in HD. Furthermore, it examined whether training-induced microstructural changes are related to improvements in motor and cognitive function. Methods:Participants undertook two months of drumming exercises. Working memory and executive function were assessed before and post-training. Changes in WM microstructure were investigated with diffusion tensor magnetic resonance imaging (DT-MRI)-based metrics, the restricted diffusion signal fraction (Fr) from the composite hindered and restricted model of diffusion (CHARMED) and the macromolecular proton fraction (MPF) from quantitative magnetization transfer (qMT) imaging. WM pathways linking putamen and supplementary motor areas (SMA-Putamen), and three segments of the corpus callosum (CCI, CCII, CCIII) were studied using deterministic tractography. Baseline MPF differences between patients and controls were assessed with tract-based spatial statistics. Results:MPF was reduced in the mid-section of the CC in HD subjects at baseline, while a significantly greater change in MPF was detected in HD patients relative to controls in the CCII, CCIII, and the right SMA-putamen post-training. Further, although patients improved their drumming and executive function performance, such improvements did not correlate with microstructural changes. Increased MPF suggests training-induced myelin changes in HD. Conclusion:Though only preliminary and based on a small sample size, these results suggest that tailored behavioural stimulation may lead to neural benefits in early HD, that could be exploited for delaying disease progression

Attenuation of brain BOLD response following lipid ingestion

A great deal of heterogeneity exists in fMRI data. Even within the same subject, results on successive days or scan sessions often differ in the number of significantly activated pixels and/or the intensity of activation. We sought to assess whether controllable physiologic modulators, such as dietary factors, could influence the outcome of fMRI data. A high fat diet, for example, prior to a fMRI scan could change microvascular blood rheologic factors and potentially alter brain blood oxygen-level dependent (BOLD) signal patterns. In healthy adult volunteers, we measured brain BOLD signal during bilateral finger tapping (2 Hz) in the fasted state, and at 40 and 100 minutes post-ingestion of a 235 mL can of Ensure Plus (Ross Labs), alone or supplemented with either 25cc or 50cc of canola oil. Both the 25cc and 50cc Canola oil treatments produced a significant bilateral decrease in BOLD signal 40 and 100 minutes postprandial. No significant effect was observed with Ensure in the absence of oil. Therefore, to decrease fMRI within and between subject heterogeneity, and thereby increase fMRI statistical power, it is suggested that scanning within 2 hours post high fat ingestion should be avoided. As a corollary, a thorough understanding of a subject's physiological state, prior to an fMRI exam, may reduce the impact of other confounding variables. Hum. Brain Mapp. 20:116–121, 2003

Self-paced movements induce high-frequency gamma oscillations in primary motor cortex

There has been increasing interest in the functional role of high-frequency (> 30 Hz) cortical oscillations accompanying various sensorimotor and cognitive tasks in humans. Similar “high gamma” activity has been observed in the motor cortex, although the role of this activity in motor control is unknown. Using whole-head MEG recordings combined with advanced source localization methods, we identified high-frequency (65 to 80 Hz) gamma oscillations in the primary motor cortex during self-paced movements of the upper and lower limbs. Brief bursts of gamma activity were localized to the contralateral precentral gyrus (MI) during self-paced index finger abductions, elbow flexions and foot dorsiflexions. In comparison to lower frequency (10–30 Hz) sensorimotor rhythms that are bilaterally suppressed prior to and during movement (Jurkiewicz et al., 2006), high gamma activity increased only during movement, reaching maximal increase 100 to 250 ms following EMG onset, and was lateralized to contralateral MI, similar to findings from intracranial EEG studies. Peak frequency of gamma activity was significantly lower during foot dorsiflexion (67.4 ± 5.2 Hz) than during finger abduction (75.3 ± 4.4 Hz) and elbow flexion (73.9 ± 3.7 Hz) although markedly similar for left and right movements of the same body part within subjects, suggesting activation of a common underlying network for gamma oscillations in the left and right motor cortex. These findings demonstrate that voluntary movements elicit high-frequency gamma oscillations in the primary motor cortex that are effector specific, and possibly reflect the activation of cortico-subcortical networks involved in the feedback control of discrete movements

How and how not to correct for CSF-contamination in diffusion MRI

Diffusion MRI is used extensively to investigate changes in white matter microstructure related to brain development and pathology. Ageing, however, is also associated with significant white and grey matter loss which in turn can lead to cerebrospinal fluid (CSF) based partial volume artefacts in diffusion MRI metrics. This is especially problematic in regions prone to CSF contamination, such as the fornix and the genu of corpus callosum, structures that pass through or close to the ventricles respectively. The aim of this study was to model the effects of CSF contamination on diffusion MRI metrics, and to evaluate different post-acquisition strategies to correct for CSF-contamination: Controlling for whole brain volume and correcting on a voxel-wise basis using the Free Water Elimination (FWE) approach. Using the fornix as an exemplar of a structure prone to CSF-contamination, corrections were applied to tract-specific and voxel-based [tract based spatial statistics (TBSS)] analyses of empirical DT-MRI data from 39 older adults (53–93 years of age). In addition to significant age-related decreases in whole brain volume and fornix tissue volume fraction, age was also associated with a reduction in mean fractional anisotropy and increase in diffusivity metrics in the fornix. The experimental data agreed with the simulations in that diffusivity metrics (mean diffusivity, axial and radial diffusivity) were more prone to partial volume CSF-contamination errors than fractional anisotropy. After FWE-based voxel-by-voxel partial volume corrections, the significant positive correlations between age and diffusivity metrics, in particular with axial diffusivity, disappeared whereas the correlation with anisotropy remained. In contrast, correcting for whole brain volume had little effect in removing these spurious correlations. Our study highlights the importance of correcting for CSF-contamination partial volume effects in the structures of interest on a voxel-by-voxel basis prior to drawing inferences about underlying changes in white matter structures and have implications for the interpretation of many recent diffusion MRI results in ageing and disease