MWF of the corpus callosum is a robust measure of remyelination: Results from the ReBUILD trial.

Myelin repair is an unrealized therapeutic goal in the treatment of multiple sclerosis (MS). Uncertainty remains about the optimal techniques for assessing therapeutic efficacy and imaging biomarkers are required to measure and corroborate myelin restoration. We analyzed myelin water fraction imaging from ReBUILD, a double-blind, randomized placebo-controlled (delayed treatment) remyelination trial, that showed a significant reduction in VEP latency in patients with MS. We focused on brain regions rich in myelin. Fifty MS subjects in two arms underwent 3T MRI at baseline and months 3 and 5. Half of the cohort was randomly assigned to receive treatment from baseline through 3 mo, whereas the other half received treatment from 3 mo to 5 mo post-baseline. We computed myelin water fraction changes occurring in normal-appearing white matter of corpus callosum, optic radiations, and corticospinal tracts. An increase in myelin water fraction was documented in the normal-appearing white matter of the corpus callosum, in correspondence with the administration of the remyelinating treatment clemastine. This study provides direct, biologically validated imaging-based evidence of medically induced myelin repair. Moreover, our work strongly suggests that significant myelin repair occurs outside of lesions. We therefore propose myelin water fraction within the normal-appearing white matter of the corpus callosum as a biomarker for clinical trials looking at remyelination.

Origin of orientation-dependent R1 (=1/T1 ) relaxation in white matter.

PURPOSE: In a recent MRI study, it was shown that the longitudinal relaxation rate, R1 , in white matter (WM) is influenced by the relative orientation of nerve fibers with respect to the main magnetic field (B0 ). Even though the exact nature of this R1 orientation dependency is still unclear, it can be assumed that the origin of the phenomenon can be attributed to the anisotropic and unique molecular environment within the myelin sheath surrounding the axons. The current work investigates the contribution of dipolar induced R1 relaxation of the myelin associated hydrogen nuclei theoretically and compares the results with the experimentally observed R1 orientation dependency. METHODS: Atomistic molecular dynamics simulations were employed and the R1 relaxation rate of hydrogen nuclei of a myelin-alike molecular environment was calculated for various orientations of the trajectory sets relative to the B0 -field. Based on the calculated relaxation rates, the observable R1 relaxation was simulated for various fiber orientations and fitted to the experimental data using a suitable signal weighting-scheme. RESULTS: The results obtained show that the R1 relaxation rate of both solid myelin (SM) and myelin water (MW) depends on the fiber orientation relative to the main B0 -field. Moreover, employing a realistic signal weighing scheme and tissue characteristics, the theoretically investigated R1 orientation dependency matches the experimental data well. CONCLUSION: The good agreement between theoretical and experimental findings indicates that the R1 orientation dependency in WM mainly originates from anisotropic dipole-dipole interactions between hydrogen nuclei located within the myelin sheath.

Dipolar induced spin-lattice relaxation in the myelin sheath: A molecular dynamics study.

Interactions between hydrogen protons of water molecules and macromolecules within the myelin sheath surrounding the axons are a major factor influencing the magnetic resonance (MR) contrast in white matter (WM) regions. In past decades, several studies have investigated the underlying effects and reported a wide range of R1 rates for the myelin associated compartments at different field strengths. However, it was also shown that the experimental quantification of the compartment-specific R1 rates is associated with large uncertainties. The current study therefore investigates the longitudinal relaxation rates within the myelin sheath using a molecular dynamic (MD) simulation. For this purpose, a realistic molecular model of the myelin sheath was employed to determine the dipole-dipole induced R1 relaxation rate of the hydrogen protons at clinically relevant field strengths. The results obtained clearly reflect the spatial heterogeneity of R1 with a increased relaxivity of myelin water due to a reduced molecular mobility near the membrane surface. Moreover, the calculated R1 rates for both myelin water and macromolecules are in excellent agreement with experimental findings from the literature at different field strengths.

Multivariate Platelet Analysis Differentiates Between Patients with Alzheimer's Disease and Healthy Controls at First Clinical Diagnosis.

BACKGROUND: Early diagnosis of Alzheimer's disease (AD) is challenging, and easily accessible biomarkers are an unmet need. Blood platelets frequently serve as peripheral model for studying AD pathogenesis and might represent a reasonable biomarker source. OBJECTIVE: In the present study, we investigated the potential to differentiate AD patients from healthy controls (HC) based on blood count, platelet morphology, and function as well as molecular markers at the time of first clinical diagnosis. METHODS: Blood samples from 40 AD patients and 29 age-matched HC were included for determination of 78 parameter by blood counting, platelet morphometry, aggregometry, flow cytometry (CD62P, CD63, activated fibrinogen receptor), protein quantification of nicotinic acetylcholine receptor α7 (nAChRα7) and caveolin-1 (CAV-1), and miRNA quantification (miR-26b, miR-199a, miR-335). Group comparison between patients and controls was performed in univariate and multivariate statistical analyses. RESULTS: AD patients showed significantly lower aggregation response to ADP and arachidonic acid and significantly decreased CD62P and CD63 surface expression induced by ADP and U46619 compared to HC. Relative nAChRα7 and CAV-1 expression was significantly higher AD platelets than in HC. Multivariate analysis of 63 parameter revealed significant differences between AD patients and healthy controls. The best performing feature model revealed a sensitivity of 96.6%, a specificity of 80.0%, and a positive predictive value of 89.3%. No grouping could be achieved by using single parameter groups. CONCLUSION: Significant differences between platelet characteristics from AD patients and HC at the time of first clinical diagnosis were observed. The best performing parameter can be used as a blood-based biomarker for AD diagnosis in a multivariate model in addition to the standardized mental tests.

Fibre-orientation dependent R1(=1/T1) relaxation in the brain: The role of susceptibility induced spin-lattice relaxation in the myelin water compartment.

We have recently observed a dependence of the longitudinal relaxation rate, R1, on the orientation of nerve fibres with respect to the main magnetic field. A similar dependence of R2∗ is long established and can be well explained by spin-dephasing in an inhomogeneous magnetic field induced by the susceptibility shift between myelin and water protons. The current study investigates if the same effect can also explain the R1 dependence, neglecting a possible directional dependence of magnetisation transfer between solid myelin and myelin water. A molecular model of the myelin lipid bilayer was employed to simulate the susceptibility induced fields on a microscopic scale for the different nerve fibre orientations. The resulting simulated magnetic fields were used to calculate an orientation dependent relaxation offset, ΔR1, based on both first-order perturbation theory and a simulation of the spin transition probabilities. Even though both methods yielded consistent orientation dependent relaxation offsets with a distribution that resembles the experimental data, the determined ΔR1 values are too low to explain the reported R1 angular dependency. Therefore, unlike R2∗, susceptibility induced spin flips can be excluded as a dominant source for the observed R1 angular dependence.

Multivariate prediction of multiple sclerosis using robust quantitative MR-based image metrics.

OBJECTIVES: The current work investigates the performance of different multivariate supervised machine learning models to predict the presence or absence of multiple sclerosis (MS) based on features derived from quantitative MRI acquisitions. The performance of these models was evaluated for images which are significantly degraded due to subject motion, a problem which is often observed in clinical routine diagnostics. Finally, the difference between a true multivariate analysis and the corresponding univariate analysis based on single parameters alone was addressed. MATERIALS AND METHODS: 52 MS patients and 45 healthy controls where scanned on a 3T system. The datasets showed variable degrees of motion-associated artefacts. For each dataset, the average of T1, T2*, total and myelin bound water content was determined in white and grey matter. Based on these parameters, different multivariate models were trained and their cross-validated performance to predict the presence of MS was evaluated. Furthermore, the univariate distributions of each quantitative parameter were employed to define optimised cut-offs that differentiate MS patients from healthy controls. RESULTS: For data not affected by motion, 83.7% of all subjects were correctly classified using a crossvalidated multivariate model. Inclusion of data with significant artefacts reduces the rate of correct classification to 74.5%. T1 in grey and myelin water content in white matter where the most discriminating variables in the multivariate analysis. In contrast, the total water content in white matter and the ratio of white and grey matter total water content each resulted in 77% correct classifications in a univariate regression analysis. CONCLUSION: The results demonstrate that even simple quantitative MRI-based measures allow for an automated prediction of the presence/absence of multiple sclerosis with good specificity. Importantly, even highly degraded datasets due to motion-artefacts could be correctly classified, especially when pooling features derived from grey and white matter. Finally, the advantage of a multivariate over a univariate analysis of quantitative MR data was shown.

The impact of fibre orientation on T1-relaxation and apparent tissue water content in white matter.

OBJECTIVE: Recent MRI studies have shown that the orientation of nerve fibres relative to the main magnetic field affects the R2*(= 1/T2*) relaxation rate in white matter (WM) structures. The underlying physical causes have been discussed in several studies but are still not completely understood. However, understanding these effects in detail is of great importance since this might serve as a basis for the development of new diagnostic tools and/or improve quantitative susceptibility mapping techniques. Therefore, in addition to the known angular dependence of R2*, the current study investigates the relationship between fibre orientation and the longitudinal relaxation rate, R1 (= 1/T1), as well as the apparent water content. MATERIALS AND METHODS: For a group of 16 healthy subjects, a series of gradient echo, echo-planar and diffusion weighted images were acquired at 3T from which the decay rates, the apparent water content and the diffusion direction were reconstructed. The diffusion weighted data were used to determine the angle between the principle fibre direction and the main magnetic field to examine the angular dependence of R1 and apparent water content. RESULTS: The obtained results demonstrate that both parameters depend on the fibre orientation and exhibit a positive correlation with the angle between fibre direction and main magnetic field. CONCLUSION: These observations could be helpful to improve and/or constrain existing biophysical models of brain microstructure by imposing additional constraints resulting from the observed angular dependence R1 and apparent water content in white matter.

Fractal and Euclidean descriptors of platelet shape.

Platelet shape change is a dynamic membrane surface process that exhibits remarkable morphological heterogeneity. Once the outline of an irregular shape is identified and segmented from a digital image, several mathematical descriptors can be applied to numerical characterize the irregularity of the shapes surface. 13072 platelet outlines (PLO) were segmented automatically from 1928 microscopic images using a newly developed algorithm for the software product Matlab R2012b. The fractal dimension (FD), circularity, eccentricity, area and perimeter of each PLO were determined. 972 PLO were randomly assigned for computer-assisted manual measurement of platelet diameter as well as number, width and length of filopodia per platelet. FD can be used as a surrogate parameter for determining the roughness of the PLO and circularity can be used as a surrogate to estimate the number and length of filopodia. The relationship between FD and perimeter of the PLO reveals the existence of distinct groups of platelets with significant structural differences which may be caused by platelet activation. This new method allows for the standardized continuous numerical classification of platelet shape and its dynamic change, which is useful for the analysis of altered platelet activity (e.g. inflammatory diseases, contact activation, drug testing).

Rapid myelin water content mapping on clinical MR systems.

We present an algorithm for the fast mapping of myelin water content using standard multiecho gradient echo acquisitions of the human brain. The method extents a previously published approach for the simultaneous measurement of brain T(1), T(2)(*) and total water content. Employing the multiexponential T(2)(*) decay signal of myelinated tissue, myelin water content was measured based on the quantification of two water pools ("myelin water" and "rest") with different relaxation times. As the existing protocol was focussed on the fast mapping of quantitative MR parameters with whole brain coverage in clinically relevant measurement times, the sampling density of the T(2)(*) curve was compromised to 10 echo times with a TE(max) of approx. 40ms. Therefore, pool amplitudes were determined using a quadratic optimisation approach. The optimisation was constrained by including à priori knowledge about brain water pools. All constraints were optimised in a simulation study to minimise systematic error sources given the incomplete knowledge about the real pool-specific relaxation properties. Based on the simulation results, whole brain in vivo myelin water content maps were acquired in 10 healthy controls and one subject with multiple sclerosis. The in vivo results obtained were consistent with previous reports which demonstrates that a simultaneous whole brain mapping of T(1), T(2)(*), total and myelin water content is feasible on almost any modern MR scanner in less than 10 minutes.

Multicentre absolute myelin water content mapping: Development of a whole brain atlas and application to low-grade multiple sclerosis.

The current study investigates the whole brain myelin water content distribution applying a new approach that allows for the simultaneous mapping of total and relative myelin water content, T 1 and T 2* with full brain coverage and high resolution (1 × 1 × 2 mm(3)). The data was collected at two different sites in healthy controls to validate the independence of a specific setup. In addition, a group of patients with known white matter affections was investigated to compare two measures of myelin, i.e. relative and absolute myelin water content. Based on the first dataset, a quantitative myelin water content atlas was created which served as a control set for the other two datasets. Both control groups measured at different institutions yielded consistent results. However, distinct regions of reduced myelin water content were observed for the patient dataset, both on an individual basis and in a group-wise comparison. The comparison between the absolute and relative measurement of myelin water content in MS patients showed that the relative measurement, which is employed by many researchers, overestimates both disease volume and the corresponding reduction of myelin water content in white matter lesions. However, for normal appearing white matter, no difference between both approaches was detected. The results obtained in the current study demonstrate that absolute myelin water content can reliably be determined in a multicentre environment using standard MR sequences. The optimised protocol allows for a measurement of four quantitative parameters with full brain coverage in only 10 min. This might expedite a more widespread future use of quantitative MRI methods for clinical research and diagnosis.

Fully-automated detection of cerebral water content changes: study of age- and gender-related H2O patterns with quantitative MRI.

We present a simple and robust method for the automated image analysis of quantitative cerebral water content maps acquired with MRI. The method is based on a new approach for the absolute and quantitative mapping of water content in vivo. Water content maps were automatically segmented into grey and white matter by employing the quantitative T1 information acquired as part of the water content mapping procedure. Based on the segmented maps, twenty-two parameters sensitive to both absolute water content and its spatial organisation are automatically extracted without user interaction. The parameters include, amongst others, absolute water content in grey and white matter and spatial asymmetries of the cerebral water content distribution. Significant age- and gender-related changes in the parameters determined were observed in a study of forty-four healthy subjects. Most notably, the grey matter water content decreases at a rate of 0.034%/year for females between the 3rd and 8th decade of life, whilst a much stronger decrease is observed in males which sets in after the 5th decade of life. In addition, female grey matter water content is, on average, 1.2% higher than the respective male grey matter water content. In contrast to the heterogeneity observed in grey matter, no significant physiological variation was observed for white matter water content. In addition to absolute grey matter water content, characteristic age- and gender-specific variations were also observed in most of the other variables. To check the potential loss of information associated with the large reduction of the dimensionality of the dataset to 22 parameters only, the age and gender of each individual subject were predicted by employing robust linear discriminant analysis based on only the determined twenty-two variables. The median deviation between predicted and real age was 6.3 years resulting in a high correlation coefficient between both values (r = 0.69). Gender is correctly predicted in 68.2% of all cases which improves to 87.5% when age-dependent effects are first corrected, demonstrating the high information content present in the variables even though the dimension of the dataset was significantly reduced. These results form the baseline for future studies of cerebral pathology. The method presented is fully automated, robust and flexible, making it an ideal tool for routine application in both neuroscientific studies and clinical diagnosis based on the quantitative measurement of cerebral water content.

Quantitative T1 mapping of hepatic encephalopathy using magnetic resonance imaging.

Changes are shown in the spin-lattice (T1) relaxation time caused by the putative deposition of manganese in various brain regions of hepatic encephalopathy (HE) patients using a novel and fast magnetic resonance imaging (MRI) method for quantitative relaxation time mapping. A new method, T1 mapping with partial inversion recovery (TAPIR), was used to obtain a series of T1-weighted images to produce T1 maps. Imaging of 15 control subjects and 11 patients was performed on a 1.5T MRI scanner. The measurement time per patient with this technique, including adjustments, was approximately 5 minutes. Regions of interest in the globus pallidus, the caudate nucleus, the posterior and anterior limbs of the internal capsule, the putamen, the frontal and occipital white matter, the white matter of the corona radiata, the occipital visual and frontal cortices, and the thalamus were interactively defined in the left hemisphere and analyzed with respect to their T1 values. T1 changes in the brains of HE patients can be determined quantitatively with TAPIR in short, clinically relevant measurement times. Significant correlations between the change in T1 and HE severity have been shown in the globus pallidus, the caudate nucleus, and the posterior limb of the internal capsule. No significant correlation of T1 with grade of HE was found in the putamen, frontal white matter, white matter of the corona radiata, white matter in the occipital lobe, the anterior limb of the internal capsule, visual cortex, thalamus, or frontal cortex. In conclusion, these measurements show that T1 mapping is feasible in short, clinically relevant acquisition times.