Multi-Parametric Representation of Voxel-Based Quantitative Magnetic Resonance Imaging

The aim of the study was to explore the possibilities of multi-parametric representations of voxel-wise quantitative MRI data to objectively discriminate pathological cerebral tissue in patients with brain disorders. For this purpose, we recruited 19 patients with Multiple Sclerosis (MS) as benchmark samples and 19 age and gender matched healthy subjects as a reference group. The subjects were examined using quantitative Magnetic Resonance Imaging (MRI) measuring the tissue structure parameters: relaxation rates, R and R, and proton density. The resulting parameter images were normalized to a standard template. Tissue structure in MS patients was assessed by voxel-wise comparisons with the reference group and with correlation to a clinical measure, the Expanded Disability Status Scale (EDSS). The results were visualized by conventional geometric representations and also by multi-parametric representations. Data showed that MS patients had lower R and R, and higher proton density in periventricular white matter and in wide-spread areas encompassing central and sub-cortical white matter structures. MS-related tissue abnormality was highlighted in posterior white matter whereas EDSS correlation appeared especially in the frontal cortex. The multi-parameter representation highlighted disease-specific features. In conclusion, the proposed method has the potential to visualize both high-probability focal anomalies and diffuse tissue changes. Results from voxel-based statistical analysis, as exemplified in the present work, may guide radiologists where in the image to inspect for signs of disease. Future clinical studies must validate the usability of the method in clinical practice.     

Brain Characterization Using Normalized Quantitative Magnetic Resonance Imaging

Objectives

To present a method for generating reference maps of typical brain characteristics of groups of subjects using a novel combination of rapid quantitative Magnetic Resonance Imaging (qMRI) and brain normalization. The reference maps can be used to detect significant tissue differences in patients, both locally and globally.

Materials and Methods

A rapid qMRI method was used to obtain the longitudinal relaxation rate (R₁), the transverse relaxation rate (R₂) and the proton density (PD). These three tissue properties were measured in the brains of 32 healthy subjects and in one patient diagnosed with Multiple Sclerosis (MS). The maps were normalized to a standard brain template using a linear affine registration. The differences of the mean value ofR₁, R₂ and PD of 31 healthy subjects in comparison to the oldest healthy subject and in comparison to an MS patient were calculated. Larger anatomical structures were characterized using a standard atlas. The vector sum of the normalized differences was used to show significant tissue differences.

Results

The coefficient of variation of the reference maps was high at the edges of the brain and the ventricles, moderate in the cortical grey matter and low in white matter and the deep grey matter structures. The elderly subject mainly showed significantly lower R₁ and R₂ and higher PD values along all sulci. The MS patient showed significantly lower R₁ and R₂ and higher PD values at the edges of the ventricular system as well as throughout the periventricular white matter, at the internal and external capsules and at each of the MS lesions.

Conclusion

Brain normalization of rapid qMRI is a promising new method to generate reference maps of typical brain characteristics and to automatically detect deviating tissue properties in the brain.     

Characterization of central nervous system structures by magnetic resonance diffusion anisotropy

Diffusion-weighted magnetic resonance imaging (MRI) provides information about tissue water diffusion. Diffusion anisotropy, which can be measured with diffusion tensor MRI, is a quantitative measure of the directional dependence of the diffusion restriction that is introduced by biological structures such as nerve fibers. Diffusion tensor MRI data was obtained in the brain, brain stem, and cervical spinal cord. For each region, scans were performed in four normal volunteers. Fractional anisotropy (FA), an index of diffusion anisotropy, was measured within regions of interest located in the corpus callosum, capsula interna, thalamus, caudate nucleus, putamen, brain cortex, pyramidal tract of the medulla, accessory olivary nucleus, dorsal olivary nucleus, inferior olivary nucleus, spinal white and gray matter. The highest FA value was measured in the corpus callosum (81 +/- 3%). The values of the other areas decreased in the following order: pyramidal tract in the medulla (72 +/- 1%), spinal white matter (65 +/- 4%), capsula interna (62 +/- 3%), accessory olivary nucleus (36 +/- 2%), spinal gray matter (35 +/- 5%), dorsal olivary nucleus in the medulla (29 +/- 2%), thalamus (28 +/- 2%), inferior olivary nucleus (15 +/- 2%), putamen (13 +/- 2%), caudate nucleus (13 +/- 2%), and brain cortex (9 +/- 1%). Our results indicate that the underlying fiber architecture, fiber density, and uniformity of nerve fiber direction affect anisotropy values of the various structures. Characterization of various central nervous system structures with diffusion anisotropy is possible and may be useful to monitor degenerative diseases in the central nervous system.     

Orientation Dependent MR Signal Decay Differentiates between People with MS,Their Asymptomatic Siblings and Unrelated Healthy Controls

R2* relaxometry of the brain is a quantitative magnetic resonance technique which is influenced by iron and myelin content across different brain regions. Multiple sclerosis (MS) is a common inflammatory, demyelinating disease affecting both white and grey matter regions of the CNS. Using R2*, increased iron deposition has been described in deep gray matter of MS patients. Iron accumulation might promote oxidative stress in the brain, which can lead to cell death and neurodegeneration. However, recent histological work indicates that iron may be reduced within the normal appearing white matter (WM) in MS. In the present study we analyzed the R2* signal across the white matter in 39 patients with MS, 31 asymptomatic age matched siblings of patients and 30 age-matched controls. The measurement of R2* in white matter is affected by the signal''s dependency on white matter fibre orientation with respect to the main magnetic field which can be accounted using diffusion tensor imaging. We observed a clear separation of the three study groups in R2*. The values in the MS group were significantly lower compared to the siblings and controls, while the siblings group presented with significantly higher R2* values than both unrelated healthy controls and patients. Furthermore, we found significantly decreased normal-appearing white matter R2* values in patients with more severe disease course. Angle resolved analysis of R2* improves the sensitivity for detecting subtle differences in WM R2* compared to standard histogram based analyses. Our findings suggest that the decreased R2* values in MS are due to diffuse tissue damage and decreased myelin in the normal appearing and diffusely abnormal WM. The increased R2* in unaffected siblings may identify a predisposition to increased iron and the potential for oxidative stress as a risk factor for developing MS.     

Copper distribution in the normal human brain

Copper concentration was determined in samples from 38 areas of 7 normal human brains. The grey matter contained higher concentrations of copper than the white matter. Identical areas of the grey and white matter of the cerebral cortex showed significant differences between individuals. In the caudate nucleus the highest concentrations of copper were found in the tail followed by the body and the head, respectively. A negative linear regression between age and brain copper levels was demonstrated.     

MRI evaluation of basal ganglia ferritin iron and neurotoxicity in Alzheimer's and Huntingon's disease.

BACKGROUND: The basal ganglia contain the highest levels of iron in the brain and post-mortem studies indicate a disruption of iron metabolism in the basal ganglia of patients with neurodegenerative disorders such as Alzheimer's disease (AD) and Huntington's disease (HD). Iron can catalyze free radical reactions and may contribute to oxidative damage observed in AD and HD brain. Magnetic resonance imaging (MRI) can quantify transverse relaxation rates, which can be used to quantify tissue iron stores as well as evaluate increases in MR-visible water (an indicator of tissue damage). METHODS: A magnetic resonance imaging (MRI) method termed the field dependent relaxation rate increase (FDRI) was employed which quantifies the iron content of ferritin molecules (ferritin iron) with specificity through the combined use of high and low field-strength MRI instruments. Three basal ganglia structures (caudate, putamen and globus pallidus) and one comparison region (frontal lobe white matter) were evaluated. Thirty-one patients with AD and a group of 68 older control subjects, and 11 patients with HD and a group of 27 adult controls participated (4 subjects overlap between AD and HD controls). RESULTS: Compared to their respective normal control groups, increases in basal ganglia FDRI levels were seen in both AD and HD. FDRI levels were significantly increased in the caudate (p = 0.007) and putamen (p = 0.008) of patients with AD with a trend toward an increase in the globus pallidus (p = 0.13). In the patients with HD, all three basal ganglia regions showed highly significant FDRI increases (p<0.001) and the magnitude of the increases were 2 to 3 times larger than those observed in AD versus control group comparison. For both HD andAD subjects, the basal ganglia FDRI increase was not a generalized phenomenon, as frontal lobe white matter FDRI levels were decreased in HD (p = 0.015) and remained unchanged in AD. Significant low field relaxation rate decreases (suggestive of increased MR-visible water and indicative of tissue damage) were seen in the frontal lobe white matter of both HD and AD but only the HD basal ganglia showed such decreases. CONCLUSIONS: The data suggest that basal ganglia ferritin iron is increased in HD and AD. Furthermore, the increased iron levels do not appear to be a byproduct of the illness itself since they seem to be present at the onset of the diseases, and thus may be considered a putative risk factor. Published post-mortem studies suggest that the increase in basal ganglia ferritin iron may occur through different mechanisms in HD and AD. Consistent with the known severe basal ganglia damage, only HD basal ganglia demonstrated significant decreases in low field relaxation rates. MRI can be used to dissect differences in tissue characteristics, such as ferritin iron and MR-visible water, and thus could help clarify neuropathologic processes in vivo. Interventions aimed at decreasing brain iron levels, as well as reducing the oxidative stress associated with increased iron levels, may offer novel ways to delay the rate of progression and possibly defer the onset of AD and HD.     

Dolichol in Human Brain: Regional and Developmental Aspects

Distinct regional differences in dolichol content were defined in human brain from 15 to 76 years of age. Concerning the regional distribution of dolichol, levels were: higher in cortical gray matter than in subcortical white matter, highest among cortical regions in temporal gray matter, highest among all brain regions in thalamus, and lowest among all brain regions in lower brain stem and spinal cord. The developmental changes in the contents of dolichol were found to be different among brain regions. For example, among regions with the highest levels of dolichol, in thalamus there was a six to sevenfold increase, but in parietal gray matter, only a 2.5-fold increase. Regional and developmental changes in the proportions of the individual molecular species (isoprenologues) of dolichol were also observed. The findings indicate that the metabolism of dolichol is not uniform among regions of developing and aging human brain and may have implications for the role of dolichol in normal and diseased human brain.     

Magnetic resonance imaging in vivo monitoring of T2 relaxation time: Quantitative assessment of primate brain maturation

This work describes quantitative MRI assessment of primate brain maturation. Nine young baboons were followed from the age of one to 30 months. Assessment of myelination was based on the gray/white matter contrast on MR images and the evolution of T2 relaxation time respectively. The brain maturation began in the posterior fossa and progressed to the olfactory bulbs corresponding to decreasing white matter T2 values. Relaxation parameters provide new opportunities to trace the myelination process in vivo.     

Assessment of trace elements in human brain using inductively coupled plasma mass spectrometry

Recent brain research reveals a major role of trace elements in various diseases such as multiple sclerosis, Alzheimer's and Wilson's disease. The majority of published tissue concentrations dates back decades, and was assessed with various methods. Little is known about hemispherical differences, the correlation of trace elements or age-dependent changes in the human brain. Thus, the aim of this study was to examine trace element concentrations in different human brain regions after whole brain formalin fixation.549 samples of 13 brain regions were investigated in 11 deceased subjects without known history of brain pathology. Regional wet-to-dry mass ratios and concentrations of iron, copper, magnesium, manganese, calcium and zinc were determined using inductively coupled plasma mass spectrometry.Cortical gray matter revealed higher water content (wet-to-dry mass ratios 5.84–6.40) than white matter regions (wet-to-dry mass ratios 2.95–3.05). Element concentrations displayed specific regional differences. Good linear correlation of concentrations between elements was found for iron/copper as well as for manganese/magnesium (Spearman's rank correlation coefficient 0.74 and 0.65, respectively). Significant inter-hemispherical differences were found for copper in occipital white matter, for magnesium and calcium in putamen and for iron and copper in temporal white matter. An age dependent increase was seen in cortical gray matter for calcium, for magnesium in all regions except in cortical gray matter, for copper in substantia nigra and for zinc in occipital cortex.The presented trace element concentrations can serve as a fundamental basis for further brain research. Wet-to-dry mass ratios allow a comparison with reference data from other studies.     

Associations between age and gray matter volume in anatomical brain networks in middle‐aged to older adults

Aging is associated with cognitive decline, diminished brain function, regional brain atrophy, and disrupted structural and functional brain connectivity. Understanding brain networks in aging is essential, as brain function depends on large‐scale distributed networks. Little is known of structural covariance networks to study inter‐regional gray matter anatomical associations in aging. Here, we investigate anatomical brain networks based on structural covariance of gray matter volume among 370 middle‐aged to older adults of 45–85 years. For each of 370 subjects, we acquired a T1‐weighted anatomical MRI scan. After segmentation of structural MRI scans, nine anatomical networks were defined based on structural covariance of gray matter volume among subjects. We analyzed associations between age and gray matter volume in anatomical networks using linear regression analyses. Age was negatively associated with gray matter volume in four anatomical networks (P < 0.001, corrected): a subcortical network, sensorimotor network, posterior cingulate network, and an anterior cingulate network. Age was not significantly associated with gray matter volume in five networks: temporal network, auditory network, and three cerebellar networks. These results were independent of gender and white matter hyperintensities. Gray matter volume decreases with age in networks containing subcortical structures, sensorimotor structures, posterior, and anterior cingulate cortices. Gray matter volume in temporal, auditory, and cerebellar networks remains relatively unaffected with advancing age.     

d-Aspartate in Human Brain

The presence of the biologically uncommon D-aspartic acid (D-aspartate) in human brain white matter has been previously reported. The earlier study has now been expanded to include D/L-aspartate ratios from 67 normal brains. The data show that the D-aspartate content increases rapidly from 1 year to approximately 35 years of age, levels off in middle age, and then appears to decrease somewhat. The D-aspartate content in gray matter remains at a consistently low level (half of that found in white matter) throughout the human life span. Within the limitations of current analytical methods, there was no detectable difference in D/L-aspartate ratios in white and gray matter of brains with Alzheimer's disease and several other pathologies when compared with brains of normal subjects. However, the presence of a significant D-aspartate level in white matter during the adult life span may lead to changes in protein configuration related to dysfunctions associated with the aging brain.     

The regional distribution of manganese in the normal human brain

The concentration of manganese per gram dry tissue weight was determined in samples from 39 areas of 8 normal human brains. Manganese was shown to be unevenly distributed with the largest concentrations in the pineal gland and the olfactory bulb. The gray matter yielded a higher content of manganese than the white matter. Significant differences between individuals were found for identical areas of the gray and white matter of the cerebral cortex. Higher levels of manganese were demonstrated in the tail of the caudate nucleus than in the body and the head of the same structure. No significant correlation was shown between the amount of manganese in brain and age.     

Global and Regional Associations of Smaller Cerebral Gray and White Matter Volumes with Gait in Older People

Background

Gait impairments increase with advancing age and can lead to falls and loss of independence. Brain atrophy also occurs in older age and may contribute to gait decline. We aimed to investigate global and regional relationships of cerebral gray and white matter volumes with gait speed, and its determinants step length and cadence, in older people.

Methods

In a population-based study, participants aged >60 years without Parkinson''s disease or brain infarcts underwent magnetic resonance imaging and gait measurements using a computerized walkway. Linear regression was used to study associations of total gray and white matter volumes with gait, adjusting for each other, age, sex, height and white matter hyperintensity volume. Other covariates considered in analyses included weight and vascular disease history. Voxel-based morphometry was used to study regional relationships of gray and white matter with gait.

Results

There were 305 participants, mean age 71.4 (6.9) years, 54% male, mean gait speed 1.16 (0.22) m/s. Smaller total gray matter volume was independently associated with poorer gait speed (p = 0.001) and step length (p<0.001), but not cadence. Smaller volumes of cortical and subcortical gray matter in bilateral regions important for motor control, vision, perception and memory were independently associated with slower gait speed and shorter steps. No global or regional associations were observed between white matter volume and gait independent of gray matter volume, white matter hyperintensity volume and other covariates.

Conclusion

Smaller gray matter volume in bilaterally distributed brain networks serving motor control was associated with slower gait speed and step length, but not cadence.     

Measurement of the hyperelastic properties of ex vivo brain tissue slices

The elastic and hyperelastic properties of brain tissue are of interest to the medical research community as there are several applications where accurate characterization of these properties is crucial for an accurate outcome. The linear response is applicable to brain elastography, while the non-linear response is of interest for surgical simulation programs. Because of the biological differences between gray and white matter, it is reasonable to expect a difference in their mechanical properties. The goal of this work is to characterize the elastic and hyperelastic properties of the brain gray and white matter. In this method, force-displacement data of these tissues were acquired from 25 different brain samples using an indentation apparatus. These data were processed with an inverse problem algorithm using finite element method as the forward problem solver. Young's modulus and the hyperelastic parameters corresponding to the commonly used Polynomial, Yeoh, Arruda-Boyce, and Ogden models were obtained. The parameters characterizing the linear and non-linear mechanical behavior of gray and white matters were found to be significantly different. Young's modulus was 1787±186 and 1195±157Pa for white matter and gray matter, respectively. Among hyperelastic models, due to its accuracy, fewer parameters and shorter computational time requirements, Yeoh model was found to be the most suitable. Due to the significant differences between the linear and non-linear tissue response, we conclude that incorporating these differences into brain biomechanical models is necessary to increase accuracy.     

Cerebral blood flow during rest associates with general intelligence and creativity

Recently, much scientific attention has been focused on resting brain activity and its investigation through such methods as the analysis of functional connectivity during rest (the temporal correlation of brain activities in different regions). However, investigation of the magnitude of brain activity during rest has focused on the relative decrease of brain activity during a task, rather than on the absolute resting brain activity. It is thus necessary to investigate the association between cognitive factors and measures of absolute resting brain activity, such as cerebral blood flow (CBF), during rest (rest-CBF). In this study, we examined this association using multiple regression analyses. Rest-CBF was the dependent variable and the independent variables included two essential components of cognitive functions, psychometric general intelligence and creativity. CBF was measured using arterial spin labeling and there were three analyses for rest-CBF; namely mean gray matter rest-CBF, mean white matter rest-CBF, and regional rest-CBF. The results showed that mean gray and white matter rest-CBF were significantly and positively correlated with individual psychometric intelligence. Furthermore, mean white matter rest-CBF was significantly and positively correlated with creativity. After correcting the effect of mean gray matter rest-CBF the significant and positive correlation between regional rest-CBF in the perisylvian anatomical cluster that includes the left superior temporal gyrus and insula and individual psychometric intelligence was found. Also, regional rest-CBF in the precuneus was significantly and negatively correlated with individual creativity. Significance of these results of regional rest-CBF did not change when the effect of regional gray matter density was corrected. The findings showed mean and regional rest-CBF in healthy young subjects to be correlated with cognitive functions. The findings also suggest that, even in young cognitively intact subjects, resting brain activity (possibly underlain by default cognitive activity or metabolic demand from developed brain structures) is associated with cognitive functions.     

Comprehensive brain MRI segmentation in high risk preterm newborns

Most extremely preterm newborns exhibit cerebral atrophy/growth disturbances and white matter signal abnormalities on MRI at term-equivalent age. MRI brain volumes could serve as biomarkers for evaluating the effects of neonatal intensive care and predicting neurodevelopmental outcomes. This requires detailed, accurate, and reliable brain MRI segmentation methods. We describe our efforts to develop such methods in high risk newborns using a combination of manual and automated segmentation tools. After intensive efforts to accurately define structural boundaries, two trained raters independently performed manual segmentation of nine subcortical structures using axial T2-weighted MRI scans from 20 randomly selected extremely preterm infants. All scans were re-segmented by both raters to assess reliability. High intra-rater reliability was achieved, as assessed by repeatability and intra-class correlation coefficients (ICC range: 0.97 to 0.99) for all manually segmented regions. Inter-rater reliability was slightly lower (ICC range: 0.93 to 0.99). A semi-automated segmentation approach was developed that combined the parametric strengths of the Hidden Markov Random Field Expectation Maximization algorithm with non-parametric Parzen window classifier resulting in accurate white matter, gray matter, and CSF segmentation. Final manual correction of misclassification errors improved accuracy (similarity index range: 0.87 to 0.89) and facilitated objective quantification of white matter signal abnormalities. The semi-automated and manual methods were seamlessly integrated to generate full brain segmentation within two hours. This comprehensive approach can facilitate the evaluation of large cohorts to rigorously evaluate the utility of regional brain volumes as biomarkers of neonatal care and surrogate endpoints for neurodevelopmental outcomes.     

Unconfined compression of white matter

The porous properties of brain tissue are important for understanding normal and abnormal cerebrospinal fluid flow in the brain. In this study, a poroviscoelastic model was fitted to the stress relaxation response of white matter in unconfined compression performed under a range of low strain rates. A set of experiments was also performed on the tissue samples using a no-slip boundary condition. Results from these experiments demonstrated that the rheological response of the white matter is primarily governed by the intrinsic viscoelastic properties of the solid phase. The permeability of white matter was found to be of the order of 10(-12) m4/Ns.     

Poor Cerebral Inflammatory Response in eIF2B Knock-In Mice: Implications for the Aetiology of Vanishing White Matter Disease

Background

Mutations in any of the five subunits of eukaryotic translation initiation factor 2B (eIF2B) can lead to an inherited chronic-progressive fatal brain disease of unknown aetiology termed leucoencephalopathy with vanishing white matter (VWM). VWM is one of the most prevalent childhood white matter disorders, which markedly deteriorates after inflammation or exposure to other stressors. eIF2B is a major housekeeping complex that governs the rate of global protein synthesis under normal and stress conditions. A previous study demonstrated that Eif2b5^R132H/R132H mice suffer delayed white matter development and fail to recover from cuprizone-induced demyelination, although eIF2B enzymatic activity in the mutant brain is reduced by merely 20%.

Principal Findings

Poor astrogliosis was observed in Eif2b5^R132H/R132H mice brain in response to systemic stress induced by peripheral injections of lipopolysaccharide (LPS). Even with normal rates of protein synthesis under normal conditions, primary astrocytes and microglia isolated from mutant brains fail to adequately synthesise and secrete cytokines in response to LPS treatment despite proper induction of cytokine mRNAs.

Conclusions

The mild reduction in eIF2B activity prevents the appropriate increase in translation rates upon exposure to the inflammatory stressor LPS. The data underscore the importance of fully-functional translation machinery for efficient cerebral inflammatory response upon insults. It highlights the magnitude of proficient translation rates in restoration of brain homeostasis via microglia-astrocyte crosstalk. This study is the first to suggest the involvement of microglia in the pathology of VWM disease. Importantly, it rationalises the deterioration of clinical symptoms upon exposure of VWM patients to physiological stressors and provides possible explanation for their high phenotypic variability.     

Cerebral white matter blood flow is constant during human non-rapid eye movement sleep: a positron emission tomographic study.

This study aimed to identify brain regions with the least decreased cerebral blood flow (CBF) and their relationship to physiological parameters during human non-rapid eye movement (NREM) sleep. Using [(15)O]H(2)O positron emission tomography, CBF was measured for nine normal young adults during nighttime. As NREM sleep progressed, mean arterial blood pressure and whole brain mean CBF decreased significantly; arterial partial pressure of CO(2) and, selectively, relative CBF of the cerebral white matter increased significantly. Absolute CBF remained constant in the cerebral white matter, registering 25.9 +/- 3.8 during wakefulness, 25.8 +/- 3.3 during light NREM sleep, and 26.9 +/- 3.0 (ml.100 g(-1).min(-1)) during deep NREM sleep (P = 0.592), and in the occipital cortex (P = 0.611). The regression slope of the absolute CBF significantly differed with respect to arterial partial pressure of CO(2) between the cerebral white matter (slope 0.054, R = - 0.04) and frontoparietal association cortex (slope - 0.776, R = - 0.31) (P = 0.005) or thalamus (slope - 1.933, R = - 0.47) (P = 0.004) and between the occipital cortex (slope 0.084, R = 0.06) and frontoparietal association cortex (P = 0.021) or thalamus (P < 0.001), and, with respect to mean arterial blood pressure, between the cerebral white matter (slope - 0.067, R = - 0.10) and thalamus (slope 0.637, R = 0.31) (P = 0.044). The cerebral white matter CBF keeps constant during NREM sleep as well as the occipital cortical CBF, and may be specifically regulated by both CO(2) vasoreactivity and pressure autoregulation.