Temporal trajectory of brain tissue property changes induced by electroconvulsive therapy.

BACKGROUND: After more than eight decades of electroconvulsive therapy (ECT) for pharmaco-resistant depression, the mechanisms governing its anti-depressant effects remain poorly understood. Computational anatomy studies using longitudinal T1-weighted magnetic resonance imaging (MRI) data have demonstrated ECT effects on hippocampus volume and cortical thickness, but they lack the interpretational specificity about underlying neurobiological processes. METHODS: We sought to fill in the gap of knowledge by acquiring quantitative MRI indicative for brain's myelin, iron and tissue water content at multiple time-points before, during and after ECT treatment. We adapted established tools for longitudinal spatial registration of MRI data to the relaxometry-based multi-parameter maps aiming to preserve the initial total signal amount and introduced a dedicated multivariate analytical framework. RESULTS: The whole-brain voxel-based analysis based on a multivariate general linear model showed that there is no brain tissue oedema contributing to the predicted ECT-induced hippocampus volume increase neither in the short, nor in the long-term observations. Improvements in depression symptom severity over time were associated with changes in both volume estimates and brain tissue properties expanding beyond mesial temporal lobe structures to anterior cingulate cortex, precuneus and striatum. CONCLUSION: The obtained results stemming from multi-contrast MRI quantitative data provided a fingerprint of ECT-induced brain tissue changes over time that are contrasted against the background of established morphometry findings. The introduced data processing and statistical testing algorithms provided a reliable analytical framework for longitudinal multi-parameter brain maps. The results, particularly the evidence of lack of ECT impact on brain tissue water, should be considered preliminary considering the small sample size of the study.

New tissue priors for improved automated classification of subcortical brain structures on MRI.

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 gray-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 gray-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 gray matter regions. Supported by atlas-derived spatial information, raters manually labeled subcortical structures in a cohort of healthy subjects using magnetization transfer saturation and R2* MRI maps, which feature optimal gray-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 gray 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.

Disentangling in vivo the effects of iron content and atrophy on the ageing human brain.

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 21-88 years) 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.

Tissue- and column-specific measurements from multi-parameter mapping of the human cervical spinal cord at 3 T.

The aim of this study was to quantify a range of MR parameters [apparent proton density, longitudinal relaxation time T1, magnetisation transfer (MT) ratio, MT saturation (which represents the additional percentage MT saturation of the longitudinal magnetisation caused by a single MT pulse) and apparent transverse relaxation rate R2*] in the white matter columns and grey matter of the healthy cervical spinal cord. The cervical cords of 13 healthy volunteers were scanned at 3 T using a protocol optimised for multi-parameter mapping. Intra-subject co-registration was performed using linear registration, and tissue- and column-specific parameter values were calculated. Cervical cord parameter values measured from levels C1-C5 in 13 subjects are: apparent proton density, 4822 ± 718 a.u.; MT ratio, 40.4 ± 1.53 p.u.; MT saturation, 1.40 ± 0.12 p.u.; T1 = 1848 ± 143 ms; R2* = 22.6 ± 1.53 s(-1). Inter-subject coefficients of variation were low in both the cervical cord and tissue- and column-specific measurements, illustrating the potential of this method for the investigation of changes in these parameters caused by pathology. In summary, an optimised cervical cord multi-parameter mapping protocol was developed, enabling tissue- and column-specific measurements to be made. This technique has the potential to provide insight into the pathological processes occurring in the cervical cord affected by neurological disorders.

Measurement of diffusion in the presence of shear flow.

We demonstrate here a method whereby molecular diffusion coefficients may be measured in the presence of the deformational flow field of a rheo-NMR cell. The method, which uses a repetitive CPMG train of rf pulses interspersed with magnetic field gradient pulses, allows the anisotropic diffusion spectrum to be directly probed. We focus on the cylindrical Couette cell, for which the radial, tangential, and axial directions correspond to the hydrodynamic velocity gradient, velocity, and vorticity directions. While ideal Couette flow does not perturb the vorticity direction, it does perturb diffusion measurements for the velocity gradient direction, and to a lesser extent, the velocity direction. We show that with closely spaced gradient pulses operating in a flow-compensating mode, there exists a diffusion limit below which one cannot measure, that scales as T(2)gamma(4), where gamma is the shear rate and T the gradient pulse repetition period. For a typical rheo-NMR cell, and for the more challenging velocity gradient direction, diffusion rates above 10(-12) m(2) s(-1) can be accurately measured (to 1% error) at shear rates up to 3s(-1). We demonstrate the use of the method in measuring the diffusion spectrum of a lyotropic lamellar phase under shear.

Undulations and fluctuations in a lamellar phase lyotropic liquid crystal and their suppression by weak shear flow.

Using multi-echo pulsed gradient nuclear magnetic resonance (NMR) we measure the anisotropic diffusion of water molecules in the lamellar phase of lyotropic system composed of cetylpyridinium chloride/hexanol diluted in brine. The technique reveals the Fourier spectrum of the molecular velocity autocorrelation function, and its repetitive compensating nature permits effective measurement in the presence of shear flow. We show that under zero shear the phase is highly oriented and that both the amplitude and fluctuation correlation time of lamellar undulations can be measured. The suppression of undulations by weak shear is apparent. We further measure transverse lamellae permeability arising from defects.

Effect of shear on an onion texture.

Lamellar systems are self-assemblies of surfactant molecules forming planar bilayers separated by layers of solvent. At sufficiently high shear rates, they are known to form spherical objects often referred to as onions. In this paper, we are concerned with the effect of shear on those multi-lamellar vesicles. We measure solvent diffusion by nuclear magnetic resonance (NMR) using a method which is sensitive to the time dependence of mean-squared displacements. This method, combined with NMR velocimetry, allows us to infer onion structure as a function of shear rate, identifying different regimes in which local viscosity is related to the onion size. The role of slip is examined and the stress dependence of wall slip velocities is determined.